ArticleHealth services research2019
Comparison group selection in the presence of rolling entry for health services research: Rolling entry matching.
Article in Health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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.
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Who cites it
10 citing papers in PubMed.
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- Improving the evaluation of an integrated healthcare system using entropy balancing: Population health improvements in Gesundes Kinzigtal.SSM - population health · 2023Article
- Protection against Omicron from Vaccination and Previous Infection in a Prison System.The New England journal of medicine · 2022Article
- Effectiveness of BBIBP-CorV vaccine against severe outcomes of COVID-19 in Abu Dhabi, United Arab Emirates.Nature communications · 2022Article
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- A Propensity-Matched Cohort Study of Tocilizumab in Patients With Coronavirus Disease 2019.Critical care explorations · 2020Article
- Matching with time-dependent treatments: A review and look forward.Statistics in medicine · 2020Review
- Comparison group selection in the presence of rolling entry for health services research: Rolling entry matching.Health services research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveTo demonstrate rolling entry matching (REM), a new statistical method, for comparison group selection in the context of staggered nonuniform participant entry in nonrandomized interventions. STUDY
settingFour Health Care Innovation Award (HCIA) interventions between 2012 and 2016. STUDY
designCenter for Medicare and Medicaid Innovation HCIA participants entering these interventions over time were matched with nonparticipants who exhibited a similar pattern of health care use and expenditures during each participant's baseline period. DATA EXTRACTION
methodsMedicare fee-for-service claims data were used to identify nonparticipating, fee-for-service beneficiaries as a potential comparison group and conduct REM. PRINCIPAL
findingsRolling entry matching achieved conventionally-accepted levels of balance on observed characteristics between participants and nonparticipants. The method overcame difficulties associated with a small number of intervention entrants.
conclusionsIn nonrandomized interventions, valid inference regarding intervention effects relies on the suitability of the comparison group to act as the counterfactual case for the intervention group. When participants enter over time, comparison group selection is complicated. Rolling entry matching is a possible solution for comparison group selection in rolling entry interventions that is particularly useful with small sample sizes and merits further investigation in a variety of contexts.
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Registered trials
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.