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A comparison of Bayesian methods for profiling hospital performance.

Peter C Austin1

  • 1Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. peter.austin@ices.on.ca

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|April 18, 2002
PubMed
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Bayesian methods for classifying hospital performance show limited agreement. Researchers found inconsistencies between different Bayesian approaches, highlighting the need for better methods to identify outlier institutions effectively.

Area of Science:

  • Health Services Research
  • Biostatistics
  • Health Outcomes

Background:

  • Growing interest in Bayesian methods for institutional performance profiling.
  • Existing literature primarily compares frequentist methods for hospital outlier classification.
  • Need for robust Bayesian approaches to assess healthcare quality.

Purpose of the Study:

  • To compare four distinct Bayesian methods for classifying hospitals as outcomes outliers.
  • Utilized 30-day mortality rates for acute myocardial infarction (AMI) patients as a test case.
  • Evaluate the agreement and consistency among different Bayesian classification techniques.

Main Methods:

  • Method 1: Probability of exceeding a mortality rate threshold for an average patient.
  • Method 2: Ranking hospitals based on their mortality rate for an average patient.

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  • Method 3: Probability of a hospital's standardized mortality ratio (SMR) exceeding a threshold.
  • Method 4: Ranking hospitals based on their SMR.

    • Main Results:

    • Marginal agreement observed between the four Bayesian methods across most scenarios.
    • Good agreement (kappa 0.40–0.75) was found in only 4 out of 19 comparisons.
    • Ranking-based methods demonstrated relative insensitivity to inter-hospital differences.

    Conclusions:

    • Inconsistencies among Bayesian methods raise concerns regarding hospital performance classification.
    • Urgent research is needed to identify methods that best discriminate between institutions.
    • Further investigation required to determine which methods are most meaningful for decision-makers in healthcare.