Harvard University, Cambridge, Massachusetts, USA.
Health Serv Res. 2024 Aug;59(4):e14293. doi: 10.1111/1475-6773.14293. Epub 2024 Feb 21.
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.
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.
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.
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.
了解长期服务和支持(LTSS)劳动力的趋势,并评估劳动力数据,作为将 LTSS 资源从机构向社区转移的进展衡量标准。
数据来源/研究环境:2008 年至 2022 年美国社区调查的劳动力数据。
构建了 LTSS 再平衡指标以及每 1000 名有 LTSS 需求的人在机构和社区中的劳动力供应指标。在展示研究期间的全国趋势后,使用州固定效应回归评估这些指标与现有 LTSS 使用措施之间的内在关系。劳动力供应指标与州医疗补助 LTSS 支出中用于社区的比例进行了比较,以评估它们在州际比较中的效用。然后使用劳动力数据展示每个州在研究期间在 LTSS 再平衡方面的进展。
数据收集/提取方法:从美国社区调查数据中得出了一个涵盖研究期间 336316 名 LTSS 工作者和 3015284 名有 LTSS 需求的人的样本。
从 2008 年到 2022 年,从事社区工作的 LTSS 劳动力比例从 44%上升到 58%。30 个州的增幅超过 10 个百分点。从 2008 年到 2013 年,社区劳动力规模急剧扩大,但此后一直停滞不前。相比之下,机构劳动力从 2015 年开始进入长期下降趋势,在 COVID-19 大流行期间加速下降。州固定效应回归表明,劳动力供应指标与老年人的 LTSS 使用指标密切相关,但与年轻残疾人士的指标无关。
劳动力数据可以作为衡量老年人 LTSS 使用变化的有效指标。这为研究人员和政策制定者提供了一种有用的替代行政管理索赔的方法,避免了因编码变更和向管理式医疗的转变对可比性的威胁。需要更多关于年轻 LTSS 消费者服务劳动力趋势的数据。