Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics

Abstract Background Colorectal cancer (CRC) is the 3rd leading cancer killer among men and women in the US. The Strategies and Opportunities to STOP Colon Cancer in Priority Populations (STOP CRC) project aimed to increase CRC screening among patients in Federally Qualified Health Centers (FQHCs) th...

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Main Authors: Amanda F. Petrik, Erin Keast, Eric S. Johnson, David H. Smith, Gloria D. Coronado
Format: Article
Language:English
Published: BMC 2020-11-01
Series:BMC Health Services Research
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12913-020-05883-2
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spelling doaj-ff8f8666f37e4574993990942ad7dcf82020-11-25T04:06:00ZengBMCBMC Health Services Research1472-69632020-11-0120111110.1186/s12913-020-05883-2Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinicsAmanda F. Petrik0Erin Keast1Eric S. Johnson2David H. Smith3Gloria D. Coronado4The Center for Health Research, Kaiser Permanente NorthwestThe Center for Health Research, Kaiser Permanente NorthwestThe Center for Health Research, Kaiser Permanente NorthwestThe Center for Health Research, Kaiser Permanente NorthwestThe Center for Health Research, Kaiser Permanente NorthwestAbstract Background Colorectal cancer (CRC) is the 3rd leading cancer killer among men and women in the US. The Strategies and Opportunities to STOP Colon Cancer in Priority Populations (STOP CRC) project aimed to increase CRC screening among patients in Federally Qualified Health Centers (FQHCs) through a mailed fecal immunochemical test (FIT) outreach program. However, rates of completion of the follow-up colonoscopy following an abnormal FIT remain low. We developed a multivariable prediction model using data available in the electronic health record to assess the probability of patients obtaining a colonoscopy following an abnormal FIT test. Methods To assess the probability of obtaining a colonoscopy, we used Cox regression to develop a risk prediction model among a retrospective cohort of patients with an abnormal FIT result. Results Of 1596 patients with an abnormal FIT result, 556 (34.8%) had a recorded colonoscopy within 6 months. The model shows an adequate separation of patients across risk levels for non-adherence to follow-up colonoscopy (bootstrap-corrected C-statistic > 0.63). The refined model included 8 variables: age, race, insurance, GINI income inequality, long-term anticoagulant use, receipt of a flu vaccine in the past year, frequency of missed clinic appointments, and clinic site. The probability of obtaining a follow-up colonoscopy within 6 months varied across quintiles; patients in the lowest quintile had an estimated 18% chance, whereas patients in the top quintile had a greater than 55% chance of obtaining a follow-up colonoscopy. Conclusions Knowing who is unlikely to follow-up on an abnormal FIT test could help identify patients who need an early intervention aimed at completing a follow-up colonoscopy. Trial registration This trial was registered at ClinicalTrials.gov ( NCT01742065 ) on December 5, 2012. The protocol is available.http://link.springer.com/article/10.1186/s12913-020-05883-2Colorectal cancer screeningFecal immunochemical testColonoscopyMultivariable prediction modelPredictive analyticsPrecision medicine
collection DOAJ
language English
format Article
sources DOAJ
author Amanda F. Petrik
Erin Keast
Eric S. Johnson
David H. Smith
Gloria D. Coronado
spellingShingle Amanda F. Petrik
Erin Keast
Eric S. Johnson
David H. Smith
Gloria D. Coronado
Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
BMC Health Services Research
Colorectal cancer screening
Fecal immunochemical test
Colonoscopy
Multivariable prediction model
Predictive analytics
Precision medicine
author_facet Amanda F. Petrik
Erin Keast
Eric S. Johnson
David H. Smith
Gloria D. Coronado
author_sort Amanda F. Petrik
title Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
title_short Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
title_full Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
title_fullStr Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
title_full_unstemmed Development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test in community clinics
title_sort development of a multivariable prediction model to identify patients unlikely to complete a colonoscopy following an abnormal fit test in community clinics
publisher BMC
series BMC Health Services Research
issn 1472-6963
publishDate 2020-11-01
description Abstract Background Colorectal cancer (CRC) is the 3rd leading cancer killer among men and women in the US. The Strategies and Opportunities to STOP Colon Cancer in Priority Populations (STOP CRC) project aimed to increase CRC screening among patients in Federally Qualified Health Centers (FQHCs) through a mailed fecal immunochemical test (FIT) outreach program. However, rates of completion of the follow-up colonoscopy following an abnormal FIT remain low. We developed a multivariable prediction model using data available in the electronic health record to assess the probability of patients obtaining a colonoscopy following an abnormal FIT test. Methods To assess the probability of obtaining a colonoscopy, we used Cox regression to develop a risk prediction model among a retrospective cohort of patients with an abnormal FIT result. Results Of 1596 patients with an abnormal FIT result, 556 (34.8%) had a recorded colonoscopy within 6 months. The model shows an adequate separation of patients across risk levels for non-adherence to follow-up colonoscopy (bootstrap-corrected C-statistic > 0.63). The refined model included 8 variables: age, race, insurance, GINI income inequality, long-term anticoagulant use, receipt of a flu vaccine in the past year, frequency of missed clinic appointments, and clinic site. The probability of obtaining a follow-up colonoscopy within 6 months varied across quintiles; patients in the lowest quintile had an estimated 18% chance, whereas patients in the top quintile had a greater than 55% chance of obtaining a follow-up colonoscopy. Conclusions Knowing who is unlikely to follow-up on an abnormal FIT test could help identify patients who need an early intervention aimed at completing a follow-up colonoscopy. Trial registration This trial was registered at ClinicalTrials.gov ( NCT01742065 ) on December 5, 2012. The protocol is available.
topic Colorectal cancer screening
Fecal immunochemical test
Colonoscopy
Multivariable prediction model
Predictive analytics
Precision medicine
url http://link.springer.com/article/10.1186/s12913-020-05883-2
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