Tracking long‐term services and supports rebalancing through workforce data

• Published in: Health services research 2024-08, Vol.59 (4), p.e14293-n/a
• Main Author: Ne'eman, Ari
• Format: Article
• Language: English
• Subjects: Adults; aging; Community; Consumers; COVID-19; Data collection; disability; Extraction; long‐term services and supports; Managed care; Medicaid; Older people; Pandemics; People with disabilities; Policy making; Polls & surveys; Support services; Surveys; Tracking; Trends; Utilization; Workforce
• ISSN: 0017-9124; 1475-6773; 1475-6773
• DOI: 10.1111/1475-6773.14293

Objective To understand trends in the long‐term services and supports (LTSS) workforce and assess workforce data as a measure of progress in shifting LTSS resources from institutional to community‐based settings. Data Sources/Study Setting Workforce data from the American Community Survey from 2008 to 2022. Study Design Measures of LTSS rebalancing and institutional and community workforce supply per 1000 persons with LTSS needs were constructed. After showing national trends over the study period, state fixed effects regressions were used to evaluate the within‐state relationship of these measures with existing measures of LTSS utilization. Workforce supply measures were compared to the percentage of state Medicaid LTSS spending spent in the community to assess their utility for across state comparisons. Each state's progress in LTSS rebalancing over the study period was then shown using workforce data. Data Collection/Extraction Methods A sample of 336,316 LTSS workers and 3,015,284 people with LTSS needs over the study period was derived from American Community Survey data. Principal Findings From 2008 to 2022, the percentage of the LTSS workforce employed in the community rose from 44% to 58%. Thirty states saw more than a 10 percentage point increase. From 2008 to 2013, the size of the community workforce expanded dramatically but has since stagnated. In contrast, the institutional workforce entered a long‐term decline beginning in 2015 that accelerated during the COVID‐19 pandemic. State fixed effects regressions showed that measures of workforce supply have a strong relationship with LTSS utilization measures for older adults, but not for younger people with disabilities. Conclusions Workforce data can serve as an effective measure of changes in LTSS utilization for older adults. This offers researchers and policymakers a useful alternative to administrative claims, bypassing threats to comparability from coding changes and the shift to managed care. Additional data is needed on workforce trends in services for younger LTSS consumers.