Chris Miller-Rosales1, Isomi M Miake-Lye2,3, Amanda L Brewster4, Stephen M Shortell4, Hector P Rodriguez4. 1. Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA. 2. Evidence-based Synthesis Program (ESP) Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California, USA. 3. Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA. 4. School of Public Health, University of California, Berkeley, Berkeley, California, USA.
Abstract
OBJECTIVE: To identify potential orderings of primary care practice adoption of patient engagement strategies overall and separately for interpersonally and technologically oriented strategies. DATA SOURCES: We analyzed physician practice survey data (n = 71) on the adoption of 12 patient engagement strategies. STUDY DESIGN: Mokken scale analysis was used to assess latent traits among the patient engagement strategies. DATA COLLECTION: Three groupings of patient engagement strategies were analyzed: (1) all 12 patient engagement strategies, (2) six interpersonally oriented strategies, and (3) six technologically oriented strategies. PRINCIPAL FINDINGS: We did not find scalability among all 12 patient engagement strategies, however, separately analyzing the subgroups of six interpersonally and six technologically oriented strategies demonstrated scalability (Loevinger's H coefficient of scalability [range]: interpersonal strategies, H = 0.54 [0.49-0.60], technological strategies, H = 0.42 [0.31, 0.54]). Ordered patterns emerged in the adoption of strategies for both interpersonal and technological types. CONCLUSIONS: Common pathways of practice adoption of patient engagement strategies were identified. Implementing interpersonally intensive patient engagement strategies may require different physician practice capabilities than technological strategies. Rather than simultaneously adopting multiple patient engagement strategies, gradual and purposeful practice adoption may improve the impact of these strategies and support sustainability.
OBJECTIVE: To identify potential orderings of primary care practice adoption of patient engagement strategies overall and separately for interpersonally and technologically oriented strategies. DATA SOURCES: We analyzed physician practice survey data (n = 71) on the adoption of 12 patient engagement strategies. STUDY DESIGN: Mokken scale analysis was used to assess latent traits among the patient engagement strategies. DATA COLLECTION: Three groupings of patient engagement strategies were analyzed: (1) all 12 patient engagement strategies, (2) six interpersonally oriented strategies, and (3) six technologically oriented strategies. PRINCIPAL FINDINGS: We did not find scalability among all 12 patient engagement strategies, however, separately analyzing the subgroups of six interpersonally and six technologically oriented strategies demonstrated scalability (Loevinger's H coefficient of scalability [range]: interpersonal strategies, H = 0.54 [0.49-0.60], technological strategies, H = 0.42 [0.31, 0.54]). Ordered patterns emerged in the adoption of strategies for both interpersonal and technological types. CONCLUSIONS: Common pathways of practice adoption of patient engagement strategies were identified. Implementing interpersonally intensive patient engagement strategies may require different physician practice capabilities than technological strategies. Rather than simultaneously adopting multiple patient engagement strategies, gradual and purposeful practice adoption may improve the impact of these strategies and support sustainability.
Authors: Anjana E Sharma; Rachel Willard-Grace; Andrew Willis; Olivia Zieve; Kate Dubé; Charla Parker; Michael B Potter Journal: J Am Board Fam Med Date: 2016-11-12 Impact factor: 2.657
Authors: Stephen M Shortell; Bing Ying Poon; Patricia P Ramsay; Hector P Rodriguez; Susan L Ivey; Thomas Huber; Jeremy Rich; Tom Summerfelt Journal: J Gen Intern Med Date: 2017-02-03 Impact factor: 5.128
Authors: Alex H Krist; John W Beasley; Jesse C Crosson; David C Kibbe; Michael S Klinkman; Christoph U Lehmann; Chester H Fox; Jason M Mitchell; James W Mold; Wilson D Pace; Kevin A Peterson; Robert L Phillips; Robert Post; Jon Puro; Michael Raddock; Ray Simkus; Steven E Waldren Journal: J Am Med Inform Assoc Date: 2014-01-15 Impact factor: 4.497
Authors: Jeremy Laurance; Sarah Henderson; Peter J Howitt; Mariam Matar; Hanan Al Kuwari; Susan Edgman-Levitan; Ara Darzi Journal: Health Aff (Millwood) Date: 2014-09 Impact factor: 6.301
Authors: Isomi M Miake-Lye; Emmeline Chuang; Hector P Rodriguez; Gerald F Kominski; Elizabeth M Yano; Stephen M Shortell Journal: Implement Sci Date: 2017-08-24 Impact factor: 7.327
Authors: Donna Patricia Manca; Denise Campbell-Scherer; Kris Aubrey-Bassler; Kami Kandola; Carolina Aguilar; Julia Baxter; Christopher Meaney; Ginetta Salvalaggio; June C Carroll; Vee Faria; Candace Nykiforuk; Eva Grunfeld Journal: Implement Sci Date: 2015-08-04 Impact factor: 7.327
Authors: Manish K Mishra; Catherine H Saunders; Hector P Rodriguez; Stephen M Shortell; Elliott Fisher; Glyn Elwyn Journal: BMJ Open Date: 2018-10-31 Impact factor: 2.692
Authors: Chris Miller-Rosales; Isomi M Miake-Lye; Amanda L Brewster; Stephen M Shortell; Hector P Rodriguez Journal: Health Serv Res Date: 2022-03-04 Impact factor: 3.734