From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.^13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.^20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.²² The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,²³ as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.^13-18

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.^13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.^13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).^13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.²⁴ This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.⁸ While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.^13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.^26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.²⁸ After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; [email protected].

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.^13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.^20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.²² The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,²³ as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.^13-18

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.^13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.^13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).^13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.²⁴ This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.⁸ While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.^13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.^26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.²⁸ After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; [email protected].

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.^13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.^20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.²² The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,²³ as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.^13-18

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.^13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.^13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).^13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.²⁴ This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.⁸ While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.^13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.^26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.²⁸ After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; [email protected].

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.^1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.⁴ There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.⁵

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA₂DS₂-VASc⁶ and the Society of Thoracic Surgery risk score,⁷ to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.⁸ Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,^9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge⁵; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.¹¹

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”¹² The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; [email protected].

Financial disclosures: None.

From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.^1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.⁴ There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.⁵

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA₂DS₂-VASc⁶ and the Society of Thoracic Surgery risk score,⁷ to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.⁸ Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,^9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge⁵; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.¹¹

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”¹² The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; [email protected].

Financial disclosures: None.

From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.^1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.⁴ There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.⁵

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA₂DS₂-VASc⁶ and the Society of Thoracic Surgery risk score,⁷ to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.⁸ Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,^9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge⁵; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.¹¹

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”¹² The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; [email protected].

Financial disclosures: None.

The U.S. Senate voted mostly along party lines Wednesday to confirm Vice Adm. Vivek H. Murthy, MD, MBA, to serve as the 21st Surgeon General of the United States.

Seven Republicans – Bill Cassidy (La.), Susan Collins (Maine), Roger Marshall (Kan.), Susan Murkowski (Alaska), Rob Portman (Ohio), Mitt Romney (Utah), and Dan Sullivan (Alaska) – joined all the Democrats and independents in the 57-43 vote approving Dr. Murthy’s nomination.

Dr. Murthy, 43, previously served as the 19th Surgeon General, from December 2014 to April 2017, when he was asked to step down by President Donald J. Trump.

Surgeons General serve 4-year terms.

During his first tenure, Dr. Murthy issued the first-ever Surgeon General’s report on the crisis of addiction and issued a call to action to doctors to help battle the opioid crisis.

When Dr. Murthy was nominated by President-elect Joseph R. Biden Jr. in December, he was acting as cochair of the incoming administration’s COVID-19 transition advisory board.

Early in 2020, before the COVID-19 pandemic hit, Dr. Murthy published a timely book: “Together: The Healing Power of Human Connection in a Sometimes Lonely World”.

He earned his bachelor’s degree from Harvard and his MD and MBA degrees from Yale. He completed his internal medicine residency at Brigham and Women’s Hospital in Boston, where he also served as a hospitalist, and later joined Harvard Medical School as a faculty member in internal medicine.

He is married to Alice Chen, MD. The couple have two children.
 

A version of this article first appeared on WebMD.com.

The U.S. Senate voted mostly along party lines Wednesday to confirm Vice Adm. Vivek H. Murthy, MD, MBA, to serve as the 21st Surgeon General of the United States.

Seven Republicans – Bill Cassidy (La.), Susan Collins (Maine), Roger Marshall (Kan.), Susan Murkowski (Alaska), Rob Portman (Ohio), Mitt Romney (Utah), and Dan Sullivan (Alaska) – joined all the Democrats and independents in the 57-43 vote approving Dr. Murthy’s nomination.

Dr. Murthy, 43, previously served as the 19th Surgeon General, from December 2014 to April 2017, when he was asked to step down by President Donald J. Trump.

Surgeons General serve 4-year terms.

During his first tenure, Dr. Murthy issued the first-ever Surgeon General’s report on the crisis of addiction and issued a call to action to doctors to help battle the opioid crisis.

When Dr. Murthy was nominated by President-elect Joseph R. Biden Jr. in December, he was acting as cochair of the incoming administration’s COVID-19 transition advisory board.

Early in 2020, before the COVID-19 pandemic hit, Dr. Murthy published a timely book: “Together: The Healing Power of Human Connection in a Sometimes Lonely World”.

He earned his bachelor’s degree from Harvard and his MD and MBA degrees from Yale. He completed his internal medicine residency at Brigham and Women’s Hospital in Boston, where he also served as a hospitalist, and later joined Harvard Medical School as a faculty member in internal medicine.

He is married to Alice Chen, MD. The couple have two children.
 

A version of this article first appeared on WebMD.com.

The U.S. Senate voted mostly along party lines Wednesday to confirm Vice Adm. Vivek H. Murthy, MD, MBA, to serve as the 21st Surgeon General of the United States.

Seven Republicans – Bill Cassidy (La.), Susan Collins (Maine), Roger Marshall (Kan.), Susan Murkowski (Alaska), Rob Portman (Ohio), Mitt Romney (Utah), and Dan Sullivan (Alaska) – joined all the Democrats and independents in the 57-43 vote approving Dr. Murthy’s nomination.

Dr. Murthy, 43, previously served as the 19th Surgeon General, from December 2014 to April 2017, when he was asked to step down by President Donald J. Trump.

Surgeons General serve 4-year terms.

During his first tenure, Dr. Murthy issued the first-ever Surgeon General’s report on the crisis of addiction and issued a call to action to doctors to help battle the opioid crisis.

When Dr. Murthy was nominated by President-elect Joseph R. Biden Jr. in December, he was acting as cochair of the incoming administration’s COVID-19 transition advisory board.

Early in 2020, before the COVID-19 pandemic hit, Dr. Murthy published a timely book: “Together: The Healing Power of Human Connection in a Sometimes Lonely World”.

He earned his bachelor’s degree from Harvard and his MD and MBA degrees from Yale. He completed his internal medicine residency at Brigham and Women’s Hospital in Boston, where he also served as a hospitalist, and later joined Harvard Medical School as a faculty member in internal medicine.

He is married to Alice Chen, MD. The couple have two children.
 

A version of this article first appeared on WebMD.com.

Although supine sleep positioning of preterm infants is becoming more common, racial disparities remain, according to a retrospective analysis involving more than 66,000 mothers.

monkeybusinessimages/iStock/Getty Images

Non-Hispanic Black preterm infants were 39%-56% less likely to sleep on their backs than were non-Hispanic White preterm infants, reported lead author Sunah S. Hwang, MD, MPH, of the University Colorado, Aurora, and colleagues.

According to the investigators, these findings may explain, in part, why the risk of sudden unexpected infant death (SUID) is more than twofold higher among non-Hispanic Black preterm infants than non-Hispanic White preterm infants.

“During the first year of life, one of the most effective and modifiable parental behaviors that may reduce the risk for SUID is adhering to safe infant sleep practices, including supine sleep positioning or back-sleeping,” wrote Dr. Hwang and colleagues. The report is in the Journal of Pediatrics. “For the healthy-term population, research on the racial/ethnic disparity in adherence to safe sleep practices is robust, but for preterm infants who are at much higher risk for SUID, less is known.”

To address this knowledge gap, the investigators conducted a retrospective study using data from the Pregnancy Risk Assessment Monitoring System (PRAMS), a population-based perinatal surveillance system. The final dataset involved 66,131 mothers who gave birth to preterm infants in 16 states between 2000 and 2015. The sample size was weighted to 1,020,986 mothers.

The investigators evaluated annual marginal prevalence of supine sleep positioning among two cohorts: early preterm infants (gestational age less than 34 weeks) and late preterm infants (gestational age 34-36 weeks). The primary outcome was rate of supine sleep positioning, a practice that must have been followed consistently, excluding other positions (i.e. prone or side). Mothers were grouped by race/ethnicity into four categories: non-Hispanic Black, non-Hispanic White, Hispanic, and other. Several other maternal and infant characteristics were recorded, including marital status, maternal age, education, insurance prior to birth, history of previous live birth, insurance, method of delivery, birth weight, and sex.

From 2000 to 2015, the overall adjusted odds of supine sleep positioning increased by 8.5% in the early preterm group and 5.2% in the late preterm group. This intergroup difference may be due to disparate levels of in-hospital education, the investigators suggested.

“Perhaps the longer NICU hospitalization for early preterm infants compared with late preterm infants affords greater opportunities for parental education and engagement about safe sleep practices,” they wrote.

Among early preterm infants, odds percentages increased by 7.3%, 7.7%, and 10.0% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers, respectively. For late preterm infants, respective rates increased by 5.9%, 4.8%, and 5.8% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers.

Despite these improvements, racial disparities were still observed. Non-Hispanic Black mothers reported lower rates of supine sleep positioning for both early preterm infants (odds ratio [OR], 0.61; P less than .0001) and late preterm infants (OR, 0.44; P less than .0001) compared with non-Hispanic White mothers.

These disparities seem “to be in line with racial/ethnic disparity trends in infant mortality and in SUID rates that have persisted for decades among infants,” the investigators wrote.

To a lesser degree, and lacking statistical significance, Hispanic mothers reported lower odds of supine sleep positioning than the odds of White mothers for both early preterm infants (OR, 0.80; P = .1670) and late preterm infants (OR, 0.81; P = .1054).

According to Dr. Hwang and colleagues, more specific demographic data are needed to accurately describe supine sleep positioning rates among Hispanic mothers, partly because of the heterogeneity of this cohort.

“A large body of literature has shown significant variability by immigrant status and country of origin in several infant health outcomes among the Hispanic population,” the investigators wrote. “This study was unable to stratify the Hispanic cohort by these characteristics and thus the distribution of supine sleep positioning prevalence across different Hispanic subgroups could not be demonstrated in this study.”

The investigators also suggested that interventional studies are needed.

“Additional efforts to understand the barriers and facilitators to SSP [supine sleep positioning] adherence among all preterm infant caregivers, particularly non-Hispanic Black and Hispanic parents, are needed so that novel interventions can then be developed,” they wrote.

According to Denice Cora-Bramble, MD, MBA, chief diversity officer at Children’s National Hospital and professor of pediatrics at George Washington University, Washington, the observed improvements in supine sleep positioning may predict lower rates of infant mortality, but more work in the area is needed.

“In spite of improvement in infants’ supine sleep positioning during the study period, racial/ethnic disparities persisted among non-Hispanic Blacks and Hispanics,” Dr. Cora-Bramble said. “That there was improvement among the populations included in the study is significant because of the associated and expected decrease in infant mortality. However, the study results need to be evaluated within the context of [the study’s] limitations, such as the inclusion of only sixteen states in the data analysis. More research is needed to understand and effectively address the disparities highlighted in the study.”

The investigators and Dr. Cora-Bramble reported no conflicts of interest.

Although supine sleep positioning of preterm infants is becoming more common, racial disparities remain, according to a retrospective analysis involving more than 66,000 mothers.

monkeybusinessimages/iStock/Getty Images

Non-Hispanic Black preterm infants were 39%-56% less likely to sleep on their backs than were non-Hispanic White preterm infants, reported lead author Sunah S. Hwang, MD, MPH, of the University Colorado, Aurora, and colleagues.

According to the investigators, these findings may explain, in part, why the risk of sudden unexpected infant death (SUID) is more than twofold higher among non-Hispanic Black preterm infants than non-Hispanic White preterm infants.

“During the first year of life, one of the most effective and modifiable parental behaviors that may reduce the risk for SUID is adhering to safe infant sleep practices, including supine sleep positioning or back-sleeping,” wrote Dr. Hwang and colleagues. The report is in the Journal of Pediatrics. “For the healthy-term population, research on the racial/ethnic disparity in adherence to safe sleep practices is robust, but for preterm infants who are at much higher risk for SUID, less is known.”

To address this knowledge gap, the investigators conducted a retrospective study using data from the Pregnancy Risk Assessment Monitoring System (PRAMS), a population-based perinatal surveillance system. The final dataset involved 66,131 mothers who gave birth to preterm infants in 16 states between 2000 and 2015. The sample size was weighted to 1,020,986 mothers.

The investigators evaluated annual marginal prevalence of supine sleep positioning among two cohorts: early preterm infants (gestational age less than 34 weeks) and late preterm infants (gestational age 34-36 weeks). The primary outcome was rate of supine sleep positioning, a practice that must have been followed consistently, excluding other positions (i.e. prone or side). Mothers were grouped by race/ethnicity into four categories: non-Hispanic Black, non-Hispanic White, Hispanic, and other. Several other maternal and infant characteristics were recorded, including marital status, maternal age, education, insurance prior to birth, history of previous live birth, insurance, method of delivery, birth weight, and sex.

From 2000 to 2015, the overall adjusted odds of supine sleep positioning increased by 8.5% in the early preterm group and 5.2% in the late preterm group. This intergroup difference may be due to disparate levels of in-hospital education, the investigators suggested.

“Perhaps the longer NICU hospitalization for early preterm infants compared with late preterm infants affords greater opportunities for parental education and engagement about safe sleep practices,” they wrote.

Among early preterm infants, odds percentages increased by 7.3%, 7.7%, and 10.0% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers, respectively. For late preterm infants, respective rates increased by 5.9%, 4.8%, and 5.8% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers.

Despite these improvements, racial disparities were still observed. Non-Hispanic Black mothers reported lower rates of supine sleep positioning for both early preterm infants (odds ratio [OR], 0.61; P less than .0001) and late preterm infants (OR, 0.44; P less than .0001) compared with non-Hispanic White mothers.

These disparities seem “to be in line with racial/ethnic disparity trends in infant mortality and in SUID rates that have persisted for decades among infants,” the investigators wrote.

To a lesser degree, and lacking statistical significance, Hispanic mothers reported lower odds of supine sleep positioning than the odds of White mothers for both early preterm infants (OR, 0.80; P = .1670) and late preterm infants (OR, 0.81; P = .1054).

According to Dr. Hwang and colleagues, more specific demographic data are needed to accurately describe supine sleep positioning rates among Hispanic mothers, partly because of the heterogeneity of this cohort.

“A large body of literature has shown significant variability by immigrant status and country of origin in several infant health outcomes among the Hispanic population,” the investigators wrote. “This study was unable to stratify the Hispanic cohort by these characteristics and thus the distribution of supine sleep positioning prevalence across different Hispanic subgroups could not be demonstrated in this study.”

The investigators also suggested that interventional studies are needed.

“Additional efforts to understand the barriers and facilitators to SSP [supine sleep positioning] adherence among all preterm infant caregivers, particularly non-Hispanic Black and Hispanic parents, are needed so that novel interventions can then be developed,” they wrote.

According to Denice Cora-Bramble, MD, MBA, chief diversity officer at Children’s National Hospital and professor of pediatrics at George Washington University, Washington, the observed improvements in supine sleep positioning may predict lower rates of infant mortality, but more work in the area is needed.

“In spite of improvement in infants’ supine sleep positioning during the study period, racial/ethnic disparities persisted among non-Hispanic Blacks and Hispanics,” Dr. Cora-Bramble said. “That there was improvement among the populations included in the study is significant because of the associated and expected decrease in infant mortality. However, the study results need to be evaluated within the context of [the study’s] limitations, such as the inclusion of only sixteen states in the data analysis. More research is needed to understand and effectively address the disparities highlighted in the study.”

The investigators and Dr. Cora-Bramble reported no conflicts of interest.

Although supine sleep positioning of preterm infants is becoming more common, racial disparities remain, according to a retrospective analysis involving more than 66,000 mothers.

monkeybusinessimages/iStock/Getty Images

Non-Hispanic Black preterm infants were 39%-56% less likely to sleep on their backs than were non-Hispanic White preterm infants, reported lead author Sunah S. Hwang, MD, MPH, of the University Colorado, Aurora, and colleagues.

According to the investigators, these findings may explain, in part, why the risk of sudden unexpected infant death (SUID) is more than twofold higher among non-Hispanic Black preterm infants than non-Hispanic White preterm infants.

“During the first year of life, one of the most effective and modifiable parental behaviors that may reduce the risk for SUID is adhering to safe infant sleep practices, including supine sleep positioning or back-sleeping,” wrote Dr. Hwang and colleagues. The report is in the Journal of Pediatrics. “For the healthy-term population, research on the racial/ethnic disparity in adherence to safe sleep practices is robust, but for preterm infants who are at much higher risk for SUID, less is known.”

To address this knowledge gap, the investigators conducted a retrospective study using data from the Pregnancy Risk Assessment Monitoring System (PRAMS), a population-based perinatal surveillance system. The final dataset involved 66,131 mothers who gave birth to preterm infants in 16 states between 2000 and 2015. The sample size was weighted to 1,020,986 mothers.

The investigators evaluated annual marginal prevalence of supine sleep positioning among two cohorts: early preterm infants (gestational age less than 34 weeks) and late preterm infants (gestational age 34-36 weeks). The primary outcome was rate of supine sleep positioning, a practice that must have been followed consistently, excluding other positions (i.e. prone or side). Mothers were grouped by race/ethnicity into four categories: non-Hispanic Black, non-Hispanic White, Hispanic, and other. Several other maternal and infant characteristics were recorded, including marital status, maternal age, education, insurance prior to birth, history of previous live birth, insurance, method of delivery, birth weight, and sex.

From 2000 to 2015, the overall adjusted odds of supine sleep positioning increased by 8.5% in the early preterm group and 5.2% in the late preterm group. This intergroup difference may be due to disparate levels of in-hospital education, the investigators suggested.

“Perhaps the longer NICU hospitalization for early preterm infants compared with late preterm infants affords greater opportunities for parental education and engagement about safe sleep practices,” they wrote.

Among early preterm infants, odds percentages increased by 7.3%, 7.7%, and 10.0% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers, respectively. For late preterm infants, respective rates increased by 5.9%, 4.8%, and 5.8% for non-Hispanic Black, Hispanic, and non-Hispanic White mothers.

Despite these improvements, racial disparities were still observed. Non-Hispanic Black mothers reported lower rates of supine sleep positioning for both early preterm infants (odds ratio [OR], 0.61; P less than .0001) and late preterm infants (OR, 0.44; P less than .0001) compared with non-Hispanic White mothers.

These disparities seem “to be in line with racial/ethnic disparity trends in infant mortality and in SUID rates that have persisted for decades among infants,” the investigators wrote.

To a lesser degree, and lacking statistical significance, Hispanic mothers reported lower odds of supine sleep positioning than the odds of White mothers for both early preterm infants (OR, 0.80; P = .1670) and late preterm infants (OR, 0.81; P = .1054).

According to Dr. Hwang and colleagues, more specific demographic data are needed to accurately describe supine sleep positioning rates among Hispanic mothers, partly because of the heterogeneity of this cohort.

“A large body of literature has shown significant variability by immigrant status and country of origin in several infant health outcomes among the Hispanic population,” the investigators wrote. “This study was unable to stratify the Hispanic cohort by these characteristics and thus the distribution of supine sleep positioning prevalence across different Hispanic subgroups could not be demonstrated in this study.”

The investigators also suggested that interventional studies are needed.

“Additional efforts to understand the barriers and facilitators to SSP [supine sleep positioning] adherence among all preterm infant caregivers, particularly non-Hispanic Black and Hispanic parents, are needed so that novel interventions can then be developed,” they wrote.

According to Denice Cora-Bramble, MD, MBA, chief diversity officer at Children’s National Hospital and professor of pediatrics at George Washington University, Washington, the observed improvements in supine sleep positioning may predict lower rates of infant mortality, but more work in the area is needed.

“In spite of improvement in infants’ supine sleep positioning during the study period, racial/ethnic disparities persisted among non-Hispanic Blacks and Hispanics,” Dr. Cora-Bramble said. “That there was improvement among the populations included in the study is significant because of the associated and expected decrease in infant mortality. However, the study results need to be evaluated within the context of [the study’s] limitations, such as the inclusion of only sixteen states in the data analysis. More research is needed to understand and effectively address the disparities highlighted in the study.”

The investigators and Dr. Cora-Bramble reported no conflicts of interest.

A new genetic mutation in schizophrenia that blocks neuron communication in the brain may lead to novel treatment strategies and improve understanding of the mechanics of this disease.

The discovery of this new gene, PCDHA3, could enhance the development of genetic-risk calculators “that may help us understand vulnerability to schizophrenia in high-risk individuals and identify individuals with schizophrenia who have a greater risk for poor outcomes,” said Todd Lencz, PhD, a professor at the Feinstein Institutes for Medical Research in New York, and lead author of this research. Dr. Lencz and associates reported on this new finding in the journal Neuron.

Schizophrenia affects 20 million people worldwide. Previous research has identified the important role genes play in the disease, but isolating individual genes to better understand schizophrenia has proven to be a challenge. This is a very heterogeneous disorder, with many hundreds if not thousands of genes involved, Dr. Lencz explained in an interview. “It is very different from single-gene disorders like Huntington disease, for example. For this reason, we need very large sample sizes to find any one gene that seems to be common to many cases in a sample.”
 

Study focused on homogeneous population

To enhance the power of finding rare variants in a heterogeneous disease with large numbers of genes, Dr. Lencz and colleagues chose a homogeneous “founder” population, a cohort of Ashkenazi Jews, to examine genomes from schizophrenia patients and controls. “As we have reported in prior work over the last decade, the 10 million or so Ashkenazi Jews living worldwide today all are descended from just a few hundred people who lived approximately 750 years ago, and moved into Central and Eastern Europe,” said Dr. Lencz. The study included 786 cases of schizophrenia and 463 controls from this Ashkenazi population. This is considered to be an extremely small sample for a genetic study. However, because this population evolved from a few hundred individuals to a massive explosion in a historically short period of time, it had enhanced statistical power, said Dr. Lencz.

“We showed that just a few thousand Ashkenazi Jewish cases would have the statistical power of a regular population that was 5-10 times larger, from a genetic discovery perspective,” he added.
 

Search for ultrarare variants

The investigators used whole-genome sequencing to conduct their analysis, using public databases to filter out any variants that had been previously observed in healthy individuals worldwide. “We were looking for ultrarare variants that might have a very powerful effect on the disease,” Dr. Lencz said. Such individual mutations are very rarely seen in the general population.

Because of the disease’s ultraheterogeneity, it’s extremely unusual to find a recurrent, ultrarare variant. “In some ways, the genetics of schizophrenia is so complex that every patient worldwide is unique in the genetics that led to his or her disorder.” The goal was to find individual mutations that might be observed multiple times across the schizophrenia group, Dr. Lencz said.
 

Rare gene found in five cases

Dr. Lencz and colleagues accomplished this with their unique Ashkenazi Jewish population. “We identified one particular mutation that was repeatedly observed in our cases that has not been observed in healthy individuals that we’re aware of,” he said. The PCDHA3 mutation was identified in 3 out of the 786 schizophrenia cases.

In another dataset, they examined from the Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) consortium, they found it two additional times, bringing the total to five cases. SCHEMA is a large international consortium of genetics studies in schizophrenia that contains thousands of cases and controls, some of which are Ashkenazi Jewish cases.

“Importantly, the mutation was not observed in any controls, in either our Ashkenazi dataset, the SCHEMA dataset, or more than 100,000 other controls reported in several publicly available genetics databases,” Dr. Lencz said.
 

How the gene leads to schizophrenia

PCDHA3 derives from the protocadherin gene family, which generates a unique bar code that enables neurons to recognize and communicate with other neurons. This communication creates a scaffolding of sorts that enables normal brain function. Dr. Lencz and colleagues discovered that the PCDHA3 variant blocks this normal protocadherin function.

Among the 786 cases, the investigators found several other genes in the broad cadherin family that had implications in schizophrenia development.

Much of the genetics of schizophrenia in recent years has focused on the synapse as the point of abnormality underlying the disorder. “We think our paper demonstrates in multiple ways the synaptic scaffolding role the cadherins superfamily of genes play in schizophrenia pathophysiology. This is novel – it has never been described before,” said Dr. Lencz. The discovery of the PCDHA3 variant adds a level of detail and resolution to this process, pointing researchers toward a specific aspect of synaptic formation that may be aberrant. “So the hope is we’re not just learning about these five individuals and their synapses. This result is perhaps telling us to look very carefully at this aspect of synaptic formation.”
 

Implications for clinical practice

Dr. Lencz and colleagues plan to expand upon and enhance their existing Ashkenazi sample to take advantage of the founder effect in this population. “Of course, there are many large-scale efforts to recruit ethnically diverse patients with schizophrenia to study around the world. We encourage that. Our expectation is that the biology is not in any way unique to Ashkenazi individuals. This is just the approach we took to enhance our power,” he said.

The PCDHA3 discovery won’t have an immediate impact on clinical practice. In the longer term, “we are aware of certain pharmacologic approaches that might be able to manipulate the cadherins. That would be a worthy focus for future research,” Dr. Lencz said.

Additional studies will be critical to see how current medications in schizophrenia treatment could mitigate and improve any changes caused by this genetic mutation, noted Anthony T. Ng, MD, who was not involved with the study. More specifically, studies would help assess the impact of a schizophrenia patient with this mutation in areas of functioning, “so that psychosocial and rehabilitation treatment models of schizophrenia can provide more targeted treatment,” said Dr. Ng, medical director of community services and director of neuromodulation services at Northern Light Acadia Hospital in Bangor, Maine.

The work of Dr. Lencz and associates is significant in that “it started to identify a very specific genetic change that can help focus treatment of schizophrenia,” Dr. Ng said.

Neither Dr. Lencz nor his associates had any conflicts of interest. Dr. Ng had no disclosures.

A new genetic mutation in schizophrenia that blocks neuron communication in the brain may lead to novel treatment strategies and improve understanding of the mechanics of this disease.

The discovery of this new gene, PCDHA3, could enhance the development of genetic-risk calculators “that may help us understand vulnerability to schizophrenia in high-risk individuals and identify individuals with schizophrenia who have a greater risk for poor outcomes,” said Todd Lencz, PhD, a professor at the Feinstein Institutes for Medical Research in New York, and lead author of this research. Dr. Lencz and associates reported on this new finding in the journal Neuron.

Schizophrenia affects 20 million people worldwide. Previous research has identified the important role genes play in the disease, but isolating individual genes to better understand schizophrenia has proven to be a challenge. This is a very heterogeneous disorder, with many hundreds if not thousands of genes involved, Dr. Lencz explained in an interview. “It is very different from single-gene disorders like Huntington disease, for example. For this reason, we need very large sample sizes to find any one gene that seems to be common to many cases in a sample.”
 

Study focused on homogeneous population

To enhance the power of finding rare variants in a heterogeneous disease with large numbers of genes, Dr. Lencz and colleagues chose a homogeneous “founder” population, a cohort of Ashkenazi Jews, to examine genomes from schizophrenia patients and controls. “As we have reported in prior work over the last decade, the 10 million or so Ashkenazi Jews living worldwide today all are descended from just a few hundred people who lived approximately 750 years ago, and moved into Central and Eastern Europe,” said Dr. Lencz. The study included 786 cases of schizophrenia and 463 controls from this Ashkenazi population. This is considered to be an extremely small sample for a genetic study. However, because this population evolved from a few hundred individuals to a massive explosion in a historically short period of time, it had enhanced statistical power, said Dr. Lencz.

“We showed that just a few thousand Ashkenazi Jewish cases would have the statistical power of a regular population that was 5-10 times larger, from a genetic discovery perspective,” he added.
 

Search for ultrarare variants

The investigators used whole-genome sequencing to conduct their analysis, using public databases to filter out any variants that had been previously observed in healthy individuals worldwide. “We were looking for ultrarare variants that might have a very powerful effect on the disease,” Dr. Lencz said. Such individual mutations are very rarely seen in the general population.

Because of the disease’s ultraheterogeneity, it’s extremely unusual to find a recurrent, ultrarare variant. “In some ways, the genetics of schizophrenia is so complex that every patient worldwide is unique in the genetics that led to his or her disorder.” The goal was to find individual mutations that might be observed multiple times across the schizophrenia group, Dr. Lencz said.
 

Rare gene found in five cases

Dr. Lencz and colleagues accomplished this with their unique Ashkenazi Jewish population. “We identified one particular mutation that was repeatedly observed in our cases that has not been observed in healthy individuals that we’re aware of,” he said. The PCDHA3 mutation was identified in 3 out of the 786 schizophrenia cases.

In another dataset, they examined from the Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) consortium, they found it two additional times, bringing the total to five cases. SCHEMA is a large international consortium of genetics studies in schizophrenia that contains thousands of cases and controls, some of which are Ashkenazi Jewish cases.

“Importantly, the mutation was not observed in any controls, in either our Ashkenazi dataset, the SCHEMA dataset, or more than 100,000 other controls reported in several publicly available genetics databases,” Dr. Lencz said.
 

How the gene leads to schizophrenia

PCDHA3 derives from the protocadherin gene family, which generates a unique bar code that enables neurons to recognize and communicate with other neurons. This communication creates a scaffolding of sorts that enables normal brain function. Dr. Lencz and colleagues discovered that the PCDHA3 variant blocks this normal protocadherin function.

Among the 786 cases, the investigators found several other genes in the broad cadherin family that had implications in schizophrenia development.

Much of the genetics of schizophrenia in recent years has focused on the synapse as the point of abnormality underlying the disorder. “We think our paper demonstrates in multiple ways the synaptic scaffolding role the cadherins superfamily of genes play in schizophrenia pathophysiology. This is novel – it has never been described before,” said Dr. Lencz. The discovery of the PCDHA3 variant adds a level of detail and resolution to this process, pointing researchers toward a specific aspect of synaptic formation that may be aberrant. “So the hope is we’re not just learning about these five individuals and their synapses. This result is perhaps telling us to look very carefully at this aspect of synaptic formation.”
 

Implications for clinical practice

Dr. Lencz and colleagues plan to expand upon and enhance their existing Ashkenazi sample to take advantage of the founder effect in this population. “Of course, there are many large-scale efforts to recruit ethnically diverse patients with schizophrenia to study around the world. We encourage that. Our expectation is that the biology is not in any way unique to Ashkenazi individuals. This is just the approach we took to enhance our power,” he said.

The PCDHA3 discovery won’t have an immediate impact on clinical practice. In the longer term, “we are aware of certain pharmacologic approaches that might be able to manipulate the cadherins. That would be a worthy focus for future research,” Dr. Lencz said.

Additional studies will be critical to see how current medications in schizophrenia treatment could mitigate and improve any changes caused by this genetic mutation, noted Anthony T. Ng, MD, who was not involved with the study. More specifically, studies would help assess the impact of a schizophrenia patient with this mutation in areas of functioning, “so that psychosocial and rehabilitation treatment models of schizophrenia can provide more targeted treatment,” said Dr. Ng, medical director of community services and director of neuromodulation services at Northern Light Acadia Hospital in Bangor, Maine.

The work of Dr. Lencz and associates is significant in that “it started to identify a very specific genetic change that can help focus treatment of schizophrenia,” Dr. Ng said.

Neither Dr. Lencz nor his associates had any conflicts of interest. Dr. Ng had no disclosures.

A new genetic mutation in schizophrenia that blocks neuron communication in the brain may lead to novel treatment strategies and improve understanding of the mechanics of this disease.

The discovery of this new gene, PCDHA3, could enhance the development of genetic-risk calculators “that may help us understand vulnerability to schizophrenia in high-risk individuals and identify individuals with schizophrenia who have a greater risk for poor outcomes,” said Todd Lencz, PhD, a professor at the Feinstein Institutes for Medical Research in New York, and lead author of this research. Dr. Lencz and associates reported on this new finding in the journal Neuron.

Schizophrenia affects 20 million people worldwide. Previous research has identified the important role genes play in the disease, but isolating individual genes to better understand schizophrenia has proven to be a challenge. This is a very heterogeneous disorder, with many hundreds if not thousands of genes involved, Dr. Lencz explained in an interview. “It is very different from single-gene disorders like Huntington disease, for example. For this reason, we need very large sample sizes to find any one gene that seems to be common to many cases in a sample.”
 

Study focused on homogeneous population

To enhance the power of finding rare variants in a heterogeneous disease with large numbers of genes, Dr. Lencz and colleagues chose a homogeneous “founder” population, a cohort of Ashkenazi Jews, to examine genomes from schizophrenia patients and controls. “As we have reported in prior work over the last decade, the 10 million or so Ashkenazi Jews living worldwide today all are descended from just a few hundred people who lived approximately 750 years ago, and moved into Central and Eastern Europe,” said Dr. Lencz. The study included 786 cases of schizophrenia and 463 controls from this Ashkenazi population. This is considered to be an extremely small sample for a genetic study. However, because this population evolved from a few hundred individuals to a massive explosion in a historically short period of time, it had enhanced statistical power, said Dr. Lencz.

“We showed that just a few thousand Ashkenazi Jewish cases would have the statistical power of a regular population that was 5-10 times larger, from a genetic discovery perspective,” he added.
 

Search for ultrarare variants

The investigators used whole-genome sequencing to conduct their analysis, using public databases to filter out any variants that had been previously observed in healthy individuals worldwide. “We were looking for ultrarare variants that might have a very powerful effect on the disease,” Dr. Lencz said. Such individual mutations are very rarely seen in the general population.

Because of the disease’s ultraheterogeneity, it’s extremely unusual to find a recurrent, ultrarare variant. “In some ways, the genetics of schizophrenia is so complex that every patient worldwide is unique in the genetics that led to his or her disorder.” The goal was to find individual mutations that might be observed multiple times across the schizophrenia group, Dr. Lencz said.
 

Rare gene found in five cases

Dr. Lencz and colleagues accomplished this with their unique Ashkenazi Jewish population. “We identified one particular mutation that was repeatedly observed in our cases that has not been observed in healthy individuals that we’re aware of,” he said. The PCDHA3 mutation was identified in 3 out of the 786 schizophrenia cases.

In another dataset, they examined from the Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) consortium, they found it two additional times, bringing the total to five cases. SCHEMA is a large international consortium of genetics studies in schizophrenia that contains thousands of cases and controls, some of which are Ashkenazi Jewish cases.

“Importantly, the mutation was not observed in any controls, in either our Ashkenazi dataset, the SCHEMA dataset, or more than 100,000 other controls reported in several publicly available genetics databases,” Dr. Lencz said.
 

How the gene leads to schizophrenia

PCDHA3 derives from the protocadherin gene family, which generates a unique bar code that enables neurons to recognize and communicate with other neurons. This communication creates a scaffolding of sorts that enables normal brain function. Dr. Lencz and colleagues discovered that the PCDHA3 variant blocks this normal protocadherin function.

Among the 786 cases, the investigators found several other genes in the broad cadherin family that had implications in schizophrenia development.

Much of the genetics of schizophrenia in recent years has focused on the synapse as the point of abnormality underlying the disorder. “We think our paper demonstrates in multiple ways the synaptic scaffolding role the cadherins superfamily of genes play in schizophrenia pathophysiology. This is novel – it has never been described before,” said Dr. Lencz. The discovery of the PCDHA3 variant adds a level of detail and resolution to this process, pointing researchers toward a specific aspect of synaptic formation that may be aberrant. “So the hope is we’re not just learning about these five individuals and their synapses. This result is perhaps telling us to look very carefully at this aspect of synaptic formation.”
 

Implications for clinical practice

Dr. Lencz and colleagues plan to expand upon and enhance their existing Ashkenazi sample to take advantage of the founder effect in this population. “Of course, there are many large-scale efforts to recruit ethnically diverse patients with schizophrenia to study around the world. We encourage that. Our expectation is that the biology is not in any way unique to Ashkenazi individuals. This is just the approach we took to enhance our power,” he said.

The PCDHA3 discovery won’t have an immediate impact on clinical practice. In the longer term, “we are aware of certain pharmacologic approaches that might be able to manipulate the cadherins. That would be a worthy focus for future research,” Dr. Lencz said.

Additional studies will be critical to see how current medications in schizophrenia treatment could mitigate and improve any changes caused by this genetic mutation, noted Anthony T. Ng, MD, who was not involved with the study. More specifically, studies would help assess the impact of a schizophrenia patient with this mutation in areas of functioning, “so that psychosocial and rehabilitation treatment models of schizophrenia can provide more targeted treatment,” said Dr. Ng, medical director of community services and director of neuromodulation services at Northern Light Acadia Hospital in Bangor, Maine.

The work of Dr. Lencz and associates is significant in that “it started to identify a very specific genetic change that can help focus treatment of schizophrenia,” Dr. Ng said.

Neither Dr. Lencz nor his associates had any conflicts of interest. Dr. Ng had no disclosures.

Pregnant and breastfeeding women who receive an mRNA COVID-19 vaccine develop a strong immune response and produce antibodies that can transfer to the fetus through the placenta and to newborns through breast milk, according to a prospective cohort study published March 25 in the American Journal of Obstetrics and Gynecology.

The findings revealed that the antibody response to vaccination in this cohort was greater than that from a COVID-19 infection during pregnancy. Though the researchers detected SARS-CoV-2 antibodies in umbilical cord blood and breast milk, it’s not yet known how much protection these antibodies might provide to newborns.

“The presence of neutralizing antibody transfer in nearly all cords, and improved transfer with increased time from vaccination, points to the promise of mRNA vaccine–induced delivery of immunity to neonates,” wrote Kathryn J. Gray, MD, PhD, of Harvard Medical School and Brigham and Women’s Hospital’s department of obstetrics and gynecology, and colleagues. “Transfer would perhaps be optimized if vaccination is administered earlier during gestation, though this needs to be directly examined in future studies.”

The researchers tracked 84 pregnant women, 31 lactating women, and 16 nonpregnant women who received the COVID-19 vaccine. The titers of IgG, IgA, and IgM antibodies against the SARS-CoV-2 spike, receptor binding domain (RBD), and S1 and S2 components of the spike were measured in the 131 participants’ blood and in the lactating women’s breast milk four times: at baseline, when they received their second vaccine dose, at 2-6 weeks after their second dose, and at delivery for the 13 women who delivered during the study period.

The study population included health care workers and was predominantly White and non-Hispanic. In addition, two pregnant women, two lactating women, and one nonpregnant woman in the study had a previous SARS-CoV-2 infection.

Most of the pregnant women received the vaccine in their second (46%) or third (40%) trimester. The women across all three groups – pregnant, lactating, and nonpregnant – experienced similar side effects from the each dose of the vaccine, including fever/chills in 32% of the pregnant women and half the nonpregnant women after the second dose.

Titers induced by the vaccine were similar across the pregnant, lactating, and nonpregnant women, and titers did not differ based on the trimester when women received the vaccine. The researchers then compared the titers from the vaccine recipients to titers of 37 pregnant women drawn 4-12 weeks after a natural SARS-CoV-2 infection. Vaccine-induced titers were significantly greater than those measured in the women who had a natural infection during pregnancy (P < .001).

The researchers identified IgG, IgA, and IgM antibodies in the breast milk samples, including a boost in IgG antibodies after the second vaccine dose from baseline. “However, whether these antibodies were transferred efficiently to infants remained unclear,” the authors noted.

The researchers found vaccine-induced antibodies in all 10 umbilical cord blood samples tested, all but one of which had been exposed to two doses of the vaccine.

“The cord with the lowest spike- and RBD-specific IgG belonged to a mother who delivered between the first and second vaccine doses and had received her first vaccine dose 17 days prior to delivery, suggesting that 2 doses may be essential to optimize humoral immune transfer to the neonate,” the authors wrote. “Based on what is known about other vaccines, the amount of maternal IgG transferred across the placenta to the cord is likely to differ by trimester of vaccination.”

Although umbilical cord sera had lower titers of neutralizing antibodies than found in maternal sera, the difference was not significant (median interquartile range 52.3 vs. 104.7, P = .05). The two cord blood samples without neutralizing antibodies came from a woman who had not had the second dose and a woman who received the second dose 1 week before delivery.

“These data provide a compelling argument that COVID-19 mRNA vaccines induce similar humoral immunity in pregnant and lactating women as in the nonpregnant population,” the authors wrote. “These data do not elucidate potential risks to the fetus.”

While the study provides evidence about the immune response induced by the COVID-19 mRNA vaccines during pregnant, it leaves other questions unanswered, said Kevin A. Ault, MD, professor of ob.gyn. at The University of Kansas Medical Center in Kansas City.

“The important thing about these findings is that the COVID vaccines are immunogenic in pregnant women. There may be a benefit to the newborns because antibodies are passed on through the placenta,” Dr. Ault said in an interview. “The main questions that remain are safety of the vaccine during pregnancy and effectiveness of the vaccine during pregnancy.”

He said he expects to see more studies on the safety and effectiveness of COVID-19 vaccines during pregnancy. Despite more than 73,600 infections and 80 deaths from COVID-19 in people who were pregnant, none of the initial COVID-19 vaccine trials included pregnant or lactating participants.

“This is an important initial study to confirm the antibody generation from mRNA vaccination in pregnant women, and the passage of antibody via cord blood and breast milk,” said Linda Eckert, MD, a professor of ob.gyn. at The University of Washington, Seattle, who specializes in maternal immunization. “Further studies are important to look at the timing of vaccination in pregnancy and whether it influences the level of antibody passed to the fetus.”

Though this study is not a safety study, it “does not show increased expected vaccine reactions, such as aches, pains, and fever, in pregnant versus nonpregnant patients,” Dr. Eckert said in an interview. “It is not able to evaluate pregnancy outcome data, but it does allow pregnant women being vaccinated with the mRNA vaccines to know that the vaccine is generating protection for them, and the protection is being passed to the fetus in utero via cordblood and to the infant via breast milk.”

The research was funded by the National Institutes of Health along with the Gates Foundation, the Massachusetts Consortium on Pathogen Readiness (MassCPR), the Musk Foundation, the Ragon Institute of MGH and MIT, and Massachusetts General Hospital and Brigham and Women’s Hospital.

Lead author Dr. Gray has consulted for Illumina, BillionToOne, and Aetion, and three other authors have financial or scientific/medical advising connections to Alba Therapeutics, NextCure, Viome, Systems Seromyx, and Mirvie. Dr. Ault and Dr. Eckert had no disclosures.

Pregnant and breastfeeding women who receive an mRNA COVID-19 vaccine develop a strong immune response and produce antibodies that can transfer to the fetus through the placenta and to newborns through breast milk, according to a prospective cohort study published March 25 in the American Journal of Obstetrics and Gynecology.

The findings revealed that the antibody response to vaccination in this cohort was greater than that from a COVID-19 infection during pregnancy. Though the researchers detected SARS-CoV-2 antibodies in umbilical cord blood and breast milk, it’s not yet known how much protection these antibodies might provide to newborns.

“The presence of neutralizing antibody transfer in nearly all cords, and improved transfer with increased time from vaccination, points to the promise of mRNA vaccine–induced delivery of immunity to neonates,” wrote Kathryn J. Gray, MD, PhD, of Harvard Medical School and Brigham and Women’s Hospital’s department of obstetrics and gynecology, and colleagues. “Transfer would perhaps be optimized if vaccination is administered earlier during gestation, though this needs to be directly examined in future studies.”

The researchers tracked 84 pregnant women, 31 lactating women, and 16 nonpregnant women who received the COVID-19 vaccine. The titers of IgG, IgA, and IgM antibodies against the SARS-CoV-2 spike, receptor binding domain (RBD), and S1 and S2 components of the spike were measured in the 131 participants’ blood and in the lactating women’s breast milk four times: at baseline, when they received their second vaccine dose, at 2-6 weeks after their second dose, and at delivery for the 13 women who delivered during the study period.

The study population included health care workers and was predominantly White and non-Hispanic. In addition, two pregnant women, two lactating women, and one nonpregnant woman in the study had a previous SARS-CoV-2 infection.

Most of the pregnant women received the vaccine in their second (46%) or third (40%) trimester. The women across all three groups – pregnant, lactating, and nonpregnant – experienced similar side effects from the each dose of the vaccine, including fever/chills in 32% of the pregnant women and half the nonpregnant women after the second dose.

Titers induced by the vaccine were similar across the pregnant, lactating, and nonpregnant women, and titers did not differ based on the trimester when women received the vaccine. The researchers then compared the titers from the vaccine recipients to titers of 37 pregnant women drawn 4-12 weeks after a natural SARS-CoV-2 infection. Vaccine-induced titers were significantly greater than those measured in the women who had a natural infection during pregnancy (P < .001).

The researchers identified IgG, IgA, and IgM antibodies in the breast milk samples, including a boost in IgG antibodies after the second vaccine dose from baseline. “However, whether these antibodies were transferred efficiently to infants remained unclear,” the authors noted.

The researchers found vaccine-induced antibodies in all 10 umbilical cord blood samples tested, all but one of which had been exposed to two doses of the vaccine.

“The cord with the lowest spike- and RBD-specific IgG belonged to a mother who delivered between the first and second vaccine doses and had received her first vaccine dose 17 days prior to delivery, suggesting that 2 doses may be essential to optimize humoral immune transfer to the neonate,” the authors wrote. “Based on what is known about other vaccines, the amount of maternal IgG transferred across the placenta to the cord is likely to differ by trimester of vaccination.”

Although umbilical cord sera had lower titers of neutralizing antibodies than found in maternal sera, the difference was not significant (median interquartile range 52.3 vs. 104.7, P = .05). The two cord blood samples without neutralizing antibodies came from a woman who had not had the second dose and a woman who received the second dose 1 week before delivery.

“These data provide a compelling argument that COVID-19 mRNA vaccines induce similar humoral immunity in pregnant and lactating women as in the nonpregnant population,” the authors wrote. “These data do not elucidate potential risks to the fetus.”

While the study provides evidence about the immune response induced by the COVID-19 mRNA vaccines during pregnant, it leaves other questions unanswered, said Kevin A. Ault, MD, professor of ob.gyn. at The University of Kansas Medical Center in Kansas City.

“The important thing about these findings is that the COVID vaccines are immunogenic in pregnant women. There may be a benefit to the newborns because antibodies are passed on through the placenta,” Dr. Ault said in an interview. “The main questions that remain are safety of the vaccine during pregnancy and effectiveness of the vaccine during pregnancy.”

He said he expects to see more studies on the safety and effectiveness of COVID-19 vaccines during pregnancy. Despite more than 73,600 infections and 80 deaths from COVID-19 in people who were pregnant, none of the initial COVID-19 vaccine trials included pregnant or lactating participants.

“This is an important initial study to confirm the antibody generation from mRNA vaccination in pregnant women, and the passage of antibody via cord blood and breast milk,” said Linda Eckert, MD, a professor of ob.gyn. at The University of Washington, Seattle, who specializes in maternal immunization. “Further studies are important to look at the timing of vaccination in pregnancy and whether it influences the level of antibody passed to the fetus.”

Though this study is not a safety study, it “does not show increased expected vaccine reactions, such as aches, pains, and fever, in pregnant versus nonpregnant patients,” Dr. Eckert said in an interview. “It is not able to evaluate pregnancy outcome data, but it does allow pregnant women being vaccinated with the mRNA vaccines to know that the vaccine is generating protection for them, and the protection is being passed to the fetus in utero via cordblood and to the infant via breast milk.”

The research was funded by the National Institutes of Health along with the Gates Foundation, the Massachusetts Consortium on Pathogen Readiness (MassCPR), the Musk Foundation, the Ragon Institute of MGH and MIT, and Massachusetts General Hospital and Brigham and Women’s Hospital.

Lead author Dr. Gray has consulted for Illumina, BillionToOne, and Aetion, and three other authors have financial or scientific/medical advising connections to Alba Therapeutics, NextCure, Viome, Systems Seromyx, and Mirvie. Dr. Ault and Dr. Eckert had no disclosures.

Pregnant and breastfeeding women who receive an mRNA COVID-19 vaccine develop a strong immune response and produce antibodies that can transfer to the fetus through the placenta and to newborns through breast milk, according to a prospective cohort study published March 25 in the American Journal of Obstetrics and Gynecology.

The findings revealed that the antibody response to vaccination in this cohort was greater than that from a COVID-19 infection during pregnancy. Though the researchers detected SARS-CoV-2 antibodies in umbilical cord blood and breast milk, it’s not yet known how much protection these antibodies might provide to newborns.

“The presence of neutralizing antibody transfer in nearly all cords, and improved transfer with increased time from vaccination, points to the promise of mRNA vaccine–induced delivery of immunity to neonates,” wrote Kathryn J. Gray, MD, PhD, of Harvard Medical School and Brigham and Women’s Hospital’s department of obstetrics and gynecology, and colleagues. “Transfer would perhaps be optimized if vaccination is administered earlier during gestation, though this needs to be directly examined in future studies.”

The researchers tracked 84 pregnant women, 31 lactating women, and 16 nonpregnant women who received the COVID-19 vaccine. The titers of IgG, IgA, and IgM antibodies against the SARS-CoV-2 spike, receptor binding domain (RBD), and S1 and S2 components of the spike were measured in the 131 participants’ blood and in the lactating women’s breast milk four times: at baseline, when they received their second vaccine dose, at 2-6 weeks after their second dose, and at delivery for the 13 women who delivered during the study period.

The study population included health care workers and was predominantly White and non-Hispanic. In addition, two pregnant women, two lactating women, and one nonpregnant woman in the study had a previous SARS-CoV-2 infection.

Most of the pregnant women received the vaccine in their second (46%) or third (40%) trimester. The women across all three groups – pregnant, lactating, and nonpregnant – experienced similar side effects from the each dose of the vaccine, including fever/chills in 32% of the pregnant women and half the nonpregnant women after the second dose.

Titers induced by the vaccine were similar across the pregnant, lactating, and nonpregnant women, and titers did not differ based on the trimester when women received the vaccine. The researchers then compared the titers from the vaccine recipients to titers of 37 pregnant women drawn 4-12 weeks after a natural SARS-CoV-2 infection. Vaccine-induced titers were significantly greater than those measured in the women who had a natural infection during pregnancy (P < .001).

The researchers identified IgG, IgA, and IgM antibodies in the breast milk samples, including a boost in IgG antibodies after the second vaccine dose from baseline. “However, whether these antibodies were transferred efficiently to infants remained unclear,” the authors noted.

The researchers found vaccine-induced antibodies in all 10 umbilical cord blood samples tested, all but one of which had been exposed to two doses of the vaccine.

“The cord with the lowest spike- and RBD-specific IgG belonged to a mother who delivered between the first and second vaccine doses and had received her first vaccine dose 17 days prior to delivery, suggesting that 2 doses may be essential to optimize humoral immune transfer to the neonate,” the authors wrote. “Based on what is known about other vaccines, the amount of maternal IgG transferred across the placenta to the cord is likely to differ by trimester of vaccination.”

Although umbilical cord sera had lower titers of neutralizing antibodies than found in maternal sera, the difference was not significant (median interquartile range 52.3 vs. 104.7, P = .05). The two cord blood samples without neutralizing antibodies came from a woman who had not had the second dose and a woman who received the second dose 1 week before delivery.

“These data provide a compelling argument that COVID-19 mRNA vaccines induce similar humoral immunity in pregnant and lactating women as in the nonpregnant population,” the authors wrote. “These data do not elucidate potential risks to the fetus.”

While the study provides evidence about the immune response induced by the COVID-19 mRNA vaccines during pregnant, it leaves other questions unanswered, said Kevin A. Ault, MD, professor of ob.gyn. at The University of Kansas Medical Center in Kansas City.

“The important thing about these findings is that the COVID vaccines are immunogenic in pregnant women. There may be a benefit to the newborns because antibodies are passed on through the placenta,” Dr. Ault said in an interview. “The main questions that remain are safety of the vaccine during pregnancy and effectiveness of the vaccine during pregnancy.”

He said he expects to see more studies on the safety and effectiveness of COVID-19 vaccines during pregnancy. Despite more than 73,600 infections and 80 deaths from COVID-19 in people who were pregnant, none of the initial COVID-19 vaccine trials included pregnant or lactating participants.

“This is an important initial study to confirm the antibody generation from mRNA vaccination in pregnant women, and the passage of antibody via cord blood and breast milk,” said Linda Eckert, MD, a professor of ob.gyn. at The University of Washington, Seattle, who specializes in maternal immunization. “Further studies are important to look at the timing of vaccination in pregnancy and whether it influences the level of antibody passed to the fetus.”

Though this study is not a safety study, it “does not show increased expected vaccine reactions, such as aches, pains, and fever, in pregnant versus nonpregnant patients,” Dr. Eckert said in an interview. “It is not able to evaluate pregnancy outcome data, but it does allow pregnant women being vaccinated with the mRNA vaccines to know that the vaccine is generating protection for them, and the protection is being passed to the fetus in utero via cordblood and to the infant via breast milk.”

The research was funded by the National Institutes of Health along with the Gates Foundation, the Massachusetts Consortium on Pathogen Readiness (MassCPR), the Musk Foundation, the Ragon Institute of MGH and MIT, and Massachusetts General Hospital and Brigham and Women’s Hospital.

Lead author Dr. Gray has consulted for Illumina, BillionToOne, and Aetion, and three other authors have financial or scientific/medical advising connections to Alba Therapeutics, NextCure, Viome, Systems Seromyx, and Mirvie. Dr. Ault and Dr. Eckert had no disclosures.

Amid a substantial expansion of therapies in several drug classes for the treatment of osteoporosis, there has been a notable increase in the prescription of denosumab for patients with a cancer-related indication.

ogichobanov/iStock/Getty Images Plus

In an analysis of claims data from January 2009 to March 2020, the bisphosphonate alendronate represented more than 50% of all prescriptions for bone-directed therapies, but growth in the use of the monoclonal antibody denosumab overall and in cancer-related indications particularly was steady throughout the study period.

“In the malignancy cohort, alendronate and zoledronic acid were each used in approximately 30% of individuals at the onset of the study, but use of both then declined,” Sara Cromer, MD, reported at the annual meeting of the Endocrine Society.

For malignancy-based prescriptions, denosumab surpassed either bisphosphonate by 2013 and then continued to rise.

Denosumab use “reached approximately 50% of all bone-directed medication use in the malignancy cohort” by the end of the study period, said Dr. Cromer, a clinical research fellow in endocrinology at Massachusetts General Hospital, Boston.

The claims data for this analysis was drawn from the Clinformatics Data Mart. The analysis was restricted to individuals aged older than 50 years who received a prescription for a bone-directed therapy. The 15.48 million prescriptions evaluated were drawn from 1.46 million unique individuals. The mean age was 69 years, and 89% of those prescribed a drug were women.
 

Oncologic indications one of two tracked cohorts

In the context of a large expansion of treatment options in several drug classes for osteoporosis, the objective of this claims analysis was to document trends in treatment choice, according to Dr. Cromer. She and her coinvestigators looked at prescriptions overall as well as in two cohorts defined by ICD codes. One included patients prescribed a prescription by an oncologist. The other included everyone else.

When all prescriptions for bone-directed therapy were evaluated over the study period, alendronate was the most commonly prescribed therapy, and its use increased over time. Prescriptions of zoledronic acid also rose, doubling over the study period, but use was very low in the beginning and it never climbed above 5%.

The proportion of prescriptions written for bisphosphonates other than alendronate and zoledronic acid “declined steadily” over the study period, Dr. Cromer reported.

Denosumab, a monoclonal antibody that targets a step in the process important to maturation of osteoclasts, was approved in 2010. It accounted for 10% of all prescriptions for osteoporosis by 2015 and 15% by 2018. It was still rising through the end of the study period.

In contrast, prescriptions of raloxifene, a selective estrogen receptor modulator, began to decline after 2013. In general, the rates of prescriptions for other agents, including some of the more recently approved drugs, such as teriparatide, abaloparatide, and romosozumab, changed very little over the study period. None of these therapies ever represented more than 2% of prescriptions.

When looking at the cohort of patients who received a bone-directed reason for a noncancer indication, the trends “paralleled those in the all-user analysis,” Dr. Cromer reported.
 

Denosumab use greater in privately insured

In the malignancy cohort, the decline in the use of bisphosphonates and the rise in the use of denosumab were most pronounced in patients who were privately insured. The increased use of denosumab over the study period “outpaced gains in use of other agents despite guidelines,” said Dr. Cromer, referring to the those issued by the Endocrine Society in 2019 .

In those guidelines, written for management of postmenopausal women at high risk of fractures, bisphosphonates are recommended for initial treatment while denosumab is recommended as an alternative. However, those guidelines do not provide specific recommendations for therapies directed at osteoporosis associated with cancer.

Guidelines for this population exist, including one published by the American Society of Clinical Oncology in 2019.

In the ASCO guidelines, oral bisphosphonates, intravenous bisphosphonates, and subcutaneous denosumab were all identified as “efficacious options,” according to Charles L. Shapiro, MD, director of breast cancer translational research, Mount Sinai Health System, New York.

Specifically, “all three of them work to reduce fractures and improve bone density in women with breast cancer in whom you are trying to prevent or treat osteoporosis,” Dr. Shapiro said in an interview.

There might be relative advantages for one therapy over another in specific subgroups defined by type of cancer or stage of cancer, but trials are not definitive for such outcomes as overall survival. Citing one comparative study associating denosumab with an 18% delay to first skeletal event in women with metastatic breast cancer, Dr. Shapiro observed, “I personally don’t consider an 18% delay [for this outcome] to be that clinically meaningful.”

Although major guidelines from ASCO have not so far favored denosumab over any bisphosphonate in routine care, Dr. Shapiro did not rule out the possibility that future studies will show differences.

Dr. Comer and Dr. Shapiro reported no relevant conflicts of interest.

Amid a substantial expansion of therapies in several drug classes for the treatment of osteoporosis, there has been a notable increase in the prescription of denosumab for patients with a cancer-related indication.

ogichobanov/iStock/Getty Images Plus

In an analysis of claims data from January 2009 to March 2020, the bisphosphonate alendronate represented more than 50% of all prescriptions for bone-directed therapies, but growth in the use of the monoclonal antibody denosumab overall and in cancer-related indications particularly was steady throughout the study period.

“In the malignancy cohort, alendronate and zoledronic acid were each used in approximately 30% of individuals at the onset of the study, but use of both then declined,” Sara Cromer, MD, reported at the annual meeting of the Endocrine Society.

For malignancy-based prescriptions, denosumab surpassed either bisphosphonate by 2013 and then continued to rise.

Denosumab use “reached approximately 50% of all bone-directed medication use in the malignancy cohort” by the end of the study period, said Dr. Cromer, a clinical research fellow in endocrinology at Massachusetts General Hospital, Boston.

The claims data for this analysis was drawn from the Clinformatics Data Mart. The analysis was restricted to individuals aged older than 50 years who received a prescription for a bone-directed therapy. The 15.48 million prescriptions evaluated were drawn from 1.46 million unique individuals. The mean age was 69 years, and 89% of those prescribed a drug were women.
 

Oncologic indications one of two tracked cohorts

In the context of a large expansion of treatment options in several drug classes for osteoporosis, the objective of this claims analysis was to document trends in treatment choice, according to Dr. Cromer. She and her coinvestigators looked at prescriptions overall as well as in two cohorts defined by ICD codes. One included patients prescribed a prescription by an oncologist. The other included everyone else.

When all prescriptions for bone-directed therapy were evaluated over the study period, alendronate was the most commonly prescribed therapy, and its use increased over time. Prescriptions of zoledronic acid also rose, doubling over the study period, but use was very low in the beginning and it never climbed above 5%.

The proportion of prescriptions written for bisphosphonates other than alendronate and zoledronic acid “declined steadily” over the study period, Dr. Cromer reported.

Denosumab, a monoclonal antibody that targets a step in the process important to maturation of osteoclasts, was approved in 2010. It accounted for 10% of all prescriptions for osteoporosis by 2015 and 15% by 2018. It was still rising through the end of the study period.

In contrast, prescriptions of raloxifene, a selective estrogen receptor modulator, began to decline after 2013. In general, the rates of prescriptions for other agents, including some of the more recently approved drugs, such as teriparatide, abaloparatide, and romosozumab, changed very little over the study period. None of these therapies ever represented more than 2% of prescriptions.

When looking at the cohort of patients who received a bone-directed reason for a noncancer indication, the trends “paralleled those in the all-user analysis,” Dr. Cromer reported.
 

Denosumab use greater in privately insured

In the malignancy cohort, the decline in the use of bisphosphonates and the rise in the use of denosumab were most pronounced in patients who were privately insured. The increased use of denosumab over the study period “outpaced gains in use of other agents despite guidelines,” said Dr. Cromer, referring to the those issued by the Endocrine Society in 2019 .

In those guidelines, written for management of postmenopausal women at high risk of fractures, bisphosphonates are recommended for initial treatment while denosumab is recommended as an alternative. However, those guidelines do not provide specific recommendations for therapies directed at osteoporosis associated with cancer.

Guidelines for this population exist, including one published by the American Society of Clinical Oncology in 2019.

In the ASCO guidelines, oral bisphosphonates, intravenous bisphosphonates, and subcutaneous denosumab were all identified as “efficacious options,” according to Charles L. Shapiro, MD, director of breast cancer translational research, Mount Sinai Health System, New York.

Specifically, “all three of them work to reduce fractures and improve bone density in women with breast cancer in whom you are trying to prevent or treat osteoporosis,” Dr. Shapiro said in an interview.

There might be relative advantages for one therapy over another in specific subgroups defined by type of cancer or stage of cancer, but trials are not definitive for such outcomes as overall survival. Citing one comparative study associating denosumab with an 18% delay to first skeletal event in women with metastatic breast cancer, Dr. Shapiro observed, “I personally don’t consider an 18% delay [for this outcome] to be that clinically meaningful.”

Although major guidelines from ASCO have not so far favored denosumab over any bisphosphonate in routine care, Dr. Shapiro did not rule out the possibility that future studies will show differences.

Dr. Comer and Dr. Shapiro reported no relevant conflicts of interest.

Amid a substantial expansion of therapies in several drug classes for the treatment of osteoporosis, there has been a notable increase in the prescription of denosumab for patients with a cancer-related indication.

ogichobanov/iStock/Getty Images Plus

In an analysis of claims data from January 2009 to March 2020, the bisphosphonate alendronate represented more than 50% of all prescriptions for bone-directed therapies, but growth in the use of the monoclonal antibody denosumab overall and in cancer-related indications particularly was steady throughout the study period.

“In the malignancy cohort, alendronate and zoledronic acid were each used in approximately 30% of individuals at the onset of the study, but use of both then declined,” Sara Cromer, MD, reported at the annual meeting of the Endocrine Society.

For malignancy-based prescriptions, denosumab surpassed either bisphosphonate by 2013 and then continued to rise.

Denosumab use “reached approximately 50% of all bone-directed medication use in the malignancy cohort” by the end of the study period, said Dr. Cromer, a clinical research fellow in endocrinology at Massachusetts General Hospital, Boston.

The claims data for this analysis was drawn from the Clinformatics Data Mart. The analysis was restricted to individuals aged older than 50 years who received a prescription for a bone-directed therapy. The 15.48 million prescriptions evaluated were drawn from 1.46 million unique individuals. The mean age was 69 years, and 89% of those prescribed a drug were women.
 

Oncologic indications one of two tracked cohorts

In the context of a large expansion of treatment options in several drug classes for osteoporosis, the objective of this claims analysis was to document trends in treatment choice, according to Dr. Cromer. She and her coinvestigators looked at prescriptions overall as well as in two cohorts defined by ICD codes. One included patients prescribed a prescription by an oncologist. The other included everyone else.

When all prescriptions for bone-directed therapy were evaluated over the study period, alendronate was the most commonly prescribed therapy, and its use increased over time. Prescriptions of zoledronic acid also rose, doubling over the study period, but use was very low in the beginning and it never climbed above 5%.

The proportion of prescriptions written for bisphosphonates other than alendronate and zoledronic acid “declined steadily” over the study period, Dr. Cromer reported.

Denosumab, a monoclonal antibody that targets a step in the process important to maturation of osteoclasts, was approved in 2010. It accounted for 10% of all prescriptions for osteoporosis by 2015 and 15% by 2018. It was still rising through the end of the study period.

In contrast, prescriptions of raloxifene, a selective estrogen receptor modulator, began to decline after 2013. In general, the rates of prescriptions for other agents, including some of the more recently approved drugs, such as teriparatide, abaloparatide, and romosozumab, changed very little over the study period. None of these therapies ever represented more than 2% of prescriptions.

When looking at the cohort of patients who received a bone-directed reason for a noncancer indication, the trends “paralleled those in the all-user analysis,” Dr. Cromer reported.
 

Denosumab use greater in privately insured

In the malignancy cohort, the decline in the use of bisphosphonates and the rise in the use of denosumab were most pronounced in patients who were privately insured. The increased use of denosumab over the study period “outpaced gains in use of other agents despite guidelines,” said Dr. Cromer, referring to the those issued by the Endocrine Society in 2019 .

In those guidelines, written for management of postmenopausal women at high risk of fractures, bisphosphonates are recommended for initial treatment while denosumab is recommended as an alternative. However, those guidelines do not provide specific recommendations for therapies directed at osteoporosis associated with cancer.

Guidelines for this population exist, including one published by the American Society of Clinical Oncology in 2019.

In the ASCO guidelines, oral bisphosphonates, intravenous bisphosphonates, and subcutaneous denosumab were all identified as “efficacious options,” according to Charles L. Shapiro, MD, director of breast cancer translational research, Mount Sinai Health System, New York.

Specifically, “all three of them work to reduce fractures and improve bone density in women with breast cancer in whom you are trying to prevent or treat osteoporosis,” Dr. Shapiro said in an interview.

There might be relative advantages for one therapy over another in specific subgroups defined by type of cancer or stage of cancer, but trials are not definitive for such outcomes as overall survival. Citing one comparative study associating denosumab with an 18% delay to first skeletal event in women with metastatic breast cancer, Dr. Shapiro observed, “I personally don’t consider an 18% delay [for this outcome] to be that clinically meaningful.”

Although major guidelines from ASCO have not so far favored denosumab over any bisphosphonate in routine care, Dr. Shapiro did not rule out the possibility that future studies will show differences.

Dr. Comer and Dr. Shapiro reported no relevant conflicts of interest.

Recently, we had the opportunity to take part in a major EHR conversion project. During this “go-live,” 5 hospitals and approximately 300 ambulatory service and physician practice locations made the transition, consolidating over 100 disparate electronic systems and dozens of interfaces into one world-class medical record.

If you’ve ever been part of such an event, you know it is anything but simple. On the contrary, it requires an enormous financial investment along with years of planning, hours of meetings, and months of training. No matter how much preparation goes into it, there are sure to be bumps along the way. It is a traumatic and stressful time for all involved, but the end result is well worth the effort. Still, there are lessons to be learned and wisdom to be gleaned, and this month we’d like to share a few that we found most important. We believe that many of these are useful lessons even to those who will never live through a go-live.
 

Safety always comes first

Patient safety is a term so often used that it has a tendency to be taken for granted. Health systems build processes and procedures to ensure safety – some even win awards and recognition for their efforts. But the best (and safest) health care institutions build patient safety into their cultures. More than just being taught to use checklists or buzzwords, the staff at these institutions are encouraged to put the welfare of patients first, making all other activities secondary to this pursuit. We had the opportunity to witness the benefits of such a culture during this go-live and were incredibly impressed with the results.

To be successful in an EHR transition of any magnitude, an organization needs to hold patient safety as a core value and provide its employees with the tools to execute on that value. This enables staff to prepare adequately and to identify risks and opportunities before the conversion takes place. Once go-live occurs, staff also must feel empowered to speak up when they identify problem areas that might jeopardize patients’ care. They also must be given a clear escalation path to ensure their voices can be heard. Most importantly, everyone must understand that the electronic health record itself is just one piece of a major operational change.

As workflows are modified to adapt to the new technology, unsafe processes should be called out and fixed quickly. While the EHR may offer the latest in decision support and system integration, no advancement in technology can make up for bad outcomes, nor justify processes that lead to patient harm.
 

Training is no substitute for good support

It takes a long time to train thousands of employees, especially when that training must occur during the era of social distancing in the midst of a pandemic. Still, even in the best of times, education should be married to hands-on experience in order to have a real impact. Unfortunately, this is extremely challenging.

Trainees forget much of what they’ve learned in the weeks or months between education and go-live, so they must be given immediately accessible support to bridge the gap. This is known as “at-the-elbow” (ATE) support, and as the name implies, it consists of individuals who are familiar with the new system and are always available to end users, answering their questions and helping them navigate. Since health care never sleeps, this support needs to be offered 24/7, and it should also be flexible and plentiful.

There are many areas that will require more support than anticipated to accommodate the number of clinical and other staff who will use the system, so support staff must be nimble and available for redeployment. In addition, ensuring high-quality support is essential. As many ATE experts are hired contractors, their knowledge base and communications skills can vary widely. Accountability is key, and end users should feel empowered to identify gaps in coverage and deficits in knowledge base in the ATE.

As employees become more familiar with the new system, the need for ATE will wane, but there will still be questions that arise for many weeks to months, and new EHR users will also be added all the time. A good after–go-live support system should remain available so clinical and clerical employees can get just-in-time assistance whenever they need it.
 

Users should be given clear expectations

Clinicians going through an EHR conversion may be frustrated to discover that the data transferred from their old system into the new one is not quite what they expected. While structured elements such as allergies and immunizations may transfer, unstructured patient histories may not come over at all.

There may be gaps in data, or the opposite may even be true: an overabundance of useless information may transfer over, leaving doctors with dozens of meaningless data points to sift through and eliminate to clean up the chart. This can be extremely time-consuming and discouraging and may jeopardize the success of the go-live.

Providers deserve clear expectations prior to conversion. They should be told what will and will not transfer and be informed that there will be extra work required for documentation at the outset. They may also want the option to preemptively reduce patient volumes to accommodate the additional effort involved in preparing charts. No matter what, this will be a heavy lift, and physicians should understand the implications long before go-live to prepare accordingly.
 

Old habits die hard

One of the most common complaints we’ve heard following EHR conversions is that “things just worked better in the old system.” We always respond with a question: “Were things better, or just different?” The truth may lie somewhere in the middle, but there is no question that muscle memory develops over many years, and change is difficult no matter how much better the new system is. Still, appropriate expectations, access to just-in-time support, and a continual focus on safety will ensure that the long-term benefits of a patient-centered and integrated electronic record will far outweigh the initial challenges of go-live.

Dr. Notte is a family physician and chief medical officer of Abington (Pa.) Hospital–Jefferson Health. Dr. Skolnik is professor of family and community medicine at Sidney Kimmel Medical College, Philadelphia, and associate director of the family medicine residency program at Abington Hospital–Jefferson Health. They have no conflicts related to the content of this piece.

Recently, we had the opportunity to take part in a major EHR conversion project. During this “go-live,” 5 hospitals and approximately 300 ambulatory service and physician practice locations made the transition, consolidating over 100 disparate electronic systems and dozens of interfaces into one world-class medical record.

If you’ve ever been part of such an event, you know it is anything but simple. On the contrary, it requires an enormous financial investment along with years of planning, hours of meetings, and months of training. No matter how much preparation goes into it, there are sure to be bumps along the way. It is a traumatic and stressful time for all involved, but the end result is well worth the effort. Still, there are lessons to be learned and wisdom to be gleaned, and this month we’d like to share a few that we found most important. We believe that many of these are useful lessons even to those who will never live through a go-live.
 

Safety always comes first

Patient safety is a term so often used that it has a tendency to be taken for granted. Health systems build processes and procedures to ensure safety – some even win awards and recognition for their efforts. But the best (and safest) health care institutions build patient safety into their cultures. More than just being taught to use checklists or buzzwords, the staff at these institutions are encouraged to put the welfare of patients first, making all other activities secondary to this pursuit. We had the opportunity to witness the benefits of such a culture during this go-live and were incredibly impressed with the results.

To be successful in an EHR transition of any magnitude, an organization needs to hold patient safety as a core value and provide its employees with the tools to execute on that value. This enables staff to prepare adequately and to identify risks and opportunities before the conversion takes place. Once go-live occurs, staff also must feel empowered to speak up when they identify problem areas that might jeopardize patients’ care. They also must be given a clear escalation path to ensure their voices can be heard. Most importantly, everyone must understand that the electronic health record itself is just one piece of a major operational change.

As workflows are modified to adapt to the new technology, unsafe processes should be called out and fixed quickly. While the EHR may offer the latest in decision support and system integration, no advancement in technology can make up for bad outcomes, nor justify processes that lead to patient harm.
 

Training is no substitute for good support

It takes a long time to train thousands of employees, especially when that training must occur during the era of social distancing in the midst of a pandemic. Still, even in the best of times, education should be married to hands-on experience in order to have a real impact. Unfortunately, this is extremely challenging.

Trainees forget much of what they’ve learned in the weeks or months between education and go-live, so they must be given immediately accessible support to bridge the gap. This is known as “at-the-elbow” (ATE) support, and as the name implies, it consists of individuals who are familiar with the new system and are always available to end users, answering their questions and helping them navigate. Since health care never sleeps, this support needs to be offered 24/7, and it should also be flexible and plentiful.

There are many areas that will require more support than anticipated to accommodate the number of clinical and other staff who will use the system, so support staff must be nimble and available for redeployment. In addition, ensuring high-quality support is essential. As many ATE experts are hired contractors, their knowledge base and communications skills can vary widely. Accountability is key, and end users should feel empowered to identify gaps in coverage and deficits in knowledge base in the ATE.

As employees become more familiar with the new system, the need for ATE will wane, but there will still be questions that arise for many weeks to months, and new EHR users will also be added all the time. A good after–go-live support system should remain available so clinical and clerical employees can get just-in-time assistance whenever they need it.
 

Users should be given clear expectations

Clinicians going through an EHR conversion may be frustrated to discover that the data transferred from their old system into the new one is not quite what they expected. While structured elements such as allergies and immunizations may transfer, unstructured patient histories may not come over at all.

There may be gaps in data, or the opposite may even be true: an overabundance of useless information may transfer over, leaving doctors with dozens of meaningless data points to sift through and eliminate to clean up the chart. This can be extremely time-consuming and discouraging and may jeopardize the success of the go-live.

Providers deserve clear expectations prior to conversion. They should be told what will and will not transfer and be informed that there will be extra work required for documentation at the outset. They may also want the option to preemptively reduce patient volumes to accommodate the additional effort involved in preparing charts. No matter what, this will be a heavy lift, and physicians should understand the implications long before go-live to prepare accordingly.
 

Old habits die hard

One of the most common complaints we’ve heard following EHR conversions is that “things just worked better in the old system.” We always respond with a question: “Were things better, or just different?” The truth may lie somewhere in the middle, but there is no question that muscle memory develops over many years, and change is difficult no matter how much better the new system is. Still, appropriate expectations, access to just-in-time support, and a continual focus on safety will ensure that the long-term benefits of a patient-centered and integrated electronic record will far outweigh the initial challenges of go-live.

Dr. Notte is a family physician and chief medical officer of Abington (Pa.) Hospital–Jefferson Health. Dr. Skolnik is professor of family and community medicine at Sidney Kimmel Medical College, Philadelphia, and associate director of the family medicine residency program at Abington Hospital–Jefferson Health. They have no conflicts related to the content of this piece.

Recently, we had the opportunity to take part in a major EHR conversion project. During this “go-live,” 5 hospitals and approximately 300 ambulatory service and physician practice locations made the transition, consolidating over 100 disparate electronic systems and dozens of interfaces into one world-class medical record.

If you’ve ever been part of such an event, you know it is anything but simple. On the contrary, it requires an enormous financial investment along with years of planning, hours of meetings, and months of training. No matter how much preparation goes into it, there are sure to be bumps along the way. It is a traumatic and stressful time for all involved, but the end result is well worth the effort. Still, there are lessons to be learned and wisdom to be gleaned, and this month we’d like to share a few that we found most important. We believe that many of these are useful lessons even to those who will never live through a go-live.
 

Safety always comes first

Patient safety is a term so often used that it has a tendency to be taken for granted. Health systems build processes and procedures to ensure safety – some even win awards and recognition for their efforts. But the best (and safest) health care institutions build patient safety into their cultures. More than just being taught to use checklists or buzzwords, the staff at these institutions are encouraged to put the welfare of patients first, making all other activities secondary to this pursuit. We had the opportunity to witness the benefits of such a culture during this go-live and were incredibly impressed with the results.

To be successful in an EHR transition of any magnitude, an organization needs to hold patient safety as a core value and provide its employees with the tools to execute on that value. This enables staff to prepare adequately and to identify risks and opportunities before the conversion takes place. Once go-live occurs, staff also must feel empowered to speak up when they identify problem areas that might jeopardize patients’ care. They also must be given a clear escalation path to ensure their voices can be heard. Most importantly, everyone must understand that the electronic health record itself is just one piece of a major operational change.

As workflows are modified to adapt to the new technology, unsafe processes should be called out and fixed quickly. While the EHR may offer the latest in decision support and system integration, no advancement in technology can make up for bad outcomes, nor justify processes that lead to patient harm.
 

Training is no substitute for good support

It takes a long time to train thousands of employees, especially when that training must occur during the era of social distancing in the midst of a pandemic. Still, even in the best of times, education should be married to hands-on experience in order to have a real impact. Unfortunately, this is extremely challenging.

Trainees forget much of what they’ve learned in the weeks or months between education and go-live, so they must be given immediately accessible support to bridge the gap. This is known as “at-the-elbow” (ATE) support, and as the name implies, it consists of individuals who are familiar with the new system and are always available to end users, answering their questions and helping them navigate. Since health care never sleeps, this support needs to be offered 24/7, and it should also be flexible and plentiful.

There are many areas that will require more support than anticipated to accommodate the number of clinical and other staff who will use the system, so support staff must be nimble and available for redeployment. In addition, ensuring high-quality support is essential. As many ATE experts are hired contractors, their knowledge base and communications skills can vary widely. Accountability is key, and end users should feel empowered to identify gaps in coverage and deficits in knowledge base in the ATE.

As employees become more familiar with the new system, the need for ATE will wane, but there will still be questions that arise for many weeks to months, and new EHR users will also be added all the time. A good after–go-live support system should remain available so clinical and clerical employees can get just-in-time assistance whenever they need it.
 

Users should be given clear expectations

Clinicians going through an EHR conversion may be frustrated to discover that the data transferred from their old system into the new one is not quite what they expected. While structured elements such as allergies and immunizations may transfer, unstructured patient histories may not come over at all.

There may be gaps in data, or the opposite may even be true: an overabundance of useless information may transfer over, leaving doctors with dozens of meaningless data points to sift through and eliminate to clean up the chart. This can be extremely time-consuming and discouraging and may jeopardize the success of the go-live.

Providers deserve clear expectations prior to conversion. They should be told what will and will not transfer and be informed that there will be extra work required for documentation at the outset. They may also want the option to preemptively reduce patient volumes to accommodate the additional effort involved in preparing charts. No matter what, this will be a heavy lift, and physicians should understand the implications long before go-live to prepare accordingly.
 

Old habits die hard

One of the most common complaints we’ve heard following EHR conversions is that “things just worked better in the old system.” We always respond with a question: “Were things better, or just different?” The truth may lie somewhere in the middle, but there is no question that muscle memory develops over many years, and change is difficult no matter how much better the new system is. Still, appropriate expectations, access to just-in-time support, and a continual focus on safety will ensure that the long-term benefits of a patient-centered and integrated electronic record will far outweigh the initial challenges of go-live.

Dr. Notte is a family physician and chief medical officer of Abington (Pa.) Hospital–Jefferson Health. Dr. Skolnik is professor of family and community medicine at Sidney Kimmel Medical College, Philadelphia, and associate director of the family medicine residency program at Abington Hospital–Jefferson Health. They have no conflicts related to the content of this piece.

Jose Angel Soria-Lopez, MD, has an unusually wide perspective on how neurology patients are responding to the coronavirus pandemic. He treats patients at two San Diego–area clinics, one in a poor neighborhood near the Mexican border and another in an upscale city about 65 miles to the north. While the patient populations are quite different, he’s noticed they’ve share one thing in common lately: An unusually intense focus on their personal health.

“All of a sudden people are really thinking about their health,” Dr. Soria-Lopez said. “There’s a sense that their health is even more important than it used to be.”

But patients are divided on how exactly they want their health care delivered. Some are embracing the convenience of telemedicine, while others want to be seen in person no matter what. Moving forward beyond the pandemic, Dr. Soria-Lopez expects the upswing of interest in health will persist. And he predicts two kinds of neurological care will emerge: “One based on ongoing relationships that rely on physical encounters as a culture, and a second kind of neurology service where other patients – perhaps the younger ones – will switch to convenient, online follow-ups.”
 

Telemedicine will endure post pandemic

While some don’t foresee such a big divide between in-person and online visits, several of Dr. Soria-Lopez’s colleagues from around the country agreed in interviews that telemedicine will continue to play a larger role in neurology when the pandemic ends. One neurologist, however, cautioned that telemedicine can worsen disparities in care. And he raised the alarm about another aspect of the pandemic that isn’t going to lift when it’s over: The rise in neurological disorders linked to infection with COVID-19.

Before the pandemic, neurologists said, they rarely if ever treated patients via telemedicine outside of specific settings such as remote stroke care. Over the past year, the use of telemedicine has dramatically increased in neurology as in medicine as a whole. But the levels of adoption differ markedly. Neurologist Andrew N. Wilner, MD, of University of Tennessee Health Science Center, said he has used telemedicine to see a single patient so far. But Johns Hopkins Center for Sleep neurologist Charlene Gamaldo, MD, said her clinic converted to 100% remote visits in March 2020 and remains at that level.

“Where [the rate of telemedicine use] will land will be based on insurance reimbursement and license reciprocation, so it is difficult to predict,” she said. “I imagine that sleep will likely remain a hybrid model if current allowances remain.”

Some patients, especially the older ones, resisted the telemedicine visits at first, Dr. Gamaldo said, and family members had to step in to help. Now, she said, patients prefer them because of their convenience.

Some neurological conditions, of course, can’t be easily evaluated via online video. Dr. Soria-Lopez, who has offices in Chula Vista and Temecula, Calif., prefers that a patient appear in person at first. “It really takes 1-2 physical encounters for there to be some level of trust,” he said, adding that “it’s hard to do the first few visits online unless it’s a very straightforward case with one or two symptoms.”

Neurologists have found that telemedicine is especially useful for med-check visits. Mitzi Joi Williams, MD, an Atlanta-area neurologist and multiple sclerosis specialist, said some patients previously drove 2-3 hours for these visits, which can easily be conducted online. Dr. Williams added that online software can allow her to show MRIs to patients remotely. She simply shares her screen and talks about what the images show.

Neurological sequelae from COVID-19

Dr. Pérez, the Houston neurologist, said his colleagues should expect another aspect of the pandemic to persist: an influx of patients with neurological sequelae from COVID-19. As he noted in a 2020 report in Neurology Clinical Practice, coronaviruses have been linked to numerous neurological complications during and after the infectious period. “I have seen a few cases of Guillain-Barré and even postinfectious encephalitis in the clinic [linked to COVID-19],” he said. “Neurologists in general should be aware of the risk for chronic, postinfectious neurologic complications from prior COVID-19 infection.”

And, he said, it’s reasonable for neurologists to add a question to patient histories. It’s a simple yet powerful query: Have you had COVID-19?

Jose Angel Soria-Lopez, MD, has an unusually wide perspective on how neurology patients are responding to the coronavirus pandemic. He treats patients at two San Diego–area clinics, one in a poor neighborhood near the Mexican border and another in an upscale city about 65 miles to the north. While the patient populations are quite different, he’s noticed they’ve share one thing in common lately: An unusually intense focus on their personal health.

“All of a sudden people are really thinking about their health,” Dr. Soria-Lopez said. “There’s a sense that their health is even more important than it used to be.”

But patients are divided on how exactly they want their health care delivered. Some are embracing the convenience of telemedicine, while others want to be seen in person no matter what. Moving forward beyond the pandemic, Dr. Soria-Lopez expects the upswing of interest in health will persist. And he predicts two kinds of neurological care will emerge: “One based on ongoing relationships that rely on physical encounters as a culture, and a second kind of neurology service where other patients – perhaps the younger ones – will switch to convenient, online follow-ups.”
 

Telemedicine will endure post pandemic

While some don’t foresee such a big divide between in-person and online visits, several of Dr. Soria-Lopez’s colleagues from around the country agreed in interviews that telemedicine will continue to play a larger role in neurology when the pandemic ends. One neurologist, however, cautioned that telemedicine can worsen disparities in care. And he raised the alarm about another aspect of the pandemic that isn’t going to lift when it’s over: The rise in neurological disorders linked to infection with COVID-19.

Before the pandemic, neurologists said, they rarely if ever treated patients via telemedicine outside of specific settings such as remote stroke care. Over the past year, the use of telemedicine has dramatically increased in neurology as in medicine as a whole. But the levels of adoption differ markedly. Neurologist Andrew N. Wilner, MD, of University of Tennessee Health Science Center, said he has used telemedicine to see a single patient so far. But Johns Hopkins Center for Sleep neurologist Charlene Gamaldo, MD, said her clinic converted to 100% remote visits in March 2020 and remains at that level.

“Where [the rate of telemedicine use] will land will be based on insurance reimbursement and license reciprocation, so it is difficult to predict,” she said. “I imagine that sleep will likely remain a hybrid model if current allowances remain.”

Some patients, especially the older ones, resisted the telemedicine visits at first, Dr. Gamaldo said, and family members had to step in to help. Now, she said, patients prefer them because of their convenience.

Some neurological conditions, of course, can’t be easily evaluated via online video. Dr. Soria-Lopez, who has offices in Chula Vista and Temecula, Calif., prefers that a patient appear in person at first. “It really takes 1-2 physical encounters for there to be some level of trust,” he said, adding that “it’s hard to do the first few visits online unless it’s a very straightforward case with one or two symptoms.”

Neurologists have found that telemedicine is especially useful for med-check visits. Mitzi Joi Williams, MD, an Atlanta-area neurologist and multiple sclerosis specialist, said some patients previously drove 2-3 hours for these visits, which can easily be conducted online. Dr. Williams added that online software can allow her to show MRIs to patients remotely. She simply shares her screen and talks about what the images show.

Neurological sequelae from COVID-19

Dr. Pérez, the Houston neurologist, said his colleagues should expect another aspect of the pandemic to persist: an influx of patients with neurological sequelae from COVID-19. As he noted in a 2020 report in Neurology Clinical Practice, coronaviruses have been linked to numerous neurological complications during and after the infectious period. “I have seen a few cases of Guillain-Barré and even postinfectious encephalitis in the clinic [linked to COVID-19],” he said. “Neurologists in general should be aware of the risk for chronic, postinfectious neurologic complications from prior COVID-19 infection.”

And, he said, it’s reasonable for neurologists to add a question to patient histories. It’s a simple yet powerful query: Have you had COVID-19?

Jose Angel Soria-Lopez, MD, has an unusually wide perspective on how neurology patients are responding to the coronavirus pandemic. He treats patients at two San Diego–area clinics, one in a poor neighborhood near the Mexican border and another in an upscale city about 65 miles to the north. While the patient populations are quite different, he’s noticed they’ve share one thing in common lately: An unusually intense focus on their personal health.

“All of a sudden people are really thinking about their health,” Dr. Soria-Lopez said. “There’s a sense that their health is even more important than it used to be.”

But patients are divided on how exactly they want their health care delivered. Some are embracing the convenience of telemedicine, while others want to be seen in person no matter what. Moving forward beyond the pandemic, Dr. Soria-Lopez expects the upswing of interest in health will persist. And he predicts two kinds of neurological care will emerge: “One based on ongoing relationships that rely on physical encounters as a culture, and a second kind of neurology service where other patients – perhaps the younger ones – will switch to convenient, online follow-ups.”
 

Telemedicine will endure post pandemic

While some don’t foresee such a big divide between in-person and online visits, several of Dr. Soria-Lopez’s colleagues from around the country agreed in interviews that telemedicine will continue to play a larger role in neurology when the pandemic ends. One neurologist, however, cautioned that telemedicine can worsen disparities in care. And he raised the alarm about another aspect of the pandemic that isn’t going to lift when it’s over: The rise in neurological disorders linked to infection with COVID-19.

Before the pandemic, neurologists said, they rarely if ever treated patients via telemedicine outside of specific settings such as remote stroke care. Over the past year, the use of telemedicine has dramatically increased in neurology as in medicine as a whole. But the levels of adoption differ markedly. Neurologist Andrew N. Wilner, MD, of University of Tennessee Health Science Center, said he has used telemedicine to see a single patient so far. But Johns Hopkins Center for Sleep neurologist Charlene Gamaldo, MD, said her clinic converted to 100% remote visits in March 2020 and remains at that level.

“Where [the rate of telemedicine use] will land will be based on insurance reimbursement and license reciprocation, so it is difficult to predict,” she said. “I imagine that sleep will likely remain a hybrid model if current allowances remain.”

Some patients, especially the older ones, resisted the telemedicine visits at first, Dr. Gamaldo said, and family members had to step in to help. Now, she said, patients prefer them because of their convenience.

Some neurological conditions, of course, can’t be easily evaluated via online video. Dr. Soria-Lopez, who has offices in Chula Vista and Temecula, Calif., prefers that a patient appear in person at first. “It really takes 1-2 physical encounters for there to be some level of trust,” he said, adding that “it’s hard to do the first few visits online unless it’s a very straightforward case with one or two symptoms.”

Neurologists have found that telemedicine is especially useful for med-check visits. Mitzi Joi Williams, MD, an Atlanta-area neurologist and multiple sclerosis specialist, said some patients previously drove 2-3 hours for these visits, which can easily be conducted online. Dr. Williams added that online software can allow her to show MRIs to patients remotely. She simply shares her screen and talks about what the images show.

Neurological sequelae from COVID-19

Dr. Pérez, the Houston neurologist, said his colleagues should expect another aspect of the pandemic to persist: an influx of patients with neurological sequelae from COVID-19. As he noted in a 2020 report in Neurology Clinical Practice, coronaviruses have been linked to numerous neurological complications during and after the infectious period. “I have seen a few cases of Guillain-Barré and even postinfectious encephalitis in the clinic [linked to COVID-19],” he said. “Neurologists in general should be aware of the risk for chronic, postinfectious neurologic complications from prior COVID-19 infection.”

And, he said, it’s reasonable for neurologists to add a question to patient histories. It’s a simple yet powerful query: Have you had COVID-19?

One of the top research journals in the United States has placed its editor-in-chief on administrative leave pending the outcome of an investigation into a controversial podcast episode that critics labeled as racist.

The American Medical Association’s Joint Oversight Committee announced that Howard Bauchner, MD, is on leave beginning at the end of the day on March 25. Dr. Bauchner is the top editor at JAMA, the journal of the AMA.

“The decision to place the editor-in-chief on administrative leave neither implicates nor exonerates individuals and is standard operating procedure for such investigations,” the committee said in a statement.

More than 2,000 people signed a petition on Change.org calling for an investigation at JAMA over the February podcast episode, called “Structural Racism for Doctors: What Is It?”

Already, Edward H. Livingston, MD, the host of the podcast, has resigned as deputy editor of the journal.

During the podcast, Dr. Livingston, who is White, said, “Structural racism is an unfortunate term. Personally, I think taking racism out of the conversation will help. Many of us are offended by the concept that we are racist.”

The audio of the podcast has been deleted from JAMA’s website. In its place is audio of a statement from Dr. Bauchner. In his statement, which he released in the week prior to his being on leave, he said the comments in the podcast, which also featured Mitch Katz, MD, were “inaccurate, offensive, hurtful, and inconsistent with the standards of JAMA.”

Also deleted was a JAMA tweet promoting the podcast episode. The tweet said: “No physician is racist, so how can there be structural racism in health care? An explanation of the idea by doctors for doctors in this user-friendly podcast.”

This story will be updated.

A version of this article first appeared on WedMD.com.
 

One of the top research journals in the United States has placed its editor-in-chief on administrative leave pending the outcome of an investigation into a controversial podcast episode that critics labeled as racist.

The American Medical Association’s Joint Oversight Committee announced that Howard Bauchner, MD, is on leave beginning at the end of the day on March 25. Dr. Bauchner is the top editor at JAMA, the journal of the AMA.

“The decision to place the editor-in-chief on administrative leave neither implicates nor exonerates individuals and is standard operating procedure for such investigations,” the committee said in a statement.

More than 2,000 people signed a petition on Change.org calling for an investigation at JAMA over the February podcast episode, called “Structural Racism for Doctors: What Is It?”

Already, Edward H. Livingston, MD, the host of the podcast, has resigned as deputy editor of the journal.

During the podcast, Dr. Livingston, who is White, said, “Structural racism is an unfortunate term. Personally, I think taking racism out of the conversation will help. Many of us are offended by the concept that we are racist.”

The audio of the podcast has been deleted from JAMA’s website. In its place is audio of a statement from Dr. Bauchner. In his statement, which he released in the week prior to his being on leave, he said the comments in the podcast, which also featured Mitch Katz, MD, were “inaccurate, offensive, hurtful, and inconsistent with the standards of JAMA.”

Also deleted was a JAMA tweet promoting the podcast episode. The tweet said: “No physician is racist, so how can there be structural racism in health care? An explanation of the idea by doctors for doctors in this user-friendly podcast.”

This story will be updated.

A version of this article first appeared on WedMD.com.
 

One of the top research journals in the United States has placed its editor-in-chief on administrative leave pending the outcome of an investigation into a controversial podcast episode that critics labeled as racist.

The American Medical Association’s Joint Oversight Committee announced that Howard Bauchner, MD, is on leave beginning at the end of the day on March 25. Dr. Bauchner is the top editor at JAMA, the journal of the AMA.

“The decision to place the editor-in-chief on administrative leave neither implicates nor exonerates individuals and is standard operating procedure for such investigations,” the committee said in a statement.

More than 2,000 people signed a petition on Change.org calling for an investigation at JAMA over the February podcast episode, called “Structural Racism for Doctors: What Is It?”

Already, Edward H. Livingston, MD, the host of the podcast, has resigned as deputy editor of the journal.

During the podcast, Dr. Livingston, who is White, said, “Structural racism is an unfortunate term. Personally, I think taking racism out of the conversation will help. Many of us are offended by the concept that we are racist.”

The audio of the podcast has been deleted from JAMA’s website. In its place is audio of a statement from Dr. Bauchner. In his statement, which he released in the week prior to his being on leave, he said the comments in the podcast, which also featured Mitch Katz, MD, were “inaccurate, offensive, hurtful, and inconsistent with the standards of JAMA.”

Also deleted was a JAMA tweet promoting the podcast episode. The tweet said: “No physician is racist, so how can there be structural racism in health care? An explanation of the idea by doctors for doctors in this user-friendly podcast.”

This story will be updated.

A version of this article first appeared on WedMD.com.