BACKGROUND: Integrated models of primary care depression management improve outcomes. Subsequent dissemination efforts and their evaluation need a fidelity measure. OBJECTIVES: We sought to develop and validate a fidelity measure using data gathered during routine clinical application of the clinical model. METHODS: Longitudinal outcome data on depression severity were obtained from 224 subjects experiencing major depression or dysthymia and assigned to a3-component model (3CM) intervention. Data on 10 essential 3CM process-of-care components were obtained from telephone logs maintained by care managers administering 3CM care. Stakeholders (n = 23), including researchers, health care administrators, and care managers, independently rated the importance of the 10 elements distributing 100 points among the elements. Mean ratings were used as weights to construct a fidelity score. Predictive validity was assessed using logistic regression for patient response and remission at 3 and 6 months. RESULTS:3CM fidelity was high, with a mean of 74.1 at 3 months and 75.9 at 6 months. Given a large gap in the scores' distribution, subjects were classified into zero, low-, and high-fidelity groups. Logistic regressions adjusting for baseline depression found a distinct continuum. Patients that were provided high fidelity 3CM were significantly more likely to achieve treatment response and remission at 3 months. At 6 months, high-fidelity care was again significantly more likely to produce a response, but remission rate did not differ from patients provided low fidelity. CONCLUSIONS: Most patients received a substantially implemented "3CM dose." Even within this high implementation, however, a higher fidelity score was associated with better outcomes. The easily applied measure is a promising tool for monitoring the quality of implementation of integrated care.
RCT Entities:
BACKGROUND: Integrated models of primary care depression management improve outcomes. Subsequent dissemination efforts and their evaluation need a fidelity measure. OBJECTIVES: We sought to develop and validate a fidelity measure using data gathered during routine clinical application of the clinical model. METHODS: Longitudinal outcome data on depression severity were obtained from 224 subjects experiencing major depression or dysthymia and assigned to a 3-component model (3CM) intervention. Data on 10 essential 3CM process-of-care components were obtained from telephone logs maintained by care managers administering 3CM care. Stakeholders (n = 23), including researchers, health care administrators, and care managers, independently rated the importance of the 10 elements distributing 100 points among the elements. Mean ratings were used as weights to construct a fidelity score. Predictive validity was assessed using logistic regression for patient response and remission at 3 and 6 months. RESULTS: 3CM fidelity was high, with a mean of 74.1 at 3 months and 75.9 at 6 months. Given a large gap in the scores' distribution, subjects were classified into zero, low-, and high-fidelity groups. Logistic regressions adjusting for baseline depression found a distinct continuum. Patients that were provided high fidelity 3CM were significantly more likely to achieve treatment response and remission at 3 months. At 6 months, high-fidelity care was again significantly more likely to produce a response, but remission rate did not differ from patients provided low fidelity. CONCLUSIONS: Most patients received a substantially implemented "3CM dose." Even within this high implementation, however, a higher fidelity score was associated with better outcomes. The easily applied measure is a promising tool for monitoring the quality of implementation of integrated care.
Authors: Gregory P Beehler; Jennifer S Funderburk; Paul R King; Kyle Possemato; John A Maddoux; Wade R Goldstein; Michael Wade Journal: J Clin Psychol Med Settings Date: 2020-03
Authors: Herbert C Schulberg; Bea Herbeck Belnap; Patricia R Houck; Sati Mazumdar; Charles F Reynolds; Bruce L Rollman Journal: Am J Geriatr Psychiatry Date: 2011-10 Impact factor: 4.105
Authors: Bradley E Belsher; Daniel P Evatt; Xian Liu; Michael C Freed; Charles C Engel; Erin H Beech; Lisa H Jaycox Journal: J Gen Intern Med Date: 2018-04-27 Impact factor: 5.128
Authors: Paula P Schnurr; Matthew J Friedman; Thomas E Oxman; Allen J Dietrich; Mark W Smith; Brian Shiner; Elizabeth Forshay; Jiang Gui; Veronica Thurston Journal: J Gen Intern Med Date: 2012-08-03 Impact factor: 5.128
Authors: Howard Waitzkin; Christina Getrich; Shirley Heying; Laura Rodríguez; Anita Parmar; Cathleen Willging; Joel Yager; Richard Santos Journal: J Community Health Date: 2011-04
Authors: Moniek C Vlasveld; Johannes R Anema; Aartjan T F Beekman; Willem van Mechelen; Rob Hoedeman; Harm W J van Marwijk; Frans F Rutten; Leona Hakkaart-van Roijen; Christina M van der Feltz-Cornelis Journal: BMC Health Serv Res Date: 2008-05-05 Impact factor: 2.655
Authors: Emma Hofstra; Iman Elfeddali; Margot Metz; Marjan Bakker; Jacobus J de Jong; Chijs van Nieuwenhuizen; Christina M van der Feltz-Cornelis Journal: BMC Psychiatry Date: 2019-11-19 Impact factor: 3.630