Not provided
Not provided
Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| LTF-2024C2-39670 | Other Grant/Funding Number | Patient-Centered Outcomes Research Institute |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Patient-Centered Outcomes Research Institute | OTHER |
Not provided
Not provided
Not provided
Not provided
"Gold-standard" medications for opioid use disorder (MOUD) treatment combines FDA-approved medications, primarily methadone and buprenorphine, with behavioral therapies to provide "whole-patient" treatment. Prior to the pandemic, methadone and buprenorphine were subject to greater federal regulations than medications for other substance use disorders, including medication for alcohol use disorder (MAUD), which created barriers to MOUD initiation and retention. These barriers were exacerbated by physical distancing and diminished clinic capacities during the COVID-19 pandemic. To prevent healthcare disruption and expand access to MOUD treatment during the public health emergency, federal and state authorities implemented several MOUD policy changes during the pandemic to reduce barriers to MOUD initiation and retention, which subsequently became permanent.
This study is an evaluation of the impacts of these policies on treatment use, retention, and patient outcomes pre- and post-MOUD policy implementation.
A mixed method study design will be implemented for this research study which has 3 specific aims.
Aim 1. Examine the long-term effects of MOUD policy changes on MOUD receipt, coverage, retention, and receipt of behavioral therapy, relative to commensurate measures among patients with AUD.
Aim 2. Examine the long-term effects of MOUD policy changes on outcomes for patients with OUD, including emergency department (ED) visits, inpatient hospitalization, substance use, relapse, and fatal and non-fatal overdoses, in contrast to pre-/post-period trends among our AUD comparison group.
Aim 3. Contextualize longitudinal results using qualitative methods to examine the impacts of MOUD policy changes from the perspectives of veteran patients with OUD, MOUD providers, and the Veteran's Health Administration Substance Use Disorder (VHA SUD) treatment leadership, and actors influencing the reach, effectiveness, adoption, implementation, and maintenance of MOUD policy changes.
For Aims 1 and 2, an observational cohort study will be conducted, using an interrupted time-series or difference-in-difference design to evaluate pre/post changes in treatment utilization and patient outcomes related to the nationwide MOUD policy changes introduced in 2020 expanding on access to MOUD treatment. The comparator for these analyses are patients with alcohol use disorder (AUD) for whom COVID-19 treatment disruptions applied but MOUD policies did not.
Data will be sourced from the Veteran's Health Administration Corporate Data Warehouse (CDW), including notes and Veteran's Administrations (VA) Mortality Data Repository and Community Care (CC) data. Aim 3 is a qualitative aim for which we will interview VA MOUD providers, VA substance use disorder treatment leadership, and VA patients with OUD.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| VA Patients with substance use disorder | Mutually exclusive groups of patients with OUD and AUD (and no co-occurring OUD), who will be matched 1:1 on age, gender, race, rural/urban residence, and state for the the pre (03/2016-02/2020) and post periods (03/2020-02/2024). |
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Change in MOUD/MAUD Receipt | Based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in MOUD/MAUD Coverage | Based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in MOUD/MAUD Retention | Based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in Behavioral Therapy Receipt | Based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in Behavioral Therapy Count | Based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Measure | Description | Time Frame |
|---|---|---|
| Change in any emergency department visits | Receipt of any vs none emergency department visits based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in the number of emergency department visits |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
A quasi-experimental and comparative interrupted time-series observational cohort study design will be used to compare trends across the pre- and post-MOUD policy change years, between mutually exclusive groups of patients with OUD and AUD (and no co-occurring OUD), who will be matched 1:1 on age, gender, race, rural/urban residence, and state for the pre (03/2016-02/2020) and post periods (03/2020-02/2024).
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Nicholas Livingston, PhD | Contact | 857-364-6612 | livingn@bu.edu |
| Name | Affiliation | Role |
|---|---|---|
| Nicholas Livingston, PhD | BUCA School of Medicine, Psychiatry and VA Medical Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| VA Medical Center | Recruiting | Boston | Massachusetts | 02130 | United States |
Not provided
| Label | URL |
|---|---|
| Related parent grant. | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D019966 | Substance-Related Disorders |
| D000437 | Alcoholism |
| D009293 | Opioid-Related Disorders |
| ID | Term |
|---|---|
| D064419 | Chemically-Induced Disorders |
| D001523 | Mental Disorders |
| D019973 | Alcohol-Related Disorders |
| D000079524 | Narcotic-Related Disorders |
Not provided
Not provided
Not provided
Not provided
Not provided
The count of emergency department visits based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) |
| 4 years pre/post policy change |
| Change in any inpatient admissions | Receipt of any vs none inpatient admissions based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in the number of inpatient admissions | The count of inpatient admissions based on Current Procedural Terminology (CPT) codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in any non-fatal Overdoses | Defined as the presence of > International Classification of Diseases (ICD)-10 non-fatal overdose codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in the count of non-fatal Overdoses | Based on non-fatal overdose codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in Fatal Overdoses | Based on fatal overdose codes abstracted from the Veterans Administration VA Corporate Data Warehouse (CDW) | 4 years pre/post policy change |
| Change in Substance Use | Documented in the electronic Health Record (EHR) and natural language processing large language models (NLP/LLM) | 4 years pre/post policy change |
| Change in Substance Use Relapse | Documented in the electronic Health Record (EHR) and NLP/LLM | 4 years pre/post policy change |