Evidence map›Paper›PMID 38384002›Full record

ArticleHealth services research2024

Tracking long-term services and supports rebalancing through workforce data.

Ari Ne'eman

Open access · bronzeAbstract read
In one paragraph

Article in Health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
10.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Ari Ne'emanHarvard University, Cambridge, Massachusetts, USA.ORCID 0000-0001-7687-1265
Harvard University Press · US

Funding

Health Policy Training Program: Promoting Outcomes, Quality, Equity and Diffusion of AdvancesT32MH019733 · NIMH · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Benjamin Le Cook, Haiden A Huskamp · 1993 to 2026
$7.0M
ACL HHS 90RTCP0004NIMH NIH HHS T32 MH019733NIMH NIH HHS T32MH019733
6 · The paper itself

Abstract

objectiveTo 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

settingWorkforce data from the American Community Survey from 2008 to 2022. STUDY

designMeasures 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

methodsA 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

findingsFrom 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.

conclusionsWorkforce 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.

Indexed as

Long-Term CareMedicaidAdultAgedCOVID-19FemaleHealth WorkforceHumansMaleMiddle AgedUnited Statesagingdisabilitylong‐term services and supportsworkforce

Identifiers

PMID38384002
PMCPMC11250136
OpenAlexW4392055695

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.