What is the best way to estimate hospital quality outcomes? A simulation approach.

Health Services Research
Andrew RyanJustin Dimick

Abstract

To test the accuracy of alternative estimators of hospital mortality quality using a Monte Carlo simulation experiment. Data are simulated to create an admission-level analytic dataset. The simulated data are validated by comparing distributional parameters (e.g., mean and standard deviation of 30-day mortality rate, hospital sample size) with the same parameters observed in Medicare data for acute myocardial infarction (AMI) inpatient admissions. We perform a Monte Carlo simulation experiment in which true quality is known to test the accuracy of the Observed-over-Expected estimator, the Risk Standardized Mortality Rate (RSMR), the Dimick and Staiger (DS) estimator, the Hierarchical Poisson estimator, and the Moving Average estimator using hospital 30-day mortality for AMI as the outcome. Estimator accuracy is evaluated for all hospitals and for small, medium, and large hospitals. Data are simulated. Significant and substantial variation is observed in the accuracy of the tested outcome estimators. The DS estimator is the most accurate for all hospitals and for small hospitals using both accuracy criteria (root mean squared error and proportion of hospitals correctly classified into quintiles). The mortality estimator currentl...Continue Reading

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Citations

Dec 15, 2011·Health Care Management Science·Theodore StefosPeter Almenoff
Jun 8, 2012·International Journal of Evidence-based Healthcare·Naleef Fareed
Jul 19, 2014·Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America·Michael E OhlEli N Perencevich
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Oct 8, 2013·American Heart Journal·Marco D HueschGregg C Fonarow
Jun 4, 2021·Health Services Research·Benjamin A Y CherAndrew M Ryan

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