The goal of this proposal is to test whether a theory-informed multicomponent intervention involving an electronic shared decision making (eSDM) tool (iHeart Trial) can increase the uptake of depression treatment following acute coronary syndromes (post-ACS). Depression is three times more common in depressed post- ACS patients than the general population and doubles the risk of recurrent cardiac events and mortality. Depression treatment can improve debilitating depressive symptoms and quality of life. Multiple scientific groups recommend screening for depression and treating when indicated in post-ACS patients. Despite decades of observational data and expert guidelines, only 30% of depressed post-ACS patients receive treatment, far lower than the treatment rates seen in the general depression population. This proposal is a culmination of years of work with multiple study sites, innumerable patients, IT personnel and experts in depression and cardiovascular disease. We reviewed systematically all interventions targeting depression treatment engagement in primary care settings. We conducted a nationwide survey of 352 depressed post-ACS patients. We ran behavioral and primary care provider focus groups to ascertain barriers to depression treatment in primary care in 8 healthcare systems that had implemented depression screening and treatment. We learned that key barriers to depression treatment are (1) suboptimal rates of depression recognition and referral by providers and (2) dismissal of the importance of depressive symptoms and lack of ability to choose type of depression treatment by patients. Using these formative data, we applied a theory- informed process of engaging stakeholders to select an acceptable, feasible intervention and determined that eSDM would target the greatest number of barriers to implementing patient preferred depression treatment in post-ACS patients. We subsequently developed and alpha tested an iPad delivered, video-assisted, interactive eSDM tool that aims to reduce barriers to depression treatment in cardiac patients. We hypothesize that this state-of-the-art, theory-driven eSDM tool that automates the SDM process, activates providers, staff, and patients and interfaces with the electronic health record will improve implementation of depression guidelines in post-ACS patients with persistently elevated depressive symptoms. We propose to conduct a stepped wedge trial across 8 primary care clinics to assess the effectiveness of our eSDM tool on depressive symptoms (primary outcome) and depression treatment uptake (Aim 1) and implementation processes such as depression screening and treatment referral (Aim 2). Key outcomes will be rigorously assessed amongst 368 depressed post-ACS patients. Our study has the potential to produce a theory-informed, scalable eSDM tool that improves the implementation of post-ACS depression guidelines.

Public Health Relevance

Even though multiple expert guidelines recommend depression screening and treatment following acute coronary syndrome (ACS), only 30% of depressed post-ACS patients receive depression treatment. Key barriers include suboptimal depression recognition/referral rates by providers and low engagement in treatment by patients. We propose a stepped wedge trial across 8 primary care clinics to test the effectiveness of a scalable, theory-driven electronic shared decision making tool that is designed to increase depression recognition and treatment engagement, and ultimately, improve depressive symptoms in post-ACS patients.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL141609-01
Application #
9499524
Study Section
Dissemination and Implementation Research in Health Study Section (DIRH)
Program Officer
Campo, Rebecca A
Project Start
2018-04-01
Project End
2023-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032