Follow-up after residential treatment is considered best practice in supporting patients with opioid use disorder (OUD) in their recovery. Yet, little is known about rates of follow-up after discharge. The objective of this analysis was to measure rates of follow-up and use of medications for OUD (MOUD) after residential treatment among Medicaid enrollees in 10 states, and to understand the enrollee and episode characteristics that are associated with both outcomes.
Senior Policy Analyst Shamis Mohamoud was part of the Medicaid Outcomes Distributed Research Network (MODRN) team of authors of this article published in Drug and Alcohol Dependence.
The Hilltop Pre-DC Model™—which generates the rankings for the Severe Diabetes Complications (Pre-DC) scores—is designed to facilitate the active management of type 2 diabetes by estimating individuals’ risk of incurring inpatient admissions or emergency department (ED) visits for severe diabetes complications. The Pre-DC Model provides risk scores and reasons for risk for all attributed beneficiaries of Maryland Primary Care Program (MDPCP) practices every month to help care teams proactively identify high-risk individuals and allocate scarce care management resources.
In the US, Medicaid covers over 80 million Americans. Comparing access, quality, and costs across Medicaid programs can provide policymakers with much-needed information. As each Medicaid agency collects its member data, multiple barriers prevent sharing Medicaid data between states. To address this gap, the Medicaid Outcomes Distributed Research Network (MODRN) developed a research network of states to conduct rapid multi-state analyses without sharing individual-level data across states.
Senior Policy Analyst Shamis Mohamoud and Director of Medicaid Policy Studies David Idala were part of the Medicaid Outcomes Distributed Research Network (MODRN) team of authors of this article published in Medical Care.
The Community Pathways Waiver provides community-based services and supports to individuals with developmental or intellectual disabilities. The waiver includes both self-directed and traditional service delivery models. This infographic presents information for fiscal year (FY) 2016 through FY 2020.
The cash prices for emergency department facility fees are associated with various hospital and regional characteristics. Principal Data Scientist Morgan Henderson, PhD, and Policy Analyst Morgane Mouslim, ScM, DVM, conducted a study published in Health Affairs that uses newly released standard charge data, now available because of a 2021 hospital price transparency regulation mandating that almost all hospitals across the country disclose previously confidential data on the prices that they charge for the items and services they provide.
The Model Waiver provides services to individuals with medically complex needs and a chronic hospital or nursing facility level of care to be supported in their own homes or community-based settings. A unique aspect of the Model Waiver is that, due to the medically complex needs of its participants, non-waiver expenditures typically far exceed waiver expenditures. This infographic provides information for fiscal years (FYs) 2016 through 2020.
The Brain Injury (BI) Waiver provides services to individuals aged 22 or older with a brain injury diagnosis who require specialty hospital or nursing facility level of care to be supported in their own homes or community-based settings. Each year, the Maryland Department of Health strives to serve an additional ten participants through the BI Waiver. This infographic presents information for fiscal years (FYs) 2016 through 2020.
Autism Waiver services enable individuals who have Autism Spectrum Disorder and who meet an institutional level of care to be supported in their own homes or community-based settings. This infographic provides information about Maryland Medicaid participants who received services through the Autism Waiver in fiscal years (FYs) 2016 through 2020.
The objectives of this research are to determine a potential policy alternative to the current recommended budgeting methodology and to simulate the gains in administrative efficiency on actual Maryland Medicaid data from FY 2019. The broader hope is that this study can potentially serve as a guide to other states that are considering adoption of the Community First Choice program.
Senior Director of Research and Analytics/Chief Data Scientist Ian Stockwell, PhD, and Principal Data Scientist Morgan Henderson, PhD, co-authored this article published in the American Journal of Managed Care.