The COMPASS initiative: description of a nationwide collaborative approach to the care of patients with depression and diabetes and/or cardiovascular disease
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- 作者：Karen J. Coleman ; Ph.D.a ; Karen.J.Coleman@kp.org ; Sanne Magnan ; M.D. ; Ph.D.b ; Claire Neely ; M.D.b ; Leif Solberg ; M.D.c ; Arne Beck ; Ph.D.d ; Jim Trevis ; B.S.b ; Carla Heim ; B.S.b ; Mark Williams ; M.D.e ; David Katzelnick ; M.D.e ; Jü ; rgen Unü ; tzer ; M.D.f ; Betsy Pollock ; M.S.W.f ; g ; Erin Hafer ; MPHh ; Robert Ferguson ; B.S.i ; Steve Williams ; B.S.j
- 关键词：Collaborative care ; Integrated behavioral health ; Implementation ; Depression ; Cardiovascular disease
- 刊名：General Hospital Psychiatry
- 出版年：2017
- 出版时间：January-February 2017
- 年：2017
- 卷：44
- 期：Complete
- 页码：69-76
- 全文大小：764 K
- 卷排序：44
文摘
To describe a national effort to disseminate and implement an evidence-based collaborative care management model for patients with both depression and poorly controlled diabetes and/or cardiovascular disease across multiple, real-world diverse clinical practice sites.MethodsGoals for the initiative were as follows: (1) to improve depression symptoms in 40% of patients, (2) to improve diabetes and hypertension control rates by 20%, (3) to increase provider satisfaction by 20%, (4) to improve patient satisfaction with their care by 20% and (5) to demonstrate cost savings. A Care Management Tracking System was used for collecting clinical care information to create performance measures for quality improvement while also assessing the overall accomplishment of these goals.ResultsThe Care of Mental, Physical and Substance-use Syndromes (COMPASS) initiative spread an evidence-based collaborative care model among 18 medical groups and 172 clinics in eight states. We describe the initiative's evidence-base and methods for others to replicate our work.ConclusionsThe COMPASS initiative demonstrated that a diverse set of health care systems and other organizations can work together to rapidly implement an evidence-based care model for complex, hard-to-reach patients. We present this model as an example of how the time gap between research and practice can be reduced on a large scale.