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Study Overview
Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.
Design. Randomized clinical trial.
Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.
The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.
Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.
Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.
Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.
Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.
Commentary
The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.
The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.
Applications for Clinical Practice
PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.
—Ajay Dharod, MD
1. Calonge N, Petitti DB, DeWitt TG, et al. Screening for breast cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2009;151:716–26.
2. Moyer VA; US Preventive Services Task Force. Screening for cervical cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2012;156:880–91.
3. Phillips CE, Rothstein JD, Beaver K, et al. Patient navigation to increase mammography screening among inner city women. J Gen Intern Med 2011;26:123–9.
4. Jandorf L, Braschi C, Ernstoff E, et al. Culturally targeted patient navigation for increasing African Americans’ adherence to screening colonoscopy: a randomized clinical trial. Cancer Epidemiol Biomarkers Prev 2013;22:1577–87.
5. Braschi CD, Sly JR, Singh S, et al. Increasing colonoscopy screening for Latino Americans through a patient navigation model: a randomized clinical trial. J Immigr Minor Health 2014;16:934–40.
6. US Preventive Services Task Force. Published recommendations. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/BrowseRec/Index/browse-recommendations.
7. US Preventive Services Task Force. Final recommendation statement: Breast cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/breast-cancer-screening1.
8. US Preventive Services Task Force. Final Recommendation Statement: Cervical cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/cervical-cancer-screening.
9. US Preventive Services Task Force. Final Recommendation Statement: Colorectal cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/colorectal-cancer-screening2.
10. Inadomi JM, Vijan S, Janz NK, et al. Adherence to colorectal cancer screening: a randomized clinical trial of competing strategies. Arch Intern Med 2012;172:575–82.
Study Overview
Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.
Design. Randomized clinical trial.
Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.
The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.
Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.
Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.
Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.
Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.
Commentary
The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.
The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.
Applications for Clinical Practice
PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.
—Ajay Dharod, MD
Study Overview
Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.
Design. Randomized clinical trial.
Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.
The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.
Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.
Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.
Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.
Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.
Commentary
The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.
The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.
Applications for Clinical Practice
PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.
—Ajay Dharod, MD
1. Calonge N, Petitti DB, DeWitt TG, et al. Screening for breast cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2009;151:716–26.
2. Moyer VA; US Preventive Services Task Force. Screening for cervical cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2012;156:880–91.
3. Phillips CE, Rothstein JD, Beaver K, et al. Patient navigation to increase mammography screening among inner city women. J Gen Intern Med 2011;26:123–9.
4. Jandorf L, Braschi C, Ernstoff E, et al. Culturally targeted patient navigation for increasing African Americans’ adherence to screening colonoscopy: a randomized clinical trial. Cancer Epidemiol Biomarkers Prev 2013;22:1577–87.
5. Braschi CD, Sly JR, Singh S, et al. Increasing colonoscopy screening for Latino Americans through a patient navigation model: a randomized clinical trial. J Immigr Minor Health 2014;16:934–40.
6. US Preventive Services Task Force. Published recommendations. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/BrowseRec/Index/browse-recommendations.
7. US Preventive Services Task Force. Final recommendation statement: Breast cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/breast-cancer-screening1.
8. US Preventive Services Task Force. Final Recommendation Statement: Cervical cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/cervical-cancer-screening.
9. US Preventive Services Task Force. Final Recommendation Statement: Colorectal cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/colorectal-cancer-screening2.
10. Inadomi JM, Vijan S, Janz NK, et al. Adherence to colorectal cancer screening: a randomized clinical trial of competing strategies. Arch Intern Med 2012;172:575–82.
1. Calonge N, Petitti DB, DeWitt TG, et al. Screening for breast cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2009;151:716–26.
2. Moyer VA; US Preventive Services Task Force. Screening for cervical cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 2012;156:880–91.
3. Phillips CE, Rothstein JD, Beaver K, et al. Patient navigation to increase mammography screening among inner city women. J Gen Intern Med 2011;26:123–9.
4. Jandorf L, Braschi C, Ernstoff E, et al. Culturally targeted patient navigation for increasing African Americans’ adherence to screening colonoscopy: a randomized clinical trial. Cancer Epidemiol Biomarkers Prev 2013;22:1577–87.
5. Braschi CD, Sly JR, Singh S, et al. Increasing colonoscopy screening for Latino Americans through a patient navigation model: a randomized clinical trial. J Immigr Minor Health 2014;16:934–40.
6. US Preventive Services Task Force. Published recommendations. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/BrowseRec/Index/browse-recommendations.
7. US Preventive Services Task Force. Final recommendation statement: Breast cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/breast-cancer-screening1.
8. US Preventive Services Task Force. Final Recommendation Statement: Cervical cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/cervical-cancer-screening.
9. US Preventive Services Task Force. Final Recommendation Statement: Colorectal cancer: Screening. 2016. Accessed 12 July 2016 at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/colorectal-cancer-screening2.
10. Inadomi JM, Vijan S, Janz NK, et al. Adherence to colorectal cancer screening: a randomized clinical trial of competing strategies. Arch Intern Med 2012;172:575–82.