People with serious mental illness (SMI) (schizophrenia, schizoaffective disorder, bipolar disorder) die 25 years eariier than their peers, and cardiovascular (CV) disease is the leading cause of death. Primary care providers (PCPs) often are not aware of the significantly increased CV risk in patients with SMI and, even when CV risk factors are identified, appropriate clinical actions often are not provided. Electronic medical record (EMR)-based clinical decision support (CDS) delivered at a clinical encounter may be a powerful tool to help primary care providers (PCPs) identify and control CV risk factors in patients with SMI. This proposal will adapt a point-of-care EMR-based CDS system (CV Wizard) to help PCPs identify, provide appropriate care for, and control CV risk factors for patients with SMI. CV Wizard is designed to educate PCPs about the increased risk of CV disease and mortality in people with SMI, identify elevated CV risk factors in patients with SMI, prioritize these CV risks based on how much improvement in CV risk a patient would experience if the CV risk factor was adequately addressed, recommend specific medications and other interventions to decrease each elevated CV risk factor, and provide this information in an easy-tounderstand format for both patients with SMI and their PCPs. For those patients who are on the SMI medications most associated with weight gain, they will be able to work with a psychiatric care manager who, under the supervision of the patient's treating psychiatrist and with the consent of the patient, will switch the. SMI medication to one less associated with weight gain. The effectiveness of this intervention will be assessed in a clinic-randomized trial with 52 primary care clinics, 150 PCPs, and about 2,250 adults with SMI. We hypothesize that, relative to patients with SMI receiving care in control clinics, those in the CV Wizard clinics will have (a) reduced total modifiable CV risk;(b) better control of six individual modifiable CV risk factors, including blood pressure, lipids, tobacco use, aspirin use, ovenA/eight/obesity, and, for those with diabetes, glucose control, and (c) lower rates of prescriptions of SMI medications that are most associated with weight gain. In secondary analyses, we will also explore the impact of CV Wizard and care management on CV risk factor identification, treatment initiation and intensification;medication adherence; outpatient and inpatient utilization;risky prescribing events;and CV events. This study targets an important area of research that is a priority for the National Institute of Mental Health, - our health system partners, and our external stakeholder advisory board;leverages previous infrastructure investments in the Mental Health Research Network;and capitalizes on the expertise of our researchers. Developing an effective EMR-driven point-of-care CDS strategy that identifies and prioritizes available treatment options to better address uncontrolled CV risk factors in adults with SMI is a critical next step to improving the health and reducing the CV risk of this medically underserved population.

Public Health Relevance

People with serious mental illness (SM|;schizophrenia, schizoaffective disorder, or bipolar disorder) die an average of 25 years eariier than their peers, and cardiovascular (CV) disease is the leading cause of death. Primary care providers are not adequately aware of the significantly increased CV risk in patients with SMI, and, even when CV risk factors are identified, often do not take appropriate clinical actions. This project will test the ability of an electronic medical record-based clinical decision support system to help primary care providers identify, provide more appropriate care for, and control CV risk factors for patients with SMI.

Agency
National Institute of Health (NIH)
Type
Research Program--Cooperative Agreements (U19)
Project #
2U19MH092201-04
Application #
8721663
Study Section
Special Emphasis Panel (ZMH1)
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Group Health Cooperative
Department
Type
DUNS #
City
Seattle
State
WA
Country
United States
Zip Code
98101
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