PURPOSE: The purpose of this project was to evaluate the utility of using the 6 elements of the chronic care model (CCM; health system, community, decision support, self-management support, clinical information systems, and delivery system design) to implement and financially sustain an effective diabetes self-management training (DSMT) program. METHODS: The University of Pittsburgh Medical Center (UPMC) uses all elements of the CCM. Partnerships were formed between UPMC and western Pennsylvanian community hospitals and practices; the American Diabetes Association DSMT recognition program provided decision support. A clinical data repository and reorganization of primary care practices aided in supporting DSMT. The following process and patient outcomes were measured: number of recognized programs, reimbursement, patient hemoglobin A1C levels, and the proportion of patients who received DSMT in primary care practices versus hospital-based programs. RESULTS: Using elements of the CCM, the researchers were able to gain administrative support; expand the number of recognized programs from 3 to 21; cover costs through increased reimbursement; reduce hemoglobin A1C levels (P < .0001), and increase the proportion of patients receiving DSMT through delivery in primary care (26.4% suburban; 19.8% urban) versus hospital-based practices (8.3%; P < .0001). CONCLUSIONS: The CCM serves as an effective model for implementing and sustaining DSMT programs.
PURPOSE: The purpose of this project was to evaluate the utility of using the 6 elements of the chronic care model (CCM; health system, community, decision support, self-management support, clinical information systems, and delivery system design) to implement and financially sustain an effective diabetes self-management training (DSMT) program. METHODS: The University of Pittsburgh Medical Center (UPMC) uses all elements of the CCM. Partnerships were formed between UPMC and western Pennsylvanian community hospitals and practices; the American Diabetes Association DSMT recognition program provided decision support. A clinical data repository and reorganization of primary care practices aided in supporting DSMT. The following process and patient outcomes were measured: number of recognized programs, reimbursement, patient hemoglobin A1C levels, and the proportion of patients who received DSMT in primary care practices versus hospital-based programs. RESULTS: Using elements of the CCM, the researchers were able to gain administrative support; expand the number of recognized programs from 3 to 21; cover costs through increased reimbursement; reduce hemoglobin A1C levels (P < .0001), and increase the proportion of patients receiving DSMT through delivery in primary care (26.4% suburban; 19.8% urban) versus hospital-based practices (8.3%; P < .0001). CONCLUSIONS: The CCM serves as an effective model for implementing and sustaining DSMT programs.
Authors: Pamela A Ohman Strickland; Shawna V Hudson; Alicja Piasecki; Karissa Hahn; Deborah Cohen; A John Orzano; Michael L Parchman; Benjamin F Crabtree Journal: J Am Board Fam Med Date: 2010 May-Jun Impact factor: 2.657
Authors: Donald E Bailey; Sharron L Docherty; Judith A Adams; Dana L Carthron; Kirsten Corazzini; Jennifer R Day; Elizabeth Neglia; Marcus Thygeson; Ruth A Anderson Journal: J Healthc Leadersh Date: 2012-08
Authors: Thomas D Sequist; Ted von Glahn; Angela Li; William H Rogers; Dana Gelb Safran Journal: J Gen Intern Med Date: 2009-06-09 Impact factor: 5.128
Authors: Linda Haas; Melinda Maryniuk; Joni Beck; Carla E Cox; Paulina Duker; Laura Edwards; Edwin B Fisher; Lenita Hanson; Daniel Kent; Leslie Kolb; Sue McLaughlin; Eric Orzeck; John D Piette; Andrew S Rhinehart; Russell Rothman; Sara Sklaroff; Donna Tomky; Gretchen Youssef Journal: Diabetes Care Date: 2012-09-20 Impact factor: 19.112
Authors: Martha M Funnell; Tammy L Brown; Belinda P Childs; Linda B Haas; Gwen M Hosey; Brian Jensen; Melinda Maryniuk; Mark Peyrot; John D Piette; Diane Reader; Linda M Siminerio; Katie Weinger; Michael A Weiss Journal: Diabetes Care Date: 2010-01 Impact factor: 19.112