Evidence map›Paper›PMID 26770710›Full record

ArticleSAGE open medicine2014

Who is watching the watchmen: Is quality reporting ever harmful?

R Scott Braithwaite, Arthur Caplan

Abstract read
In one paragraph

Article in SAGE open medicine, 2014. 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. Review
  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

2 authors.

R Scott BraithwaiteDivision of Comparative Effectiveness and Decision Science, Department of Population Health, School of Medicine, New York University, New York, NY, USA.
Arthur CaplanDivision of Bioethics, Department of Population Health, School of Medicine, New York University, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuality reporting is increasingly used as a tool to encourage health systems, hospitals, and their practitioners to deliver the greatest health benefit. However, quality reporting systems may have unintended negative consequences, such as inadvertently encouraging "cherry-picking" by inadequately adjusting for patients who are challenging to take care of, or underpowering to reliably detect meaningful differences in care. There have been no reports seeking to identify a minimum level of accuracy that ought to be viewed as a prerequisite for quality reporting.

methodUsing a decision analytic model, we seek to delineate minimal standards for quality measures to meet, using the simplest assumptions to illustrate what those standards may be.

resultsWe find that even under assumptions regarding optimal performance of the quality reporting system (sensitivity and specificity of 1), we can identify a minimal level of accuracy required for the quality reporting system to "do no harm": the increase in health-related quality of life from a higher rather than lower quality practitioner must be greater than the number of practitioners per patient divided by the proportion of patients willing to switch from a lower to a higher quality provider.

conclusionQuality measurement systems that have not been demonstrated to improve health outcomes should be held to a specific standard of measurement accuracy.

Indexed as

decision analysispay for performancephysician reportingqualityQuality reporting

Identifiers

PMID26770710
PMCPMC4607192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.