Background and Summary
The Ohio Department of Mental Health and Addiction Services (MHAS) engaged the InnovateOhio Platform (IOP) Data and Analytics team to assess the behavioral landscape in Ohio. Different factors that were assessed include geography, practitioner types, and patient demographics, to identify where variants in workforce supply and demand exist. The ultimate goal of this project was to identify strategies to reduce the gaps in behavioral health, in order to best serve Ohioans most in need of these services.
Data Used in the Analysis
To begin analysis, the IOP team gathered data from 11 different data sources. Ohio-specific claims data from Medicaid and MHAS was used to drive demand analysis, and demand was segmented across counties, practitioners, ages, facilities, and service types. State-specific licensing, education, and demographic data enabled detailed practitioner supply analysis. With this analysis, the team was able to forecast demand and supply for behavioral health services across the state for each county and practitioner.
This analysis had major impact across the state because the team was able to determine behavioral health demand at the county and board level. Detailed demand breakdown was used to identify specific behavioral health needs and direct comparison of practitioner demand and workforce supply across each county. With this data, key areas were identified where variance is growing or shrinking, giving MHAS insight into where to focus their push for workforce recruitment.
Some key observations gleaned from this project include:
- Demand for behavioral health services increased 353% from CY2013-2019, with an average 29% increase per year
- Mental Health services account for 52% of the total behavioral health demand in Ohio.
- Demand for substance use disorder services increased sharply in CY2018, correlating to a decrease in opioid overdose deaths and the introduction of new SUD services
- Demand correlates well with population, however there are regions, such as the southeastern Ohio counties, that show above normal demand
- Demand for behavioral health services provided by nurse practitioners and physicians has increased since the behavioral health redesign
- Community behavioral health centers are the most common facility type for services
- In adults, two-thirds of the demand is for SUD Services
With this information, it became clear that there was a need to focus on building up a strong workforce equipped to handle the mental health and addiction needs of Ohioans. In regard to Ohio’s mental health and addiction services workforce, the team learned:
- The behavioral health workforce increased significantly from CY2013-2019 with a 174% increase over this time period, averaging 36% growth per year
- The supply of Chemical Dependency Counselors is increasing most rapidly at a yearly average of 61%
- As of CY2019 Social workers make up the largest portion of licensed professionals at 31%, just 7% of the population is made up of physicians
- Behavioral health workforce is generally concentrated in densely populated counties, with less populated counties displaying lower numbers of practitioners per 10,000 residents
- Nursing degrees are increasing most rapidly year over year at an average of 54%, whereas physician related degrees increased 12%
- Nearly half of the behavioral health workforce, 44%, is between 25 and 34 years of age
- Only Cuyahoga, Franklin, and Allen counties display a surplus of practitioners, while all others show a workforce deficit
In summary, using datasets unique to Ohio, a detailed analysis of the demand for behavioral health across Ohio was constructed. Demand segmented across counties, diagnoses, age groups, practitioner types, services, and facilities. A granular view of the behavioral health workforce, through partnering with state agencies, allowed creation of detailed analysis of the behavioral health workforce supply across Ohio, assessing the workforce across counties and practitioner types. Through identifying variance between demand and supply, comparison of these datasets identifies the varying levels of met/unmet demand throughout the state and identifies how this variance is spread across practitioner types. As of CY2019 overall unmet demand is between 41-46%. These results will project the future of the behavioral health landscape in Ohio, by forecasting the demand and workforce supply for behavioral health services into the future and identifying emerging trends and potential changes in the variance between supply and demand.