Evidence map›Paper›PMID 27334868›Full record

ArticleBMJ quality & safety2017

Reviewing deaths in British and US hospitals: a study of two scales for assessing preventability.

Semira Manaseki-Holland, Richard J Lilford, Jonathan R B Bishop, Alan J Girling, Yen-Fu Chen, Peter J Chilton, Timothy P Hofer, UK Case Note Review Group

Open access · hybridAbstract readComparative Study
In one paragraph

Article in BMJ quality & safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 6% of its field
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Quality and patient safety research in pediatric neurosurgery: a review.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2023
    Review
  4. Article
  5. Review
  6. Article
  7. 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

8 authors at 3 institutions in 2 countries.

Semira Manaseki-HollandPublic Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK.
Richard J LilfordWarwick Medical School, University of Warwick, Coventry, UK.
Jonathan R B BishopPublic Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK.
Alan J GirlingPublic Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK.
Yen-Fu ChenWarwick Medical School, University of Warwick, Coventry, UK.
Peter J ChiltonWarwick Medical School, University of Warwick, Coventry, UK.ORCID 0000-0001-8809-9735
Timothy P HoferCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
UK Case Note Review Group
University of Birmingham · GBUniversity of Warwick · GBUniversity of Michigan · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Department of Health WMCLAHRC-2014-1NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

backgroundStandardised mortality ratios do not provide accurate measures of preventable mortality. This has generated interest in using case notes to assess the preventable component of mortality. But, different methods of measurement have not been compared. We compared the reliability of two scales for assessing preventability and the correspondence between them.

methodsMedical specialists reviewed case notes of patients who had died in hospital, using two instruments: a five-point Likert scale and a continuous (0-100) scale of preventability. To enhance generalisability, we used two different hospital datasets with different types of acute medical patients across different epochs, and in two jurisdictions (UK and USA). We investigated the reliability of measurement and correspondence of preventability estimates across the two scales. Ordinal mixed effects regression methods were used to analyse the Likert scale and to calibrate it against the continuous scale. We report the estimates of the probability a death could have been prevented, accounting for reviewer inconsistency.

resultsCorrespondence between the two scales was strong; the Likert categories explained most of the variation (76% UK, 73% USA) in the continuous scale. Measurement reliability was low, but similar across the two instruments in each dataset (intraclass correlation: 0.27, UK; 0.23, USA). Adjusting for the inconsistency of reviewer judgements reduced the proportion of cases with high preventability, such that the proportion of all deaths judged probably or definitely preventable on the balance of probability was less than 1%.

conclusionsThe correspondence is high between a Likert and a continuous scale, although the low reliability of both would suggest careful measurement design would be needed to use either scale. Few to no cases are above the threshold when using a balance of probability approach to determining a preventable death, and in any case, there is little evidence supporting anything more than an ordinal correspondence between these reviewer estimates of probability and the true probability. Thus, it would be more defensible to use them as an ordinal measure of the quality of care received by patients who died in the hospital.

Indexed as

Hospital MortalityAgedData CollectionFemaleHumansMaleOutcome and Process Assessment, Health CarePreventive MedicineRegression AnalysisReproducibility of ResultsRespiratory Tract DiseasesUnited KingdomUnited StatesAdverse events, epidemiology and detectionMedical error, measurement/epidemiologyMortality (standardized mortality ratios)Quality improvement methodologies

Identifiers

PMID27334868
PMCPMC5530333
OpenAlexW2463773267

What OpenQuestion holds

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LicenceCC BY
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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.