Evidence map›Paper›PMID 26579336›Full record

ArticlePlastic and reconstructive surgery. Global open2015

A Review of the Use of Medicare Claims Data in Plastic Surgery Outcomes Research.

Elham Mahmoudi, Sandra V Kotsis, Kevin C Chung

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  3. Article
  4. Review
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.

Elham MahmoudiSection of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, Mich.; and Section of Plastic Surgery, Department of Surgery, The University of Michigan Health System, Ann Arbor, Mich.
Sandra V KotsisSection of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, Mich.; and Section of Plastic Surgery, Department of Surgery, The University of Michigan Health System, Ann Arbor, Mich.
Kevin C ChungSection of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, Mich.; and Section of Plastic Surgery, Department of Surgery, The University of Michigan Health System, Ann Arbor, Mich.

Funding

Evidence-Based Research in Hand SurgeryK24AR053120 · NIAMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHUNG, KEVIN C · 2008 to 2018
$1.6M
NIAMS NIH HHS K24 AR053120
6 · The paper itself

Abstract

With a growing national emphasis in data transparency and reporting of public health data, it is essential for researchers to know more about Medicare claims data, the largest and most reliable source of health-care utilization and expenditure for individuals older than 65 years in the United States. This article provides an overview of Medicare claims data for plastic surgery outcomes research. We highlight essential information on various files included in Medicare claims data, strengths and limitations of the data, and ways to expand the use of existing data for research purposes. As of now, Medicare data are limited in providing adequate information regarding severity of diagnosed conditions, health status of individuals, and health outcomes after certain procedures. However, the data contain all health-care utilization and expenditures for services that are covered by Medicare Parts A, B, and D (inpatient, outpatient, ambulatory-based and physician-based services, and prescription drugs). Additionally, Medicare claims data can be used for longitudinal analysis of variations in utilization and cost of health-care services at the patient level and provider level. Linking Medicare claims data with other national databases and utilizing the ICD-10 coding system would further expand the use of these datasets in health services research.

Identifiers

PMID26579336
PMCPMC4634167

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.