Harbor Health Integrated Care Evaluation
Similar to the Behavioral Health Home Evaluation, at Harbor Health Services (http://www.hhsi.us/) The Health Equity Lab at CHA will conduct a 3-month evaluation of the Primary Care Behavioral Health Integration Model at Harbor Health Service, Inc. Harbor Health received funding from HRSA to implement an integrated primary care/behavioral health care model in four of their community centers located in Massachusetts: Neponset Health Center, Geiger Gibson Community Health Center, Harbor Community Health Center-Plymouth, and Harbor Community Health Center-Hyannis. Drs. Benjamin Cook and Andrea Ault-Brutus will co-lead a mixed methods evaluation of their integrated model. Dr. Cook will lead the quantitative evaluation which will consist of analyzing EHR data and previous reports to assess process measures and outcomes related to BHI. Dr. Ault-Brutus will lead the qualitative evaluation which will consist of conducting semi-structured interviews with key stakeholder groups (behavioral health and primary care providers; care coordinators; administrators; patients) to assess the feasibility and acceptability of integrating care.
CMS Disparities (ACOs) by Race/Ethnicity, Gender, and Gender Identity Status
The Health Equity Research Lab was awarded one of the 5 Office of Minority Health seats with the CMS Virtual Research Data Center. This project will study the differences in ACO participation by race/ethnicity, gender (including gender minority status), and mental health status of beneficiaries. This project will also study disparities within ACO's by dual eligibility status, race/ethnicity and gender/gender identity in access, utilization, and quality of mental health services, and also compare access, utilization, and quality of disparities for beneficiaries treated within ACOs to those not treated in ACO's by race/ethnicity and gender.
Cambridge Health Alliance (CHA) Behavioral Health Home Evaluation
This pilot Behavioral Health Home Program (BHHP) at CHA provides “reverse integration” of primary care services within Central Street Health Center, an outpatient specialty behavioral health clinic at Cambridge Health Alliance (CHA), with a multidisciplinary team, enhanced training and care coordination, increased screening and monitoring of co-morbid medical conditions, IT tools for population management, and expanded health promotion activities.
Past attempts at eliciting patient preferences have not taken into account the prior negative experiences of the patient and his or her family and community. This may lead minority patients to prefer different treatment options or no treatment at all. Eliciting preferences without sufficient context may result in treatment plans centered on incomplete preferences information. A mismatch between treatment and patient preferences worsens health outcomes via lower patient engagement, poorer adherence, and higher attrition. In this funded grant, we will developing a new method that more accurately elicits patient preferences and to apply this method for depression and type II diabetes.
To learn more, visit the PCORI page
Collaborating partners: The Transformation Center
The Cambridge Health Alliance Primary Care Practice Improvement
Health Equity Research Lab
1035 Cambridge Street, 2nd Floor
Cambridge, MA 02141
Current Evaluations and Major Projects
Medicare Policy Effects on Mental Health Care Disparities
The Medicare Policy Effects on Mental Health Care Disparities project will assess the impact of recent Medicare policy changes on racial/ethnic disparities in mental health (MH) care. Medicare covers primarily elderly and non-elderly disabled Americans with mental illness and two recent policy changes have the potential to reduce wide disparities in access to mental health care. The Affordable Care Act (ACA) temporarily increased payments in 2013-2014 by up to 25% for primary care providers of Full Subsidy dual-eligible beneficiaries. Additionally, the Medicare Improvements for Patients and Providers Act (MIPPA) gradually increased mental health providers' payments by up to 37% for Full Subsidy beneficiaries, and reduced beneficiary coinsurance for MHP visits to 20% for other beneficiaries. We will use the natural experiments created by the ACA and MIPPA to assess the effects of these policy changes on racial/ethnic disparities in MH.
RISE Literature Review
The goal of the project is to survey the current landscape of literature in the intersection between mental health services and juvenile justice, and then consolidate our findings into actionable recommendations to the RISE initiative for future funding.
About RISE RISE at the University of Pennsylvania
Safety Net Collaborative Evaluation
The Health Equity Research Lab is involved in the evaluation of Safety Net, a multiagency integrated model of preventive services for at-risk youth involving mental health providers, police officers, schools, and the department of youth and families.
To learn more, visit the Cambridge Safety Net Page
Comparative Effectiveness Research and Racial/Ethnic Health Care Equity (AHRQ R01)
We examine whether specific information in FDA warnings influenced disparity trends in psychotropic drug use and mental health care and to identify how provider characteristics and HMO enrollment act as mechanisms that underlie the differential diffusion of CER via health risk warnings. Identifying the influence of FDA risk warnings on trends in psychotropic drug use and related health care provides a platform to understand how CER will influence disparities and will help us to assess whether information regarding the risks and benefits of medications are being equitably disseminated. Our examination of how an increased reliance on CER will likely influence disparities in treatment after health care reform will provide policymakers with actionable information that might avert the negative equity consequences of incorporating CER into routine practice.
Natural Language Processing Projects
Using electronic health records (EHR) to evaluate hospital interventions and predict re-hospitalizations and adverse health events from unstructured clinician records and structured EHR fields.