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Ranking hospital performance based on individual indicators: can we increase reliability by creating composite

Peter C Austin1, Iris E Ceyisakar2, Ewout W Steyerberg2,3

  • 1ICES, G106, 2075 Bayview Avenue, Toronto, Ontario, Canada. peter.austin@ices.on.ca.

BMC Medical Research Methodology
|June 28, 2019
PubMed
Summary
This summary is machine-generated.

Combining multiple healthcare quality indicators can improve hospital rankability, but only if the indicators are highly correlated. Otherwise, combining them may reduce accuracy, especially if indicators measure different quality aspects.

Keywords:
Hospital performancePerformance indicatorsProvider profilingRankabilityReliability

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Area of Science:

  • Health Services Research
  • Quality Improvement
  • Biostatistics

Background:

  • Healthcare report cards increasingly use provider-specific performance indicators.
  • Hospital performance data is often presented in 'league tables' for comparison.
  • Many individual indicators have low to moderate rankability, limiting accurate hospital comparisons.

Purpose of the Study:

  • To define conditions for improving hospital rankability by combining multiple binary indicators.
  • To assess the rankability of composite indicators formed from pooling less rankable binary indicators.

Main Methods:

  • Utilized Monte Carlo simulations to evaluate the rankability of composite ordinal indicators.
  • Examined scenarios with varying prevalences (0.05, 0.10, 0.25) of three binary indicators.
  • Assessed the impact of within-hospital correlation (ranging from -0.25 to 0.90) on rankability.

Main Results:

  • High rankability of a composite indicator was achieved when component binary indicators were strongly correlated (≥0.5).
  • When correlations were weak (<0.5), composite rankability often decreased compared to individual indicators.
  • Composite rankability was significantly influenced by the prevalence of the most common indicator and the degree of within-hospital correlation.

Conclusions:

  • Pooling highly correlated binary indicators can yield a composite indicator with enhanced rankability.
  • Combining weakly correlated or independent indicators may result in lower rankability than constituent components.
  • Combine binary indicators to improve rankability only if they represent the same underlying quality of care concept.