Evidence map›Paper›PMID 39958809›Full record

ArticleHealth services & outcomes research methodology2025

Home- and community-based care in the new generation of Medicaid administrative data.

Sijiu Wang, Mingyu Qi, R Tamara Konetzka

Abstract read
In one paragraph

Article in Health services & outcomes research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
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  4. Observational
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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

3 authors.

Sijiu WangUniversity of Chicago, Chicago, USA.
Mingyu QiUniversity of Chicago, Chicago, USA.
R Tamara KonetzkaUniversity of Chicago, Chicago, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess the quality of Home and Community-Based Services (HCBS) data elements within the Transformed Medicaid Statistical Information System Analytical File (TAF) and to devise strategies for improving its research usability. Analyzing Medicaid TAF data from 2016 to 2018, we conducted a retrospective data quality analysis, focusing specifically on HCBS-related data elements. Through secondary data analysis, we identified significant challenges, including considerable missingness and inconsistencies that hamper the effective use of TAF for research purposes. Despite these issues, we developed three approaches that enabled us to identify 94% of known 1915(c) waiver claims as HCBS. Our study also revealed considerable cross-state variations in data quality, prompting specific recommendations for utilizing HCBS data within TAF. Ultimately, the study concludes that while challenges exist, applying our recommended strategies can yield data of acceptable quality for most states, particularly in identifying HCBS usage and classifying them into service categories. Given the growing importance of home-based care, there is a pressing need to prioritize improvements in TAF's HCBS data quality to better inform policy and practice. Supplementary Information: The online version contains supplementary material available at 10.1007/s10742-024-00325-6.

Indexed as

Administrative dataHCBSLong-term careMedicaid

Identifiers

PMID39958809
PMCPMC11821789

What OpenQuestion holds

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Registered trials

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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.