Evidence map›Paper›PMID 27140395›Full record

ArticleHealth services research2017

Guidelines for Measuring Disease Episodes: An Analysis of the Effects on the Components of Expenditure Growth.

Abe Dunn, Eli Liebman, Lindsey Rittmueller, Adam Hale Shapiro

Abstract read
In one paragraph

Article in Health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Abe DunnBureau of Economic Analysis, Washington, DC.
Eli LiebmanDepartment of Economics, Duke University, Durham, NC.
Lindsey RittmuellerBureau of Economic Analysis, Washington, DC.
Adam Hale ShapiroFederal Reserve Bank of San Francisco, San Francisco, CA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo provide guidelines to researchers measuring health expenditures by disease and compare these methodologies' implied inflation estimates. DATA SOURCE: A convenience sample of commercially insured individuals over the 2003 to 2007 period from Truven Health. Population weights are applied, based on age, sex, and region, to make the sample of over 4 million enrollees representative of the entire commercially insured population. STUDY

designDifferent methods are used to allocate medical-care expenditures to distinct condition categories. We compare the estimates of disease-price inflation by method. PRINCIPAL

findingsAcross a variety of methods, the compound annual growth rate stays within the range 3.1 to 3.9 percentage points. Disease-specific inflation measures are more sensitive to the selected methodology.

conclusionThe selected allocation method impacts aggregate inflation rates, but considering the variety of methods applied, the differences appear small. Future research is necessary to better understand these differences in other population samples and to connect disease expenditures to measures of quality.

Indexed as

Delivery of Health CareDiseaseEpidemiologyGuidelines as TopicHealth ExpendituresHumansResource Allocationdisease episodesHealth care expendituresmeasuring expenditures of treatment

Identifiers

PMID27140395
PMCPMC5346493

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.