Birth-Cohort Evaluation to Advance Screening and Testing for Hepatitis C (Best-C)

NORC at the University of Chicago, University of Alabama at Birmingham, Henry Ford Health System, Icahn School of Medicine at Mount Sinai, Centers for Disease Control and Prevention

The Birth-Cohort Evaluation to Advance Screening and Testing for Hepatitis C (BEST-C) compares the effectiveness of the birth cohort HCV screening strategy with the current risk-based screening approach to detect previous unidentified persons with viral hepatitis C who receive health care in primary systems. The study involved three clinical sites, The University of Alabama, Birmingham; The Henry Ford Health System; and the Mount Sinai Medical Center, each of which developed an independent intervention to experimentally compare the number of positive Hepatitis C Virus (HCV) diagnoses found using the birth-cohort screening approach with that found using traditional risk-based screening, or standard of care strategies. Birth cohort testing is defined as the systematic recommendation of HCV antibody testing to any persons born during the years of 1945 to 1965 who do not have clinically documented evidence of a prior antibody test without regards to the patient's stated risk of exposure to the virus.

The Birth-Cohort Evaluation to Advance Screening and Testing for Hepatitis C (BEST-C) compares the effectiveness of the birth cohort HCV screening strategy with the current risk-based HCV screening approach to detect previously unidentified persons with viral hepatitis C who receive health care in primary care systems. BEST-C funded sites to implement birth-cohort testing in a clinic sample of primary care patients using an experimental design to compare the effect of birth-cohort testing on testing rates and identified prevalence between a case and a control sample. Additional data will be collected to assess linkage to care for those testing positive, feasibility, and acceptance of the new strategy by medical staff, cost effectiveness, and patient impact. The sites used three models to measure the net effect of change: One site used study coordinators to actively screen and recruit patients who met the inclusion criteria for birth-cohort screening. Study coordinators were located at two internal medicine clinics, where they approached eligible participants in person. A control group was pulled from an additional two internal medicine clinics, which screened using a risk-based strategy. A cluster randomized cross-over approach was used, so that the intervention and control clinics switched at the midpoint of data collection, allowing all four clinics to participate in both arms of the study. A second site reached out directly to the patient using direct communication through the mail. Mailers contained HCV guidelines, the importance of screening, laboratory slips and locations for patients to act directly on their own behalf. This site used simple randomization of patients who used the health system in the past, met the definition of birth-cohort membership (born during 1945 to 1965) and had not previously tested positive for hepatitis C. The patients received up to 5 mailings including prepaid, lab registration forms that they were instructed to bring to an affiliated lab location for testing. A third site implemented a physican best practice alert into the Epic electronic health record system of their clinic setting. This site had the pop-ups enabled for Medical Assistants (MAs) who were asked to pend the lab to the order in the chart for the clinician. When MAs open the chart of an arrived, untested patient, they are alerted to pend the Hepatitis C antibody test order when entering patient vitals prior to the patient seeing the physician. When the clinician subsequently opened the same patient chart, the lab order was present in the orders section of the chart for signature and execution or deletion depending on the circumstances of the patient encounter. As a back-up pathway alerted the physician directly in the event that the MA bypassed or did not open the prompt. This alert details the CDC recommendations for age-based screening and links to the proper Hepatitis C antibody test order and diagnosis code for them to address with the patient. This site used a cluster randomized experimental design in which physicians and MA's from specific primary care practices were consented into the study. Experimental clusters received an education about HCV testing and the implemented best practice alert. Control clusters received only education about HCV testing.

Henry Ford intentifies patients meeting birth cohort screening criteria and then sends mailers to those individuals. Mailers contained HCV guidelines, the importance of screening, laboratory slips and locations for patients to act directly on their own behalf. If patients do not respond to the initial mailer, Henry Ford sends additional mailers.

UAB used study coordinators to actively screen and recruit patients who met the inclusion criteria for birth-cohort screening. Study coordinators were located at two internal medicine clinics, where they approached eligible participants in person. A control group was pulled from an additional two internal medicine clinics, which screened using a risk-based strategy. A cross-over approach was used, so that the intervention and control clinics switched at the midpoint of data collection, allowing all four clinics to participate in both arms of the study.

EHR include a Best Practice Alert (BPA) prompting the Medical Assistant and/or clinican to order a Hepatitis C lab test for patients in the birth cohort.

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