Evidence map›Paper›PMID 25954419›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014

Adding flexible temporal constraints to identify chronic comorbid conditions in ambulatory claims data.

Walton Sumner, Dustin L Stwalley, Phillip V Asaro, Michael D Hagen, Margaret A Olsen

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

5 authors.

Walton SumnerWashington University School of Medicine, St. Louis, MO.
Dustin L StwalleyWashington University School of Medicine, St. Louis, MO.
Phillip V AsaroWashington University School of Medicine, St. Louis, MO.
Michael D HagenAmerican Board of Family Medicine, Lexington, KY.
Margaret A OlsenWashington University School of Medicine, St. Louis, MO.

Funding

Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
WASHINGTON UNIVERSITY COMPARATIVE EFFECTIVENESS ADMINISTRATIVE DATA REPOSITORYR24HS019455 · AHRQ · WASHINGTON UNIVERSITY · PI FRASER, VICTORIA J. · 2010 to 2010
$969k
AHRQ HHS R24 HS019455AHRQ HHS R24 HS19455NCATS NIH HHS UL1 TR000448
6 · The paper itself

Abstract

Chronic comorbid conditions are important predictors of primary care outcomes, provide context for clinical decisions, and are potential complications of diseases and treatments. Comorbidity indices and multimorbidity categorization strategies based on administrative claims data enumerate diagnostic codes in easily modifiable lists, but usually have inflexible temporal requirements, such as requiring two claims greater than 30 days apart, or three claims in three quarters. Table structures and claims data search algorithms were developed to support flexible temporal constraints. Tables of disease categories allow subgroups with different numbers of events, different times between similar claims, variable periods of interest, and specified diagnostic code substitutability. The strategy was tested on five years of private insurance claims from 2.2 million working age adults. The contrast between rarely recorded, high prevalence diagnoses (smoking and obesity) and frequently recorded but not necessarily chronic diagnoses (musculoskeletal complaints) demonstrated the advantage of flexible temporal criteria.

Indexed as

Ambulatory CareComorbidityInsurance Claim ReviewAdultAlgorithmsChronic DiseaseFamily PracticeHumansPrevalence

Identifiers

PMID25954419
PMCPMC4420007

What OpenQuestion holds

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Read underepoch 390

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.