Susanne Hempel1,2,3, Maria Bolshakova1, Barbara J Turner2, Jennifer Dinalo4, Danielle Rose5, Aneesa Motala1,2,3, Ning Fu6,7, Chase G Clemesha4, Lisa Rubenstein3, Susan Stockdale5. 1. Southern California Evidence Review Center, University of Southern California, Los Angeles, CA, USA. 2. Gehr Family Center for Health Systems Science and Innovation, University of Southern California, Los Angeles, CA, USA. 3. RAND Health, RAND Corporation, Santa Monica, CA, USA. 4. University of Southern California, Los Angeles, CA, USA. 5. Center for the Study of Healthcare Innovation, Implementation & Policy, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. 6. Southern California Evidence Review Center, University of Southern California, Los Angeles, CA, USA. fu.ning@mail.shufe.edu.cn. 7. School of Economics, Shanghai University of Finance and Economics, Shanghai, China. fu.ning@mail.shufe.edu.cn.
Abstract
BACKGROUND: Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development. METHODS: In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI? RESULTS: We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term "EBQI." Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term "EBQI" with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes. CONCLUSIONS: EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.
BACKGROUND: Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development. METHODS: In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI? RESULTS: We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term "EBQI." Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term "EBQI" with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes. CONCLUSIONS: EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.
Authors: David Meyers; Therese Miller; Janice Genevro; Chunliu Zhan; Jan De La Mare; Alaina Fournier; Harriet Bennett; Robert J McNellis Journal: Ann Fam Med Date: 2018-04 Impact factor: 5.166
Authors: Lisa V Rubenstein; Edmund F Chaney; Scott Ober; Bradford Felker; Scott E Sherman; Andy Lanto; Susan Vivell Journal: Fam Syst Health Date: 2010-06 Impact factor: 1.950
Authors: Elizabeth M Yano; Lisa V Rubenstein; Melissa M Farmer; Bruce A Chernof; Brian S Mittman; Andrew B Lanto; Barbara F Simon; Martin L Lee; Scott E Sherman Journal: Health Serv Res Date: 2008-06-03 Impact factor: 3.402
Authors: Andrea C Tricco; Erin Lillie; Wasifa Zarin; Kelly K O'Brien; Heather Colquhoun; Danielle Levac; David Moher; Micah D J Peters; Tanya Horsley; Laura Weeks; Susanne Hempel; Elie A Akl; Christine Chang; Jessie McGowan; Lesley Stewart; Lisa Hartling; Adrian Aldcroft; Michael G Wilson; Chantelle Garritty; Simon Lewin; Christina M Godfrey; Marilyn T Macdonald; Etienne V Langlois; Karla Soares-Weiser; Jo Moriarty; Tammy Clifford; Özge Tunçalp; Sharon E Straus Journal: Ann Intern Med Date: 2018-09-04 Impact factor: 25.391
Authors: Susanne Hempel; Lisa V Rubenstein; Roberta M Shanman; Robbie Foy; Su Golder; Marjorie Danz; Paul G Shekelle Journal: Implement Sci Date: 2011-08-01 Impact factor: 7.327
Authors: Edmund F Chaney; Lisa V Rubenstein; Chuan-Fen Liu; Elizabeth M Yano; Cory Bolkan; Martin Lee; Barbara Simon; Andy Lanto; Bradford Felker; Jane Uman Journal: Implement Sci Date: 2011-10-27 Impact factor: 7.327
Authors: Susan E Stockdale; Alison B Hamilton; Alicia A Bergman; Danielle E Rose; Karleen F Giannitrapani; Timothy R Dresselhaus; Elizabeth M Yano; Lisa V Rubenstein Journal: Implement Sci Date: 2020-03-18 Impact factor: 7.327