INTRODUCTION: Hepatitis C virus (HCV) infection leads to significant morbidity and mortality. Rates of HCV infection are greatest in patients born from 1945 to 1965, so the Centers for Disease Control recommends a one-time screening in this cohort. Previous interventions utilizing the electronic medical record (EMR) capabilities at two University of Utah Family Medicine clinics have increased screening rates significantly, but further improvement is possible. METHODS: A family medicine resident-led continuous quality improvement (CQI) team used the Model for Improvement methods popularized by the Institute for Healthcare Improvement to create a team-based intervention with the goal of improving HCV screening in a family medicine faculty and resident clinic. An order set was created and a protocol developed that allowed medical assistants or clinic phlebotomists to order the appropriate HCV screening lab if this had not yet been done by the primary care provider. Data were extracted from the EMR that showed changes in total and monthly screening rates as well as the frequency of order set use. RESULTS: Monthly screening rates at the Madsen Family Medicine Clinic (Salt Lake City, UT) increased from approximately 40% to greater than 50% in the 5-month intervention period. The order set was used 19 times during this period which accounted for 18.8% of new screens. CONCLUSIONS: Creating an order set that allows medical assistants to order the HCV screening lab increased HCV screening rates in our clinic. Because order set utilization data can be extracted from the EMR, this intervention provided a process measure that can differentiate the effect of this intervention from the effects of other interventions previously undertaken in the clinic.
INTRODUCTION: Hepatitis C virus (HCV) infection leads to significant morbidity and mortality. Rates of HCV infection are greatest in patients born from 1945 to 1965, so the Centers for Disease Control recommends a one-time screening in this cohort. Previous interventions utilizing the electronic medical record (EMR) capabilities at two University of Utah Family Medicine clinics have increased screening rates significantly, but further improvement is possible. METHODS: A family medicine resident-led continuous quality improvement (CQI) team used the Model for Improvement methods popularized by the Institute for Healthcare Improvement to create a team-based intervention with the goal of improving HCV screening in a family medicine faculty and resident clinic. An order set was created and a protocol developed that allowed medical assistants or clinic phlebotomists to order the appropriate HCV screening lab if this had not yet been done by the primary care provider. Data were extracted from the EMR that showed changes in total and monthly screening rates as well as the frequency of order set use. RESULTS: Monthly screening rates at the Madsen Family Medicine Clinic (Salt Lake City, UT) increased from approximately 40% to greater than 50% in the 5-month intervention period. The order set was used 19 times during this period which accounted for 18.8% of new screens. CONCLUSIONS: Creating an order set that allows medical assistants to order the HCV screening lab increased HCV screening rates in our clinic. Because order set utilization data can be extracted from the EMR, this intervention provided a process measure that can differentiate the effect of this intervention from the effects of other interventions previously undertaken in the clinic.
Authors: Barbara S Taylor; Joshua T Hanson; Poornachand Veerapaneni; Roberto Villarreal; Kristin Fiebelkorn; Barbara J Turner Journal: Public Health Rep Date: 2016 May-Jun Impact factor: 2.792
Authors: Bryce D Smith; Rebecca L Morgan; Geoff A Beckett; Yngve Falck-Ytter; Deborah Holtzman; Chong-Gee Teo; Amy Jewett; Brittney Baack; David B Rein; Nita Patel; Miriam Alter; Anthony Yartel; John W Ward Journal: MMWR Recomm Rep Date: 2012-08-17
Authors: Joshua A Barocas; Jianing Wang; Laura F White; Abriana Tasillo; Joshua A Salomon; Kenneth A Freedberg; Benjamin P Linas Journal: Health Aff (Millwood) Date: 2017-12 Impact factor: 9.048