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Fed Pract
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gaming
gambling
compulsive behaviors
ammunition
assault rifle
black jack
Boko Haram
bondage
child abuse
cocaine
Daech
drug paraphernalia
explosion
gun
human trafficking
ISIL
ISIS
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Islamic state
mixed martial arts
MMA
molestation
national rifle association
NRA
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pedophilia
poker
porn
pornography
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recreational drug
sex slave rings
slot machine
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Texas hold 'em
UFC
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bunges
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butt
butt fuck
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buttfucked
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cock sucker
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A peer-reviewed clinical journal serving healthcare professionals working with the Department of Veterans Affairs, the Department of Defense, and the Public Health Service.

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Community Care Radiation Oncology Cost Calculations for a VA Medical Center

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Community Care Radiation Oncology Cost Calculations for a VA Medical Center

William Kissick’s description of health care’s iron triangle in 1994 still resonates. Access, quality, and cost will always come at the expense of the others.1 In 2018, Congress passed the VA MISSION Act, allowing patients to pursue community care options for extended waits (> 28 days) or longer distance drive times of > 60 minutes for specialty care services, such as radiation oncology. According to Albanese et al, the VA MISSION Act sought to address gaps in care for veterans living in rural and underserved areas.2 The Veterans Health Administration (VHA) continues to increase community care spending, with a 13.8% increase in fiscal year 2024 and an expected cost of > $40 billion for 2025.3 One could argue this pays for access for remote patients and quality when services are unavailable, making it a direct application of the iron triangle.

The VA MISSION Act also bolstered the expansion of existing community care department staff to expediently facilitate and coordinate care and payments.2 Cost management and monitoring have become critical in predicting future staff requirements, maintaining functionality, and ensuring patients receive optimal care. The VHA purchases care through partner networks and defines these bundled health care services as standard episodes of care (SEOCs), which are “clinically related health care services for a specific unique illness or medical condition… over a defined period of time.”4 Medicare publishes its rates quarterly, and outpatient procedure pricing is readily available online.5 Along these same lines, the US Department of Veterans Affairs (VA) publishes a current list of available procedures and associated Current Procedure Technology (CPT) codes that are covered under its VA fee schedule for community care.

Unique challenges persist when using this system to accurately account for radiation oncology expenditures. This study was based on the current practices at the Richard L. Roudebush VA Medical Center (RLRVAMC), a large 1a hospital. A detailed analysis reveals the contemporaneous cost of radiation oncology cancer care from October 1, 2021, through February 1, 2024, highlights the challenges in SEOC definition and duration, communication issues between RLRVAMC and purchase partners, inconsistencies in billing, erroneous payments, and difficulty of cost categorization.

METHODS

Community care radiation oncology-related costs were examined from October 1, 2021, to February 1, 2024 for RLRVAMC, 6 months prior to billing data extraction. Figure 1 shows a simple radiation oncology patient pathway with consultation or visit, simulation and planning, and treatment, with codes used to check billing. It illustrates the expected relationships between the VHA (radiation oncology, primary, and specialty care) and community care (clinicians and radiation oncology treatment sites).

0525FED-AVAHO-RAD_F1

VHA standard operating procedures for a patient requesting community-based radiation oncology care require a board-certified radiation oncologist at RLRVAMC to review and approve the outside care request. Community care radiation oncology consultation data were accessed from the VA Corporate Data Warehouse (CDW) using Pyramid Analytics (V25.2). Nurses, physicians, and community care staff can add comments, forward consultations to other services, and mark them as complete or discontinued, when appropriate. Consultations not completed within 91 days are automatically discontinued. All community care requests from 2018 through 2024 were extracted; analysis began April 1, 2021, 6 months prior to the cost evaluation date of October 1, 2021.

An approved consultation is reviewed for eligibility by a nurse in the community care department and assigned an authorization number (a VA prefix followed by 12 digits). Billing codes are approved and organized by the community care networks, and all procedure codes should be captured and labeled under this number. The VAMC Community Care department obtains initial correspondence from the treating clinicians. Subsequent records from the treating radiation oncologist are expected to be scanned into the electronic health record and made accessible via the VA Joint Legacy Viewer (JLV) and Computerized Patient Record System (CPRS).

Radiation Oncology SEOC

The start date of the radiation oncology SEOC is determined by the community care nurse based on guidance established by the VA. It can be manually backdated or delayed, but current practice is to start at first visit or procedure code entry after approval from the VAMC Radiation Oncology department. Approved CPT codes from SEOC versions between October 1, 2021, and February 1, 2024, are in eAppendix 1 (available at doi:10.12788/fp.0585). These generally include 10 types of encounters, about 115 different laboratory tests, 115 imaging studies, 25 simulation and planning procedures, and 115 radiation treatment codes. The radiation oncology SEOCs during the study period had an approval duration of 180 days. Advanced Medical Cost Management Solutions software (AMCMS) is the VHA data analytics platform for community care medical service costs. AMCMS includes all individual CPT codes billed by specific radiation oncology SEOC versions. Data are refreshed monthly, and all charges were extracted on September 12, 2024, > 6 months after the final evaluated service date to allow for complete billing returns.6

0525FED-AVAHO-RAD_eApp1
Radiation Oncology-Specific Costs

The VA Close to Me (CTM) program was used to find 84 specific radiation oncology CPT codes, nearly all within the 77.XXX or G6.XXX series, which included all radiation oncology-specific (ROS) codes (except visits accrued during consultation and return appointments). ROS costs are those that could not be performed by any other service and include procedures related to radiation oncology simulation, treatment planning, treatment delivery (with or without image guidance), and physician or physicist management. All ROS costs should be included in a patient’s radiation oncology SEOC. Other costs that may accompany operating room or brachytherapy administration did not follow a 77.XXX or G6.XXX pattern but were included in total radiation therapy operating costs.

Data obtained from AMCMS and CTM included patient name and identifier; CPT billed amount; CPT paid amount; dates of service; number of claims; International Classification of Diseases, Tenth Revision (ICD) diagnosis; and VA authorization numbers. Only CTM listed code modifiers. Only items categorized as paid were included in the analysis. Charges associated with discontinued consultations that had accrued costs also were included. Codes that were not directly related to ROS were separately characterized as other and further subcategorized.

Deep Dive Categorization

All scanned documents tagged to the community consultation were accessed and evaluated for completeness by a radiation oncologist (RS). The presence or absence of consultation notes and treatment summaries was evaluated based on necessity (ie, not needed for continuation of care or treatment was not given). In the absence of a specific completion summary or follow-up note detailing the treatment modality, number of fractions, and treatment sites, available documentation, including clinical notes and billing information, was used. Radical or curative therapies were identified as courses expected to eradicate disease, including stereotactic ablative radiotherapy to the brain, lung, liver, and other organs. Palliative therapies included whole-brain radiotherapy or other low-dose treatments. If the patient received the intended course, this was categorized as full. If incomplete, it was considered partial.

Billing Deviations

The complete document review allowed for close evaluation of paid therapy and identification of gaps in billing (eg, charges not found in extracted data that should have occurred) for external beam radiotherapy patients. Conversely, extra charges, such as an additional weekly treatment management charge (CPT code 77427), would be noted. Patients were expected to have the number of treatments specified in the summary, a clinical treatment planning code, and weekly treatment management notes from physicians and physicists every 5 fractions. Consultations and follow-up visits were expected to have 1 visit code; CPT codes 99205 and 99215, respectively, were used to estimate costs in their absence.

Costs were based on Medicare rates as of January 1 of the year in which they were accrued. 7-10 Duplicates were charges with the same code, date, billed quantity, and paid amounts for a given patient. These would always be considered erroneous. Medicare treatment costs for procedures such as intensity modulated radiotherapy (CPT code 77385 or 77386) are available on the Medicare website. When reviewing locality deviations for 77427, there was a maximum of 33% increase in Medicare rates. Therefore, for treatment codes, one would expect the range to be at least the Medicare rate and maximally 33% higher. These rates are negotiated with insurance companies, but this range was used for the purpose of reviewing and adjusting large data sets.

RESULTS

Since 2018, > 500 community care consults have been placed by radiation oncology for treatment in the community, with more following implementation of the VA MISSION Act. Use of radiation oncology community care services annually increased during the study period for this facility (Table 1, Figure 2). Of the 325 community care consults placed from October 1, 2021, to February 1, 2024, 248 radiation oncology SEOCs were recorded with charges for 181 patients (range, 1-5 SEOCs). Long drive time was the rationale for > 97% of patients directed to community care (Supplemental materials, available at doi:10.12788/fp.0585). Based on AMCMS data, $22.2 million was billed and $2.7 million was paid (20%) for 8747 CPT codes. Each community care interval cost the VA a median (range) of $5000 ($8-$168,000 (Figure 3).

0525FED-AVAHO-RAD_T10525FED-AVAHO-RAD_F20525FED-AVAHO-RAD_F3

After reviewing ROS charges extracted from CTM, 20 additional patients had radiation oncology charges but did not have a radiation oncology SEOC for 268 episodes of care for 201 unique patients. In addition to the 20 patients who did not have a SEOC, 42 nonradiation oncology SEOCs contained 1148 radiation oncology codes, corresponding to almost $500,000 paid. Additional charges of about $416,000, which included biologic agents (eg, durvalumab, nivolumab), procedures (eg, mastectomies), and ambulance rides were inappropriately added to radiation oncology SEOCs.

While 77% of consultations were scanned into CPRS and JLV, only 54% of completion summaries were available with an estimated $115,000 in additional costs. The total adjusted costs was about $2.9 million. Almost 37% of SEOCs were for visits only. For the 166 SEOCs where patients received any radiation treatment or planning, the median cost was $18,000. Differences in SEOC pathways are shown in Figure 4. One hundred twenty-one SEOCs (45%) followed the standard pathway, with median SEOC costs of $15,500; when corrected for radiation-specific costs, the median cost increased to $18,000. When adjusted for billing irregularities, the median cost was $20,600. Ninety-nine SEOCs (37%) were for consultation/ follow-up visits only, with a median cost of $220. When omitting shared scans and nonradiation therapy costs and correcting for billing gaps, the median cost decreased to $170. A median of $9200 was paid per patient, with $12,900 for radiation therapy-specific costs and $13,300 adjusted for billing deviations. Narrowing to the 106 patients who received full, radical courses, the median SEOC, ROS, and adjusted radiation therapy costs increased to $19,400, $22,200, and $22,900, respectively (Table 2, Figure 5). Seventy-one SEOCs (26%) had already seen a radiation oncologist before the VA radiation oncology department was aware, and 49 SEOCs (18%) had retroactive approvals (Supplemental materials available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T20525FED-AVAHO-RAD_F40525FED-AVAHO-RAD_F5

Every consultation charge was reviewed. A typical patient following the standard pathway (eAppendix 2, available at doi:10.12788/ fp.0585) exhibited a predictable pattern of consultation payment, simulation and planning, multiple radiation treatments interspersed with treatment management visits and a cone-down phase, and finishing with a follow-up visit. A less predictable case with excess CPT codes, gaps in charges, and an additional unexpected palliative course is shown in eAppendix 3 (available at doi:10.12788/fp.0585). Gaps occurred in 42% of SEOCs with missed bills costing as much as $12,000. For example, a patient with lung cancer had a treatment summary note for lung cancer after completion that showed the patient received 30 fractions of 2 Gy, a typical course. Only 10 treatment codes and 3 of 6 weekly treatment management codes were available. There was a gap of 20 volumetric modulated arc therapy treatments, 3 physics weekly status checks, 3 physician managements notes, and a computed tomography simulation charge.

0525FED-AVAHO-RAD_eApp20525FED-AVAHO-RAD_eApp3

Between AMCMS and CTM, 10,005 CPT codes were evaluated; 1255 (12.5%) were unique to AMCMS (either related to the radiation oncology course, such as Evaluation and Management CPT codes or “other” unrelated codes) while 1158 (11.6%) were unique to CTM. Of the 7592 CPT codes shared between AMCMS and CTM, there was a discrepancy in 135 (1.8%); all were duplicates (CTM showed double payment while AMCMS showed $0 paid). The total CPT code costs came to $3.2 million with $560,000 unique to SEOCs and $500,000 unique to CTM. Treatment codes were the most common (33%) as shown in Table 3 and accounted for 55% of the cost ($1.8 million). About 700 CPT codes were considered “other,” typically for biologic therapeutic agents (Table 4 and eAppendix 4, available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T30525FED-AVAHO-RAD_T40525FED-AVAHO-RAD_eApp4

DISCUSSION

The current method of reporting radiation oncology costs used by VA is insufficient and misleading. Better data are needed to summarize purchased care costs to guide decisions about community care at the VA. Investigations into whether the extra costs for quality care (ie, expensive capital equipment, specialized staff, mandatory accreditations) are worthwhile if omitted at other facilities patients choose for their health care needs. No study has defined specialty care-specific costs by evaluating billing receipts from the CDW to answer the question. Kenamond et al highlight the need for radiation oncology for rural patients.11 Drive time was cited as the reason for community care referral for 97% of veterans, many of whom lived in rural locations. Of patients with rurality information who enrolled in community care, 57% came from rural or highly rural counties, and this ratio held for those who received full curative therapies. An executive administrator relying on AMCMS reports would see a median SEOC cost of $5000, but without ROS knowledge in coding, the administrator would miss many additional costs. For example, 2 patients who each had 5 SEOCs during the evaluated period, incurred a total cost of only $1800.

Additionally, an administrator could include miscategorized costs with significant ramifications. The 2 most expensive SEOCs were not typical radiation oncology treatments. A patient undergoing radium-223 dichloride therapy incurred charges exceeding $165,000, contributing disproportionately to the overall median cost analysis; this would normally be administered by the nuclear medicine department. Immunotherapy and chemotherapy are uniformly overseen by medical oncology services, but drug administration codes were still found in radiation oncology SEOCs. A patient (whose SEOC was discontinued but accrued charges) had an electrocardiogram interpretation for $8 as the SEOC cost; 3 other SEOCs continued to incur costs after being discontinued. There were 24 empty SEOCs for patients that had consults to the community, and 2 had notes stating treatment had been delivered yet there was no ROS costs or SEOC costs. Of the 268 encounters, 43% had some sort of billing irregularities (ie, missing treatment costs) that would be unlikely for a private practice to omit; it would be much more likely that the CDW miscategorized the payment despite confirmation of the 2 retrieval systems.

It would be inadvisable to make staffing decisions or forecast costs based on current SEOC reports without specialized curation. A simple yet effective improvement to the cost attribution process would be to restrict the analysis to encounters containing primary radiation treatment codes. This targeted approach allows more accurate identification of patients actively receiving radiation oncology treatment, while excluding those seen solely for consultations or follow-up visits. Implementing this refinement leads to a substantial increase in the median payment—from $5000 to $13,000—without requiring additional coding or data processing, thereby enhancing the accuracy of cost estimates with minimal effort.

Clarifying radiation oncology service costs requires addressing the time frame and services included, given laxity and interpretation of the SEOCs. VA community care departments have streamlined the reimbursement process at the expense of medical cost organization and accuracy; 86% of VA practitioners reported that ≥ 1 potential community health care partners had refused to work with the VA because of payment delays.12 Payments are contingent on correspondence from outside practices for community work. For radiation oncology, this includes the consultation but also critical radiation-related details of treatment, which were omitted nearly half the time. SEOC approval forms have many costly laboratory tests, imaging, and procedures that have little to do with radiation oncology cancer treatments but may be used in the workup and staging process; this creates noise when calculating radiation oncology fiscal cost.

The presumption that an episode of care equates to a completed radiation therapy course is incorrect; this occurs less than half of the time. An episode often refers to a return visit, or conversely, multiple treatment courses. As the patients’ medical homes are their VHA primary care practitioners, it would be particularly challenging to care for the patients without full treatment information, especially if adverse effects from therapy were to arise. As a tertiary specialty, radiation oncology does not seek out patients and are sent consultations from medical oncology, surgical, and medical oncologic specialties. Timesensitive processes such as workup, staging, and diagnosis often occur in parallel. This analysis revealed that patients see outside radiation oncologists prior to the VA. There are ≥ 100 patients who had radiation oncology codes without a radiation oncology SEOC or community care consultation, and in many cases, the consultation was placed after the patient was seen.

Given the lack of uniformity and standardization of patient traffic, the typical and expected pathways were insufficient to find the costs. Too many opportunities for errors and incorrect categorization of costs meant a different method would be necessary. Starting at the inception of the community care consult, only 1 diagnosis code can be entered. For patients with multiple diagnoses, one would not be able to tell what was treated without chart access. Radiation oncology consults come from primary and specialty care practitioners and nurses throughout the VA. Oftentimes, the referral would be solicited by the community radiation oncology clinic, diagnosing community specialty (ie, urology for a patient with prostate cancer), or indirectly from the patient through primary care. Many cases were retroactively approved as the veteran had already been consulted by the community care radiation oncologist. If the patient is drive-time eligible, it would be unlikely that they would leave and choose to return to the VA. There is no way for a facility VA service chief or administrator to mitigate VA community costs of care, especially as shown by the miscategorization of several codes. Database challenges exacerbate the issue: 1 patient changed her first and last name during this time frame, and 2 patients had the same name but different social security numbers. In order to strictly find costs between 2 discrete timepoints, 39 (15%) SEOCs were split and incomplete, and 6 SEOCs contained charges for 2 different patients. This was corrected, and all inadvertent charges were cancelled. Only 1 ICD code is allowed per community care consultation, so an investigation is required to find costs for patients with multiple sites of disease. Additionally, 5 of the patients marked for drive time were actually patients who received Gamma Knife and brachytherapy, services not available at the VA.

Hanks et al first attempted to calculate cost of radiation oncology services. External beam prostate cancer radiotherapy at 3 suburban California centers cost $6750 ($20,503 inflation adjusted) per patient before October 1984 and $5600 ($17,010 inflation adjusted) afterwards.13 According to the American Society for Radiation Oncology, Advocacy Radiation Oncology Case Rate Program Curative radiation courses should cost $20,000 to $30,000 and palliative courses should cost $10,000 to $15,000. These costs are consistent with totals demonstrated in this analysis and similar to the inflation-adjusted Hanks et al figures. Preliminary findings suggest that radiation treatment constituted more than half of the total expenditures, with a notable $4 million increase in adjusted cost compared to the Medicare rates, indicating significant variation. Direct comparisons with Medicaid or commercial payer rates remain unexplored.

Future Directions

During the study period, 201 patients received 186 courses of radiation therapy in the community, while 1014 patients were treated in-house for a total of 833 courses. A forthcoming analysis will directly compare the cost of in-house care with that of communitybased treatment, specifically breaking down expenditure differences by diagnosis. Future research should investigate strategies to align reimbursement with quality metrics, including the potential role of tertiary accreditation in incentivizing high-value care. Additional work is also warranted to assess patient out-ofpocket expenses across care settings and to benchmark VA reimbursement against Medicare, Medicaid, and private insurance rates. In any case, with the increasing possibility of fewer fractions for treatments such as stereotactic radiotherapy or palliative care therapy, there is a clear financial incentive to treat as frequently as allowed despite equal clinical outcomes.

CONCLUSIONS

Veterans increasingly choose to receive care closer to home if the option is available. In the VA iron triangle, cost comes at the expense of access but quantifying this has proved elusive in the cost accounting model currently used at the VA.1 The inclusion of all charges loosely associated with SEOCs significantly impairs the ability to conduct meaningful cost analyses. The current VA methodology not only introduces substantial noise into the data but also leads to a marked underestimation of the true cost of care delivered in community settings. Such misrepresentation risks driving policy decisions that could inappropriately reduce or eliminate in-house radiation oncology services. Categorizing costs effectively in the VA could assist in making managerial and administrative decisions and would prevent damaging service lines based on misleading or incorrect data. A system which differentiates between patients who have received any treatment codes vs those who have not would increase accuracy.

References
  1. Kissick W. Medicine’s Dilemmas: Infinite Needs Versus Finite Resources. 1st ed. Yale University Press; 1994.
  2. Albanese AP, Bope ET, Sanders KM, Bowman M. The VA MISSION Act of 2018: a potential game changer for rural GME expansion and veteran health care. J Rural Health. 2020;36(1):133-136. doi:10.1111/jrh.12360
  3. Office of Management and Budget (US). Budget of the United States Government, Fiscal Year 2025. Washington, DC: US Government Publishing Office; 2024. Available from: US Department of Veterans Affairs FY 2025 Budget Submission: Budget in Brief.
  4. US Department of Veterans Affairs. Veteran care claims. Accessed April 3, 2025. https://www.va.gov/COMMUNITYCARE/revenue-ops/Veteran-Care-Claims.asp
  5. US Centers for Medicare and Medicaid Services. Accessed April 3, 2025. Procedure price lookup https://www.medicare.gov/procedure-price-lookup
  6. US Department of Veterans Affairs. WellHive -Enterprise. Accessed April 3, 2025. https://department.va.gov/privacy/wp-content/uploads/sites/5/2023/05/FY23WellHiveEnterprisePIA.pdf
  7. US Centers for Medicare and Medicaid Services. RVU21a physician fee schedule, January 2021 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu21a
  8. US Centers for Medicare and Medicaid Services. RVU22a physician fee schedule, January 2022 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu22a
  9. US Centers for Medicare and Medicaid Services. RVU23a physician fee schedule, January 2023 release. Accessed April 3, 2025. https://www.cms.gov/medicare/medicare-fee-service-payment/physicianfeesched/pfs-relative-value-files/rvu23a
  10. US Centers for Medicare and Medicaid Services. RVU23a Medicare Physician Fee Schedule rates effective January 1, 2024, through March 8, 2024. Accessed on April 3, 2025. https://www.cms.gov/medicare/payment/fee-schedules/physician/pfs-relative-value-files/rvu24a
  11. Kenamond MC, Mourad WF, Randall ME, Kaushal A. No oncology patient left behind: challenges and solutions in rural radiation oncology. Lancet Reg Health Am. 2022;13:100289. doi:10.1016/j.lana.2022.100289
  12. Mattocks KM, Kroll-Desrosiers A, Kinney R, Elwy AR, Cunningham KJ, Mengeling MA. Understanding VA’s use of and relationships with community care providers under the MISSION Act. Med Care. 2021;59(Suppl 3):S252-S258. doi:10.1097/MLR.0000000000001545
  13. Hanks GE, Dunlap K. A comparison of the cost of various treatment methods for early cancer of the prostate. Int J Radiat Oncol Biol Phys. 1986;12(10):1879-1881. doi:10.1016/0360-3016(86)90334-2
  14. American Society of Radiation Oncology. Radiation oncology case rate program (ROCR). Accessed April 3, 2025. https://www.astro.org/advocacy/key-issues-8f3e5a3b76643265ee93287d79c4fc40/rocr
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Ronald H. Shapiro, MD, MBAa; Reid F. Thompson, MD, PhDb,c; David A. Elliott, MDd,e,f; Christopher N. Watson, MDa; Helen Fosmire, MDa

Author affiliations
aRichard L. Roudebush Veterans Affairs Medical Center, Indianapolis, Indiana
bOregon Health & Science University, Portland
cVeterans Affairs Portland Health Care System, Oregon
dCharles S. Kettles Veterans Affairs Medical Center, Ann Arbor, Michigan
eUniversity of Michigan, Ann Arbor
fRogel Cancer Center, Ann Arbor, Michigan

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ronald Shapiro ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0585

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Ronald H. Shapiro, MD, MBAa; Reid F. Thompson, MD, PhDb,c; David A. Elliott, MDd,e,f; Christopher N. Watson, MDa; Helen Fosmire, MDa

Author affiliations
aRichard L. Roudebush Veterans Affairs Medical Center, Indianapolis, Indiana
bOregon Health & Science University, Portland
cVeterans Affairs Portland Health Care System, Oregon
dCharles S. Kettles Veterans Affairs Medical Center, Ann Arbor, Michigan
eUniversity of Michigan, Ann Arbor
fRogel Cancer Center, Ann Arbor, Michigan

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ronald Shapiro ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0585

Author and Disclosure Information

Ronald H. Shapiro, MD, MBAa; Reid F. Thompson, MD, PhDb,c; David A. Elliott, MDd,e,f; Christopher N. Watson, MDa; Helen Fosmire, MDa

Author affiliations
aRichard L. Roudebush Veterans Affairs Medical Center, Indianapolis, Indiana
bOregon Health & Science University, Portland
cVeterans Affairs Portland Health Care System, Oregon
dCharles S. Kettles Veterans Affairs Medical Center, Ann Arbor, Michigan
eUniversity of Michigan, Ann Arbor
fRogel Cancer Center, Ann Arbor, Michigan

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ronald Shapiro ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0585

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William Kissick’s description of health care’s iron triangle in 1994 still resonates. Access, quality, and cost will always come at the expense of the others.1 In 2018, Congress passed the VA MISSION Act, allowing patients to pursue community care options for extended waits (> 28 days) or longer distance drive times of > 60 minutes for specialty care services, such as radiation oncology. According to Albanese et al, the VA MISSION Act sought to address gaps in care for veterans living in rural and underserved areas.2 The Veterans Health Administration (VHA) continues to increase community care spending, with a 13.8% increase in fiscal year 2024 and an expected cost of > $40 billion for 2025.3 One could argue this pays for access for remote patients and quality when services are unavailable, making it a direct application of the iron triangle.

The VA MISSION Act also bolstered the expansion of existing community care department staff to expediently facilitate and coordinate care and payments.2 Cost management and monitoring have become critical in predicting future staff requirements, maintaining functionality, and ensuring patients receive optimal care. The VHA purchases care through partner networks and defines these bundled health care services as standard episodes of care (SEOCs), which are “clinically related health care services for a specific unique illness or medical condition… over a defined period of time.”4 Medicare publishes its rates quarterly, and outpatient procedure pricing is readily available online.5 Along these same lines, the US Department of Veterans Affairs (VA) publishes a current list of available procedures and associated Current Procedure Technology (CPT) codes that are covered under its VA fee schedule for community care.

Unique challenges persist when using this system to accurately account for radiation oncology expenditures. This study was based on the current practices at the Richard L. Roudebush VA Medical Center (RLRVAMC), a large 1a hospital. A detailed analysis reveals the contemporaneous cost of radiation oncology cancer care from October 1, 2021, through February 1, 2024, highlights the challenges in SEOC definition and duration, communication issues between RLRVAMC and purchase partners, inconsistencies in billing, erroneous payments, and difficulty of cost categorization.

METHODS

Community care radiation oncology-related costs were examined from October 1, 2021, to February 1, 2024 for RLRVAMC, 6 months prior to billing data extraction. Figure 1 shows a simple radiation oncology patient pathway with consultation or visit, simulation and planning, and treatment, with codes used to check billing. It illustrates the expected relationships between the VHA (radiation oncology, primary, and specialty care) and community care (clinicians and radiation oncology treatment sites).

0525FED-AVAHO-RAD_F1

VHA standard operating procedures for a patient requesting community-based radiation oncology care require a board-certified radiation oncologist at RLRVAMC to review and approve the outside care request. Community care radiation oncology consultation data were accessed from the VA Corporate Data Warehouse (CDW) using Pyramid Analytics (V25.2). Nurses, physicians, and community care staff can add comments, forward consultations to other services, and mark them as complete or discontinued, when appropriate. Consultations not completed within 91 days are automatically discontinued. All community care requests from 2018 through 2024 were extracted; analysis began April 1, 2021, 6 months prior to the cost evaluation date of October 1, 2021.

An approved consultation is reviewed for eligibility by a nurse in the community care department and assigned an authorization number (a VA prefix followed by 12 digits). Billing codes are approved and organized by the community care networks, and all procedure codes should be captured and labeled under this number. The VAMC Community Care department obtains initial correspondence from the treating clinicians. Subsequent records from the treating radiation oncologist are expected to be scanned into the electronic health record and made accessible via the VA Joint Legacy Viewer (JLV) and Computerized Patient Record System (CPRS).

Radiation Oncology SEOC

The start date of the radiation oncology SEOC is determined by the community care nurse based on guidance established by the VA. It can be manually backdated or delayed, but current practice is to start at first visit or procedure code entry after approval from the VAMC Radiation Oncology department. Approved CPT codes from SEOC versions between October 1, 2021, and February 1, 2024, are in eAppendix 1 (available at doi:10.12788/fp.0585). These generally include 10 types of encounters, about 115 different laboratory tests, 115 imaging studies, 25 simulation and planning procedures, and 115 radiation treatment codes. The radiation oncology SEOCs during the study period had an approval duration of 180 days. Advanced Medical Cost Management Solutions software (AMCMS) is the VHA data analytics platform for community care medical service costs. AMCMS includes all individual CPT codes billed by specific radiation oncology SEOC versions. Data are refreshed monthly, and all charges were extracted on September 12, 2024, > 6 months after the final evaluated service date to allow for complete billing returns.6

0525FED-AVAHO-RAD_eApp1
Radiation Oncology-Specific Costs

The VA Close to Me (CTM) program was used to find 84 specific radiation oncology CPT codes, nearly all within the 77.XXX or G6.XXX series, which included all radiation oncology-specific (ROS) codes (except visits accrued during consultation and return appointments). ROS costs are those that could not be performed by any other service and include procedures related to radiation oncology simulation, treatment planning, treatment delivery (with or without image guidance), and physician or physicist management. All ROS costs should be included in a patient’s radiation oncology SEOC. Other costs that may accompany operating room or brachytherapy administration did not follow a 77.XXX or G6.XXX pattern but were included in total radiation therapy operating costs.

Data obtained from AMCMS and CTM included patient name and identifier; CPT billed amount; CPT paid amount; dates of service; number of claims; International Classification of Diseases, Tenth Revision (ICD) diagnosis; and VA authorization numbers. Only CTM listed code modifiers. Only items categorized as paid were included in the analysis. Charges associated with discontinued consultations that had accrued costs also were included. Codes that were not directly related to ROS were separately characterized as other and further subcategorized.

Deep Dive Categorization

All scanned documents tagged to the community consultation were accessed and evaluated for completeness by a radiation oncologist (RS). The presence or absence of consultation notes and treatment summaries was evaluated based on necessity (ie, not needed for continuation of care or treatment was not given). In the absence of a specific completion summary or follow-up note detailing the treatment modality, number of fractions, and treatment sites, available documentation, including clinical notes and billing information, was used. Radical or curative therapies were identified as courses expected to eradicate disease, including stereotactic ablative radiotherapy to the brain, lung, liver, and other organs. Palliative therapies included whole-brain radiotherapy or other low-dose treatments. If the patient received the intended course, this was categorized as full. If incomplete, it was considered partial.

Billing Deviations

The complete document review allowed for close evaluation of paid therapy and identification of gaps in billing (eg, charges not found in extracted data that should have occurred) for external beam radiotherapy patients. Conversely, extra charges, such as an additional weekly treatment management charge (CPT code 77427), would be noted. Patients were expected to have the number of treatments specified in the summary, a clinical treatment planning code, and weekly treatment management notes from physicians and physicists every 5 fractions. Consultations and follow-up visits were expected to have 1 visit code; CPT codes 99205 and 99215, respectively, were used to estimate costs in their absence.

Costs were based on Medicare rates as of January 1 of the year in which they were accrued. 7-10 Duplicates were charges with the same code, date, billed quantity, and paid amounts for a given patient. These would always be considered erroneous. Medicare treatment costs for procedures such as intensity modulated radiotherapy (CPT code 77385 or 77386) are available on the Medicare website. When reviewing locality deviations for 77427, there was a maximum of 33% increase in Medicare rates. Therefore, for treatment codes, one would expect the range to be at least the Medicare rate and maximally 33% higher. These rates are negotiated with insurance companies, but this range was used for the purpose of reviewing and adjusting large data sets.

RESULTS

Since 2018, > 500 community care consults have been placed by radiation oncology for treatment in the community, with more following implementation of the VA MISSION Act. Use of radiation oncology community care services annually increased during the study period for this facility (Table 1, Figure 2). Of the 325 community care consults placed from October 1, 2021, to February 1, 2024, 248 radiation oncology SEOCs were recorded with charges for 181 patients (range, 1-5 SEOCs). Long drive time was the rationale for > 97% of patients directed to community care (Supplemental materials, available at doi:10.12788/fp.0585). Based on AMCMS data, $22.2 million was billed and $2.7 million was paid (20%) for 8747 CPT codes. Each community care interval cost the VA a median (range) of $5000 ($8-$168,000 (Figure 3).

0525FED-AVAHO-RAD_T10525FED-AVAHO-RAD_F20525FED-AVAHO-RAD_F3

After reviewing ROS charges extracted from CTM, 20 additional patients had radiation oncology charges but did not have a radiation oncology SEOC for 268 episodes of care for 201 unique patients. In addition to the 20 patients who did not have a SEOC, 42 nonradiation oncology SEOCs contained 1148 radiation oncology codes, corresponding to almost $500,000 paid. Additional charges of about $416,000, which included biologic agents (eg, durvalumab, nivolumab), procedures (eg, mastectomies), and ambulance rides were inappropriately added to radiation oncology SEOCs.

While 77% of consultations were scanned into CPRS and JLV, only 54% of completion summaries were available with an estimated $115,000 in additional costs. The total adjusted costs was about $2.9 million. Almost 37% of SEOCs were for visits only. For the 166 SEOCs where patients received any radiation treatment or planning, the median cost was $18,000. Differences in SEOC pathways are shown in Figure 4. One hundred twenty-one SEOCs (45%) followed the standard pathway, with median SEOC costs of $15,500; when corrected for radiation-specific costs, the median cost increased to $18,000. When adjusted for billing irregularities, the median cost was $20,600. Ninety-nine SEOCs (37%) were for consultation/ follow-up visits only, with a median cost of $220. When omitting shared scans and nonradiation therapy costs and correcting for billing gaps, the median cost decreased to $170. A median of $9200 was paid per patient, with $12,900 for radiation therapy-specific costs and $13,300 adjusted for billing deviations. Narrowing to the 106 patients who received full, radical courses, the median SEOC, ROS, and adjusted radiation therapy costs increased to $19,400, $22,200, and $22,900, respectively (Table 2, Figure 5). Seventy-one SEOCs (26%) had already seen a radiation oncologist before the VA radiation oncology department was aware, and 49 SEOCs (18%) had retroactive approvals (Supplemental materials available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T20525FED-AVAHO-RAD_F40525FED-AVAHO-RAD_F5

Every consultation charge was reviewed. A typical patient following the standard pathway (eAppendix 2, available at doi:10.12788/ fp.0585) exhibited a predictable pattern of consultation payment, simulation and planning, multiple radiation treatments interspersed with treatment management visits and a cone-down phase, and finishing with a follow-up visit. A less predictable case with excess CPT codes, gaps in charges, and an additional unexpected palliative course is shown in eAppendix 3 (available at doi:10.12788/fp.0585). Gaps occurred in 42% of SEOCs with missed bills costing as much as $12,000. For example, a patient with lung cancer had a treatment summary note for lung cancer after completion that showed the patient received 30 fractions of 2 Gy, a typical course. Only 10 treatment codes and 3 of 6 weekly treatment management codes were available. There was a gap of 20 volumetric modulated arc therapy treatments, 3 physics weekly status checks, 3 physician managements notes, and a computed tomography simulation charge.

0525FED-AVAHO-RAD_eApp20525FED-AVAHO-RAD_eApp3

Between AMCMS and CTM, 10,005 CPT codes were evaluated; 1255 (12.5%) were unique to AMCMS (either related to the radiation oncology course, such as Evaluation and Management CPT codes or “other” unrelated codes) while 1158 (11.6%) were unique to CTM. Of the 7592 CPT codes shared between AMCMS and CTM, there was a discrepancy in 135 (1.8%); all were duplicates (CTM showed double payment while AMCMS showed $0 paid). The total CPT code costs came to $3.2 million with $560,000 unique to SEOCs and $500,000 unique to CTM. Treatment codes were the most common (33%) as shown in Table 3 and accounted for 55% of the cost ($1.8 million). About 700 CPT codes were considered “other,” typically for biologic therapeutic agents (Table 4 and eAppendix 4, available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T30525FED-AVAHO-RAD_T40525FED-AVAHO-RAD_eApp4

DISCUSSION

The current method of reporting radiation oncology costs used by VA is insufficient and misleading. Better data are needed to summarize purchased care costs to guide decisions about community care at the VA. Investigations into whether the extra costs for quality care (ie, expensive capital equipment, specialized staff, mandatory accreditations) are worthwhile if omitted at other facilities patients choose for their health care needs. No study has defined specialty care-specific costs by evaluating billing receipts from the CDW to answer the question. Kenamond et al highlight the need for radiation oncology for rural patients.11 Drive time was cited as the reason for community care referral for 97% of veterans, many of whom lived in rural locations. Of patients with rurality information who enrolled in community care, 57% came from rural or highly rural counties, and this ratio held for those who received full curative therapies. An executive administrator relying on AMCMS reports would see a median SEOC cost of $5000, but without ROS knowledge in coding, the administrator would miss many additional costs. For example, 2 patients who each had 5 SEOCs during the evaluated period, incurred a total cost of only $1800.

Additionally, an administrator could include miscategorized costs with significant ramifications. The 2 most expensive SEOCs were not typical radiation oncology treatments. A patient undergoing radium-223 dichloride therapy incurred charges exceeding $165,000, contributing disproportionately to the overall median cost analysis; this would normally be administered by the nuclear medicine department. Immunotherapy and chemotherapy are uniformly overseen by medical oncology services, but drug administration codes were still found in radiation oncology SEOCs. A patient (whose SEOC was discontinued but accrued charges) had an electrocardiogram interpretation for $8 as the SEOC cost; 3 other SEOCs continued to incur costs after being discontinued. There were 24 empty SEOCs for patients that had consults to the community, and 2 had notes stating treatment had been delivered yet there was no ROS costs or SEOC costs. Of the 268 encounters, 43% had some sort of billing irregularities (ie, missing treatment costs) that would be unlikely for a private practice to omit; it would be much more likely that the CDW miscategorized the payment despite confirmation of the 2 retrieval systems.

It would be inadvisable to make staffing decisions or forecast costs based on current SEOC reports without specialized curation. A simple yet effective improvement to the cost attribution process would be to restrict the analysis to encounters containing primary radiation treatment codes. This targeted approach allows more accurate identification of patients actively receiving radiation oncology treatment, while excluding those seen solely for consultations or follow-up visits. Implementing this refinement leads to a substantial increase in the median payment—from $5000 to $13,000—without requiring additional coding or data processing, thereby enhancing the accuracy of cost estimates with minimal effort.

Clarifying radiation oncology service costs requires addressing the time frame and services included, given laxity and interpretation of the SEOCs. VA community care departments have streamlined the reimbursement process at the expense of medical cost organization and accuracy; 86% of VA practitioners reported that ≥ 1 potential community health care partners had refused to work with the VA because of payment delays.12 Payments are contingent on correspondence from outside practices for community work. For radiation oncology, this includes the consultation but also critical radiation-related details of treatment, which were omitted nearly half the time. SEOC approval forms have many costly laboratory tests, imaging, and procedures that have little to do with radiation oncology cancer treatments but may be used in the workup and staging process; this creates noise when calculating radiation oncology fiscal cost.

The presumption that an episode of care equates to a completed radiation therapy course is incorrect; this occurs less than half of the time. An episode often refers to a return visit, or conversely, multiple treatment courses. As the patients’ medical homes are their VHA primary care practitioners, it would be particularly challenging to care for the patients without full treatment information, especially if adverse effects from therapy were to arise. As a tertiary specialty, radiation oncology does not seek out patients and are sent consultations from medical oncology, surgical, and medical oncologic specialties. Timesensitive processes such as workup, staging, and diagnosis often occur in parallel. This analysis revealed that patients see outside radiation oncologists prior to the VA. There are ≥ 100 patients who had radiation oncology codes without a radiation oncology SEOC or community care consultation, and in many cases, the consultation was placed after the patient was seen.

Given the lack of uniformity and standardization of patient traffic, the typical and expected pathways were insufficient to find the costs. Too many opportunities for errors and incorrect categorization of costs meant a different method would be necessary. Starting at the inception of the community care consult, only 1 diagnosis code can be entered. For patients with multiple diagnoses, one would not be able to tell what was treated without chart access. Radiation oncology consults come from primary and specialty care practitioners and nurses throughout the VA. Oftentimes, the referral would be solicited by the community radiation oncology clinic, diagnosing community specialty (ie, urology for a patient with prostate cancer), or indirectly from the patient through primary care. Many cases were retroactively approved as the veteran had already been consulted by the community care radiation oncologist. If the patient is drive-time eligible, it would be unlikely that they would leave and choose to return to the VA. There is no way for a facility VA service chief or administrator to mitigate VA community costs of care, especially as shown by the miscategorization of several codes. Database challenges exacerbate the issue: 1 patient changed her first and last name during this time frame, and 2 patients had the same name but different social security numbers. In order to strictly find costs between 2 discrete timepoints, 39 (15%) SEOCs were split and incomplete, and 6 SEOCs contained charges for 2 different patients. This was corrected, and all inadvertent charges were cancelled. Only 1 ICD code is allowed per community care consultation, so an investigation is required to find costs for patients with multiple sites of disease. Additionally, 5 of the patients marked for drive time were actually patients who received Gamma Knife and brachytherapy, services not available at the VA.

Hanks et al first attempted to calculate cost of radiation oncology services. External beam prostate cancer radiotherapy at 3 suburban California centers cost $6750 ($20,503 inflation adjusted) per patient before October 1984 and $5600 ($17,010 inflation adjusted) afterwards.13 According to the American Society for Radiation Oncology, Advocacy Radiation Oncology Case Rate Program Curative radiation courses should cost $20,000 to $30,000 and palliative courses should cost $10,000 to $15,000. These costs are consistent with totals demonstrated in this analysis and similar to the inflation-adjusted Hanks et al figures. Preliminary findings suggest that radiation treatment constituted more than half of the total expenditures, with a notable $4 million increase in adjusted cost compared to the Medicare rates, indicating significant variation. Direct comparisons with Medicaid or commercial payer rates remain unexplored.

Future Directions

During the study period, 201 patients received 186 courses of radiation therapy in the community, while 1014 patients were treated in-house for a total of 833 courses. A forthcoming analysis will directly compare the cost of in-house care with that of communitybased treatment, specifically breaking down expenditure differences by diagnosis. Future research should investigate strategies to align reimbursement with quality metrics, including the potential role of tertiary accreditation in incentivizing high-value care. Additional work is also warranted to assess patient out-ofpocket expenses across care settings and to benchmark VA reimbursement against Medicare, Medicaid, and private insurance rates. In any case, with the increasing possibility of fewer fractions for treatments such as stereotactic radiotherapy or palliative care therapy, there is a clear financial incentive to treat as frequently as allowed despite equal clinical outcomes.

CONCLUSIONS

Veterans increasingly choose to receive care closer to home if the option is available. In the VA iron triangle, cost comes at the expense of access but quantifying this has proved elusive in the cost accounting model currently used at the VA.1 The inclusion of all charges loosely associated with SEOCs significantly impairs the ability to conduct meaningful cost analyses. The current VA methodology not only introduces substantial noise into the data but also leads to a marked underestimation of the true cost of care delivered in community settings. Such misrepresentation risks driving policy decisions that could inappropriately reduce or eliminate in-house radiation oncology services. Categorizing costs effectively in the VA could assist in making managerial and administrative decisions and would prevent damaging service lines based on misleading or incorrect data. A system which differentiates between patients who have received any treatment codes vs those who have not would increase accuracy.

William Kissick’s description of health care’s iron triangle in 1994 still resonates. Access, quality, and cost will always come at the expense of the others.1 In 2018, Congress passed the VA MISSION Act, allowing patients to pursue community care options for extended waits (> 28 days) or longer distance drive times of > 60 minutes for specialty care services, such as radiation oncology. According to Albanese et al, the VA MISSION Act sought to address gaps in care for veterans living in rural and underserved areas.2 The Veterans Health Administration (VHA) continues to increase community care spending, with a 13.8% increase in fiscal year 2024 and an expected cost of > $40 billion for 2025.3 One could argue this pays for access for remote patients and quality when services are unavailable, making it a direct application of the iron triangle.

The VA MISSION Act also bolstered the expansion of existing community care department staff to expediently facilitate and coordinate care and payments.2 Cost management and monitoring have become critical in predicting future staff requirements, maintaining functionality, and ensuring patients receive optimal care. The VHA purchases care through partner networks and defines these bundled health care services as standard episodes of care (SEOCs), which are “clinically related health care services for a specific unique illness or medical condition… over a defined period of time.”4 Medicare publishes its rates quarterly, and outpatient procedure pricing is readily available online.5 Along these same lines, the US Department of Veterans Affairs (VA) publishes a current list of available procedures and associated Current Procedure Technology (CPT) codes that are covered under its VA fee schedule for community care.

Unique challenges persist when using this system to accurately account for radiation oncology expenditures. This study was based on the current practices at the Richard L. Roudebush VA Medical Center (RLRVAMC), a large 1a hospital. A detailed analysis reveals the contemporaneous cost of radiation oncology cancer care from October 1, 2021, through February 1, 2024, highlights the challenges in SEOC definition and duration, communication issues between RLRVAMC and purchase partners, inconsistencies in billing, erroneous payments, and difficulty of cost categorization.

METHODS

Community care radiation oncology-related costs were examined from October 1, 2021, to February 1, 2024 for RLRVAMC, 6 months prior to billing data extraction. Figure 1 shows a simple radiation oncology patient pathway with consultation or visit, simulation and planning, and treatment, with codes used to check billing. It illustrates the expected relationships between the VHA (radiation oncology, primary, and specialty care) and community care (clinicians and radiation oncology treatment sites).

0525FED-AVAHO-RAD_F1

VHA standard operating procedures for a patient requesting community-based radiation oncology care require a board-certified radiation oncologist at RLRVAMC to review and approve the outside care request. Community care radiation oncology consultation data were accessed from the VA Corporate Data Warehouse (CDW) using Pyramid Analytics (V25.2). Nurses, physicians, and community care staff can add comments, forward consultations to other services, and mark them as complete or discontinued, when appropriate. Consultations not completed within 91 days are automatically discontinued. All community care requests from 2018 through 2024 were extracted; analysis began April 1, 2021, 6 months prior to the cost evaluation date of October 1, 2021.

An approved consultation is reviewed for eligibility by a nurse in the community care department and assigned an authorization number (a VA prefix followed by 12 digits). Billing codes are approved and organized by the community care networks, and all procedure codes should be captured and labeled under this number. The VAMC Community Care department obtains initial correspondence from the treating clinicians. Subsequent records from the treating radiation oncologist are expected to be scanned into the electronic health record and made accessible via the VA Joint Legacy Viewer (JLV) and Computerized Patient Record System (CPRS).

Radiation Oncology SEOC

The start date of the radiation oncology SEOC is determined by the community care nurse based on guidance established by the VA. It can be manually backdated or delayed, but current practice is to start at first visit or procedure code entry after approval from the VAMC Radiation Oncology department. Approved CPT codes from SEOC versions between October 1, 2021, and February 1, 2024, are in eAppendix 1 (available at doi:10.12788/fp.0585). These generally include 10 types of encounters, about 115 different laboratory tests, 115 imaging studies, 25 simulation and planning procedures, and 115 radiation treatment codes. The radiation oncology SEOCs during the study period had an approval duration of 180 days. Advanced Medical Cost Management Solutions software (AMCMS) is the VHA data analytics platform for community care medical service costs. AMCMS includes all individual CPT codes billed by specific radiation oncology SEOC versions. Data are refreshed monthly, and all charges were extracted on September 12, 2024, > 6 months after the final evaluated service date to allow for complete billing returns.6

0525FED-AVAHO-RAD_eApp1
Radiation Oncology-Specific Costs

The VA Close to Me (CTM) program was used to find 84 specific radiation oncology CPT codes, nearly all within the 77.XXX or G6.XXX series, which included all radiation oncology-specific (ROS) codes (except visits accrued during consultation and return appointments). ROS costs are those that could not be performed by any other service and include procedures related to radiation oncology simulation, treatment planning, treatment delivery (with or without image guidance), and physician or physicist management. All ROS costs should be included in a patient’s radiation oncology SEOC. Other costs that may accompany operating room or brachytherapy administration did not follow a 77.XXX or G6.XXX pattern but were included in total radiation therapy operating costs.

Data obtained from AMCMS and CTM included patient name and identifier; CPT billed amount; CPT paid amount; dates of service; number of claims; International Classification of Diseases, Tenth Revision (ICD) diagnosis; and VA authorization numbers. Only CTM listed code modifiers. Only items categorized as paid were included in the analysis. Charges associated with discontinued consultations that had accrued costs also were included. Codes that were not directly related to ROS were separately characterized as other and further subcategorized.

Deep Dive Categorization

All scanned documents tagged to the community consultation were accessed and evaluated for completeness by a radiation oncologist (RS). The presence or absence of consultation notes and treatment summaries was evaluated based on necessity (ie, not needed for continuation of care or treatment was not given). In the absence of a specific completion summary or follow-up note detailing the treatment modality, number of fractions, and treatment sites, available documentation, including clinical notes and billing information, was used. Radical or curative therapies were identified as courses expected to eradicate disease, including stereotactic ablative radiotherapy to the brain, lung, liver, and other organs. Palliative therapies included whole-brain radiotherapy or other low-dose treatments. If the patient received the intended course, this was categorized as full. If incomplete, it was considered partial.

Billing Deviations

The complete document review allowed for close evaluation of paid therapy and identification of gaps in billing (eg, charges not found in extracted data that should have occurred) for external beam radiotherapy patients. Conversely, extra charges, such as an additional weekly treatment management charge (CPT code 77427), would be noted. Patients were expected to have the number of treatments specified in the summary, a clinical treatment planning code, and weekly treatment management notes from physicians and physicists every 5 fractions. Consultations and follow-up visits were expected to have 1 visit code; CPT codes 99205 and 99215, respectively, were used to estimate costs in their absence.

Costs were based on Medicare rates as of January 1 of the year in which they were accrued. 7-10 Duplicates were charges with the same code, date, billed quantity, and paid amounts for a given patient. These would always be considered erroneous. Medicare treatment costs for procedures such as intensity modulated radiotherapy (CPT code 77385 or 77386) are available on the Medicare website. When reviewing locality deviations for 77427, there was a maximum of 33% increase in Medicare rates. Therefore, for treatment codes, one would expect the range to be at least the Medicare rate and maximally 33% higher. These rates are negotiated with insurance companies, but this range was used for the purpose of reviewing and adjusting large data sets.

RESULTS

Since 2018, > 500 community care consults have been placed by radiation oncology for treatment in the community, with more following implementation of the VA MISSION Act. Use of radiation oncology community care services annually increased during the study period for this facility (Table 1, Figure 2). Of the 325 community care consults placed from October 1, 2021, to February 1, 2024, 248 radiation oncology SEOCs were recorded with charges for 181 patients (range, 1-5 SEOCs). Long drive time was the rationale for > 97% of patients directed to community care (Supplemental materials, available at doi:10.12788/fp.0585). Based on AMCMS data, $22.2 million was billed and $2.7 million was paid (20%) for 8747 CPT codes. Each community care interval cost the VA a median (range) of $5000 ($8-$168,000 (Figure 3).

0525FED-AVAHO-RAD_T10525FED-AVAHO-RAD_F20525FED-AVAHO-RAD_F3

After reviewing ROS charges extracted from CTM, 20 additional patients had radiation oncology charges but did not have a radiation oncology SEOC for 268 episodes of care for 201 unique patients. In addition to the 20 patients who did not have a SEOC, 42 nonradiation oncology SEOCs contained 1148 radiation oncology codes, corresponding to almost $500,000 paid. Additional charges of about $416,000, which included biologic agents (eg, durvalumab, nivolumab), procedures (eg, mastectomies), and ambulance rides were inappropriately added to radiation oncology SEOCs.

While 77% of consultations were scanned into CPRS and JLV, only 54% of completion summaries were available with an estimated $115,000 in additional costs. The total adjusted costs was about $2.9 million. Almost 37% of SEOCs were for visits only. For the 166 SEOCs where patients received any radiation treatment or planning, the median cost was $18,000. Differences in SEOC pathways are shown in Figure 4. One hundred twenty-one SEOCs (45%) followed the standard pathway, with median SEOC costs of $15,500; when corrected for radiation-specific costs, the median cost increased to $18,000. When adjusted for billing irregularities, the median cost was $20,600. Ninety-nine SEOCs (37%) were for consultation/ follow-up visits only, with a median cost of $220. When omitting shared scans and nonradiation therapy costs and correcting for billing gaps, the median cost decreased to $170. A median of $9200 was paid per patient, with $12,900 for radiation therapy-specific costs and $13,300 adjusted for billing deviations. Narrowing to the 106 patients who received full, radical courses, the median SEOC, ROS, and adjusted radiation therapy costs increased to $19,400, $22,200, and $22,900, respectively (Table 2, Figure 5). Seventy-one SEOCs (26%) had already seen a radiation oncologist before the VA radiation oncology department was aware, and 49 SEOCs (18%) had retroactive approvals (Supplemental materials available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T20525FED-AVAHO-RAD_F40525FED-AVAHO-RAD_F5

Every consultation charge was reviewed. A typical patient following the standard pathway (eAppendix 2, available at doi:10.12788/ fp.0585) exhibited a predictable pattern of consultation payment, simulation and planning, multiple radiation treatments interspersed with treatment management visits and a cone-down phase, and finishing with a follow-up visit. A less predictable case with excess CPT codes, gaps in charges, and an additional unexpected palliative course is shown in eAppendix 3 (available at doi:10.12788/fp.0585). Gaps occurred in 42% of SEOCs with missed bills costing as much as $12,000. For example, a patient with lung cancer had a treatment summary note for lung cancer after completion that showed the patient received 30 fractions of 2 Gy, a typical course. Only 10 treatment codes and 3 of 6 weekly treatment management codes were available. There was a gap of 20 volumetric modulated arc therapy treatments, 3 physics weekly status checks, 3 physician managements notes, and a computed tomography simulation charge.

0525FED-AVAHO-RAD_eApp20525FED-AVAHO-RAD_eApp3

Between AMCMS and CTM, 10,005 CPT codes were evaluated; 1255 (12.5%) were unique to AMCMS (either related to the radiation oncology course, such as Evaluation and Management CPT codes or “other” unrelated codes) while 1158 (11.6%) were unique to CTM. Of the 7592 CPT codes shared between AMCMS and CTM, there was a discrepancy in 135 (1.8%); all were duplicates (CTM showed double payment while AMCMS showed $0 paid). The total CPT code costs came to $3.2 million with $560,000 unique to SEOCs and $500,000 unique to CTM. Treatment codes were the most common (33%) as shown in Table 3 and accounted for 55% of the cost ($1.8 million). About 700 CPT codes were considered “other,” typically for biologic therapeutic agents (Table 4 and eAppendix 4, available at doi:10.12788/fp.0585).

0525FED-AVAHO-RAD_T30525FED-AVAHO-RAD_T40525FED-AVAHO-RAD_eApp4

DISCUSSION

The current method of reporting radiation oncology costs used by VA is insufficient and misleading. Better data are needed to summarize purchased care costs to guide decisions about community care at the VA. Investigations into whether the extra costs for quality care (ie, expensive capital equipment, specialized staff, mandatory accreditations) are worthwhile if omitted at other facilities patients choose for their health care needs. No study has defined specialty care-specific costs by evaluating billing receipts from the CDW to answer the question. Kenamond et al highlight the need for radiation oncology for rural patients.11 Drive time was cited as the reason for community care referral for 97% of veterans, many of whom lived in rural locations. Of patients with rurality information who enrolled in community care, 57% came from rural or highly rural counties, and this ratio held for those who received full curative therapies. An executive administrator relying on AMCMS reports would see a median SEOC cost of $5000, but without ROS knowledge in coding, the administrator would miss many additional costs. For example, 2 patients who each had 5 SEOCs during the evaluated period, incurred a total cost of only $1800.

Additionally, an administrator could include miscategorized costs with significant ramifications. The 2 most expensive SEOCs were not typical radiation oncology treatments. A patient undergoing radium-223 dichloride therapy incurred charges exceeding $165,000, contributing disproportionately to the overall median cost analysis; this would normally be administered by the nuclear medicine department. Immunotherapy and chemotherapy are uniformly overseen by medical oncology services, but drug administration codes were still found in radiation oncology SEOCs. A patient (whose SEOC was discontinued but accrued charges) had an electrocardiogram interpretation for $8 as the SEOC cost; 3 other SEOCs continued to incur costs after being discontinued. There were 24 empty SEOCs for patients that had consults to the community, and 2 had notes stating treatment had been delivered yet there was no ROS costs or SEOC costs. Of the 268 encounters, 43% had some sort of billing irregularities (ie, missing treatment costs) that would be unlikely for a private practice to omit; it would be much more likely that the CDW miscategorized the payment despite confirmation of the 2 retrieval systems.

It would be inadvisable to make staffing decisions or forecast costs based on current SEOC reports without specialized curation. A simple yet effective improvement to the cost attribution process would be to restrict the analysis to encounters containing primary radiation treatment codes. This targeted approach allows more accurate identification of patients actively receiving radiation oncology treatment, while excluding those seen solely for consultations or follow-up visits. Implementing this refinement leads to a substantial increase in the median payment—from $5000 to $13,000—without requiring additional coding or data processing, thereby enhancing the accuracy of cost estimates with minimal effort.

Clarifying radiation oncology service costs requires addressing the time frame and services included, given laxity and interpretation of the SEOCs. VA community care departments have streamlined the reimbursement process at the expense of medical cost organization and accuracy; 86% of VA practitioners reported that ≥ 1 potential community health care partners had refused to work with the VA because of payment delays.12 Payments are contingent on correspondence from outside practices for community work. For radiation oncology, this includes the consultation but also critical radiation-related details of treatment, which were omitted nearly half the time. SEOC approval forms have many costly laboratory tests, imaging, and procedures that have little to do with radiation oncology cancer treatments but may be used in the workup and staging process; this creates noise when calculating radiation oncology fiscal cost.

The presumption that an episode of care equates to a completed radiation therapy course is incorrect; this occurs less than half of the time. An episode often refers to a return visit, or conversely, multiple treatment courses. As the patients’ medical homes are their VHA primary care practitioners, it would be particularly challenging to care for the patients without full treatment information, especially if adverse effects from therapy were to arise. As a tertiary specialty, radiation oncology does not seek out patients and are sent consultations from medical oncology, surgical, and medical oncologic specialties. Timesensitive processes such as workup, staging, and diagnosis often occur in parallel. This analysis revealed that patients see outside radiation oncologists prior to the VA. There are ≥ 100 patients who had radiation oncology codes without a radiation oncology SEOC or community care consultation, and in many cases, the consultation was placed after the patient was seen.

Given the lack of uniformity and standardization of patient traffic, the typical and expected pathways were insufficient to find the costs. Too many opportunities for errors and incorrect categorization of costs meant a different method would be necessary. Starting at the inception of the community care consult, only 1 diagnosis code can be entered. For patients with multiple diagnoses, one would not be able to tell what was treated without chart access. Radiation oncology consults come from primary and specialty care practitioners and nurses throughout the VA. Oftentimes, the referral would be solicited by the community radiation oncology clinic, diagnosing community specialty (ie, urology for a patient with prostate cancer), or indirectly from the patient through primary care. Many cases were retroactively approved as the veteran had already been consulted by the community care radiation oncologist. If the patient is drive-time eligible, it would be unlikely that they would leave and choose to return to the VA. There is no way for a facility VA service chief or administrator to mitigate VA community costs of care, especially as shown by the miscategorization of several codes. Database challenges exacerbate the issue: 1 patient changed her first and last name during this time frame, and 2 patients had the same name but different social security numbers. In order to strictly find costs between 2 discrete timepoints, 39 (15%) SEOCs were split and incomplete, and 6 SEOCs contained charges for 2 different patients. This was corrected, and all inadvertent charges were cancelled. Only 1 ICD code is allowed per community care consultation, so an investigation is required to find costs for patients with multiple sites of disease. Additionally, 5 of the patients marked for drive time were actually patients who received Gamma Knife and brachytherapy, services not available at the VA.

Hanks et al first attempted to calculate cost of radiation oncology services. External beam prostate cancer radiotherapy at 3 suburban California centers cost $6750 ($20,503 inflation adjusted) per patient before October 1984 and $5600 ($17,010 inflation adjusted) afterwards.13 According to the American Society for Radiation Oncology, Advocacy Radiation Oncology Case Rate Program Curative radiation courses should cost $20,000 to $30,000 and palliative courses should cost $10,000 to $15,000. These costs are consistent with totals demonstrated in this analysis and similar to the inflation-adjusted Hanks et al figures. Preliminary findings suggest that radiation treatment constituted more than half of the total expenditures, with a notable $4 million increase in adjusted cost compared to the Medicare rates, indicating significant variation. Direct comparisons with Medicaid or commercial payer rates remain unexplored.

Future Directions

During the study period, 201 patients received 186 courses of radiation therapy in the community, while 1014 patients were treated in-house for a total of 833 courses. A forthcoming analysis will directly compare the cost of in-house care with that of communitybased treatment, specifically breaking down expenditure differences by diagnosis. Future research should investigate strategies to align reimbursement with quality metrics, including the potential role of tertiary accreditation in incentivizing high-value care. Additional work is also warranted to assess patient out-ofpocket expenses across care settings and to benchmark VA reimbursement against Medicare, Medicaid, and private insurance rates. In any case, with the increasing possibility of fewer fractions for treatments such as stereotactic radiotherapy or palliative care therapy, there is a clear financial incentive to treat as frequently as allowed despite equal clinical outcomes.

CONCLUSIONS

Veterans increasingly choose to receive care closer to home if the option is available. In the VA iron triangle, cost comes at the expense of access but quantifying this has proved elusive in the cost accounting model currently used at the VA.1 The inclusion of all charges loosely associated with SEOCs significantly impairs the ability to conduct meaningful cost analyses. The current VA methodology not only introduces substantial noise into the data but also leads to a marked underestimation of the true cost of care delivered in community settings. Such misrepresentation risks driving policy decisions that could inappropriately reduce or eliminate in-house radiation oncology services. Categorizing costs effectively in the VA could assist in making managerial and administrative decisions and would prevent damaging service lines based on misleading or incorrect data. A system which differentiates between patients who have received any treatment codes vs those who have not would increase accuracy.

References
  1. Kissick W. Medicine’s Dilemmas: Infinite Needs Versus Finite Resources. 1st ed. Yale University Press; 1994.
  2. Albanese AP, Bope ET, Sanders KM, Bowman M. The VA MISSION Act of 2018: a potential game changer for rural GME expansion and veteran health care. J Rural Health. 2020;36(1):133-136. doi:10.1111/jrh.12360
  3. Office of Management and Budget (US). Budget of the United States Government, Fiscal Year 2025. Washington, DC: US Government Publishing Office; 2024. Available from: US Department of Veterans Affairs FY 2025 Budget Submission: Budget in Brief.
  4. US Department of Veterans Affairs. Veteran care claims. Accessed April 3, 2025. https://www.va.gov/COMMUNITYCARE/revenue-ops/Veteran-Care-Claims.asp
  5. US Centers for Medicare and Medicaid Services. Accessed April 3, 2025. Procedure price lookup https://www.medicare.gov/procedure-price-lookup
  6. US Department of Veterans Affairs. WellHive -Enterprise. Accessed April 3, 2025. https://department.va.gov/privacy/wp-content/uploads/sites/5/2023/05/FY23WellHiveEnterprisePIA.pdf
  7. US Centers for Medicare and Medicaid Services. RVU21a physician fee schedule, January 2021 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu21a
  8. US Centers for Medicare and Medicaid Services. RVU22a physician fee schedule, January 2022 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu22a
  9. US Centers for Medicare and Medicaid Services. RVU23a physician fee schedule, January 2023 release. Accessed April 3, 2025. https://www.cms.gov/medicare/medicare-fee-service-payment/physicianfeesched/pfs-relative-value-files/rvu23a
  10. US Centers for Medicare and Medicaid Services. RVU23a Medicare Physician Fee Schedule rates effective January 1, 2024, through March 8, 2024. Accessed on April 3, 2025. https://www.cms.gov/medicare/payment/fee-schedules/physician/pfs-relative-value-files/rvu24a
  11. Kenamond MC, Mourad WF, Randall ME, Kaushal A. No oncology patient left behind: challenges and solutions in rural radiation oncology. Lancet Reg Health Am. 2022;13:100289. doi:10.1016/j.lana.2022.100289
  12. Mattocks KM, Kroll-Desrosiers A, Kinney R, Elwy AR, Cunningham KJ, Mengeling MA. Understanding VA’s use of and relationships with community care providers under the MISSION Act. Med Care. 2021;59(Suppl 3):S252-S258. doi:10.1097/MLR.0000000000001545
  13. Hanks GE, Dunlap K. A comparison of the cost of various treatment methods for early cancer of the prostate. Int J Radiat Oncol Biol Phys. 1986;12(10):1879-1881. doi:10.1016/0360-3016(86)90334-2
  14. American Society of Radiation Oncology. Radiation oncology case rate program (ROCR). Accessed April 3, 2025. https://www.astro.org/advocacy/key-issues-8f3e5a3b76643265ee93287d79c4fc40/rocr
References
  1. Kissick W. Medicine’s Dilemmas: Infinite Needs Versus Finite Resources. 1st ed. Yale University Press; 1994.
  2. Albanese AP, Bope ET, Sanders KM, Bowman M. The VA MISSION Act of 2018: a potential game changer for rural GME expansion and veteran health care. J Rural Health. 2020;36(1):133-136. doi:10.1111/jrh.12360
  3. Office of Management and Budget (US). Budget of the United States Government, Fiscal Year 2025. Washington, DC: US Government Publishing Office; 2024. Available from: US Department of Veterans Affairs FY 2025 Budget Submission: Budget in Brief.
  4. US Department of Veterans Affairs. Veteran care claims. Accessed April 3, 2025. https://www.va.gov/COMMUNITYCARE/revenue-ops/Veteran-Care-Claims.asp
  5. US Centers for Medicare and Medicaid Services. Accessed April 3, 2025. Procedure price lookup https://www.medicare.gov/procedure-price-lookup
  6. US Department of Veterans Affairs. WellHive -Enterprise. Accessed April 3, 2025. https://department.va.gov/privacy/wp-content/uploads/sites/5/2023/05/FY23WellHiveEnterprisePIA.pdf
  7. US Centers for Medicare and Medicaid Services. RVU21a physician fee schedule, January 2021 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu21a
  8. US Centers for Medicare and Medicaid Services. RVU22a physician fee schedule, January 2022 release. Accessed April 3, 2025. https://www.cms.gov/medicaremedicare-fee-service-paymentphysicianfeeschedpfs-relative-value-files/rvu22a
  9. US Centers for Medicare and Medicaid Services. RVU23a physician fee schedule, January 2023 release. Accessed April 3, 2025. https://www.cms.gov/medicare/medicare-fee-service-payment/physicianfeesched/pfs-relative-value-files/rvu23a
  10. US Centers for Medicare and Medicaid Services. RVU23a Medicare Physician Fee Schedule rates effective January 1, 2024, through March 8, 2024. Accessed on April 3, 2025. https://www.cms.gov/medicare/payment/fee-schedules/physician/pfs-relative-value-files/rvu24a
  11. Kenamond MC, Mourad WF, Randall ME, Kaushal A. No oncology patient left behind: challenges and solutions in rural radiation oncology. Lancet Reg Health Am. 2022;13:100289. doi:10.1016/j.lana.2022.100289
  12. Mattocks KM, Kroll-Desrosiers A, Kinney R, Elwy AR, Cunningham KJ, Mengeling MA. Understanding VA’s use of and relationships with community care providers under the MISSION Act. Med Care. 2021;59(Suppl 3):S252-S258. doi:10.1097/MLR.0000000000001545
  13. Hanks GE, Dunlap K. A comparison of the cost of various treatment methods for early cancer of the prostate. Int J Radiat Oncol Biol Phys. 1986;12(10):1879-1881. doi:10.1016/0360-3016(86)90334-2
  14. American Society of Radiation Oncology. Radiation oncology case rate program (ROCR). Accessed April 3, 2025. https://www.astro.org/advocacy/key-issues-8f3e5a3b76643265ee93287d79c4fc40/rocr
Issue
Federal Practitioner - 42(5)s
Issue
Federal Practitioner - 42(5)s
Page Number
S30-S39
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Mapping Pathology Work Associated With Precision Oncology Testing

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Mapping Pathology Work Associated With Precision Oncology Testing

Comprehensive genomic profiling (CGP) is becoming progressively common and appropriate as the array of molecular targets expands. However, most hospital laboratories in the United States do not perform CGP assays in-house; instead, these tests are sent to reference laboratories. As evidenced by Inal et al, only a minority of guideline-indicated molecular testing is performed.1

The workload associated with referral testing is a barrier to increased use of such tests; streamlined processes in pathology might increase molecular test use. At 6 high-complexity US Department of Veterans Affairs (VA) medical centers (VAMCs) (Manhattan, Los Angeles, San Diego, Denver, Kansas City, and Salisbury, Maryland) ranging from 150 to 750 beds, a consult process for anatomic pathology molecular testing has increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care. This report comprehensively describes and maps the anatomic pathology molecular testing consult process at a VAMC. We present areas of inefficiency and a target state process map that incorporates best practices.

MOLECULAR TESTING CONSULT PROCESS

At the Kansas City VAMC (KCVAMC), a consult process for anatomic pathology molecular testing was introduced in 2021. Prior to this, requesting anatomic pathology molecular testing was not standardized. A variety of opportunities and methods were used for requests (eg, phone, page, Teams message, email, Computerized Patient Record System alert; or in-person during tumor board, an office meeting, or in passing). Requests were not documented in a standardized way, resulting in duplicate requests. Testing status and updates were documented outside the medical record, so requests for status updates (via various opportunities and methods) were common and redundant. Data from the year preceding consult implementation and the year following consult implementation have demonstrated increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care.

Consult Request

The precision oncology testing process starts with a health care practitioner (HCP) request on behalf of any physician or advanced practice registered nurse. It can be placed by any health care employee and directed to a designated employee in the pathology department. The request is ultimately reviewed by a pathologist (Figure 1). At KCVAMC, this request comes in the form of a consult in the electronic health record (EHR) from the ordering HCP to a pathologist. The KCVAMC pathology consult form was previously published with a discussion of the rationale for this process as opposed to a laboratory order process.2 This consult form ensures ordering HCPs supply all necessary information for the pathologist to approve the request and order the test without needing to, in most cases, contact the ordering HCP for clarification or additional information. The form asks the ordering HCP to specify which test is being requested and why. Within the Veterans Health Administration (VHA) there are local and national contracts with many laboratories with hundreds of precision oncology tests to choose from. Consulting with a pathologist is necessary to determine which test is most appropriate.

0525FED-AVAHO_PATH_F1

The precision oncology consult form cannot be submitted without completing all required fields. It also contains indications for the test the ordering HCP selects to minimize unintentionally inappropriate orders. The form asks which tissue the requestor expects the test to be performed on. The requestor must provide contact information for the originating institution when the tissue was collected outside the VHA. The consult form also asks whether another anatomic site is accessible and could be biopsied without unacceptable risk or impracticality, should all previously collected tissue be insufficient. For CGP requests, this allows the pathologist to determine the appropriateness of liquid biopsy without having to reach out to the ordering HCP or wait for the question to be addressed at a tumor board. When a companion diagnostic is available for a test, the ordering HCP is asked which drug will be used so that the most appropriate assay is chosen.

Consult Review

Pathology service involvement begins with pathologist review of the consult form to ensure that the correct test is indicated. Depending on the resources and preferences at a site, consults can be directed to and reviewed by the pathologist associated with the corresponding pathology specimen or to a single pathologist or group of pathologists charged with attending to consults.

The patient’s EHR is reviewed to verify that the test has not already been performed and to determine which tissue to review. Previous surgical pathology reports are examined to assess whether sufficient tissue is available for testing, which may be determined without the need for direct slide examination. Pathologists often use wording such as “rare cells” or in some cases specify that there are not enough lesional cells for ancillary testing. In biopsy reports, the percentage of tissue occupied by lesional cells or the greatest linear length of tumor cells is often documented. As for quality, pathologists may note that a specimen is largely necrotic, and gross descriptions will indicate if a specimen was compromised for molecular analysis by exposure to fixatives such as Bouin’s solution, B-5, or decalcifying agents that contain strong acids.

Tissue Retrieval

If, after such evaluation, the test is indicated and there is tissue that could be sufficient for testing, retrieval of the tissue is pursued. For in-house cases, the pathologist reviews the corresponding surgical pathology report to determine which blocks and slides to pull from the archives. In the cancer checklist, some pathologists specify the best block for subsequent ancillary studies. From the final diagnosis and gross description, the pathologist can determine which blocks are most likely to contain lesional tissue. These slides are retrieved from the archives.

For cases collected at an outside institution (other VHA facility or non-VHA facility/institution), the outside institution must be contacted to retrieve the needed slides and blocks. The phone numbers, fax numbers, email addresses, and mailing addresses for outside institutions are housed in an electronic file and are specific to the point of contact for such requests. Maintaining a record of contacts increases efficiency of the overall process; gathering contact information and successfully requesting tissue often involves multiple automated answering systems, misdirected calls, and failed attempts.

Tissue Review

After retrieving in-house tissue, the pathologist can proceed directly to slide review. For outside cases, the case must first be accessioned so that after review of the slides the pathologist can issue a report to confirm the outside diagnosis. In reviewing the slides, the pathologist looks to see that the diagnosis is correct, that there is a sufficient number of lesional cells in a section, that the lesional cells are of a sufficient concentration in a section, or subsection of the section that could be dissected, and that the cells are viable. Depending on the requested assay and the familiarity of the pathologist with that assay, the pathologist may need to look up the technical requirements of the assay and capabilities of the testing company. Assays vary in sensitivity and require differing amounts and concentrations of tumor. Some companies will dissect tissue, others will not.

If there is sufficient tissue in the material reviewed, the corresponding blocks are retrieved from in-house archives or requests are placed for outside blocks or unstained slides. If there was not enough tissue for testing, the same process is repeated to retrieve and evaluate any other specimens the patient may have. If there are no other specimens to review, this is simply communicated to the ordering HCP via the consult. If the patient is a candidate for liquid biopsy—ie, current specimens are of insufficient quality and/or quantity and a new tissue sample cannot be obtained due to unacceptable risk or impracticality—the order is placed at this time.

Tissue Transport and Testing

Unstained slides need to be cut unless blocks are sent. Slides, blocks, reports, and requisition forms are packaged for transport. An accession number is created for the precision oncology molecular laboratory test in the clinical laboratory section of the EHR system. The clinical laboratory accession number provides a way of tracking sendout testing status. The case is accessioned just prior to placement in the mail so that when an accession number appears in the EHR, the ordering HCP knows the case has been sent out. When results are received, the clinical laboratory accession is completed and a comment is added to indicate where in the EHR to find the report or, when applicable, notes that testing failed.

RESULT REPORTING

When a result becomes available, the report file is downloaded from the vendor portal. This full report is securely transmitted to the ordering HCP. The file is then scanned into the EHR. Additionally, salient findings from the report are abstracted by the pathologist for inclusion as a supplement to the anatomic pathology case. This step ensures that this information travels with the anatomic pathology report if the patient’s care is transferred elsewhere. Templates are used to ensure essential data is captured based on the type of test. The template reminds the pathologist to comment on things such as variants that may represent clonal hematopoiesis, variants that may be germline, and variants that qualify a patient for germline testing. Even with the template, the pathologist must spend significant time reviewing the chart for things such as personal cancer history, other medical history, other masses on imaging, family history, previous surgical pathology reports, and previous molecular testing.

If results are suboptimal, recommendations for repeat testing are made based on the consult response to the question of repeat biopsy feasibility and review of previous pathology reports. The final consult report is added as a consult note, the consult is completed, and the original vendor report file is associated with the consult note in the EHR.

Ancillary Testing Technician

Due to chronic KCVAMC understaffing in the clerical office, gross room, and histology, most of the consult tasks are performed by a pathologist. In an ideal scenario, the pathology staff would divide its time between a pathologist and another dedicated laboratory position, such as an ancillary testing technician (ATT). The ATT can assume responsibilities that do not require the expertise of a pathologist (Figure 2). In such a process, the only steps that would require a pathologist would be review of requests and slides and completion of the interpretive report. All other steps could be accomplished by someone who lacks certifications, laboratory experience, or postsecondary education.

0525FED-AVAHO_PATH_F2

The ATT can receive the requests and retrieve slides and blocks. After slides have been reviewed by a pathologist, the pathologist can inform the ATT which slides or blocks testing will be performed on, provide any additional necessary information for completing the order, and answer any questions. For send-out tests, this allows the ATT to independently complete online portal forms and all other physical requirements prior to delivery of the slides and blocks to specimen processors in the laboratory.

ATTs can keep the ordering HCPs informed of status and be identified as the point of contact for all status inquiries. ATTs can receive results and get outside reports scanned into the EHR. Finally, ATTs can use pathologistdesigned templates to transpose information from outside reports such that a provisional report is prepared and a pathologist does not spend time duplicating information from the outside report. The pathologist can then complete the report with information requiring medical judgment that enhances care.

Optimal Pathologist Involvement

Only 3 steps in the process (request review, tissue review, and completion of an interpretive report) require a pathologist, which are necessary for optimal care and to address barriers to precision oncology.3 While the laboratory may consume only 5% of a health system budget, optimal laboratory use could prevent as much as 30% of avoidable costs.4 These estimates are widely recognized and addressed by campaigns such as Choosing Wisely, as well as programming of alerts and hard stops in EHR systems to reduce duplicate or otherwise inappropriate orders. The tests associated with precision oncology, such as CGP assays, require more nuanced consideration that is best achieved through pathology consultation. In vetting requests for such tests, the pathologist needs information that ordering HCPs do not routinely provide when ordering other tests. A consult asking for such information allows an ordering HCP to efficiently convey this information without having to call the laboratory to circumvent a hard stop.

Regardless of whether a formal electronic consult is used, pathologists must be involved in the review of requests. Creation of an original in-house report also provides an opportunity for pathologists to offer their expertise and maximize the contribution of pathology to patient care. If outside (other VHA facility or non-VHA facility/institution) reports are simply scanned into the EHR without review and issuance of an interpretive report by an in-house pathologist, then an interpretation by a pathologist with access to the patient’s complete chart is never provided. Testing companies are not provided with every patient diagnosis, so in patients with multiple neoplastic conditions, a report may seem to indicate that a detected mutation is from 1 tumor when it is actually from another. Even when all known diagnoses are considered, a variant may be detected that the medical record could reveal to indicate a new diagnosis.

Variation in reporting between companies necessitates pathologist review to standardize care. Some companies indicate which variants may represent clonal hematopoiesis, while others will simply list the pathogenic variants. An oncologist who sees a high volume of hematolymphoid neoplasia may recognize which variants may represent clonal hematopoiesis, but others may not. Reports from the same company may vary, and their interpretation often requires a pathologist's expertise. For example, even if a sample meets the technical requirements for analysis, the report may indicate that the quality or quantity of DNA has reduced the sensitivity for genomic alteration detection. A pathologist would know how to use this information in deciding how to proceed. In a situation where quantity was the issue, the pathologist may know there is additional tissue that could be sent for testing. If quality is the issue, the pathologist may know that additional blocks from the same case likely have the same quality of DNA and would also be unsuitable for testing.

Pathologist input is necessary for precision oncology testing. Some tasks that would ideally be completed by a molecular pathologist (eg, creation of reports to indicate which variants may represent clonal hematopoiesis of indeterminate potential) may be sufficiently completed by a pathologist without fellowship training in molecular pathology.

There are about 15,000 full-time pathologists in the US.4 In the 20 years since molecular genetic pathology was formally recognized as a specialty, there have been < 500 pathologists who have pursued fellowship training in this specialty.5 With the inundation of molecular variants uncovered by routine next-generation sequencing (NGS), there are too few fellowship-trained molecular pathologists to provide all such aforementioned input; it is incumbent on surgical pathologists in general to take on such responsibilities.

Consult Implementation Data

These results support the feasibility and effectiveness of the consult process. Prior to consult implementation, many requests were not compliant with VHA National Precision Oncology Program (NPOP) testing guidelines. Since enactment of the consult, > 90% of requests have been in compliance. In the year preceding the consult (January 2020 to December 2021), 55 of 211 (26.1%) metastatic lung and prostate cancers samples eligible for NGS were tested and 126 (59.7%) NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 151 days. In the year following enactment of the consult (January 2021 to December 2022), 168 of 224 (75.0%) of metastatic lung and prostate cancers eligible for NGS were tested and all 224 NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 83 days. These data indicate that the practices recommended increase test use, appropriateness of orders, standardization of reporting, and efficiency of care.

CONCLUSIONS

Processing precision oncology testing requires substantial work for pathology departments. Laboratory workforce shortages and ever-expanding indications necessitate additional study of pathology processes to manage increasing workload and maintain the highest quality of cancer care through maximal efficiency and the development of appropriate staffing models. The use of a consult for anatomic pathology molecular testing is one process that can increase test use, appropriateness of orders, standardization of reporting, and efficiency of care. This report provides a comprehensive description and mapping of the process, highlights best practices, identifies inefficiencies, and provides a description and mapping of a target state.

References
  1. Inal C, Yilmaz E, Cheng H, et al. Effect of reflex testing by pathologists on molecular testing rates in lung cancer patients: experience from a community-based academic center. J Clin Oncol. 2014;32(15 suppl):8098. doi:10.1200/jco.2014.32.15_suppl.8098
  2. Mettman D, Goodman M, Modzelewski J, et al. Streamlining institutional pathway processes: the development and implementation of a pathology molecular consult to facilitate convenient and efficient ordering, fulfillment, and reporting for tissue molecular tests. J Clin Pathw.Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633 2022;8(1):28-33.
  3. Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633
  4. Robboy SJ, Gupta S, Crawford JM, et al. The pathologist workforce in the United States: II. An interactive modeling tool for analyzing future qualitative and quantitative staffing demands for services. Arch Pathol Lab Med. 2015;139(11):1413-1430. doi:10.5858/arpa.2014-0559-OA doi:10.25270/jcp.2022.02.1
  5. Robboy SJ, Gross D, Park JY, et al. Reevaluation of the US pathologist workforce size. JAMA Netw Open. 2020;3(7): e2010648. doi:10.1001/jamanetworkopen.2020.10648
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Author and Disclosure Information

Daniel J. Mettman, MDa; Linlin Gao, MBBS, PhDa; Karsten Evans, MDa; Amy B. Frey, DO, MSb; Maren T. Scheuner, MD, MPHc; J. Stacey Klutts, MD, PhDd,e,f; M. Carmen Frias-Kletecka, MDg; Jessica Wang-Rodriguez, MDf,h; Daniel J. Becker, MDi; Sharad C. Mathur, MBBSa; Michael M. Goodman, MDj

Author affiliations
aKansas City Veterans Affairs Medical Center, Missouri
bRocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
cSan Francisco Veterans Affairs Health Care System, California
dUniversity of Iowa Carver College of Medicine, Iowa City
eIowa City Veterans Affairs Health Care System, Iowa
fNational Veterans Affairs Pathology and Laboratory Medicine Program Office, Bethesda, Maryland
gWest Los Angeles Veterans Affairs Healthcare System, California
hVeterans Affairs San Diego Healthcare System, California
iVeterans Affairs New York Harbor Healthcare System, Manhattan
jW. G. (Bill) Hefner Salisbury Department of Veterans Affairs Medical Center, Salisbury, North Carolina

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Daniel Mettman ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0583

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Daniel J. Mettman, MDa; Linlin Gao, MBBS, PhDa; Karsten Evans, MDa; Amy B. Frey, DO, MSb; Maren T. Scheuner, MD, MPHc; J. Stacey Klutts, MD, PhDd,e,f; M. Carmen Frias-Kletecka, MDg; Jessica Wang-Rodriguez, MDf,h; Daniel J. Becker, MDi; Sharad C. Mathur, MBBSa; Michael M. Goodman, MDj

Author affiliations
aKansas City Veterans Affairs Medical Center, Missouri
bRocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
cSan Francisco Veterans Affairs Health Care System, California
dUniversity of Iowa Carver College of Medicine, Iowa City
eIowa City Veterans Affairs Health Care System, Iowa
fNational Veterans Affairs Pathology and Laboratory Medicine Program Office, Bethesda, Maryland
gWest Los Angeles Veterans Affairs Healthcare System, California
hVeterans Affairs San Diego Healthcare System, California
iVeterans Affairs New York Harbor Healthcare System, Manhattan
jW. G. (Bill) Hefner Salisbury Department of Veterans Affairs Medical Center, Salisbury, North Carolina

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Daniel Mettman ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0583

Author and Disclosure Information

Daniel J. Mettman, MDa; Linlin Gao, MBBS, PhDa; Karsten Evans, MDa; Amy B. Frey, DO, MSb; Maren T. Scheuner, MD, MPHc; J. Stacey Klutts, MD, PhDd,e,f; M. Carmen Frias-Kletecka, MDg; Jessica Wang-Rodriguez, MDf,h; Daniel J. Becker, MDi; Sharad C. Mathur, MBBSa; Michael M. Goodman, MDj

Author affiliations
aKansas City Veterans Affairs Medical Center, Missouri
bRocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
cSan Francisco Veterans Affairs Health Care System, California
dUniversity of Iowa Carver College of Medicine, Iowa City
eIowa City Veterans Affairs Health Care System, Iowa
fNational Veterans Affairs Pathology and Laboratory Medicine Program Office, Bethesda, Maryland
gWest Los Angeles Veterans Affairs Healthcare System, California
hVeterans Affairs San Diego Healthcare System, California
iVeterans Affairs New York Harbor Healthcare System, Manhattan
jW. G. (Bill) Hefner Salisbury Department of Veterans Affairs Medical Center, Salisbury, North Carolina

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Daniel Mettman ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0583

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Article PDF

Comprehensive genomic profiling (CGP) is becoming progressively common and appropriate as the array of molecular targets expands. However, most hospital laboratories in the United States do not perform CGP assays in-house; instead, these tests are sent to reference laboratories. As evidenced by Inal et al, only a minority of guideline-indicated molecular testing is performed.1

The workload associated with referral testing is a barrier to increased use of such tests; streamlined processes in pathology might increase molecular test use. At 6 high-complexity US Department of Veterans Affairs (VA) medical centers (VAMCs) (Manhattan, Los Angeles, San Diego, Denver, Kansas City, and Salisbury, Maryland) ranging from 150 to 750 beds, a consult process for anatomic pathology molecular testing has increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care. This report comprehensively describes and maps the anatomic pathology molecular testing consult process at a VAMC. We present areas of inefficiency and a target state process map that incorporates best practices.

MOLECULAR TESTING CONSULT PROCESS

At the Kansas City VAMC (KCVAMC), a consult process for anatomic pathology molecular testing was introduced in 2021. Prior to this, requesting anatomic pathology molecular testing was not standardized. A variety of opportunities and methods were used for requests (eg, phone, page, Teams message, email, Computerized Patient Record System alert; or in-person during tumor board, an office meeting, or in passing). Requests were not documented in a standardized way, resulting in duplicate requests. Testing status and updates were documented outside the medical record, so requests for status updates (via various opportunities and methods) were common and redundant. Data from the year preceding consult implementation and the year following consult implementation have demonstrated increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care.

Consult Request

The precision oncology testing process starts with a health care practitioner (HCP) request on behalf of any physician or advanced practice registered nurse. It can be placed by any health care employee and directed to a designated employee in the pathology department. The request is ultimately reviewed by a pathologist (Figure 1). At KCVAMC, this request comes in the form of a consult in the electronic health record (EHR) from the ordering HCP to a pathologist. The KCVAMC pathology consult form was previously published with a discussion of the rationale for this process as opposed to a laboratory order process.2 This consult form ensures ordering HCPs supply all necessary information for the pathologist to approve the request and order the test without needing to, in most cases, contact the ordering HCP for clarification or additional information. The form asks the ordering HCP to specify which test is being requested and why. Within the Veterans Health Administration (VHA) there are local and national contracts with many laboratories with hundreds of precision oncology tests to choose from. Consulting with a pathologist is necessary to determine which test is most appropriate.

0525FED-AVAHO_PATH_F1

The precision oncology consult form cannot be submitted without completing all required fields. It also contains indications for the test the ordering HCP selects to minimize unintentionally inappropriate orders. The form asks which tissue the requestor expects the test to be performed on. The requestor must provide contact information for the originating institution when the tissue was collected outside the VHA. The consult form also asks whether another anatomic site is accessible and could be biopsied without unacceptable risk or impracticality, should all previously collected tissue be insufficient. For CGP requests, this allows the pathologist to determine the appropriateness of liquid biopsy without having to reach out to the ordering HCP or wait for the question to be addressed at a tumor board. When a companion diagnostic is available for a test, the ordering HCP is asked which drug will be used so that the most appropriate assay is chosen.

Consult Review

Pathology service involvement begins with pathologist review of the consult form to ensure that the correct test is indicated. Depending on the resources and preferences at a site, consults can be directed to and reviewed by the pathologist associated with the corresponding pathology specimen or to a single pathologist or group of pathologists charged with attending to consults.

The patient’s EHR is reviewed to verify that the test has not already been performed and to determine which tissue to review. Previous surgical pathology reports are examined to assess whether sufficient tissue is available for testing, which may be determined without the need for direct slide examination. Pathologists often use wording such as “rare cells” or in some cases specify that there are not enough lesional cells for ancillary testing. In biopsy reports, the percentage of tissue occupied by lesional cells or the greatest linear length of tumor cells is often documented. As for quality, pathologists may note that a specimen is largely necrotic, and gross descriptions will indicate if a specimen was compromised for molecular analysis by exposure to fixatives such as Bouin’s solution, B-5, or decalcifying agents that contain strong acids.

Tissue Retrieval

If, after such evaluation, the test is indicated and there is tissue that could be sufficient for testing, retrieval of the tissue is pursued. For in-house cases, the pathologist reviews the corresponding surgical pathology report to determine which blocks and slides to pull from the archives. In the cancer checklist, some pathologists specify the best block for subsequent ancillary studies. From the final diagnosis and gross description, the pathologist can determine which blocks are most likely to contain lesional tissue. These slides are retrieved from the archives.

For cases collected at an outside institution (other VHA facility or non-VHA facility/institution), the outside institution must be contacted to retrieve the needed slides and blocks. The phone numbers, fax numbers, email addresses, and mailing addresses for outside institutions are housed in an electronic file and are specific to the point of contact for such requests. Maintaining a record of contacts increases efficiency of the overall process; gathering contact information and successfully requesting tissue often involves multiple automated answering systems, misdirected calls, and failed attempts.

Tissue Review

After retrieving in-house tissue, the pathologist can proceed directly to slide review. For outside cases, the case must first be accessioned so that after review of the slides the pathologist can issue a report to confirm the outside diagnosis. In reviewing the slides, the pathologist looks to see that the diagnosis is correct, that there is a sufficient number of lesional cells in a section, that the lesional cells are of a sufficient concentration in a section, or subsection of the section that could be dissected, and that the cells are viable. Depending on the requested assay and the familiarity of the pathologist with that assay, the pathologist may need to look up the technical requirements of the assay and capabilities of the testing company. Assays vary in sensitivity and require differing amounts and concentrations of tumor. Some companies will dissect tissue, others will not.

If there is sufficient tissue in the material reviewed, the corresponding blocks are retrieved from in-house archives or requests are placed for outside blocks or unstained slides. If there was not enough tissue for testing, the same process is repeated to retrieve and evaluate any other specimens the patient may have. If there are no other specimens to review, this is simply communicated to the ordering HCP via the consult. If the patient is a candidate for liquid biopsy—ie, current specimens are of insufficient quality and/or quantity and a new tissue sample cannot be obtained due to unacceptable risk or impracticality—the order is placed at this time.

Tissue Transport and Testing

Unstained slides need to be cut unless blocks are sent. Slides, blocks, reports, and requisition forms are packaged for transport. An accession number is created for the precision oncology molecular laboratory test in the clinical laboratory section of the EHR system. The clinical laboratory accession number provides a way of tracking sendout testing status. The case is accessioned just prior to placement in the mail so that when an accession number appears in the EHR, the ordering HCP knows the case has been sent out. When results are received, the clinical laboratory accession is completed and a comment is added to indicate where in the EHR to find the report or, when applicable, notes that testing failed.

RESULT REPORTING

When a result becomes available, the report file is downloaded from the vendor portal. This full report is securely transmitted to the ordering HCP. The file is then scanned into the EHR. Additionally, salient findings from the report are abstracted by the pathologist for inclusion as a supplement to the anatomic pathology case. This step ensures that this information travels with the anatomic pathology report if the patient’s care is transferred elsewhere. Templates are used to ensure essential data is captured based on the type of test. The template reminds the pathologist to comment on things such as variants that may represent clonal hematopoiesis, variants that may be germline, and variants that qualify a patient for germline testing. Even with the template, the pathologist must spend significant time reviewing the chart for things such as personal cancer history, other medical history, other masses on imaging, family history, previous surgical pathology reports, and previous molecular testing.

If results are suboptimal, recommendations for repeat testing are made based on the consult response to the question of repeat biopsy feasibility and review of previous pathology reports. The final consult report is added as a consult note, the consult is completed, and the original vendor report file is associated with the consult note in the EHR.

Ancillary Testing Technician

Due to chronic KCVAMC understaffing in the clerical office, gross room, and histology, most of the consult tasks are performed by a pathologist. In an ideal scenario, the pathology staff would divide its time between a pathologist and another dedicated laboratory position, such as an ancillary testing technician (ATT). The ATT can assume responsibilities that do not require the expertise of a pathologist (Figure 2). In such a process, the only steps that would require a pathologist would be review of requests and slides and completion of the interpretive report. All other steps could be accomplished by someone who lacks certifications, laboratory experience, or postsecondary education.

0525FED-AVAHO_PATH_F2

The ATT can receive the requests and retrieve slides and blocks. After slides have been reviewed by a pathologist, the pathologist can inform the ATT which slides or blocks testing will be performed on, provide any additional necessary information for completing the order, and answer any questions. For send-out tests, this allows the ATT to independently complete online portal forms and all other physical requirements prior to delivery of the slides and blocks to specimen processors in the laboratory.

ATTs can keep the ordering HCPs informed of status and be identified as the point of contact for all status inquiries. ATTs can receive results and get outside reports scanned into the EHR. Finally, ATTs can use pathologistdesigned templates to transpose information from outside reports such that a provisional report is prepared and a pathologist does not spend time duplicating information from the outside report. The pathologist can then complete the report with information requiring medical judgment that enhances care.

Optimal Pathologist Involvement

Only 3 steps in the process (request review, tissue review, and completion of an interpretive report) require a pathologist, which are necessary for optimal care and to address barriers to precision oncology.3 While the laboratory may consume only 5% of a health system budget, optimal laboratory use could prevent as much as 30% of avoidable costs.4 These estimates are widely recognized and addressed by campaigns such as Choosing Wisely, as well as programming of alerts and hard stops in EHR systems to reduce duplicate or otherwise inappropriate orders. The tests associated with precision oncology, such as CGP assays, require more nuanced consideration that is best achieved through pathology consultation. In vetting requests for such tests, the pathologist needs information that ordering HCPs do not routinely provide when ordering other tests. A consult asking for such information allows an ordering HCP to efficiently convey this information without having to call the laboratory to circumvent a hard stop.

Regardless of whether a formal electronic consult is used, pathologists must be involved in the review of requests. Creation of an original in-house report also provides an opportunity for pathologists to offer their expertise and maximize the contribution of pathology to patient care. If outside (other VHA facility or non-VHA facility/institution) reports are simply scanned into the EHR without review and issuance of an interpretive report by an in-house pathologist, then an interpretation by a pathologist with access to the patient’s complete chart is never provided. Testing companies are not provided with every patient diagnosis, so in patients with multiple neoplastic conditions, a report may seem to indicate that a detected mutation is from 1 tumor when it is actually from another. Even when all known diagnoses are considered, a variant may be detected that the medical record could reveal to indicate a new diagnosis.

Variation in reporting between companies necessitates pathologist review to standardize care. Some companies indicate which variants may represent clonal hematopoiesis, while others will simply list the pathogenic variants. An oncologist who sees a high volume of hematolymphoid neoplasia may recognize which variants may represent clonal hematopoiesis, but others may not. Reports from the same company may vary, and their interpretation often requires a pathologist's expertise. For example, even if a sample meets the technical requirements for analysis, the report may indicate that the quality or quantity of DNA has reduced the sensitivity for genomic alteration detection. A pathologist would know how to use this information in deciding how to proceed. In a situation where quantity was the issue, the pathologist may know there is additional tissue that could be sent for testing. If quality is the issue, the pathologist may know that additional blocks from the same case likely have the same quality of DNA and would also be unsuitable for testing.

Pathologist input is necessary for precision oncology testing. Some tasks that would ideally be completed by a molecular pathologist (eg, creation of reports to indicate which variants may represent clonal hematopoiesis of indeterminate potential) may be sufficiently completed by a pathologist without fellowship training in molecular pathology.

There are about 15,000 full-time pathologists in the US.4 In the 20 years since molecular genetic pathology was formally recognized as a specialty, there have been < 500 pathologists who have pursued fellowship training in this specialty.5 With the inundation of molecular variants uncovered by routine next-generation sequencing (NGS), there are too few fellowship-trained molecular pathologists to provide all such aforementioned input; it is incumbent on surgical pathologists in general to take on such responsibilities.

Consult Implementation Data

These results support the feasibility and effectiveness of the consult process. Prior to consult implementation, many requests were not compliant with VHA National Precision Oncology Program (NPOP) testing guidelines. Since enactment of the consult, > 90% of requests have been in compliance. In the year preceding the consult (January 2020 to December 2021), 55 of 211 (26.1%) metastatic lung and prostate cancers samples eligible for NGS were tested and 126 (59.7%) NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 151 days. In the year following enactment of the consult (January 2021 to December 2022), 168 of 224 (75.0%) of metastatic lung and prostate cancers eligible for NGS were tested and all 224 NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 83 days. These data indicate that the practices recommended increase test use, appropriateness of orders, standardization of reporting, and efficiency of care.

CONCLUSIONS

Processing precision oncology testing requires substantial work for pathology departments. Laboratory workforce shortages and ever-expanding indications necessitate additional study of pathology processes to manage increasing workload and maintain the highest quality of cancer care through maximal efficiency and the development of appropriate staffing models. The use of a consult for anatomic pathology molecular testing is one process that can increase test use, appropriateness of orders, standardization of reporting, and efficiency of care. This report provides a comprehensive description and mapping of the process, highlights best practices, identifies inefficiencies, and provides a description and mapping of a target state.

Comprehensive genomic profiling (CGP) is becoming progressively common and appropriate as the array of molecular targets expands. However, most hospital laboratories in the United States do not perform CGP assays in-house; instead, these tests are sent to reference laboratories. As evidenced by Inal et al, only a minority of guideline-indicated molecular testing is performed.1

The workload associated with referral testing is a barrier to increased use of such tests; streamlined processes in pathology might increase molecular test use. At 6 high-complexity US Department of Veterans Affairs (VA) medical centers (VAMCs) (Manhattan, Los Angeles, San Diego, Denver, Kansas City, and Salisbury, Maryland) ranging from 150 to 750 beds, a consult process for anatomic pathology molecular testing has increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care. This report comprehensively describes and maps the anatomic pathology molecular testing consult process at a VAMC. We present areas of inefficiency and a target state process map that incorporates best practices.

MOLECULAR TESTING CONSULT PROCESS

At the Kansas City VAMC (KCVAMC), a consult process for anatomic pathology molecular testing was introduced in 2021. Prior to this, requesting anatomic pathology molecular testing was not standardized. A variety of opportunities and methods were used for requests (eg, phone, page, Teams message, email, Computerized Patient Record System alert; or in-person during tumor board, an office meeting, or in passing). Requests were not documented in a standardized way, resulting in duplicate requests. Testing status and updates were documented outside the medical record, so requests for status updates (via various opportunities and methods) were common and redundant. Data from the year preceding consult implementation and the year following consult implementation have demonstrated increased test utilization, appropriateness of orders, standardization of reporting, and efficiency of care.

Consult Request

The precision oncology testing process starts with a health care practitioner (HCP) request on behalf of any physician or advanced practice registered nurse. It can be placed by any health care employee and directed to a designated employee in the pathology department. The request is ultimately reviewed by a pathologist (Figure 1). At KCVAMC, this request comes in the form of a consult in the electronic health record (EHR) from the ordering HCP to a pathologist. The KCVAMC pathology consult form was previously published with a discussion of the rationale for this process as opposed to a laboratory order process.2 This consult form ensures ordering HCPs supply all necessary information for the pathologist to approve the request and order the test without needing to, in most cases, contact the ordering HCP for clarification or additional information. The form asks the ordering HCP to specify which test is being requested and why. Within the Veterans Health Administration (VHA) there are local and national contracts with many laboratories with hundreds of precision oncology tests to choose from. Consulting with a pathologist is necessary to determine which test is most appropriate.

0525FED-AVAHO_PATH_F1

The precision oncology consult form cannot be submitted without completing all required fields. It also contains indications for the test the ordering HCP selects to minimize unintentionally inappropriate orders. The form asks which tissue the requestor expects the test to be performed on. The requestor must provide contact information for the originating institution when the tissue was collected outside the VHA. The consult form also asks whether another anatomic site is accessible and could be biopsied without unacceptable risk or impracticality, should all previously collected tissue be insufficient. For CGP requests, this allows the pathologist to determine the appropriateness of liquid biopsy without having to reach out to the ordering HCP or wait for the question to be addressed at a tumor board. When a companion diagnostic is available for a test, the ordering HCP is asked which drug will be used so that the most appropriate assay is chosen.

Consult Review

Pathology service involvement begins with pathologist review of the consult form to ensure that the correct test is indicated. Depending on the resources and preferences at a site, consults can be directed to and reviewed by the pathologist associated with the corresponding pathology specimen or to a single pathologist or group of pathologists charged with attending to consults.

The patient’s EHR is reviewed to verify that the test has not already been performed and to determine which tissue to review. Previous surgical pathology reports are examined to assess whether sufficient tissue is available for testing, which may be determined without the need for direct slide examination. Pathologists often use wording such as “rare cells” or in some cases specify that there are not enough lesional cells for ancillary testing. In biopsy reports, the percentage of tissue occupied by lesional cells or the greatest linear length of tumor cells is often documented. As for quality, pathologists may note that a specimen is largely necrotic, and gross descriptions will indicate if a specimen was compromised for molecular analysis by exposure to fixatives such as Bouin’s solution, B-5, or decalcifying agents that contain strong acids.

Tissue Retrieval

If, after such evaluation, the test is indicated and there is tissue that could be sufficient for testing, retrieval of the tissue is pursued. For in-house cases, the pathologist reviews the corresponding surgical pathology report to determine which blocks and slides to pull from the archives. In the cancer checklist, some pathologists specify the best block for subsequent ancillary studies. From the final diagnosis and gross description, the pathologist can determine which blocks are most likely to contain lesional tissue. These slides are retrieved from the archives.

For cases collected at an outside institution (other VHA facility or non-VHA facility/institution), the outside institution must be contacted to retrieve the needed slides and blocks. The phone numbers, fax numbers, email addresses, and mailing addresses for outside institutions are housed in an electronic file and are specific to the point of contact for such requests. Maintaining a record of contacts increases efficiency of the overall process; gathering contact information and successfully requesting tissue often involves multiple automated answering systems, misdirected calls, and failed attempts.

Tissue Review

After retrieving in-house tissue, the pathologist can proceed directly to slide review. For outside cases, the case must first be accessioned so that after review of the slides the pathologist can issue a report to confirm the outside diagnosis. In reviewing the slides, the pathologist looks to see that the diagnosis is correct, that there is a sufficient number of lesional cells in a section, that the lesional cells are of a sufficient concentration in a section, or subsection of the section that could be dissected, and that the cells are viable. Depending on the requested assay and the familiarity of the pathologist with that assay, the pathologist may need to look up the technical requirements of the assay and capabilities of the testing company. Assays vary in sensitivity and require differing amounts and concentrations of tumor. Some companies will dissect tissue, others will not.

If there is sufficient tissue in the material reviewed, the corresponding blocks are retrieved from in-house archives or requests are placed for outside blocks or unstained slides. If there was not enough tissue for testing, the same process is repeated to retrieve and evaluate any other specimens the patient may have. If there are no other specimens to review, this is simply communicated to the ordering HCP via the consult. If the patient is a candidate for liquid biopsy—ie, current specimens are of insufficient quality and/or quantity and a new tissue sample cannot be obtained due to unacceptable risk or impracticality—the order is placed at this time.

Tissue Transport and Testing

Unstained slides need to be cut unless blocks are sent. Slides, blocks, reports, and requisition forms are packaged for transport. An accession number is created for the precision oncology molecular laboratory test in the clinical laboratory section of the EHR system. The clinical laboratory accession number provides a way of tracking sendout testing status. The case is accessioned just prior to placement in the mail so that when an accession number appears in the EHR, the ordering HCP knows the case has been sent out. When results are received, the clinical laboratory accession is completed and a comment is added to indicate where in the EHR to find the report or, when applicable, notes that testing failed.

RESULT REPORTING

When a result becomes available, the report file is downloaded from the vendor portal. This full report is securely transmitted to the ordering HCP. The file is then scanned into the EHR. Additionally, salient findings from the report are abstracted by the pathologist for inclusion as a supplement to the anatomic pathology case. This step ensures that this information travels with the anatomic pathology report if the patient’s care is transferred elsewhere. Templates are used to ensure essential data is captured based on the type of test. The template reminds the pathologist to comment on things such as variants that may represent clonal hematopoiesis, variants that may be germline, and variants that qualify a patient for germline testing. Even with the template, the pathologist must spend significant time reviewing the chart for things such as personal cancer history, other medical history, other masses on imaging, family history, previous surgical pathology reports, and previous molecular testing.

If results are suboptimal, recommendations for repeat testing are made based on the consult response to the question of repeat biopsy feasibility and review of previous pathology reports. The final consult report is added as a consult note, the consult is completed, and the original vendor report file is associated with the consult note in the EHR.

Ancillary Testing Technician

Due to chronic KCVAMC understaffing in the clerical office, gross room, and histology, most of the consult tasks are performed by a pathologist. In an ideal scenario, the pathology staff would divide its time between a pathologist and another dedicated laboratory position, such as an ancillary testing technician (ATT). The ATT can assume responsibilities that do not require the expertise of a pathologist (Figure 2). In such a process, the only steps that would require a pathologist would be review of requests and slides and completion of the interpretive report. All other steps could be accomplished by someone who lacks certifications, laboratory experience, or postsecondary education.

0525FED-AVAHO_PATH_F2

The ATT can receive the requests and retrieve slides and blocks. After slides have been reviewed by a pathologist, the pathologist can inform the ATT which slides or blocks testing will be performed on, provide any additional necessary information for completing the order, and answer any questions. For send-out tests, this allows the ATT to independently complete online portal forms and all other physical requirements prior to delivery of the slides and blocks to specimen processors in the laboratory.

ATTs can keep the ordering HCPs informed of status and be identified as the point of contact for all status inquiries. ATTs can receive results and get outside reports scanned into the EHR. Finally, ATTs can use pathologistdesigned templates to transpose information from outside reports such that a provisional report is prepared and a pathologist does not spend time duplicating information from the outside report. The pathologist can then complete the report with information requiring medical judgment that enhances care.

Optimal Pathologist Involvement

Only 3 steps in the process (request review, tissue review, and completion of an interpretive report) require a pathologist, which are necessary for optimal care and to address barriers to precision oncology.3 While the laboratory may consume only 5% of a health system budget, optimal laboratory use could prevent as much as 30% of avoidable costs.4 These estimates are widely recognized and addressed by campaigns such as Choosing Wisely, as well as programming of alerts and hard stops in EHR systems to reduce duplicate or otherwise inappropriate orders. The tests associated with precision oncology, such as CGP assays, require more nuanced consideration that is best achieved through pathology consultation. In vetting requests for such tests, the pathologist needs information that ordering HCPs do not routinely provide when ordering other tests. A consult asking for such information allows an ordering HCP to efficiently convey this information without having to call the laboratory to circumvent a hard stop.

Regardless of whether a formal electronic consult is used, pathologists must be involved in the review of requests. Creation of an original in-house report also provides an opportunity for pathologists to offer their expertise and maximize the contribution of pathology to patient care. If outside (other VHA facility or non-VHA facility/institution) reports are simply scanned into the EHR without review and issuance of an interpretive report by an in-house pathologist, then an interpretation by a pathologist with access to the patient’s complete chart is never provided. Testing companies are not provided with every patient diagnosis, so in patients with multiple neoplastic conditions, a report may seem to indicate that a detected mutation is from 1 tumor when it is actually from another. Even when all known diagnoses are considered, a variant may be detected that the medical record could reveal to indicate a new diagnosis.

Variation in reporting between companies necessitates pathologist review to standardize care. Some companies indicate which variants may represent clonal hematopoiesis, while others will simply list the pathogenic variants. An oncologist who sees a high volume of hematolymphoid neoplasia may recognize which variants may represent clonal hematopoiesis, but others may not. Reports from the same company may vary, and their interpretation often requires a pathologist's expertise. For example, even if a sample meets the technical requirements for analysis, the report may indicate that the quality or quantity of DNA has reduced the sensitivity for genomic alteration detection. A pathologist would know how to use this information in deciding how to proceed. In a situation where quantity was the issue, the pathologist may know there is additional tissue that could be sent for testing. If quality is the issue, the pathologist may know that additional blocks from the same case likely have the same quality of DNA and would also be unsuitable for testing.

Pathologist input is necessary for precision oncology testing. Some tasks that would ideally be completed by a molecular pathologist (eg, creation of reports to indicate which variants may represent clonal hematopoiesis of indeterminate potential) may be sufficiently completed by a pathologist without fellowship training in molecular pathology.

There are about 15,000 full-time pathologists in the US.4 In the 20 years since molecular genetic pathology was formally recognized as a specialty, there have been < 500 pathologists who have pursued fellowship training in this specialty.5 With the inundation of molecular variants uncovered by routine next-generation sequencing (NGS), there are too few fellowship-trained molecular pathologists to provide all such aforementioned input; it is incumbent on surgical pathologists in general to take on such responsibilities.

Consult Implementation Data

These results support the feasibility and effectiveness of the consult process. Prior to consult implementation, many requests were not compliant with VHA National Precision Oncology Program (NPOP) testing guidelines. Since enactment of the consult, > 90% of requests have been in compliance. In the year preceding the consult (January 2020 to December 2021), 55 of 211 (26.1%) metastatic lung and prostate cancers samples eligible for NGS were tested and 126 (59.7%) NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 151 days. In the year following enactment of the consult (January 2021 to December 2022), 168 of 224 (75.0%) of metastatic lung and prostate cancers eligible for NGS were tested and all 224 NGS vendor reports were scanned into the EHR. The mean time from metastasis to NGS result was 83 days. These data indicate that the practices recommended increase test use, appropriateness of orders, standardization of reporting, and efficiency of care.

CONCLUSIONS

Processing precision oncology testing requires substantial work for pathology departments. Laboratory workforce shortages and ever-expanding indications necessitate additional study of pathology processes to manage increasing workload and maintain the highest quality of cancer care through maximal efficiency and the development of appropriate staffing models. The use of a consult for anatomic pathology molecular testing is one process that can increase test use, appropriateness of orders, standardization of reporting, and efficiency of care. This report provides a comprehensive description and mapping of the process, highlights best practices, identifies inefficiencies, and provides a description and mapping of a target state.

References
  1. Inal C, Yilmaz E, Cheng H, et al. Effect of reflex testing by pathologists on molecular testing rates in lung cancer patients: experience from a community-based academic center. J Clin Oncol. 2014;32(15 suppl):8098. doi:10.1200/jco.2014.32.15_suppl.8098
  2. Mettman D, Goodman M, Modzelewski J, et al. Streamlining institutional pathway processes: the development and implementation of a pathology molecular consult to facilitate convenient and efficient ordering, fulfillment, and reporting for tissue molecular tests. J Clin Pathw.Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633 2022;8(1):28-33.
  3. Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633
  4. Robboy SJ, Gupta S, Crawford JM, et al. The pathologist workforce in the United States: II. An interactive modeling tool for analyzing future qualitative and quantitative staffing demands for services. Arch Pathol Lab Med. 2015;139(11):1413-1430. doi:10.5858/arpa.2014-0559-OA doi:10.25270/jcp.2022.02.1
  5. Robboy SJ, Gross D, Park JY, et al. Reevaluation of the US pathologist workforce size. JAMA Netw Open. 2020;3(7): e2010648. doi:10.1001/jamanetworkopen.2020.10648
References
  1. Inal C, Yilmaz E, Cheng H, et al. Effect of reflex testing by pathologists on molecular testing rates in lung cancer patients: experience from a community-based academic center. J Clin Oncol. 2014;32(15 suppl):8098. doi:10.1200/jco.2014.32.15_suppl.8098
  2. Mettman D, Goodman M, Modzelewski J, et al. Streamlining institutional pathway processes: the development and implementation of a pathology molecular consult to facilitate convenient and efficient ordering, fulfillment, and reporting for tissue molecular tests. J Clin Pathw.Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633 2022;8(1):28-33.
  3. Ersek JL, Black LJ, Thompson MA, Kim ES. Implementing precision medicine programs and clinical trials in the community-based oncology practice: barriers and best practices. Am Soc Clin Oncol Educ Book. 2018;38:188- 196. doi:10.1200/EDBK_200633
  4. Robboy SJ, Gupta S, Crawford JM, et al. The pathologist workforce in the United States: II. An interactive modeling tool for analyzing future qualitative and quantitative staffing demands for services. Arch Pathol Lab Med. 2015;139(11):1413-1430. doi:10.5858/arpa.2014-0559-OA doi:10.25270/jcp.2022.02.1
  5. Robboy SJ, Gross D, Park JY, et al. Reevaluation of the US pathologist workforce size. JAMA Netw Open. 2020;3(7): e2010648. doi:10.1001/jamanetworkopen.2020.10648
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Handoff Delays in Teledermatology Lengthen Timeline of Care for Veterans With Melanoma

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Handoff Delays in Teledermatology Lengthen Timeline of Care for Veterans With Melanoma

Store-and-forward teledermatology (SFT) allows clinical images and information to be sent to a dermatologist for evaluation. In fiscal year (FY) 2018, 117,780 SFT consultations were completed in the Veterans Health Administration. Continued growth is expected since SFT has proven to be an effective method for improving access to face-to-face (FTF) dermatology care.1 In the same period, the US Department of Veterans Affairs (VA) Puget Sound Health Care System (VAPSHCS) completed 12,563 consultations in a mean 1.1 days from entry into episode of care (EEC), according to data reported by VA Teledermatology Program Administrator Chris Foster.

Obtaining a prompt consultation is reported to be an overwhelming advantage of using SFT.2-5 Rapid turnaround may appear to make SFT specialist care more accessible to veterans, yet this is an oversimplification. The process of delivering care (rather than consultation) through SFT is more complex than reading the images and reporting the findings. When a skin condition is identified by a primary care clinician and that person decides to request an SFT consultation, a complex set of tasks and handoffs is set into motion. A swim-lane diagram illustrates the numerous steps and handoffs that go into delivering care to a patient with a malignant melanoma on the SFT platform compared to FTF care, which requires fewer handoffs (Figure).

0525FED-AVAHO-MEL_F1

This process improvement project examined whether handoffs necessitated by SFT care lengthened the timeline of care for biopsy-proven primary cutaneous malignant melanoma. The stakes of delay in care are high. A 2018 study using the National Cancer Database found that a delay of > 30 days from biopsy to definitive excision (the date definitive surgical procedure for the condition is performed) resulted in a measurable increase in melanoma-related mortality. 6 This study sought to identify areas where the SFT timeline of care could be shortened.

Methods

This retrospective cohort study was approved by the VAPSHCS Institutional Review Board. The study drew from secondary data obtained from VistA, the VA Corporate Data Warehouse, the Veterans Integrated Service Network (VISN) 20 database, the American Academy of Dermatology Teledermatology Program database, and the VA Computerized Patient Record System.

Patients registered for ≥ 1 year at VAPSHCS with a diagnosis of primary cutaneous malignant melanoma by the Pathology service between January 1, 2006, and December 31, 2013, were included. Patients with metastatic or recurrent melanoma were excluded.

Cases were randomly selected from a melanoma database previously validated and used for another quality improvement project.7 There were initially 115 patient cases extracted from this database for both the FTF and SFT groups. Eighty-seven SFT and 107 FTF cases met inclusion criteria. To further analyze these groups, we split the FTF group into 2 subgroups: FTF dermatology (patients whose melanomas were entered into care in a dermatology clinic) and FTF primary care (patients whose melanomas were entered into care in primary care or a nondermatology setting).

The timeline of care was divided into 2 major time intervals: (1) entry into episode of care (EEC; the date a lesion was first documented in the electronic health record) to biopsy; and (2) biopsy to definitive excision. The SFT process was divided into the following intervals: EEC to imaging request (the date a clinician requested imaging); imaging request to imaging completion (the date an imager photographed a patient’s lesion); imaging completion to SFT consultation request (the date the SFT consultation was requested); SFT consultation request to consultation completion (the date an SFT reader completed the consultation request for a patient); and SFT consultation completion to biopsy. Mean and median interval lengths were compared between groups and additional analyses identified steps that may have contributed to delays in care.

To address potential bias based on access to care for rural veterans, SFT and FTF primary care cases were categorized into groups based on their location: (1) EEC and biopsy conducted at the same facility; (2) EEC and biopsy conducted at different facilities within the same health care system (main health care facility and its community-based outpatient clinics); and (3) EEC and biopsy conducted at different health care systems.

Statistics

Means, medians, and SDs were calculated in Excel. The Mann-Whitney U test was used to compare SFT medians to the FTF data and X2 test was used to compare proportions for secondary analyses.

Results

The median (mean) interval from EEC to definitive excision was 73 days (85) for SFT and 58 days (73) for FTF (P = .004) (Table). To understand this difference, the distribution of intervals from EEC to biopsy and biopsy to definitive excision were calculated. Only 38% of SFT cases were biopsied within 20 days compared to 65% of FTF cases (P < .001). The difference in time from biopsy to definitive excision distributions were not statistically significant, suggesting that the difference is actually a reflection of the differences seen in the period between EEC and biopsy.

0525FED-AVAHO-MEL_T1

EEC and biopsy occurred at the same facility in 85% and 82% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different facilities within the same health care system in 15% and 16% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different health care systems in 0% and 2% of FTF primary care and SFT cases, respectively. Geographic bias did not impact results for either group of veterans.

The interval between EEC and biopsy was shorter for FTF dermatology cases than for FTF primary care cases. For FTF dermatology cases, 96% were biopsied within 20 days compared with 34% of FTF primary care cases (P < .001).

To further analyze the difference in the EEC to biopsy interval duration between SFT and FTF primary care the timeline was divided into smaller steps: EEC to imaging completion, imaging completion to SFT consult completion, and SFT consult completion to biopsy. From EEC to SFT consult completion, SFT cases took a median of 6.0 days and a mean of 12.3 days, reflecting the administrative handoffs that must occur in SFT. A total of 82% of FTF primary care cases were entered into care and consultation was requested on the same day, while this was true for only 1% of SFT cases.

Since mortality data were not collected, the frequency of in situ melanomas and invasive melanomas (pathologic stage pT1a or greater) was used as a proxy for comparing outcomes. No significant difference was found in the frequency of in situ vs invasive melanomas in the SFT and FTF dermatology groups; however, there was a much higher frequency of invasive melanomas in the FTF primary care group (P = .007).

Discussion

This study compared the time to treatment for SFT vs FTF and identified important differences. The episode of care for melanomas diagnosed by SFT was statistically significantly longer (15 days) than those diagnosed by FTF. The interval between biopsy and definitive excision was a median of 34 and 38 days, and a mean of 48 and 44 days for SFT and FTF, respectively, which were not statistically significant. The difference in the total duration of the interval between EEC and definitive excision was accounted for by the duration of the interval from EEC to biopsy. When excluding dermatology clinic cases from the FTF group, there was no difference in the interval between EEC and biopsy for SFT and FTF primary care. The handoffs in SFT accounted for a median of 6 days and mean of 12 days, a significant portion of the timeline, and is a target for process improvement. The delay necessitated by handoffs did not significantly affect the distribution of in situ and invasive melanomas in the SFT and FTF dermatology groups. This suggests that SFT may have better outcomes than FTF primary care.

There has been extensive research on the timeline from the patient initially noticing a lesion to the EEC.8-11 There is also a body of research on the timeline from biopsy to definitive excision. 6,12-16 However, there has been little research on the timeline between EEC and biopsy, which comprises a large portion of the overall timeline of both SFT care and FTF care. This study analyzed the delays that can occur in this interval. When patients first enter FTF dermatology care, this timeline is quite short because lesions are often biopsied on the same day. When patients enter into care with their primary or nondermatology clinician, there can be significant delays.

Since the stakes are high when it comes to treating melanoma, it is important to minimize the overall timeline. A 6-day median and 12-day mean were established as targets for teledermatology handoffs. Ideally, a lesion should be entered into an episode of care, imaged, and sent for consultation on the same day. To help further understand delays in administrative handoffs, we stratified the SFT cases by VISN 20 sites and spoke with an administrator at a top performing site. Between 2006 and 2013, this site had a dedicated full-time imager as well as a backup imager that ensured images were taken quickly, usually on the same day the lesion was entered into care. Unfortunately, this is not the standard at all VISN 20 sites and certainly contributes to the overall delay in care in SFT

Minimizing the timeline of care is possible, as shown by the Danish health system, which developed a fast-track referral system after recognizing the need to minimize delays between the presentation, diagnosis, and treatment of cutaneous melanomas. In Denmark, a patient who presents to a general practitioner with a suspicious lesion is referred to secondary care for excision biopsy within 6 days. Diagnosis is made within 2 weeks, and, if necessary, definitive excision is offered within 9 days of the diagnosis. This translates into a maximum 20-day EEC to biopsy timeline and maximum 29-day EEC to definitive excision timeline. Although an intervention such as this may be difficult to implement in the United States due to its size and decentralized health care system, it would, however, be more realistic within the VA due to its centralized structure. The Danish system shows that with appropriate resource allocation and strict timeframes for treatment referrals, the timeline can be minimized.17

Despite the delay in the SFT timeline, this study found no significant difference between the distribution of in situ vs invasive melanomas in FTF dermatology and SFT groups. One possible explanation for this is that SFT increases access to dermatologist care, meaning clinicians may be more willing to consult SFT for less advanced– appearing lesions.

The finding that SFT diagnosed a larger proportion of in situ melanomas than FTF primary care is consistent with the findings of Ferrándiz et al, who reported that the mean Breslow thickness was significantly lower among patients in an SFT group compared to patients in an FTF group consisting of general practitioners. 18 However, the study population was not randomized and the results may have been impacted by ascertainment bias. Ferrándiz et al hypothesized that clinicians may have a lower threshold for consulting teledermatology, resulting in lower mean Breslow thicknesses.18 Karavan et al found the opposite results, with a higher mean Breslow thickness in SFT compared to a primary care FTF group.19 The data presented here suggest that SFT has room for process improvement yet is essentially equivalent to FTF dermatology in terms of outcomes.

Limitations

The majority of patients in this study were aged > 50 years, White, and male. The results may not be representative for other populations. The study was relatively small compared to studies that looked at other aspects of the melanoma care timeline. The study was not powered to ascertain mortality, the most important metric for melanoma.

Conclusions

The episode of care was significantly longer for melanomas diagnosed by SFT than those diagnosed by FTF; however, timelines were not statistically different when FTF lesions entered into care in dermatology were excluded. A median 6-day and mean 12.3-day delay in administrative handoffs occurred at the beginning of the SFT process and is a target for process improvement. Considering the high stakes of melanoma, the SFT timeline could be reduced if EEC, imaging, and SFT consultation all happened in the same day.

References
  1. Raugi GJ, Nelson W, Miethke M, et al. Teledermatology implementation in a VHA secondary treatment facility improves access to face-to-face care. Telemed J E Health. 2016;22(1):12-17. doi:10.1089/tmj.2015.0036
  2. Moreno-Ramirez D, Ferrandiz L, Nieto-Garcia A, et al. Store-and-forward teledermatology in skin cancer triage: experience and evaluation of 2009 teleconsultations. Arch Dermatol. 2007;143(4):479-484. doi:10.1001/archderm.143.4.479
  3. Landow SM, Oh DH, Weinstock MA. Teledermatology within the Veterans Health Administration, 2002–2014. Telemed J E Health. 2015;21(10):769-773. doi:10.1089/tmj.2014.0225
  4. Whited JD, Hall RP, Foy ME, et al. Teledermatology’s impact on time to intervention among referrals to a dermatology consult service. Telemed J E Health. 2002;8(3):313-321. doi:10.1089/15305620260353207
  5. Hsiao JL, Oh DH. The impact of store-and-forward teledermatology on skin cancer diagnosis and treatment. J Am Acad Dermatol. 2008;59(2):260-267. doi:10.1016/j.jaad.2008.04.011
  6. Conic RZ, Cabrera CI, Khorana AA, Gastman BR. Determination of the impact of melanoma surgical timing on survival using the National Cancer Database. J Am Acad Dermatol. 2018;78(1):40-46.e7. doi:10.1016/j.jaad.2017.08.039
  7. Dougall B, Gendreau J, Das S, et al. Melanoma registry underreporting in the Veterans Health Administration. Fed Pract. 2016;33(suppl 5):55S-59S
  8. Xavier MHSB, Drummond-Lage AP, Baeta C, Rocha L, Almeida AM, Wainstein AJA. Delay in cutaneous melanoma diagnosis: sequence analyses from suspicion to diagnosis in 211 patients. Medicine (Baltimore). 2016;95(31):e4396. doi:10.1097/md.0000000000004396
  9. Schmid-Wendtner MH, Baumert J, Stange J, Volkenandt M. Delay in the diagnosis of cutaneous melanoma: an analysis of 233 patients. Melanoma Res. 2002;12(4):389-394. doi:10.1097/00008390-200208000-00012
  10. Betti, R, Vergani R, Tolomio E, Santambrogio R, Crosti C. Factors of delay in the diagnosis of melanoma. Eur J Dermatol. 2003;13(2):183-188.
  11. Blum A, Brand CU, Ellwanger U, et al. Awareness and early detection of cutaneous melanoma: An analysis of factors related to delay in treatment. Br J Dermatol. 1999;141(5):783-787. doi:10.1046/j.1365-2133.1999.03196.x
  12. Brian T, Adams B, Jameson M. Cutaneous melanoma: an audit of management timeliness against New Zealand guidelines. N Z Med J. 2017;130(1462):54-61. https://pubmed.ncbi.nlm.nih.gov/28934768
  13. Adamson AS, Zhou L, Baggett CD, Thomas NE, Meyer AM. Association of delays in surgery for melanoma with Insurance type. JAMA Dermatol. 2017;153(11):1106-1113. doi:https://doi.org/10.1001/jamadermatol.2017.3338
  14. Niehues NB, Evanson B, Smith WA, Fiore CT, Parekh P. Melanoma patient notification and treatment timelines. Dermatol Online J. 2019;25(4)13. doi:10.5070/d3254043588
  15. Lott JP, Narayan D, Soulos PR, Aminawung J, Gross CP. Delay of surgery for melanoma among Medicare beneficiaries. JAMA Dermatol. 2015;151(7):731-741. doi:10.1001/jamadermatol.2015.119
  16. Baranowski MLH, Yeung H, Chen SC, Gillespie TW, Goodman M. Factors associated with time to surgery in melanoma: an analysis of the National Cancer Database. J Am Acad Dermatol. 2019;81(4):908-916. doi:10.1016/j.jaad.2019.05.079
  17. Jarjis RD, Hansen LB, Matzen SH. A fast-track referral system for skin lesions suspicious of melanoma: population-based cross-sectional study from a plastic surgery center. Plast Surg Int. 2016;2016:2908917. doi:10.1155/2016/2908917
  18. Ferrándiz L, Ruiz-de-Casas A, Martin-Gutierrez FJ, et al. Effect of teledermatology on the prognosis of patients with cutaneous melanoma. Arch Dermatol. 2012;148(9):1025-1028. doi:10.1001/archdermatol.2012.778
  19. Karavan M, Compton N, Knezevich S, et al. Teledermatology in the diagnosis of melanoma. J Telemed Telecare. 2014;20(1):18-23. doi:10.1177/1357633x13517354
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Samuel Byrne, BSa,b; Clayton Lau, BSa; Maya Gopalan, BSa; Sandra Mata-Diaz, BSa; Gregory J. Raugi, MD, PhDc,d

Author affiliations;
aUniversity of Washington School of Public Health, Seattle
bUniversity of Arizona College of Medicine, Phoenix
cVeterans Affairs Puget Sound Health Care System, Seattle, Washington
dUniversity of Washington Department of Medicine, Seattle

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Samuel Byrne ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0587

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Samuel Byrne, BSa,b; Clayton Lau, BSa; Maya Gopalan, BSa; Sandra Mata-Diaz, BSa; Gregory J. Raugi, MD, PhDc,d

Author affiliations;
aUniversity of Washington School of Public Health, Seattle
bUniversity of Arizona College of Medicine, Phoenix
cVeterans Affairs Puget Sound Health Care System, Seattle, Washington
dUniversity of Washington Department of Medicine, Seattle

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Samuel Byrne ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0587

Author and Disclosure Information

Samuel Byrne, BSa,b; Clayton Lau, BSa; Maya Gopalan, BSa; Sandra Mata-Diaz, BSa; Gregory J. Raugi, MD, PhDc,d

Author affiliations;
aUniversity of Washington School of Public Health, Seattle
bUniversity of Arizona College of Medicine, Phoenix
cVeterans Affairs Puget Sound Health Care System, Seattle, Washington
dUniversity of Washington Department of Medicine, Seattle

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Samuel Byrne ([email protected])

Fed Pract. 2025;42(suppl 2). Published online May 8. doi:10.12788/fp.0587

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Article PDF

Store-and-forward teledermatology (SFT) allows clinical images and information to be sent to a dermatologist for evaluation. In fiscal year (FY) 2018, 117,780 SFT consultations were completed in the Veterans Health Administration. Continued growth is expected since SFT has proven to be an effective method for improving access to face-to-face (FTF) dermatology care.1 In the same period, the US Department of Veterans Affairs (VA) Puget Sound Health Care System (VAPSHCS) completed 12,563 consultations in a mean 1.1 days from entry into episode of care (EEC), according to data reported by VA Teledermatology Program Administrator Chris Foster.

Obtaining a prompt consultation is reported to be an overwhelming advantage of using SFT.2-5 Rapid turnaround may appear to make SFT specialist care more accessible to veterans, yet this is an oversimplification. The process of delivering care (rather than consultation) through SFT is more complex than reading the images and reporting the findings. When a skin condition is identified by a primary care clinician and that person decides to request an SFT consultation, a complex set of tasks and handoffs is set into motion. A swim-lane diagram illustrates the numerous steps and handoffs that go into delivering care to a patient with a malignant melanoma on the SFT platform compared to FTF care, which requires fewer handoffs (Figure).

0525FED-AVAHO-MEL_F1

This process improvement project examined whether handoffs necessitated by SFT care lengthened the timeline of care for biopsy-proven primary cutaneous malignant melanoma. The stakes of delay in care are high. A 2018 study using the National Cancer Database found that a delay of > 30 days from biopsy to definitive excision (the date definitive surgical procedure for the condition is performed) resulted in a measurable increase in melanoma-related mortality. 6 This study sought to identify areas where the SFT timeline of care could be shortened.

Methods

This retrospective cohort study was approved by the VAPSHCS Institutional Review Board. The study drew from secondary data obtained from VistA, the VA Corporate Data Warehouse, the Veterans Integrated Service Network (VISN) 20 database, the American Academy of Dermatology Teledermatology Program database, and the VA Computerized Patient Record System.

Patients registered for ≥ 1 year at VAPSHCS with a diagnosis of primary cutaneous malignant melanoma by the Pathology service between January 1, 2006, and December 31, 2013, were included. Patients with metastatic or recurrent melanoma were excluded.

Cases were randomly selected from a melanoma database previously validated and used for another quality improvement project.7 There were initially 115 patient cases extracted from this database for both the FTF and SFT groups. Eighty-seven SFT and 107 FTF cases met inclusion criteria. To further analyze these groups, we split the FTF group into 2 subgroups: FTF dermatology (patients whose melanomas were entered into care in a dermatology clinic) and FTF primary care (patients whose melanomas were entered into care in primary care or a nondermatology setting).

The timeline of care was divided into 2 major time intervals: (1) entry into episode of care (EEC; the date a lesion was first documented in the electronic health record) to biopsy; and (2) biopsy to definitive excision. The SFT process was divided into the following intervals: EEC to imaging request (the date a clinician requested imaging); imaging request to imaging completion (the date an imager photographed a patient’s lesion); imaging completion to SFT consultation request (the date the SFT consultation was requested); SFT consultation request to consultation completion (the date an SFT reader completed the consultation request for a patient); and SFT consultation completion to biopsy. Mean and median interval lengths were compared between groups and additional analyses identified steps that may have contributed to delays in care.

To address potential bias based on access to care for rural veterans, SFT and FTF primary care cases were categorized into groups based on their location: (1) EEC and biopsy conducted at the same facility; (2) EEC and biopsy conducted at different facilities within the same health care system (main health care facility and its community-based outpatient clinics); and (3) EEC and biopsy conducted at different health care systems.

Statistics

Means, medians, and SDs were calculated in Excel. The Mann-Whitney U test was used to compare SFT medians to the FTF data and X2 test was used to compare proportions for secondary analyses.

Results

The median (mean) interval from EEC to definitive excision was 73 days (85) for SFT and 58 days (73) for FTF (P = .004) (Table). To understand this difference, the distribution of intervals from EEC to biopsy and biopsy to definitive excision were calculated. Only 38% of SFT cases were biopsied within 20 days compared to 65% of FTF cases (P < .001). The difference in time from biopsy to definitive excision distributions were not statistically significant, suggesting that the difference is actually a reflection of the differences seen in the period between EEC and biopsy.

0525FED-AVAHO-MEL_T1

EEC and biopsy occurred at the same facility in 85% and 82% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different facilities within the same health care system in 15% and 16% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different health care systems in 0% and 2% of FTF primary care and SFT cases, respectively. Geographic bias did not impact results for either group of veterans.

The interval between EEC and biopsy was shorter for FTF dermatology cases than for FTF primary care cases. For FTF dermatology cases, 96% were biopsied within 20 days compared with 34% of FTF primary care cases (P < .001).

To further analyze the difference in the EEC to biopsy interval duration between SFT and FTF primary care the timeline was divided into smaller steps: EEC to imaging completion, imaging completion to SFT consult completion, and SFT consult completion to biopsy. From EEC to SFT consult completion, SFT cases took a median of 6.0 days and a mean of 12.3 days, reflecting the administrative handoffs that must occur in SFT. A total of 82% of FTF primary care cases were entered into care and consultation was requested on the same day, while this was true for only 1% of SFT cases.

Since mortality data were not collected, the frequency of in situ melanomas and invasive melanomas (pathologic stage pT1a or greater) was used as a proxy for comparing outcomes. No significant difference was found in the frequency of in situ vs invasive melanomas in the SFT and FTF dermatology groups; however, there was a much higher frequency of invasive melanomas in the FTF primary care group (P = .007).

Discussion

This study compared the time to treatment for SFT vs FTF and identified important differences. The episode of care for melanomas diagnosed by SFT was statistically significantly longer (15 days) than those diagnosed by FTF. The interval between biopsy and definitive excision was a median of 34 and 38 days, and a mean of 48 and 44 days for SFT and FTF, respectively, which were not statistically significant. The difference in the total duration of the interval between EEC and definitive excision was accounted for by the duration of the interval from EEC to biopsy. When excluding dermatology clinic cases from the FTF group, there was no difference in the interval between EEC and biopsy for SFT and FTF primary care. The handoffs in SFT accounted for a median of 6 days and mean of 12 days, a significant portion of the timeline, and is a target for process improvement. The delay necessitated by handoffs did not significantly affect the distribution of in situ and invasive melanomas in the SFT and FTF dermatology groups. This suggests that SFT may have better outcomes than FTF primary care.

There has been extensive research on the timeline from the patient initially noticing a lesion to the EEC.8-11 There is also a body of research on the timeline from biopsy to definitive excision. 6,12-16 However, there has been little research on the timeline between EEC and biopsy, which comprises a large portion of the overall timeline of both SFT care and FTF care. This study analyzed the delays that can occur in this interval. When patients first enter FTF dermatology care, this timeline is quite short because lesions are often biopsied on the same day. When patients enter into care with their primary or nondermatology clinician, there can be significant delays.

Since the stakes are high when it comes to treating melanoma, it is important to minimize the overall timeline. A 6-day median and 12-day mean were established as targets for teledermatology handoffs. Ideally, a lesion should be entered into an episode of care, imaged, and sent for consultation on the same day. To help further understand delays in administrative handoffs, we stratified the SFT cases by VISN 20 sites and spoke with an administrator at a top performing site. Between 2006 and 2013, this site had a dedicated full-time imager as well as a backup imager that ensured images were taken quickly, usually on the same day the lesion was entered into care. Unfortunately, this is not the standard at all VISN 20 sites and certainly contributes to the overall delay in care in SFT

Minimizing the timeline of care is possible, as shown by the Danish health system, which developed a fast-track referral system after recognizing the need to minimize delays between the presentation, diagnosis, and treatment of cutaneous melanomas. In Denmark, a patient who presents to a general practitioner with a suspicious lesion is referred to secondary care for excision biopsy within 6 days. Diagnosis is made within 2 weeks, and, if necessary, definitive excision is offered within 9 days of the diagnosis. This translates into a maximum 20-day EEC to biopsy timeline and maximum 29-day EEC to definitive excision timeline. Although an intervention such as this may be difficult to implement in the United States due to its size and decentralized health care system, it would, however, be more realistic within the VA due to its centralized structure. The Danish system shows that with appropriate resource allocation and strict timeframes for treatment referrals, the timeline can be minimized.17

Despite the delay in the SFT timeline, this study found no significant difference between the distribution of in situ vs invasive melanomas in FTF dermatology and SFT groups. One possible explanation for this is that SFT increases access to dermatologist care, meaning clinicians may be more willing to consult SFT for less advanced– appearing lesions.

The finding that SFT diagnosed a larger proportion of in situ melanomas than FTF primary care is consistent with the findings of Ferrándiz et al, who reported that the mean Breslow thickness was significantly lower among patients in an SFT group compared to patients in an FTF group consisting of general practitioners. 18 However, the study population was not randomized and the results may have been impacted by ascertainment bias. Ferrándiz et al hypothesized that clinicians may have a lower threshold for consulting teledermatology, resulting in lower mean Breslow thicknesses.18 Karavan et al found the opposite results, with a higher mean Breslow thickness in SFT compared to a primary care FTF group.19 The data presented here suggest that SFT has room for process improvement yet is essentially equivalent to FTF dermatology in terms of outcomes.

Limitations

The majority of patients in this study were aged > 50 years, White, and male. The results may not be representative for other populations. The study was relatively small compared to studies that looked at other aspects of the melanoma care timeline. The study was not powered to ascertain mortality, the most important metric for melanoma.

Conclusions

The episode of care was significantly longer for melanomas diagnosed by SFT than those diagnosed by FTF; however, timelines were not statistically different when FTF lesions entered into care in dermatology were excluded. A median 6-day and mean 12.3-day delay in administrative handoffs occurred at the beginning of the SFT process and is a target for process improvement. Considering the high stakes of melanoma, the SFT timeline could be reduced if EEC, imaging, and SFT consultation all happened in the same day.

Store-and-forward teledermatology (SFT) allows clinical images and information to be sent to a dermatologist for evaluation. In fiscal year (FY) 2018, 117,780 SFT consultations were completed in the Veterans Health Administration. Continued growth is expected since SFT has proven to be an effective method for improving access to face-to-face (FTF) dermatology care.1 In the same period, the US Department of Veterans Affairs (VA) Puget Sound Health Care System (VAPSHCS) completed 12,563 consultations in a mean 1.1 days from entry into episode of care (EEC), according to data reported by VA Teledermatology Program Administrator Chris Foster.

Obtaining a prompt consultation is reported to be an overwhelming advantage of using SFT.2-5 Rapid turnaround may appear to make SFT specialist care more accessible to veterans, yet this is an oversimplification. The process of delivering care (rather than consultation) through SFT is more complex than reading the images and reporting the findings. When a skin condition is identified by a primary care clinician and that person decides to request an SFT consultation, a complex set of tasks and handoffs is set into motion. A swim-lane diagram illustrates the numerous steps and handoffs that go into delivering care to a patient with a malignant melanoma on the SFT platform compared to FTF care, which requires fewer handoffs (Figure).

0525FED-AVAHO-MEL_F1

This process improvement project examined whether handoffs necessitated by SFT care lengthened the timeline of care for biopsy-proven primary cutaneous malignant melanoma. The stakes of delay in care are high. A 2018 study using the National Cancer Database found that a delay of > 30 days from biopsy to definitive excision (the date definitive surgical procedure for the condition is performed) resulted in a measurable increase in melanoma-related mortality. 6 This study sought to identify areas where the SFT timeline of care could be shortened.

Methods

This retrospective cohort study was approved by the VAPSHCS Institutional Review Board. The study drew from secondary data obtained from VistA, the VA Corporate Data Warehouse, the Veterans Integrated Service Network (VISN) 20 database, the American Academy of Dermatology Teledermatology Program database, and the VA Computerized Patient Record System.

Patients registered for ≥ 1 year at VAPSHCS with a diagnosis of primary cutaneous malignant melanoma by the Pathology service between January 1, 2006, and December 31, 2013, were included. Patients with metastatic or recurrent melanoma were excluded.

Cases were randomly selected from a melanoma database previously validated and used for another quality improvement project.7 There were initially 115 patient cases extracted from this database for both the FTF and SFT groups. Eighty-seven SFT and 107 FTF cases met inclusion criteria. To further analyze these groups, we split the FTF group into 2 subgroups: FTF dermatology (patients whose melanomas were entered into care in a dermatology clinic) and FTF primary care (patients whose melanomas were entered into care in primary care or a nondermatology setting).

The timeline of care was divided into 2 major time intervals: (1) entry into episode of care (EEC; the date a lesion was first documented in the electronic health record) to biopsy; and (2) biopsy to definitive excision. The SFT process was divided into the following intervals: EEC to imaging request (the date a clinician requested imaging); imaging request to imaging completion (the date an imager photographed a patient’s lesion); imaging completion to SFT consultation request (the date the SFT consultation was requested); SFT consultation request to consultation completion (the date an SFT reader completed the consultation request for a patient); and SFT consultation completion to biopsy. Mean and median interval lengths were compared between groups and additional analyses identified steps that may have contributed to delays in care.

To address potential bias based on access to care for rural veterans, SFT and FTF primary care cases were categorized into groups based on their location: (1) EEC and biopsy conducted at the same facility; (2) EEC and biopsy conducted at different facilities within the same health care system (main health care facility and its community-based outpatient clinics); and (3) EEC and biopsy conducted at different health care systems.

Statistics

Means, medians, and SDs were calculated in Excel. The Mann-Whitney U test was used to compare SFT medians to the FTF data and X2 test was used to compare proportions for secondary analyses.

Results

The median (mean) interval from EEC to definitive excision was 73 days (85) for SFT and 58 days (73) for FTF (P = .004) (Table). To understand this difference, the distribution of intervals from EEC to biopsy and biopsy to definitive excision were calculated. Only 38% of SFT cases were biopsied within 20 days compared to 65% of FTF cases (P < .001). The difference in time from biopsy to definitive excision distributions were not statistically significant, suggesting that the difference is actually a reflection of the differences seen in the period between EEC and biopsy.

0525FED-AVAHO-MEL_T1

EEC and biopsy occurred at the same facility in 85% and 82% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different facilities within the same health care system in 15% and 16% of FTF primary care and SFT cases, respectively. EEC and biopsy occurred at different health care systems in 0% and 2% of FTF primary care and SFT cases, respectively. Geographic bias did not impact results for either group of veterans.

The interval between EEC and biopsy was shorter for FTF dermatology cases than for FTF primary care cases. For FTF dermatology cases, 96% were biopsied within 20 days compared with 34% of FTF primary care cases (P < .001).

To further analyze the difference in the EEC to biopsy interval duration between SFT and FTF primary care the timeline was divided into smaller steps: EEC to imaging completion, imaging completion to SFT consult completion, and SFT consult completion to biopsy. From EEC to SFT consult completion, SFT cases took a median of 6.0 days and a mean of 12.3 days, reflecting the administrative handoffs that must occur in SFT. A total of 82% of FTF primary care cases were entered into care and consultation was requested on the same day, while this was true for only 1% of SFT cases.

Since mortality data were not collected, the frequency of in situ melanomas and invasive melanomas (pathologic stage pT1a or greater) was used as a proxy for comparing outcomes. No significant difference was found in the frequency of in situ vs invasive melanomas in the SFT and FTF dermatology groups; however, there was a much higher frequency of invasive melanomas in the FTF primary care group (P = .007).

Discussion

This study compared the time to treatment for SFT vs FTF and identified important differences. The episode of care for melanomas diagnosed by SFT was statistically significantly longer (15 days) than those diagnosed by FTF. The interval between biopsy and definitive excision was a median of 34 and 38 days, and a mean of 48 and 44 days for SFT and FTF, respectively, which were not statistically significant. The difference in the total duration of the interval between EEC and definitive excision was accounted for by the duration of the interval from EEC to biopsy. When excluding dermatology clinic cases from the FTF group, there was no difference in the interval between EEC and biopsy for SFT and FTF primary care. The handoffs in SFT accounted for a median of 6 days and mean of 12 days, a significant portion of the timeline, and is a target for process improvement. The delay necessitated by handoffs did not significantly affect the distribution of in situ and invasive melanomas in the SFT and FTF dermatology groups. This suggests that SFT may have better outcomes than FTF primary care.

There has been extensive research on the timeline from the patient initially noticing a lesion to the EEC.8-11 There is also a body of research on the timeline from biopsy to definitive excision. 6,12-16 However, there has been little research on the timeline between EEC and biopsy, which comprises a large portion of the overall timeline of both SFT care and FTF care. This study analyzed the delays that can occur in this interval. When patients first enter FTF dermatology care, this timeline is quite short because lesions are often biopsied on the same day. When patients enter into care with their primary or nondermatology clinician, there can be significant delays.

Since the stakes are high when it comes to treating melanoma, it is important to minimize the overall timeline. A 6-day median and 12-day mean were established as targets for teledermatology handoffs. Ideally, a lesion should be entered into an episode of care, imaged, and sent for consultation on the same day. To help further understand delays in administrative handoffs, we stratified the SFT cases by VISN 20 sites and spoke with an administrator at a top performing site. Between 2006 and 2013, this site had a dedicated full-time imager as well as a backup imager that ensured images were taken quickly, usually on the same day the lesion was entered into care. Unfortunately, this is not the standard at all VISN 20 sites and certainly contributes to the overall delay in care in SFT

Minimizing the timeline of care is possible, as shown by the Danish health system, which developed a fast-track referral system after recognizing the need to minimize delays between the presentation, diagnosis, and treatment of cutaneous melanomas. In Denmark, a patient who presents to a general practitioner with a suspicious lesion is referred to secondary care for excision biopsy within 6 days. Diagnosis is made within 2 weeks, and, if necessary, definitive excision is offered within 9 days of the diagnosis. This translates into a maximum 20-day EEC to biopsy timeline and maximum 29-day EEC to definitive excision timeline. Although an intervention such as this may be difficult to implement in the United States due to its size and decentralized health care system, it would, however, be more realistic within the VA due to its centralized structure. The Danish system shows that with appropriate resource allocation and strict timeframes for treatment referrals, the timeline can be minimized.17

Despite the delay in the SFT timeline, this study found no significant difference between the distribution of in situ vs invasive melanomas in FTF dermatology and SFT groups. One possible explanation for this is that SFT increases access to dermatologist care, meaning clinicians may be more willing to consult SFT for less advanced– appearing lesions.

The finding that SFT diagnosed a larger proportion of in situ melanomas than FTF primary care is consistent with the findings of Ferrándiz et al, who reported that the mean Breslow thickness was significantly lower among patients in an SFT group compared to patients in an FTF group consisting of general practitioners. 18 However, the study population was not randomized and the results may have been impacted by ascertainment bias. Ferrándiz et al hypothesized that clinicians may have a lower threshold for consulting teledermatology, resulting in lower mean Breslow thicknesses.18 Karavan et al found the opposite results, with a higher mean Breslow thickness in SFT compared to a primary care FTF group.19 The data presented here suggest that SFT has room for process improvement yet is essentially equivalent to FTF dermatology in terms of outcomes.

Limitations

The majority of patients in this study were aged > 50 years, White, and male. The results may not be representative for other populations. The study was relatively small compared to studies that looked at other aspects of the melanoma care timeline. The study was not powered to ascertain mortality, the most important metric for melanoma.

Conclusions

The episode of care was significantly longer for melanomas diagnosed by SFT than those diagnosed by FTF; however, timelines were not statistically different when FTF lesions entered into care in dermatology were excluded. A median 6-day and mean 12.3-day delay in administrative handoffs occurred at the beginning of the SFT process and is a target for process improvement. Considering the high stakes of melanoma, the SFT timeline could be reduced if EEC, imaging, and SFT consultation all happened in the same day.

References
  1. Raugi GJ, Nelson W, Miethke M, et al. Teledermatology implementation in a VHA secondary treatment facility improves access to face-to-face care. Telemed J E Health. 2016;22(1):12-17. doi:10.1089/tmj.2015.0036
  2. Moreno-Ramirez D, Ferrandiz L, Nieto-Garcia A, et al. Store-and-forward teledermatology in skin cancer triage: experience and evaluation of 2009 teleconsultations. Arch Dermatol. 2007;143(4):479-484. doi:10.1001/archderm.143.4.479
  3. Landow SM, Oh DH, Weinstock MA. Teledermatology within the Veterans Health Administration, 2002–2014. Telemed J E Health. 2015;21(10):769-773. doi:10.1089/tmj.2014.0225
  4. Whited JD, Hall RP, Foy ME, et al. Teledermatology’s impact on time to intervention among referrals to a dermatology consult service. Telemed J E Health. 2002;8(3):313-321. doi:10.1089/15305620260353207
  5. Hsiao JL, Oh DH. The impact of store-and-forward teledermatology on skin cancer diagnosis and treatment. J Am Acad Dermatol. 2008;59(2):260-267. doi:10.1016/j.jaad.2008.04.011
  6. Conic RZ, Cabrera CI, Khorana AA, Gastman BR. Determination of the impact of melanoma surgical timing on survival using the National Cancer Database. J Am Acad Dermatol. 2018;78(1):40-46.e7. doi:10.1016/j.jaad.2017.08.039
  7. Dougall B, Gendreau J, Das S, et al. Melanoma registry underreporting in the Veterans Health Administration. Fed Pract. 2016;33(suppl 5):55S-59S
  8. Xavier MHSB, Drummond-Lage AP, Baeta C, Rocha L, Almeida AM, Wainstein AJA. Delay in cutaneous melanoma diagnosis: sequence analyses from suspicion to diagnosis in 211 patients. Medicine (Baltimore). 2016;95(31):e4396. doi:10.1097/md.0000000000004396
  9. Schmid-Wendtner MH, Baumert J, Stange J, Volkenandt M. Delay in the diagnosis of cutaneous melanoma: an analysis of 233 patients. Melanoma Res. 2002;12(4):389-394. doi:10.1097/00008390-200208000-00012
  10. Betti, R, Vergani R, Tolomio E, Santambrogio R, Crosti C. Factors of delay in the diagnosis of melanoma. Eur J Dermatol. 2003;13(2):183-188.
  11. Blum A, Brand CU, Ellwanger U, et al. Awareness and early detection of cutaneous melanoma: An analysis of factors related to delay in treatment. Br J Dermatol. 1999;141(5):783-787. doi:10.1046/j.1365-2133.1999.03196.x
  12. Brian T, Adams B, Jameson M. Cutaneous melanoma: an audit of management timeliness against New Zealand guidelines. N Z Med J. 2017;130(1462):54-61. https://pubmed.ncbi.nlm.nih.gov/28934768
  13. Adamson AS, Zhou L, Baggett CD, Thomas NE, Meyer AM. Association of delays in surgery for melanoma with Insurance type. JAMA Dermatol. 2017;153(11):1106-1113. doi:https://doi.org/10.1001/jamadermatol.2017.3338
  14. Niehues NB, Evanson B, Smith WA, Fiore CT, Parekh P. Melanoma patient notification and treatment timelines. Dermatol Online J. 2019;25(4)13. doi:10.5070/d3254043588
  15. Lott JP, Narayan D, Soulos PR, Aminawung J, Gross CP. Delay of surgery for melanoma among Medicare beneficiaries. JAMA Dermatol. 2015;151(7):731-741. doi:10.1001/jamadermatol.2015.119
  16. Baranowski MLH, Yeung H, Chen SC, Gillespie TW, Goodman M. Factors associated with time to surgery in melanoma: an analysis of the National Cancer Database. J Am Acad Dermatol. 2019;81(4):908-916. doi:10.1016/j.jaad.2019.05.079
  17. Jarjis RD, Hansen LB, Matzen SH. A fast-track referral system for skin lesions suspicious of melanoma: population-based cross-sectional study from a plastic surgery center. Plast Surg Int. 2016;2016:2908917. doi:10.1155/2016/2908917
  18. Ferrándiz L, Ruiz-de-Casas A, Martin-Gutierrez FJ, et al. Effect of teledermatology on the prognosis of patients with cutaneous melanoma. Arch Dermatol. 2012;148(9):1025-1028. doi:10.1001/archdermatol.2012.778
  19. Karavan M, Compton N, Knezevich S, et al. Teledermatology in the diagnosis of melanoma. J Telemed Telecare. 2014;20(1):18-23. doi:10.1177/1357633x13517354
References
  1. Raugi GJ, Nelson W, Miethke M, et al. Teledermatology implementation in a VHA secondary treatment facility improves access to face-to-face care. Telemed J E Health. 2016;22(1):12-17. doi:10.1089/tmj.2015.0036
  2. Moreno-Ramirez D, Ferrandiz L, Nieto-Garcia A, et al. Store-and-forward teledermatology in skin cancer triage: experience and evaluation of 2009 teleconsultations. Arch Dermatol. 2007;143(4):479-484. doi:10.1001/archderm.143.4.479
  3. Landow SM, Oh DH, Weinstock MA. Teledermatology within the Veterans Health Administration, 2002–2014. Telemed J E Health. 2015;21(10):769-773. doi:10.1089/tmj.2014.0225
  4. Whited JD, Hall RP, Foy ME, et al. Teledermatology’s impact on time to intervention among referrals to a dermatology consult service. Telemed J E Health. 2002;8(3):313-321. doi:10.1089/15305620260353207
  5. Hsiao JL, Oh DH. The impact of store-and-forward teledermatology on skin cancer diagnosis and treatment. J Am Acad Dermatol. 2008;59(2):260-267. doi:10.1016/j.jaad.2008.04.011
  6. Conic RZ, Cabrera CI, Khorana AA, Gastman BR. Determination of the impact of melanoma surgical timing on survival using the National Cancer Database. J Am Acad Dermatol. 2018;78(1):40-46.e7. doi:10.1016/j.jaad.2017.08.039
  7. Dougall B, Gendreau J, Das S, et al. Melanoma registry underreporting in the Veterans Health Administration. Fed Pract. 2016;33(suppl 5):55S-59S
  8. Xavier MHSB, Drummond-Lage AP, Baeta C, Rocha L, Almeida AM, Wainstein AJA. Delay in cutaneous melanoma diagnosis: sequence analyses from suspicion to diagnosis in 211 patients. Medicine (Baltimore). 2016;95(31):e4396. doi:10.1097/md.0000000000004396
  9. Schmid-Wendtner MH, Baumert J, Stange J, Volkenandt M. Delay in the diagnosis of cutaneous melanoma: an analysis of 233 patients. Melanoma Res. 2002;12(4):389-394. doi:10.1097/00008390-200208000-00012
  10. Betti, R, Vergani R, Tolomio E, Santambrogio R, Crosti C. Factors of delay in the diagnosis of melanoma. Eur J Dermatol. 2003;13(2):183-188.
  11. Blum A, Brand CU, Ellwanger U, et al. Awareness and early detection of cutaneous melanoma: An analysis of factors related to delay in treatment. Br J Dermatol. 1999;141(5):783-787. doi:10.1046/j.1365-2133.1999.03196.x
  12. Brian T, Adams B, Jameson M. Cutaneous melanoma: an audit of management timeliness against New Zealand guidelines. N Z Med J. 2017;130(1462):54-61. https://pubmed.ncbi.nlm.nih.gov/28934768
  13. Adamson AS, Zhou L, Baggett CD, Thomas NE, Meyer AM. Association of delays in surgery for melanoma with Insurance type. JAMA Dermatol. 2017;153(11):1106-1113. doi:https://doi.org/10.1001/jamadermatol.2017.3338
  14. Niehues NB, Evanson B, Smith WA, Fiore CT, Parekh P. Melanoma patient notification and treatment timelines. Dermatol Online J. 2019;25(4)13. doi:10.5070/d3254043588
  15. Lott JP, Narayan D, Soulos PR, Aminawung J, Gross CP. Delay of surgery for melanoma among Medicare beneficiaries. JAMA Dermatol. 2015;151(7):731-741. doi:10.1001/jamadermatol.2015.119
  16. Baranowski MLH, Yeung H, Chen SC, Gillespie TW, Goodman M. Factors associated with time to surgery in melanoma: an analysis of the National Cancer Database. J Am Acad Dermatol. 2019;81(4):908-916. doi:10.1016/j.jaad.2019.05.079
  17. Jarjis RD, Hansen LB, Matzen SH. A fast-track referral system for skin lesions suspicious of melanoma: population-based cross-sectional study from a plastic surgery center. Plast Surg Int. 2016;2016:2908917. doi:10.1155/2016/2908917
  18. Ferrándiz L, Ruiz-de-Casas A, Martin-Gutierrez FJ, et al. Effect of teledermatology on the prognosis of patients with cutaneous melanoma. Arch Dermatol. 2012;148(9):1025-1028. doi:10.1001/archdermatol.2012.778
  19. Karavan M, Compton N, Knezevich S, et al. Teledermatology in the diagnosis of melanoma. J Telemed Telecare. 2014;20(1):18-23. doi:10.1177/1357633x13517354
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Handoff Delays in Teledermatology Lengthen Timeline of Care for Veterans With Melanoma

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Clinicians Should Have Private Spaces for Telehealth According to VA Memo

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US Department of Veterans Affairs (VA) officials are insisting that when remote telehealth clinicians return to an office setting, they must have private workspaces “that foster trusted, confidential, and therapeutic relationships with veterans,” according to an April internal memo reported on by NPR

The return-to-office mandate followed a Trump Administration executive order in February indicated that mental health clinicians at the US Department of Veterans Affairs (VA) must physically return to their workplace by May 5. For some, the deadline came as early as April 14; however, that order, like many others, may now be being revised or reconsidered due to concerns that have been raised. Many mental health clinicians were hired specifically to work remotely. They worried there would simply not be enough space for them, particularly to provide confidential counseling.

Millions of veterans use telehealth to access VA care. More than 98% of VA mental health clinicians have conducted 1 video visit to screen and treat patients for anxiety, depression, posttraumatic stress disorder, and more. Telehealth has been particularly important for veterans living in rural communities.

The April VA memo stipulated that “spaces used to deliver synchronous telehealth services should offer the same level of privacy and therapeutic environment applicable to an in-person visit in the same space.”

Therapists, patients, advocacy groups, and lawmakers have expressed concern about the potential impacts the policy change could have on patient care for veterans and, above all, about what it could mean for privacy. On Mar. 27, the American Psychological Association issued a statement noting that the change “resulted in providers being asked to conduct sensitive therapy sessions in open office environments, cubicles, or shared spaces that fail to meet basic confidentiality and privacy requirements for the delivery of mental health care services.”

Twenty Democrats in the House of Representatives sent a letter to VA Secretary Doug Collins expressing concern with the return to office policy. According to the letter a VA social worker supervisor reported managing their caseload while sharing a 100 ft2 shower space with another supervisor. It also reported that Clinical Resource Hub employees were being told to report to buildings where federal employees from other agencies work. “We have heard from countless stakeholders, veterans, and Department of Veterans Affairs (VA) employees that by carrying out President Trump’s blanket return-to-office policy your administration is damaging veteran and employee trust in VA, disrupting and impeding veterans’ access to care, and creating untenable and inefficient conditions for both veterans and the VA workforce,” the letter stated.

“This is a clear violation of veterans’ privacy and VA’s obligation to protect veterans’ private health information, and risks violation of the Health Insurance Portability and Accountability Act (HIPAA),” the letter added.

The lawmakers noted that, as of March 10, the VA was exempting Veterans Crisis Line workers, most of whom had been working remotely for the past 5 years, responding to more than 10 million calls, texts, and chats. That move, they said, indicated “that you understand there will be negative impacts to veterans’ care due to the return-to-office order and that these must be mitigated.”

VA spokesperson Peter Kasperowicz called the privacy concerns “nonsensical” and blamed “fear mongering from the media.” The VA, he said, “is no longer a place where the status quo for employees is to simply phone it in from home.” He also claimed that “the small number of employees who are desperate to avoid returning to the office will do more to drive away staff and patients than VA’s commonsense return-to-office policy ever will.”

VA care, he said, would continue uninterrupted and the “VA will ensure that employees have a workspace that is appropriate for the work they do.”

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US Department of Veterans Affairs (VA) officials are insisting that when remote telehealth clinicians return to an office setting, they must have private workspaces “that foster trusted, confidential, and therapeutic relationships with veterans,” according to an April internal memo reported on by NPR

The return-to-office mandate followed a Trump Administration executive order in February indicated that mental health clinicians at the US Department of Veterans Affairs (VA) must physically return to their workplace by May 5. For some, the deadline came as early as April 14; however, that order, like many others, may now be being revised or reconsidered due to concerns that have been raised. Many mental health clinicians were hired specifically to work remotely. They worried there would simply not be enough space for them, particularly to provide confidential counseling.

Millions of veterans use telehealth to access VA care. More than 98% of VA mental health clinicians have conducted 1 video visit to screen and treat patients for anxiety, depression, posttraumatic stress disorder, and more. Telehealth has been particularly important for veterans living in rural communities.

The April VA memo stipulated that “spaces used to deliver synchronous telehealth services should offer the same level of privacy and therapeutic environment applicable to an in-person visit in the same space.”

Therapists, patients, advocacy groups, and lawmakers have expressed concern about the potential impacts the policy change could have on patient care for veterans and, above all, about what it could mean for privacy. On Mar. 27, the American Psychological Association issued a statement noting that the change “resulted in providers being asked to conduct sensitive therapy sessions in open office environments, cubicles, or shared spaces that fail to meet basic confidentiality and privacy requirements for the delivery of mental health care services.”

Twenty Democrats in the House of Representatives sent a letter to VA Secretary Doug Collins expressing concern with the return to office policy. According to the letter a VA social worker supervisor reported managing their caseload while sharing a 100 ft2 shower space with another supervisor. It also reported that Clinical Resource Hub employees were being told to report to buildings where federal employees from other agencies work. “We have heard from countless stakeholders, veterans, and Department of Veterans Affairs (VA) employees that by carrying out President Trump’s blanket return-to-office policy your administration is damaging veteran and employee trust in VA, disrupting and impeding veterans’ access to care, and creating untenable and inefficient conditions for both veterans and the VA workforce,” the letter stated.

“This is a clear violation of veterans’ privacy and VA’s obligation to protect veterans’ private health information, and risks violation of the Health Insurance Portability and Accountability Act (HIPAA),” the letter added.

The lawmakers noted that, as of March 10, the VA was exempting Veterans Crisis Line workers, most of whom had been working remotely for the past 5 years, responding to more than 10 million calls, texts, and chats. That move, they said, indicated “that you understand there will be negative impacts to veterans’ care due to the return-to-office order and that these must be mitigated.”

VA spokesperson Peter Kasperowicz called the privacy concerns “nonsensical” and blamed “fear mongering from the media.” The VA, he said, “is no longer a place where the status quo for employees is to simply phone it in from home.” He also claimed that “the small number of employees who are desperate to avoid returning to the office will do more to drive away staff and patients than VA’s commonsense return-to-office policy ever will.”

VA care, he said, would continue uninterrupted and the “VA will ensure that employees have a workspace that is appropriate for the work they do.”

US Department of Veterans Affairs (VA) officials are insisting that when remote telehealth clinicians return to an office setting, they must have private workspaces “that foster trusted, confidential, and therapeutic relationships with veterans,” according to an April internal memo reported on by NPR

The return-to-office mandate followed a Trump Administration executive order in February indicated that mental health clinicians at the US Department of Veterans Affairs (VA) must physically return to their workplace by May 5. For some, the deadline came as early as April 14; however, that order, like many others, may now be being revised or reconsidered due to concerns that have been raised. Many mental health clinicians were hired specifically to work remotely. They worried there would simply not be enough space for them, particularly to provide confidential counseling.

Millions of veterans use telehealth to access VA care. More than 98% of VA mental health clinicians have conducted 1 video visit to screen and treat patients for anxiety, depression, posttraumatic stress disorder, and more. Telehealth has been particularly important for veterans living in rural communities.

The April VA memo stipulated that “spaces used to deliver synchronous telehealth services should offer the same level of privacy and therapeutic environment applicable to an in-person visit in the same space.”

Therapists, patients, advocacy groups, and lawmakers have expressed concern about the potential impacts the policy change could have on patient care for veterans and, above all, about what it could mean for privacy. On Mar. 27, the American Psychological Association issued a statement noting that the change “resulted in providers being asked to conduct sensitive therapy sessions in open office environments, cubicles, or shared spaces that fail to meet basic confidentiality and privacy requirements for the delivery of mental health care services.”

Twenty Democrats in the House of Representatives sent a letter to VA Secretary Doug Collins expressing concern with the return to office policy. According to the letter a VA social worker supervisor reported managing their caseload while sharing a 100 ft2 shower space with another supervisor. It also reported that Clinical Resource Hub employees were being told to report to buildings where federal employees from other agencies work. “We have heard from countless stakeholders, veterans, and Department of Veterans Affairs (VA) employees that by carrying out President Trump’s blanket return-to-office policy your administration is damaging veteran and employee trust in VA, disrupting and impeding veterans’ access to care, and creating untenable and inefficient conditions for both veterans and the VA workforce,” the letter stated.

“This is a clear violation of veterans’ privacy and VA’s obligation to protect veterans’ private health information, and risks violation of the Health Insurance Portability and Accountability Act (HIPAA),” the letter added.

The lawmakers noted that, as of March 10, the VA was exempting Veterans Crisis Line workers, most of whom had been working remotely for the past 5 years, responding to more than 10 million calls, texts, and chats. That move, they said, indicated “that you understand there will be negative impacts to veterans’ care due to the return-to-office order and that these must be mitigated.”

VA spokesperson Peter Kasperowicz called the privacy concerns “nonsensical” and blamed “fear mongering from the media.” The VA, he said, “is no longer a place where the status quo for employees is to simply phone it in from home.” He also claimed that “the small number of employees who are desperate to avoid returning to the office will do more to drive away staff and patients than VA’s commonsense return-to-office policy ever will.”

VA care, he said, would continue uninterrupted and the “VA will ensure that employees have a workspace that is appropriate for the work they do.”

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Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends

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Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends

Click to view more from Cancer Data Trends 2025. 

References
  1. Shepherd-Banigan M, Zullig LL, Berkowitz TSZ, et al. Improving Cancer Care
    for Women Seeking Services in the Veterans Health Administration Through the
    Breast and Gynecological Oncology System of Excellence. Mil Med. 2024:usae447.
    doi:10.1093/milmed/usae447
  2. US Preventive Services Task Force, Nicholson WK, Silverstein M, et al. Screening
    for Breast Cancer: US Preventive Services Task Force Recommendation Statement.
    JAMA. 2024;331(22):1918-1930. doi:10.1001/jama.2024.5534
  3. VA announces steps to increase life-saving screening, access to benefits for
    Veterans with cancer. VA News. March 8, 2024. Accessed January 14, 2025. https://
    news.va.gov/press-room/va-expands-health-care-benefits-veterans-cancer/
  4. Rezoug Z, Totten SP, Szlachtycz D, et al. Universal Genetic Testing for Newly
    Diagnosed Invasive Breast Cancer. JAMA Netw Open. 2024;7(9):e2431427.
    doi:10.1001/jamanetworkopen.2024.31427
  5. National Institutes of Health. National Cancer Institute. Surveillance, Epidemiology,
    and End Results Program. Cancer Stat Facts: Uterine Cancer. Accessed January 14,
    2025. https://seer.cancer.gov/statfacts/html/corp.html
  6. Clarke MA, Devesa SS, Hammer A, Wentzensen N. Racial and Ethnic Differences in
    Hysterectomy-Corrected Uterine Corpus Cancer Mortality by Stage and Histologic
    Subtype. JAMA Oncol. 2022;8(6):895-903. doi:10.1001/jamaoncol.2022.0009
  7. Moss HA, Rasmussen, KM, Patil, V, et al. Demographic Characteristics of Veterans
    Diagnosed With Breast and Gynecologic Cancers: A Comparative Analysis With the
    General Population. Abstract presented at: Annual Meeting of the Association of
    VA Hematology/Oncology (AVAHO); September 29–October 1, 2023; Chicago, IL.
    Abstract 47.
  8. Breland JY, Frayne SM, Saechao F, Gujral K, Vashi AA, Shaw JG, Gray KM, Illarmo SS,
    Urech T, Grant N, Berg E, Offer C, Veldanda S, Schoemaker L, Dalton AL, Esmaeili
    A, Phibbs CS, Hayes PM, Haskell S. Sourcebook: Women Veterans in the Veterans
    Health Administration. Volume 5: Longitudinal Trends in Sociodemographics and
    Utilization, Including Type, Modality, and Source of Care. Women’s Health Evaluation
    Initiative, Office of Women’s Health, Veterans Health Administration, Department of
    Veterans Affairs, Washington DC. June 2024.
  9. NCCN: National Comprehensive Cancer Network. Breast Cancer Screening and
    Diagnosis. V2.2024 April 9, 2024. Accessed January 14, 2025. https://www.nccn.
    org/professionals/physician_gls/pdf/breast-screening.pdf
  10. ACS: American Cancer Society. Breast Cancer Early Detection and Diagnosis.
    Revised December 19, 2023. Accessed January 14, 2025. https://www.cancer.org/
    cancer/types/breast-cancer/screening-tests-and-early-detection/american-cancersociety-
    recommendations-for-the-early-detection-of-breast-cancer.html
  11. Somasegar S, Bashi A, Lang SM, et al. Trends in Uterine Cancer Mortality
    in the United States: A 50-Year Population-Based Analysis. Obstet Gynecol.
    2023;142(4):978-986. doi:10.1097/AOG.0000000000005321
Author and Disclosure Information

Haley A. Moss, MD, MBA
Assistant Professor, Department of
Obstetrics and Gynecology
Duke University;
Director, Department of Veterans Affairs
Breast and Gynecologic Oncology System
of Excellence
Durham, North Carolina


Dr. Moss has no relevant financial relationships to disclose.

Publications
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Author and Disclosure Information

Haley A. Moss, MD, MBA
Assistant Professor, Department of
Obstetrics and Gynecology
Duke University;
Director, Department of Veterans Affairs
Breast and Gynecologic Oncology System
of Excellence
Durham, North Carolina


Dr. Moss has no relevant financial relationships to disclose.

Author and Disclosure Information

Haley A. Moss, MD, MBA
Assistant Professor, Department of
Obstetrics and Gynecology
Duke University;
Director, Department of Veterans Affairs
Breast and Gynecologic Oncology System
of Excellence
Durham, North Carolina


Dr. Moss has no relevant financial relationships to disclose.

Click to view more from Cancer Data Trends 2025. 

Click to view more from Cancer Data Trends 2025. 

References
  1. Shepherd-Banigan M, Zullig LL, Berkowitz TSZ, et al. Improving Cancer Care
    for Women Seeking Services in the Veterans Health Administration Through the
    Breast and Gynecological Oncology System of Excellence. Mil Med. 2024:usae447.
    doi:10.1093/milmed/usae447
  2. US Preventive Services Task Force, Nicholson WK, Silverstein M, et al. Screening
    for Breast Cancer: US Preventive Services Task Force Recommendation Statement.
    JAMA. 2024;331(22):1918-1930. doi:10.1001/jama.2024.5534
  3. VA announces steps to increase life-saving screening, access to benefits for
    Veterans with cancer. VA News. March 8, 2024. Accessed January 14, 2025. https://
    news.va.gov/press-room/va-expands-health-care-benefits-veterans-cancer/
  4. Rezoug Z, Totten SP, Szlachtycz D, et al. Universal Genetic Testing for Newly
    Diagnosed Invasive Breast Cancer. JAMA Netw Open. 2024;7(9):e2431427.
    doi:10.1001/jamanetworkopen.2024.31427
  5. National Institutes of Health. National Cancer Institute. Surveillance, Epidemiology,
    and End Results Program. Cancer Stat Facts: Uterine Cancer. Accessed January 14,
    2025. https://seer.cancer.gov/statfacts/html/corp.html
  6. Clarke MA, Devesa SS, Hammer A, Wentzensen N. Racial and Ethnic Differences in
    Hysterectomy-Corrected Uterine Corpus Cancer Mortality by Stage and Histologic
    Subtype. JAMA Oncol. 2022;8(6):895-903. doi:10.1001/jamaoncol.2022.0009
  7. Moss HA, Rasmussen, KM, Patil, V, et al. Demographic Characteristics of Veterans
    Diagnosed With Breast and Gynecologic Cancers: A Comparative Analysis With the
    General Population. Abstract presented at: Annual Meeting of the Association of
    VA Hematology/Oncology (AVAHO); September 29–October 1, 2023; Chicago, IL.
    Abstract 47.
  8. Breland JY, Frayne SM, Saechao F, Gujral K, Vashi AA, Shaw JG, Gray KM, Illarmo SS,
    Urech T, Grant N, Berg E, Offer C, Veldanda S, Schoemaker L, Dalton AL, Esmaeili
    A, Phibbs CS, Hayes PM, Haskell S. Sourcebook: Women Veterans in the Veterans
    Health Administration. Volume 5: Longitudinal Trends in Sociodemographics and
    Utilization, Including Type, Modality, and Source of Care. Women’s Health Evaluation
    Initiative, Office of Women’s Health, Veterans Health Administration, Department of
    Veterans Affairs, Washington DC. June 2024.
  9. NCCN: National Comprehensive Cancer Network. Breast Cancer Screening and
    Diagnosis. V2.2024 April 9, 2024. Accessed January 14, 2025. https://www.nccn.
    org/professionals/physician_gls/pdf/breast-screening.pdf
  10. ACS: American Cancer Society. Breast Cancer Early Detection and Diagnosis.
    Revised December 19, 2023. Accessed January 14, 2025. https://www.cancer.org/
    cancer/types/breast-cancer/screening-tests-and-early-detection/american-cancersociety-
    recommendations-for-the-early-detection-of-breast-cancer.html
  11. Somasegar S, Bashi A, Lang SM, et al. Trends in Uterine Cancer Mortality
    in the United States: A 50-Year Population-Based Analysis. Obstet Gynecol.
    2023;142(4):978-986. doi:10.1097/AOG.0000000000005321
References
  1. Shepherd-Banigan M, Zullig LL, Berkowitz TSZ, et al. Improving Cancer Care
    for Women Seeking Services in the Veterans Health Administration Through the
    Breast and Gynecological Oncology System of Excellence. Mil Med. 2024:usae447.
    doi:10.1093/milmed/usae447
  2. US Preventive Services Task Force, Nicholson WK, Silverstein M, et al. Screening
    for Breast Cancer: US Preventive Services Task Force Recommendation Statement.
    JAMA. 2024;331(22):1918-1930. doi:10.1001/jama.2024.5534
  3. VA announces steps to increase life-saving screening, access to benefits for
    Veterans with cancer. VA News. March 8, 2024. Accessed January 14, 2025. https://
    news.va.gov/press-room/va-expands-health-care-benefits-veterans-cancer/
  4. Rezoug Z, Totten SP, Szlachtycz D, et al. Universal Genetic Testing for Newly
    Diagnosed Invasive Breast Cancer. JAMA Netw Open. 2024;7(9):e2431427.
    doi:10.1001/jamanetworkopen.2024.31427
  5. National Institutes of Health. National Cancer Institute. Surveillance, Epidemiology,
    and End Results Program. Cancer Stat Facts: Uterine Cancer. Accessed January 14,
    2025. https://seer.cancer.gov/statfacts/html/corp.html
  6. Clarke MA, Devesa SS, Hammer A, Wentzensen N. Racial and Ethnic Differences in
    Hysterectomy-Corrected Uterine Corpus Cancer Mortality by Stage and Histologic
    Subtype. JAMA Oncol. 2022;8(6):895-903. doi:10.1001/jamaoncol.2022.0009
  7. Moss HA, Rasmussen, KM, Patil, V, et al. Demographic Characteristics of Veterans
    Diagnosed With Breast and Gynecologic Cancers: A Comparative Analysis With the
    General Population. Abstract presented at: Annual Meeting of the Association of
    VA Hematology/Oncology (AVAHO); September 29–October 1, 2023; Chicago, IL.
    Abstract 47.
  8. Breland JY, Frayne SM, Saechao F, Gujral K, Vashi AA, Shaw JG, Gray KM, Illarmo SS,
    Urech T, Grant N, Berg E, Offer C, Veldanda S, Schoemaker L, Dalton AL, Esmaeili
    A, Phibbs CS, Hayes PM, Haskell S. Sourcebook: Women Veterans in the Veterans
    Health Administration. Volume 5: Longitudinal Trends in Sociodemographics and
    Utilization, Including Type, Modality, and Source of Care. Women’s Health Evaluation
    Initiative, Office of Women’s Health, Veterans Health Administration, Department of
    Veterans Affairs, Washington DC. June 2024.
  9. NCCN: National Comprehensive Cancer Network. Breast Cancer Screening and
    Diagnosis. V2.2024 April 9, 2024. Accessed January 14, 2025. https://www.nccn.
    org/professionals/physician_gls/pdf/breast-screening.pdf
  10. ACS: American Cancer Society. Breast Cancer Early Detection and Diagnosis.
    Revised December 19, 2023. Accessed January 14, 2025. https://www.cancer.org/
    cancer/types/breast-cancer/screening-tests-and-early-detection/american-cancersociety-
    recommendations-for-the-early-detection-of-breast-cancer.html
  11. Somasegar S, Bashi A, Lang SM, et al. Trends in Uterine Cancer Mortality
    in the United States: A 50-Year Population-Based Analysis. Obstet Gynecol.
    2023;142(4):978-986. doi:10.1097/AOG.0000000000005321
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Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends

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Breast and Uterine Cancer: Screening Guidelines, Genetic Testing, and Mortality Trends

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The VHA Breast and Gynecologic Oncology System of Excellence (BGSoE), established in 2021, provides comprehensive, high-quality cancer care tailored to veterans diagnosed with breast and gynecologic cancers and those considered high-risk based on genetic testing or family history.1 Since its inception, the BGSoE has supported more than 7000 patients.1 For breast cancer, new USPSTF guidelines now recommend initiating biennial mammography at age 40, reflecting efforts to address rising incidence in younger populations.2 The VHA recommends genetic testing for all veterans diagnosed with invasive breast cancer in order to expand access to targeted therapies, facilitate risk reduction for secondary cancers, and enable cascade testing for at-risk family members.3,4

Uterine cancer is a growing concern for veterans, with rising incidence and mortality, particularly in aggressive nonendometrioid subtypes.5,6 Black women in particular have higher uterine cancer mortality rates. This is of particular relevance within the VA, as Black women are overrepresented compared to the general population.6,7 This disparity underscores the need to improve outcomes for all patients while prioritizing targeted interventions for Black women.

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References
  1. Bihn JR, Cioffi G, Waite KA, et al. Brain tumors in United States military veterans.
    Neuro Oncol. 2024;26(2):387-396. doi:10.1093/neuonc/noad182
  2. Stewart IJ, Howard JT, Poltavsky E, et al. Traumatic Brain Injury and Subsequent
    Risk of Brain Cancer in US Veterans of the Iraq and Afghanistan Wars. JAMA Netw
    Open. 2024;7(2):e2354588. doi:10.1001/jamanetworkopen.2023.54588
  3. DoD/USU Brain Tissue Repository. December 15, 2023. Accessed December 11,
    2024. https://researchbraininjury.org/
  4. Munch TN, Gørtz S, Wohlfahrt J, Melbye M. The long-term risk of malignant
    astrocytic tumors after structural brain injury--a nationwide cohort study. Neuro
    Oncol. 2015;17(5):718-724. doi:10.1093/neuonc/nou312
  5. Strowd RE, Dunbar EM, Gan HK, et al. Practical guidance for telemedicine use in
    neuro-oncology. Neurooncol Pract. 2022;9(2):91-104. doi:10.1093/nop/npac002
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(e100042. doi:10.1200/EDBK_100042
  7. Batool SM, Escobedo AK, Hsia T, et al. Clinical utility of a blood based assay for
    the detection of IDH1.R132H-mutant gliomas. Nat Commun. 2024;15(1):7074.
    doi:10.1038/s41467-024-51332-7
  8. Mellinghoff IK, van den Bent MJ, Blumenthal DT, et al; INDIGO Trial Investigators.
    Vorasidenib in IDH1- or IDH2-Mutant Low-Grade Glioma. N Engl J Med.
    2023;389(7):589-601. doi:10.1056/NEJMoa2304194
  9. FDA. US Food and Drug Administration. FDA approves vorasidenib for Grade 2
    astrocytoma or oligodendroglioma with a susceptible IDH1 or IDH2 mutation.
    Accessed December 11, 2024. https://www.fda.gov/drugs/resourcesinformation-
    approved-drugs/fda-approves-vorasidenib-grade-2-astrocytoma-oroligodendroglioma-
    susceptible-idh1-or-idh2-mutation
  10. NIH. National Cancer Institute. Tovorafenib Approved for Some Children with Low-
    Grade Glioma. Accessed December 11, 2024. https://www.cancer.gov/news-events/
    cancer-currents-blog/2024/pediatric-low-grade-glioma-tovorafenib-braf
  11. The Veteran Population. Accessed December 11, 2024. https://www.va.gov/vetdata/
    docs/surveysandstudies/vetpop.pdf
  12. Miller AM, Szalontay L, Bouvier N, et al. Next-generation sequencing of
    cerebrospinal fluid for clinical molecular diagnostics in pediatric, adolescent
    and young adult brain tumor patients. Neuro Oncol. 2022;24(10):1763-1772.
    doi:10.1093/neuonc/noac035
Author and Disclosure Information

Margaret O. Johnson, MD, MPH
Assistant Professor,
Department of Neurosurgery
Duke University School of Medicine;
Staff Physician
Department of Veterans Affairs
National Tele-Oncology Program
Durham, North Carolina


Dr. Johnson has no relevant financial relationships to disclose. 

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Margaret O. Johnson, MD, MPH
Assistant Professor,
Department of Neurosurgery
Duke University School of Medicine;
Staff Physician
Department of Veterans Affairs
National Tele-Oncology Program
Durham, North Carolina


Dr. Johnson has no relevant financial relationships to disclose. 

Author and Disclosure Information

Margaret O. Johnson, MD, MPH
Assistant Professor,
Department of Neurosurgery
Duke University School of Medicine;
Staff Physician
Department of Veterans Affairs
National Tele-Oncology Program
Durham, North Carolina


Dr. Johnson has no relevant financial relationships to disclose. 

Click to view more from Cancer Data Trends 2025. 

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References
  1. Bihn JR, Cioffi G, Waite KA, et al. Brain tumors in United States military veterans.
    Neuro Oncol. 2024;26(2):387-396. doi:10.1093/neuonc/noad182
  2. Stewart IJ, Howard JT, Poltavsky E, et al. Traumatic Brain Injury and Subsequent
    Risk of Brain Cancer in US Veterans of the Iraq and Afghanistan Wars. JAMA Netw
    Open. 2024;7(2):e2354588. doi:10.1001/jamanetworkopen.2023.54588
  3. DoD/USU Brain Tissue Repository. December 15, 2023. Accessed December 11,
    2024. https://researchbraininjury.org/
  4. Munch TN, Gørtz S, Wohlfahrt J, Melbye M. The long-term risk of malignant
    astrocytic tumors after structural brain injury--a nationwide cohort study. Neuro
    Oncol. 2015;17(5):718-724. doi:10.1093/neuonc/nou312
  5. Strowd RE, Dunbar EM, Gan HK, et al. Practical guidance for telemedicine use in
    neuro-oncology. Neurooncol Pract. 2022;9(2):91-104. doi:10.1093/nop/npac002
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(e100042. doi:10.1200/EDBK_100042
  7. Batool SM, Escobedo AK, Hsia T, et al. Clinical utility of a blood based assay for
    the detection of IDH1.R132H-mutant gliomas. Nat Commun. 2024;15(1):7074.
    doi:10.1038/s41467-024-51332-7
  8. Mellinghoff IK, van den Bent MJ, Blumenthal DT, et al; INDIGO Trial Investigators.
    Vorasidenib in IDH1- or IDH2-Mutant Low-Grade Glioma. N Engl J Med.
    2023;389(7):589-601. doi:10.1056/NEJMoa2304194
  9. FDA. US Food and Drug Administration. FDA approves vorasidenib for Grade 2
    astrocytoma or oligodendroglioma with a susceptible IDH1 or IDH2 mutation.
    Accessed December 11, 2024. https://www.fda.gov/drugs/resourcesinformation-
    approved-drugs/fda-approves-vorasidenib-grade-2-astrocytoma-oroligodendroglioma-
    susceptible-idh1-or-idh2-mutation
  10. NIH. National Cancer Institute. Tovorafenib Approved for Some Children with Low-
    Grade Glioma. Accessed December 11, 2024. https://www.cancer.gov/news-events/
    cancer-currents-blog/2024/pediatric-low-grade-glioma-tovorafenib-braf
  11. The Veteran Population. Accessed December 11, 2024. https://www.va.gov/vetdata/
    docs/surveysandstudies/vetpop.pdf
  12. Miller AM, Szalontay L, Bouvier N, et al. Next-generation sequencing of
    cerebrospinal fluid for clinical molecular diagnostics in pediatric, adolescent
    and young adult brain tumor patients. Neuro Oncol. 2022;24(10):1763-1772.
    doi:10.1093/neuonc/noac035
References
  1. Bihn JR, Cioffi G, Waite KA, et al. Brain tumors in United States military veterans.
    Neuro Oncol. 2024;26(2):387-396. doi:10.1093/neuonc/noad182
  2. Stewart IJ, Howard JT, Poltavsky E, et al. Traumatic Brain Injury and Subsequent
    Risk of Brain Cancer in US Veterans of the Iraq and Afghanistan Wars. JAMA Netw
    Open. 2024;7(2):e2354588. doi:10.1001/jamanetworkopen.2023.54588
  3. DoD/USU Brain Tissue Repository. December 15, 2023. Accessed December 11,
    2024. https://researchbraininjury.org/
  4. Munch TN, Gørtz S, Wohlfahrt J, Melbye M. The long-term risk of malignant
    astrocytic tumors after structural brain injury--a nationwide cohort study. Neuro
    Oncol. 2015;17(5):718-724. doi:10.1093/neuonc/nou312
  5. Strowd RE, Dunbar EM, Gan HK, et al. Practical guidance for telemedicine use in
    neuro-oncology. Neurooncol Pract. 2022;9(2):91-104. doi:10.1093/nop/npac002
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(e100042. doi:10.1200/EDBK_100042
  7. Batool SM, Escobedo AK, Hsia T, et al. Clinical utility of a blood based assay for
    the detection of IDH1.R132H-mutant gliomas. Nat Commun. 2024;15(1):7074.
    doi:10.1038/s41467-024-51332-7
  8. Mellinghoff IK, van den Bent MJ, Blumenthal DT, et al; INDIGO Trial Investigators.
    Vorasidenib in IDH1- or IDH2-Mutant Low-Grade Glioma. N Engl J Med.
    2023;389(7):589-601. doi:10.1056/NEJMoa2304194
  9. FDA. US Food and Drug Administration. FDA approves vorasidenib for Grade 2
    astrocytoma or oligodendroglioma with a susceptible IDH1 or IDH2 mutation.
    Accessed December 11, 2024. https://www.fda.gov/drugs/resourcesinformation-
    approved-drugs/fda-approves-vorasidenib-grade-2-astrocytoma-oroligodendroglioma-
    susceptible-idh1-or-idh2-mutation
  10. NIH. National Cancer Institute. Tovorafenib Approved for Some Children with Low-
    Grade Glioma. Accessed December 11, 2024. https://www.cancer.gov/news-events/
    cancer-currents-blog/2024/pediatric-low-grade-glioma-tovorafenib-braf
  11. The Veteran Population. Accessed December 11, 2024. https://www.va.gov/vetdata/
    docs/surveysandstudies/vetpop.pdf
  12. Miller AM, Szalontay L, Bouvier N, et al. Next-generation sequencing of
    cerebrospinal fluid for clinical molecular diagnostics in pediatric, adolescent
    and young adult brain tumor patients. Neuro Oncol. 2022;24(10):1763-1772.
    doi:10.1093/neuonc/noac035
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Brain Cancer: Epidemiology, TBI, and New Treatments

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Brain Cancer: Epidemiology, TBI, and New Treatments

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Brain cancer represents a notable health challenge for veterans. The first large-scale study on brain tumors in US veterans showed that the most frequently diagnosed tumors were nonmalignant pituitary tumors, nonmalignant meningiomas, and glioblastomas.1 Exposure to combat-related traumatic brain injuries (TBIs) may contribute to the risk for brain tumors, and further research is ongoing.2,3 A 2024 study demonstrated that veterans with moderate/severe and penetrating TBIs had an increased risk of brain cancer, but previous research in civilians has not echoed these findings.2,4 

As our understanding of the connection between TBI and brain cancer evolves, health care initiatives and new research are aiming to serve the veteran population most at risk. Telehealth is being used throughout the VA to help veterans, especially those in rural locations, receive neuro-oncology care.5,6 In terms of research, the DoD and Uniformed Services University have established a Brain Tissue Repository. This program may be better able to explore the TBI/brain cancer connection through veteran brain tissue donation.3

New assays are also being developed to help identify brain cancer faster. Liquid biopsy techniques focused on IDH1 have shown promise.7 In terms of treatment, the IDH1/IDH2 inhibitor vorasidenib prolonged progression free survival in grade 2 IDH-mutant gliomas in clinical trials and was approved by the FDA in 2024.8,9 Although not pertaining directly to the veteran population, a new treatment for pediatric brain tumors also was approved by the FDA in 2024.10 These milestones reflect an encouraging trend in precision medicine, opening doors for more targeted brain tumor therapies and tools across various patient groups.

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AI-Based Risk Stratification for Oropharyngeal Carcinomas: AIROC

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References

1.       Zevallos JP, Kramer JR, Sandulache VC, et al. National trends in oropharyngeal cancer incidence and survival within the Veterans Affairs Health Care System. Head Neck. 2021;43(1):108-115. doi:10.1002/hed.26465

2.       Fakhry C, Blackford AL, Neuner G, et al. Association of oral human papillomavirus DNA persistence with cancer progression after primary treatment for oral cavity and oropharyngeal squamous cell carcinoma. JAMA Oncol. 2019;5(7):985-992. doi:10.1001/jamaoncol.2019.0439

3.       Fakhry C, Zhang Q, Gillison ML, et al. Validation of NRG oncology/RTOG-0129 risk groups for HPV-positive and HPV-negative oropharyngeal squamous cell cancer: implications for risk-based therapeutic intensity trials. Cancer. 2019;125(12):2027-2038. doi:10.1002/cncr.32025

4.       O'Sullivan B, Huang SH, Su J, et al. Development and validation of a staging system for HPV-related oropharyngeal cancer by the International Collaboration on Oropharyngeal cancer Network for Staging (ICON-S): a multicentre cohort study. Lancet Oncol. 2016;17(4):440-451. doi:10.1016/S1470-2045(15)00560-4

5.       Koyuncu CF, Lu C, Bera K, et al. Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma. J Clin Invest. 2021;131(8):e145488. doi:10.1172/JCI145488

6.       Lu C, Lewis JS Jr, Dupont WD, Plummer WD Jr, Janowczyk A, Madabhushi A. An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival. Mod Pathol. 2017;30(12):1655-1665. doi:10.1038/modpathol.2017.98

7.       Corredor G, Toro P, Koyuncu C, et al. An imaging biomarker of tumor-infiltrating lymphocytes to risk-stratify patients with HPV-associated oropharyngeal cancer. J Natl Cancer Inst. 2022;114(4):609-617. doi:10.1093/jnci/djab215

8.       Cancer stat facts: oral cavity and pharynx cancer. National Cancer Institute, SEER Program. Accessed November 5, 2024. https://seer.cancer.gov/statfacts/html/oralcav.html

9.       Cancers associated with human papillomavirus. Centers for Disease Control and Prevention. September 18, 2024. Accessed November 5, 2024. https://www.cdc.gov/united-states-cancer-statistics/publications/hpv-associated-cancers.html

10.      Chidambaram S, Chang SH, Sandulache VC, Mazul AL, Zevallos JP. Human papillomavirus vaccination prevalence and disproportionate cancer burden among US veterans. JAMA Oncol. 2023;9(5):712-714. doi:10.1001/jamaoncol.2022.7944

11.      Corredor G, Wang X, Zhou Y, et al. Spatial architecture and arrangement of tumor-infiltrating lymphocytes for predicting likelihood of recurrence in early-stage non-small cell lung cancer. Clin Cancer Res. 2019;25(5):1526-1534. doi:10.1158/1078-0432.CCR-18-2013

12.      Alilou M, Orooji M, Beig N, et al. Quantitative vessel tortuosity: a potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Sci Rep. 2018;8(1):15290. doi:10.1038/s41598-018-33473-0

13.      Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, Meyer L, Gress DM, Byrd DR, Winchester DP. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging. CA Cancer J Clin. 2017;67(2):93-99. doi:10.3322/caac.21388

Author and Disclosure Information

Vlad C. Sandulache, MD, PhD
Associate Professor;
Department of Otolaryngology,
Head and Neck Surgery
Baylor College of Medicine;
Staff Physician
Michael E. DeBakey VA Medical Center
Houston, Texas
 

Disclosures: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for: FemtoVox Inc (Consultant; Equity holder); PDS Biotech (consultant).
Received income in an amount equal to or greater than $250 from: FemtoVox Inc; PDS Biotech.

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Author and Disclosure Information

Vlad C. Sandulache, MD, PhD
Associate Professor;
Department of Otolaryngology,
Head and Neck Surgery
Baylor College of Medicine;
Staff Physician
Michael E. DeBakey VA Medical Center
Houston, Texas
 

Disclosures: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for: FemtoVox Inc (Consultant; Equity holder); PDS Biotech (consultant).
Received income in an amount equal to or greater than $250 from: FemtoVox Inc; PDS Biotech.

Author and Disclosure Information

Vlad C. Sandulache, MD, PhD
Associate Professor;
Department of Otolaryngology,
Head and Neck Surgery
Baylor College of Medicine;
Staff Physician
Michael E. DeBakey VA Medical Center
Houston, Texas
 

Disclosures: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for: FemtoVox Inc (Consultant; Equity holder); PDS Biotech (consultant).
Received income in an amount equal to or greater than $250 from: FemtoVox Inc; PDS Biotech.

Click here to view more from Cancer Data Trends 2025.

Click here to view more from Cancer Data Trends 2025.

References

1.       Zevallos JP, Kramer JR, Sandulache VC, et al. National trends in oropharyngeal cancer incidence and survival within the Veterans Affairs Health Care System. Head Neck. 2021;43(1):108-115. doi:10.1002/hed.26465

2.       Fakhry C, Blackford AL, Neuner G, et al. Association of oral human papillomavirus DNA persistence with cancer progression after primary treatment for oral cavity and oropharyngeal squamous cell carcinoma. JAMA Oncol. 2019;5(7):985-992. doi:10.1001/jamaoncol.2019.0439

3.       Fakhry C, Zhang Q, Gillison ML, et al. Validation of NRG oncology/RTOG-0129 risk groups for HPV-positive and HPV-negative oropharyngeal squamous cell cancer: implications for risk-based therapeutic intensity trials. Cancer. 2019;125(12):2027-2038. doi:10.1002/cncr.32025

4.       O'Sullivan B, Huang SH, Su J, et al. Development and validation of a staging system for HPV-related oropharyngeal cancer by the International Collaboration on Oropharyngeal cancer Network for Staging (ICON-S): a multicentre cohort study. Lancet Oncol. 2016;17(4):440-451. doi:10.1016/S1470-2045(15)00560-4

5.       Koyuncu CF, Lu C, Bera K, et al. Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma. J Clin Invest. 2021;131(8):e145488. doi:10.1172/JCI145488

6.       Lu C, Lewis JS Jr, Dupont WD, Plummer WD Jr, Janowczyk A, Madabhushi A. An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival. Mod Pathol. 2017;30(12):1655-1665. doi:10.1038/modpathol.2017.98

7.       Corredor G, Toro P, Koyuncu C, et al. An imaging biomarker of tumor-infiltrating lymphocytes to risk-stratify patients with HPV-associated oropharyngeal cancer. J Natl Cancer Inst. 2022;114(4):609-617. doi:10.1093/jnci/djab215

8.       Cancer stat facts: oral cavity and pharynx cancer. National Cancer Institute, SEER Program. Accessed November 5, 2024. https://seer.cancer.gov/statfacts/html/oralcav.html

9.       Cancers associated with human papillomavirus. Centers for Disease Control and Prevention. September 18, 2024. Accessed November 5, 2024. https://www.cdc.gov/united-states-cancer-statistics/publications/hpv-associated-cancers.html

10.      Chidambaram S, Chang SH, Sandulache VC, Mazul AL, Zevallos JP. Human papillomavirus vaccination prevalence and disproportionate cancer burden among US veterans. JAMA Oncol. 2023;9(5):712-714. doi:10.1001/jamaoncol.2022.7944

11.      Corredor G, Wang X, Zhou Y, et al. Spatial architecture and arrangement of tumor-infiltrating lymphocytes for predicting likelihood of recurrence in early-stage non-small cell lung cancer. Clin Cancer Res. 2019;25(5):1526-1534. doi:10.1158/1078-0432.CCR-18-2013

12.      Alilou M, Orooji M, Beig N, et al. Quantitative vessel tortuosity: a potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Sci Rep. 2018;8(1):15290. doi:10.1038/s41598-018-33473-0

13.      Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, Meyer L, Gress DM, Byrd DR, Winchester DP. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging. CA Cancer J Clin. 2017;67(2):93-99. doi:10.3322/caac.21388

References

1.       Zevallos JP, Kramer JR, Sandulache VC, et al. National trends in oropharyngeal cancer incidence and survival within the Veterans Affairs Health Care System. Head Neck. 2021;43(1):108-115. doi:10.1002/hed.26465

2.       Fakhry C, Blackford AL, Neuner G, et al. Association of oral human papillomavirus DNA persistence with cancer progression after primary treatment for oral cavity and oropharyngeal squamous cell carcinoma. JAMA Oncol. 2019;5(7):985-992. doi:10.1001/jamaoncol.2019.0439

3.       Fakhry C, Zhang Q, Gillison ML, et al. Validation of NRG oncology/RTOG-0129 risk groups for HPV-positive and HPV-negative oropharyngeal squamous cell cancer: implications for risk-based therapeutic intensity trials. Cancer. 2019;125(12):2027-2038. doi:10.1002/cncr.32025

4.       O'Sullivan B, Huang SH, Su J, et al. Development and validation of a staging system for HPV-related oropharyngeal cancer by the International Collaboration on Oropharyngeal cancer Network for Staging (ICON-S): a multicentre cohort study. Lancet Oncol. 2016;17(4):440-451. doi:10.1016/S1470-2045(15)00560-4

5.       Koyuncu CF, Lu C, Bera K, et al. Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma. J Clin Invest. 2021;131(8):e145488. doi:10.1172/JCI145488

6.       Lu C, Lewis JS Jr, Dupont WD, Plummer WD Jr, Janowczyk A, Madabhushi A. An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival. Mod Pathol. 2017;30(12):1655-1665. doi:10.1038/modpathol.2017.98

7.       Corredor G, Toro P, Koyuncu C, et al. An imaging biomarker of tumor-infiltrating lymphocytes to risk-stratify patients with HPV-associated oropharyngeal cancer. J Natl Cancer Inst. 2022;114(4):609-617. doi:10.1093/jnci/djab215

8.       Cancer stat facts: oral cavity and pharynx cancer. National Cancer Institute, SEER Program. Accessed November 5, 2024. https://seer.cancer.gov/statfacts/html/oralcav.html

9.       Cancers associated with human papillomavirus. Centers for Disease Control and Prevention. September 18, 2024. Accessed November 5, 2024. https://www.cdc.gov/united-states-cancer-statistics/publications/hpv-associated-cancers.html

10.      Chidambaram S, Chang SH, Sandulache VC, Mazul AL, Zevallos JP. Human papillomavirus vaccination prevalence and disproportionate cancer burden among US veterans. JAMA Oncol. 2023;9(5):712-714. doi:10.1001/jamaoncol.2022.7944

11.      Corredor G, Wang X, Zhou Y, et al. Spatial architecture and arrangement of tumor-infiltrating lymphocytes for predicting likelihood of recurrence in early-stage non-small cell lung cancer. Clin Cancer Res. 2019;25(5):1526-1534. doi:10.1158/1078-0432.CCR-18-2013

12.      Alilou M, Orooji M, Beig N, et al. Quantitative vessel tortuosity: a potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Sci Rep. 2018;8(1):15290. doi:10.1038/s41598-018-33473-0

13.      Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, Meyer L, Gress DM, Byrd DR, Winchester DP. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging. CA Cancer J Clin. 2017;67(2):93-99. doi:10.3322/caac.21388

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AI-Based Risk Stratification for Oropharyngeal Carcinomas: AIROC

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In recent years, human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) has been on the rise in the veteran population, where smoking rates (a contributor to OPSCC development) have historically been higher than in the general population.1 Variable treatment response rates and survival in patients with OPSCC indicate that whereas some patients may benefit from treatment de-escalation and a concomitant reduction in treatment-related adverse effects, aggressive disease in a subset of patients mandates the use of rigorous chemoradiation treatments.2,3 At present, effective stratification systems identifying these patient subsets are lacking.4

To address this clinical gap, a team of VA clinicians and researchers is developing AIROC (an artificial intelligence [AI]-based risk stratification algorithm for oropharyngeal carcinomas).a AIROC is an AI and machine learning (ML)-based algorithm that may successfully stratify veterans with HPV-associated OPSCC into risk categories that can enable safer de-escalation or escalation of cancer treatments.5-7 By integrating AIROC into clinical practice, the VHA aims to personalize cancer treatment, improve patient outcomes, and establish a new standard of care for veterans with this deadly disease.
 

aThis work is funded by the Veterans Affairs Clinical Science Research and Development (CSRD) Service (grant I01BX006380).

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Rising Kidney Cancer Cases and Emerging Treatments for Veterans

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References

1. American Cancer Society website. Key Statistics About Kidney Cancer. Revised May 2024. Accessed December 18, 2024. https://www.cancer.org/cancer/types/kidney-cancer/about/key-statistics.html

2. American Cancer Society website. Cancer Facts & Figures 2024. 2024—First Year the US Expects More than 2M New Cases of Cancer. Published January 17, 2024. Accessed December 18, 2024.  https://www.cancer.org/research/acs-research-news/facts-and-figures-2024.html 

3.United States Department of Veterans Affairs factsheet. Pact Act & Gulf War, Post-911 Era Veterans. Published July 2023. Accessed December 18, 2024. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.va.gov/files/2023-08/PACT%20Act%20and%20Gulf%20War%2C%20Post-911%20Veterans%20NEW%20July%202023.pdf 

4. Li M, Li L, Zheng J, Li Z, Li S, Wang K, Chen X. Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application. Mol Cancer. 2023 Feb 21;22(1):37. doi:10.1186/s12943-023-01745-7

5. Bellman NL. Incidental Finding of Renal Cell Carcinoma: Detected by a Thrombus in the Inferior Vena Cava. Journal of Diagnostic Medical Sonography. 2015;31(2):118-121. doi:10.1177/8756479314546691

6. Brown JT. Adjuvant Therapy for Non-Clear Cell Renal Cell Carcinoma—The Ascent Continues. JAMA Network Open. 2024 Aug 1;7(8):e2425251. doi:10.1001/jamanetworkopen.2024.25251

7. Siva S, Louie AV, Kotecha R, et al. Stereotactic body radiotherapy for primary renal cell carcinoma: a systematic review and practice guideline from the International Society of Stereotactic Radiosurgery (ISRS). Lancet Oncol. 2024 Jan;25(1):e18-e28. doi: 10.1016/S1470-2045(23)00513-2.

8. Choueiri TK, Tomczak P, Park SH, et al; for the KEYNOTE-564 Investigators. Overall Survival with Adjuvant Pembrolizumab in Renal-Cell Carcinoma. N Engl J Med. 2024 Apr 18;390(15):1359-1371. doi:10.1056/NEJMoa2312695

9. Bytnar JA, McGlynn KA, Kern SQ, Shriver CD, Zhu K. Incidence rates of bladder and kidney cancers among US military servicemen: comparison with the rates in the general US population. Eur J Cancer Prev. 2024 Nov 1;33(6):505-511. doi:10.1097/CEJ.0000000000000886

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References

1. American Cancer Society website. Key Statistics About Kidney Cancer. Revised May 2024. Accessed December 18, 2024. https://www.cancer.org/cancer/types/kidney-cancer/about/key-statistics.html

2. American Cancer Society website. Cancer Facts & Figures 2024. 2024—First Year the US Expects More than 2M New Cases of Cancer. Published January 17, 2024. Accessed December 18, 2024.  https://www.cancer.org/research/acs-research-news/facts-and-figures-2024.html 

3.United States Department of Veterans Affairs factsheet. Pact Act & Gulf War, Post-911 Era Veterans. Published July 2023. Accessed December 18, 2024. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.va.gov/files/2023-08/PACT%20Act%20and%20Gulf%20War%2C%20Post-911%20Veterans%20NEW%20July%202023.pdf 

4. Li M, Li L, Zheng J, Li Z, Li S, Wang K, Chen X. Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application. Mol Cancer. 2023 Feb 21;22(1):37. doi:10.1186/s12943-023-01745-7

5. Bellman NL. Incidental Finding of Renal Cell Carcinoma: Detected by a Thrombus in the Inferior Vena Cava. Journal of Diagnostic Medical Sonography. 2015;31(2):118-121. doi:10.1177/8756479314546691

6. Brown JT. Adjuvant Therapy for Non-Clear Cell Renal Cell Carcinoma—The Ascent Continues. JAMA Network Open. 2024 Aug 1;7(8):e2425251. doi:10.1001/jamanetworkopen.2024.25251

7. Siva S, Louie AV, Kotecha R, et al. Stereotactic body radiotherapy for primary renal cell carcinoma: a systematic review and practice guideline from the International Society of Stereotactic Radiosurgery (ISRS). Lancet Oncol. 2024 Jan;25(1):e18-e28. doi: 10.1016/S1470-2045(23)00513-2.

8. Choueiri TK, Tomczak P, Park SH, et al; for the KEYNOTE-564 Investigators. Overall Survival with Adjuvant Pembrolizumab in Renal-Cell Carcinoma. N Engl J Med. 2024 Apr 18;390(15):1359-1371. doi:10.1056/NEJMoa2312695

9. Bytnar JA, McGlynn KA, Kern SQ, Shriver CD, Zhu K. Incidence rates of bladder and kidney cancers among US military servicemen: comparison with the rates in the general US population. Eur J Cancer Prev. 2024 Nov 1;33(6):505-511. doi:10.1097/CEJ.0000000000000886

References

1. American Cancer Society website. Key Statistics About Kidney Cancer. Revised May 2024. Accessed December 18, 2024. https://www.cancer.org/cancer/types/kidney-cancer/about/key-statistics.html

2. American Cancer Society website. Cancer Facts & Figures 2024. 2024—First Year the US Expects More than 2M New Cases of Cancer. Published January 17, 2024. Accessed December 18, 2024.  https://www.cancer.org/research/acs-research-news/facts-and-figures-2024.html 

3.United States Department of Veterans Affairs factsheet. Pact Act & Gulf War, Post-911 Era Veterans. Published July 2023. Accessed December 18, 2024. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.va.gov/files/2023-08/PACT%20Act%20and%20Gulf%20War%2C%20Post-911%20Veterans%20NEW%20July%202023.pdf 

4. Li M, Li L, Zheng J, Li Z, Li S, Wang K, Chen X. Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application. Mol Cancer. 2023 Feb 21;22(1):37. doi:10.1186/s12943-023-01745-7

5. Bellman NL. Incidental Finding of Renal Cell Carcinoma: Detected by a Thrombus in the Inferior Vena Cava. Journal of Diagnostic Medical Sonography. 2015;31(2):118-121. doi:10.1177/8756479314546691

6. Brown JT. Adjuvant Therapy for Non-Clear Cell Renal Cell Carcinoma—The Ascent Continues. JAMA Network Open. 2024 Aug 1;7(8):e2425251. doi:10.1001/jamanetworkopen.2024.25251

7. Siva S, Louie AV, Kotecha R, et al. Stereotactic body radiotherapy for primary renal cell carcinoma: a systematic review and practice guideline from the International Society of Stereotactic Radiosurgery (ISRS). Lancet Oncol. 2024 Jan;25(1):e18-e28. doi: 10.1016/S1470-2045(23)00513-2.

8. Choueiri TK, Tomczak P, Park SH, et al; for the KEYNOTE-564 Investigators. Overall Survival with Adjuvant Pembrolizumab in Renal-Cell Carcinoma. N Engl J Med. 2024 Apr 18;390(15):1359-1371. doi:10.1056/NEJMoa2312695

9. Bytnar JA, McGlynn KA, Kern SQ, Shriver CD, Zhu K. Incidence rates of bladder and kidney cancers among US military servicemen: comparison with the rates in the general US population. Eur J Cancer Prev. 2024 Nov 1;33(6):505-511. doi:10.1097/CEJ.0000000000000886

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Cases of kidney cancer, also known as renal cell carcinoma (RCC), are increasing, with more than 81,600 expected diagnoses in 2024, largely due to improved imaging and rising rates of risk factors, including obesity, hypertension, and diabetes.1,2 Veterans, particularly those exposed to chemicals and perfluoroalkyl and polyfluoroalkyl substances (PFAS), face a higher risk for RCC. Under the PACT Act, RCC may be recognized as service-related for Gulf War and post-9/11 veterans.3,4

RCC accounts for more than 90% of kidney cancers and is often asymptomatic, making early detection reliant on an incidental finding on imaging.4,5 Treatment for localized RCC typically involves surgery, with adjuvant immunotherapy for high-risk cases, though up to 50% of patients may still experience recurrence.6 Emerging treatments like stereotactic body radiotherapy (SBRT) are gaining attention for managing inoperable or high-risk RCC as it has demonstrated high rates of effectiveness, local control, and strong survival outcomes; however, further comparison with surgical options is needed.7 Advances in adjuvant therapies for kidney cancer emphasize the potential to extend survival for high-risk patients post-surgery, but balancing the benefits with risks of this treatment remains crucial.8

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Advances in Blood Cancer Care for Veterans

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References
  1. Li W, ed. The 5th Edition of the World Health Organization Classification of
    Hematolymphoid Tumors. In: Leukemia [Internet]. Brisbane (AU): Exon Publications;
    October 16, 2022. https://www.ncbi.nlm.nih.gov/books/NBK586208/
  2. Graf SA, Samples LS, Keating TM, Garcia JM. Clinical research in older adults with
    hematologic malignancies: Opportunities for alignment in the Veterans Affairs. Semin
    Oncol. 2020;47(1):94-101. doi:10.1053/j.seminoncol.2020.02.010.
  3. Tiu A, McKinnell Z, Liu S, et al. Risk of myeloproliferative neoplasms among
    U.S. Veterans from Korean, Vietnam, and Persian Gulf War eras. Am J Hematol.
    2024;99(10):1969-1978. doi:10.1002/ajh.27438
  4. Ma H, Wan JY, Cortessis VK, Gupta P, Cozen W. Survival in Agent Orange
    exposed and unexposed Vietnam-era veterans who were diagnosed with
    lymphoid malignancies. Blood Adv. 2024;8(4):1037-1041. doi:10.1182/
    bloodadvances.2023011999
  5. Friedman DR, Rodgers TD, Kovalick C, Yellapragada S, Szumita L, Weiss ES. Veterans
    with blood cancers: Clinical trial navigation and the challenge of rurality. J Rural
    Health. 2024;40(1):114-120. doi:10.1111/jrh.12773
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(3):e100042. doi:10.1200/EDBK_100042
  7. Pulumati A, Pulumati A, Dwarakanath BS, Verma A, Papineni RVL. Technological
    advancements in cancer diagnostics: Improvements and limitations. Cancer Rep
    (Hoboken). 2023;6(2):e1764. doi:10.1002/cnr2.1764
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Durham VA Medical Center
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References
  1. Li W, ed. The 5th Edition of the World Health Organization Classification of
    Hematolymphoid Tumors. In: Leukemia [Internet]. Brisbane (AU): Exon Publications;
    October 16, 2022. https://www.ncbi.nlm.nih.gov/books/NBK586208/
  2. Graf SA, Samples LS, Keating TM, Garcia JM. Clinical research in older adults with
    hematologic malignancies: Opportunities for alignment in the Veterans Affairs. Semin
    Oncol. 2020;47(1):94-101. doi:10.1053/j.seminoncol.2020.02.010.
  3. Tiu A, McKinnell Z, Liu S, et al. Risk of myeloproliferative neoplasms among
    U.S. Veterans from Korean, Vietnam, and Persian Gulf War eras. Am J Hematol.
    2024;99(10):1969-1978. doi:10.1002/ajh.27438
  4. Ma H, Wan JY, Cortessis VK, Gupta P, Cozen W. Survival in Agent Orange
    exposed and unexposed Vietnam-era veterans who were diagnosed with
    lymphoid malignancies. Blood Adv. 2024;8(4):1037-1041. doi:10.1182/
    bloodadvances.2023011999
  5. Friedman DR, Rodgers TD, Kovalick C, Yellapragada S, Szumita L, Weiss ES. Veterans
    with blood cancers: Clinical trial navigation and the challenge of rurality. J Rural
    Health. 2024;40(1):114-120. doi:10.1111/jrh.12773
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(3):e100042. doi:10.1200/EDBK_100042
  7. Pulumati A, Pulumati A, Dwarakanath BS, Verma A, Papineni RVL. Technological
    advancements in cancer diagnostics: Improvements and limitations. Cancer Rep
    (Hoboken). 2023;6(2):e1764. doi:10.1002/cnr2.1764
References
  1. Li W, ed. The 5th Edition of the World Health Organization Classification of
    Hematolymphoid Tumors. In: Leukemia [Internet]. Brisbane (AU): Exon Publications;
    October 16, 2022. https://www.ncbi.nlm.nih.gov/books/NBK586208/
  2. Graf SA, Samples LS, Keating TM, Garcia JM. Clinical research in older adults with
    hematologic malignancies: Opportunities for alignment in the Veterans Affairs. Semin
    Oncol. 2020;47(1):94-101. doi:10.1053/j.seminoncol.2020.02.010.
  3. Tiu A, McKinnell Z, Liu S, et al. Risk of myeloproliferative neoplasms among
    U.S. Veterans from Korean, Vietnam, and Persian Gulf War eras. Am J Hematol.
    2024;99(10):1969-1978. doi:10.1002/ajh.27438
  4. Ma H, Wan JY, Cortessis VK, Gupta P, Cozen W. Survival in Agent Orange
    exposed and unexposed Vietnam-era veterans who were diagnosed with
    lymphoid malignancies. Blood Adv. 2024;8(4):1037-1041. doi:10.1182/
    bloodadvances.2023011999
  5. Friedman DR, Rodgers TD, Kovalick C, Yellapragada S, Szumita L, Weiss ES. Veterans
    with blood cancers: Clinical trial navigation and the challenge of rurality. J Rural
    Health. 2024;40(1):114-120. doi:10.1111/jrh.12773
  6. Parikh DA, Rodgers TD, Passero VA, et al. Teleoncology in the Veterans Health
    Administration: Models of Care and the Veteran Experience. Am Soc Clin Oncol Educ
    Book. 2024;44(3):e100042. doi:10.1200/EDBK_100042
  7. Pulumati A, Pulumati A, Dwarakanath BS, Verma A, Papineni RVL. Technological
    advancements in cancer diagnostics: Improvements and limitations. Cancer Rep
    (Hoboken). 2023;6(2):e1764. doi:10.1002/cnr2.1764
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Advances in Blood Cancer Care for Veterans

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Advances in Blood Cancer Care for Veterans

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Hematologic malignancies encompass a broad range of distinct cancers, generally categorized as lymphoid (eg, lymphoma), myeloid (eg, leukemia, myelodysplastic syndromes, myeloproliferative neoplasms [MPNs]), and plasma cell neoplasms (eg, multiple myeloma).1 The veteran population is aging; this, in combination with other potential veteran-specific risk factors, is leading to an increased risk of hematologic malignancies.2 Of note, the risk for MPN diagnosis has recently been studied in veterans who served during the Korean, Vietnam, and Persian Gulf War eras.3 In addition, survival trends for different blood cancers, such as lymphoid malignancies, vary among veterans exposed to Agent Orange.4 Conflicting results have been found that point to the importance of future research.

Veterans in rural areas face barriers to treatment and clinical trial enrollment due to long travel distances and lack of trial availability, creating what are termed “clinical trial deserts.”5 Teleoncology has become crucial in bridging this gap by improving access to blood cancer treatments and clinical trials.5,6 Novel decentralized trial designs involving telehealth can further expand participation in remote areas.5 

Over the past year, there have been advances in the treatment of blood cancers as well as the use of large data sets to better understand cancers trends and new technologies to reduce disparities in access to care.6,7 The availability of greater therapeutic options, new care modalities, and improved risk assessments herald an exciting time in the care of patients with hematologic malignancies, with the expectation that this care will continue to advance through 2025.

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