ArticleJournal of the American Statistical Association2018
Modeling Heterogeneity in Healthcare Utilization Using Massive Medical Claims Data.
Article in Journal of the American Statistical Association, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Latent Class Proportional Hazards Regression with Heterogeneous Survival Data.Statistics and its interface · 2024Article
- Semiparametric Latent Class Analysis of Recurrent Event Data.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2022Article
- Quasi-linear Cox proportional hazards model with cross- LBMC medical research methodology · 2020Article
- Healthcare utilization after a first hospitalization for COPD: a new approach of State Sequence Analysis based on the '6W' multidimensional model of care trajectories.BMC health services research · 2020Observational
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
We introduce a modeling approach for characterizing heterogeneity in healthcare utilization using massive medical claims data. We first translate the medical claims observed for a large study population and across five years into individual-level discrete events of care called
Indexed as
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What OpenQuestion holds
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.