Precision Mental Health: Tools to Inform Treatment Selection in Depression
This project aims at developing a reusable pipeline to support initial tests of validation and feasibility of objective, easy-to-use, and widely accessible tools for predicting response to depression treatments. Although many treatments for depression are available, treatment-resistant depression (TRD) patients endure lengthy trial-and-error attempts on different regimes and increased risk for adverse outcomes, because clinicians lack decision support tools to select initial or subsequent TRD treatments. This reusable pipeline will be used to empirically design and evaluate a clinical decision support system (CDSS) containing optimal dynamic treatment regimes (DTRs) to personalize TRD care at a national scale. Additionally, we will use observational data to evaluate comparative effectiveness, and then we will conduct a randomized trial to clinically validate the tools.
Investigator: Rajendra Aldis
Point Person at the Lab: Danta Bien-Aimé
Team members and collaborators: Philip Wang, Alejandro Szmulewicz, Shan Siddiqi
Impact of cannabis legalization and commercialization on substance use and mental health outcomes in psychosis
This study uses quasi-experimental causal inference methods to study the relationship between cannabis commercialization and the prevalence and intensity of cannabis use among individuals with psychosis. It is the first study to investigate whether commercialization is associated with changes in symptom severity and outcomes in first episode psychosis, a particularly crucial intervention point affecting the long term trajectory of psychotic disorders. The knowledge gained from this research will be immediately applicable to develop clinical and public policy interventions to mitigate potential harms of cannabis commercialization, by rigorously evaluating “the effects of local, state, and national drug policies on public health.”
Investigator: Andrew Hyatt
Point Person at the Lab: Danta Bien-Aimé
Team members and collaborators: Julie Johnson, Evins, Anne Eden, Ongur, Dost, Michael Flores, Benjamin Cook
Impact of the New York State Medicaid Value-Based Payment Model on Opioid Use Treatment and Equity (NIDA R01)
Individuals living with Opioid Use Disorder (OUD) experience disproportionately high morbidity and premature mortality in the United States, with these burdens escalating among minoritized groups. As such, there is a need to identify state-level policy levers that can help ameliorate the devastating effects of OUD. To this end, our study assesses the overall impact of New York State’s Medicaid Value-Based Payment (VBP) policy on OUD-related outcomes and the policy’s racial and ethnic equity effects. We will also evaluate the moderating influence of individual- (e.g., comorbidities), area- (e.g., provider supply), and policy-level (e.g., variation in provider risk level within VBP arrangements) factors on OUD-related outcomes. Results from this study will fill an evidentiary gap regarding Medicaid VBP policies’ effects among vulnerable and high-need beneficiaries, providing valuable information to states implementing or considering VBP adoption. This research is being conducted in partnership with the New York State Department of Health.
Investigator: Michael Flores
Point Person at the Lab: Sarah Mazen
Team members and collaborators: Benjamin Cook, Paloma Luisi, Marcela Horvitz-Lennon, Zev Schuman-Olivier, Maureen Stewart, Sharon-Lise Normand, Gareth Parry, Sarah Mazen
Effects of pandemic-era social policy changes on healthcare outcomes and disparities (NIHMD R01)
As a part of a NINR R01 and NIMHD R01 (PI Rajan Sonik), the Health Equity Research Lab will be collaborating with researchers from Brandeis University on two studies to examine the impact of changing social policies during the COVID-19 pandemic on healthcare outcomes and disparities by race, ethnicity, and disability status.
The NIMHD R01 titled, “Growth and decline in SNAP generosity: outcome and equity implications” will utilize 1) US Medicaid data and novel, linked, Massachusetts-wide 2011-2025 healthcare claims, public health, and SNAP administrative data and 2) A natural experiment created by the Families First Coronavirus Response Act (FFCRA) to examine the effects of monthly SNAP benefit enhancements on healthcare outcomes and disparities.
The NINR R01 titled, “Unwinding pandemic-era social programs: Effects on healthcare outcomes and disparities” will study the effects of reductions in social welfare generosity after the initial period of the pandemic on healthcare outcomes and disparities by race, ethnicity, and disability status.
Investigators: Rajan Sonik, Benjamin Lê Cook
Point Person at the Lab: Danta Bien-Aime
Team Members: Kimberley Nicholson
EFFECTIVENESS AND IMPLEMENTATION OF A CLINICAL DECISION SUPPORT SYSTEM TO PREVENT SUICIDAL BEHAVIOR (nimh r01)
The months following discharge from a psychiatric hospitalization are a high risk time for suicide attempts. Machine learning and predictive algorithms could be advantageous in improving the ability to identify those at risk for suicide after discharge. The goal of this study is to test the effects of providing emergency department clinicians with enhanced information about their patients’ risk of a suicide attempt in the 6-months after leaving the emergency department through a prototype app that generates predicted probabilities of suicide attempt. As part of Massachusetts General Brigham’s Center for Suicide Research and Prevention P50, CHA’s Health Equity Research lab will be implementing the pilot study at CHA Cambridge Hospital Emergency Department.
Investigators: Nicholas Carson, Rajendra Aldis, Will Schleyer
Point Person at the Lab: Peyton Williams
Team members and collaborators: Taylor Witkowski, Jessica Stubbing
IMPROVING SUICIDE RISK PREDICTION IN RACIAL, ETHNIC, AND LINGUISTIC MINORITY YOUTH (nimh r34)
As part of Massachusetts General Brigham’s Center for Suicide and Prevention P50, CHA’s Health Equity Research lab will be working with MGH to implement a predictive suicide algorithm to predict suicide risk for racially, ethnically, and linguistically minority youth within 6 months of discharge at CHA Cambridge Hospital Emergency Department. We hope to evaluate the added predictive value of social determinants of health and computerized adaptive testing collected as part of standard care at CHA.
Investigator: Nicholas Carson
Point Person at the Lab: Peyton Williams
Team members and collaborators: Taylor Witkowski
Improving Mental Health Treatment for Individuals in Crisis Interacting with the Criminal Justice System (NIMH R34)
As part of Michigan State University’s P50 for the National Center for Health and Justice Integration for Suicide Prevention (NCHATS), CHA’s Health Equity Research Lab will be working with the Cambridge Police Department (CPD) to assess the effectiveness of the Family and Social Justice Section (FSJS) intervention, a police-based multi-system intervention to train patrol officers in mental health first aid and trauma-informed policing, link community and healthcare services, and follow-up on mental health-related calls with police department-based case management by a team of specialty mental health resource officers and mental health clinicians. The FSJS intervention will be compared to usual treatment in neighboring towns and an enhanced FSJS intervention that includes a CHA-based family navigator who works closely to connect individuals to services when they are brought into the emergency department by CPD officers. These assessments will take place at both CHA and Mt. Auburn Hospital.
Investigators: Benjamin Lê Cook, James Barrett
Point Person at the Lab: Taylor Witkowski
Team members: Christopher Fischer, Katelyn Kelly, Will Schleyer, Valeria Chambers, Dharma Cortes, Michael Flores, Peyton Williams
Check out our past projects here!