Evidence map›Paper›PMID 30181346›Full record

ArticleCMAJ open

Comparison of cardiac surgery mortality reports using administrative and clinical data sources: a prospective cohort study.

Cedric Manlhiot, Vivek Rao, Barry Rubin, Douglas S Lee

Abstract read
In one paragraph

Article in CMAJ open. 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

4 authors.

Cedric ManlhiotPeter Munk Cardiac Centre, University Health Network (Manlhiot, Rao, Rubin, Lee), Divisions of Cardiac Surgery (Manlhiot, Rao), Vascular Surgery (Rubin) and Cardiology (Lee), Institute of Health Policy, Management and Evaluation (Lee), and Institute for Clinical Evaluative Sciences (Lee), University of Toronto (Manlhiot, Rao, Rubin, Lee), Toronto, Ont.
Vivek RaoPeter Munk Cardiac Centre, University Health Network (Manlhiot, Rao, Rubin, Lee), Divisions of Cardiac Surgery (Manlhiot, Rao), Vascular Surgery (Rubin) and Cardiology (Lee), Institute of Health Policy, Management and Evaluation (Lee), and Institute for Clinical Evaluative Sciences (Lee), University of Toronto (Manlhiot, Rao, Rubin, Lee), Toronto, Ont.
Barry RubinPeter Munk Cardiac Centre, University Health Network (Manlhiot, Rao, Rubin, Lee), Divisions of Cardiac Surgery (Manlhiot, Rao), Vascular Surgery (Rubin) and Cardiology (Lee), Institute of Health Policy, Management and Evaluation (Lee), and Institute for Clinical Evaluative Sciences (Lee), University of Toronto (Manlhiot, Rao, Rubin, Lee), Toronto, Ont.
Douglas S LeePeter Munk Cardiac Centre, University Health Network (Manlhiot, Rao, Rubin, Lee), Divisions of Cardiac Surgery (Manlhiot, Rao), Vascular Surgery (Rubin) and Cardiology (Lee), Institute of Health Policy, Management and Evaluation (Lee), and Institute for Clinical Evaluative Sciences (Lee), University of Toronto (Manlhiot, Rao, Rubin, Lee), Toronto, Ont. dlee@ices.on.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOutcomes for coronary artery bypass surgery are of broadening interest, but the impact of data type on quality reporting has not been fully examined. We compared the performance of administrative and clinical data-based risk adjustment models at a tertiary-quaternary care hospital.

methodsWe used a prospective study design to test two risk adjustment models, one from administrative (Canadian Institute for Health Information [CIHI] Cardiac Care Quality Indicator) and one from clinical data (Society of Thoracic Surgeons), on cardiac surgical procedures performed between 2013 and 2016 (

resultsObserved mortality was 1.96%, which was the same as that predicted by the Society of Thoracic Surgeons model (1.96%), but significantly higher than that predicted by the CIHI model (1.03%). Despite both models having similar C statistics (0.756 CIHI; 0.758 Society of Thoracic Surgeons), the CIHI model showed significant underestimation of mortality among patients at higher risk. There was significant miscalibration of risk associated with 7 covariates: New York Heart Association class IV, congestive heart failure, ejection fraction less than 20%, atrial fibrillation, acute coronary insufficiency, cardiac compromise (shock, myocardial infarction < 24 h, intra-aortic balloon pump, cardiac resuscitation or preprocedure circulatory support) and creatinine concentration of 100 mg/dL or more. Together, these factors accounted for 84% of the difference in predicted mortality between the administrative and clinical models.

interpretationRisk prediction using administrative data underestimated risk of death, potentially inflating observed-to-predicted mortality ratios at hospitals with patients who are more ill. Caution is warranted when hospital reports of cardiac surgery outcomes are based on administrative data alone.

Identifiers

PMID30181346
PMCPMC6182118

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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.