The Use of Fixed-and Random-Effects Models for Classifying Hospitals as Mortality Outliers: A Monte Carlo Assessment
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Fixed effects modelling for provider mortality outcomes: Analysis of the Australia and New Zealand Intensive Care Society (ANZICS) Adult Patient Data-baseDo patient-reported outcomes offer a more sensitive method for comparing the outcomes of consultants than mortality? A multilevel analysis of routine data.Surveillance of healthcare-acquired infections in Queensland, Australia: data and lessons from the first 5 years.Bayes rules for optimally using Bayesian hierarchical regression models in provider profiling to identify high-mortality hospitals.On shrinkage and model extrapolation in the evaluation of clinical center performanceClassification accuracy of claims-based methods for identifying providers failing to meet performance targets.Prediction of random effects in linear and generalized linear models under model misspecification.Clinical outcomes with alternative dosing strategies for piperacillin/tazobactam: a systematic review and meta-analysis.The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo StudyAssessing the accuracy of profiling methods for identifying top providers: performance of mental health care providers.Provider Differences in Use of Implanted Ports in Older Adults With Cancer.Analyzing center specific outcomes in hematopoietic cell transplantation.On the practice of ignoring center-patient interactions in evaluating hospital performance.Analytical Problems and Suggestions in the Analysis of Behavioral Economic Demand Curves.HIV quality report cards: impact of case-mix adjustment and statistical methods.Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models.Detecting and visualizing outliers in provider profiling via funnel plots and mixed effect models.Is risk-adjustor selection more important than statistical approach for provider profiling? Asthma as an example.Measurement of faculty anesthesiologists' quality of clinical supervision has greater reliability when controlling for the leniency of the rating anesthesia resident: a retrospective cohort study.Multidimensional performance assessment of public sector organisations using dominance criteria.Variability and predictability of large-volume red blood cell transfusion in cardiac surgery: a multicenter study.Should interventions to reduce variation in care quality target doctors or hospitals?Hospital-wide mortality as a quality metric: conceptual and methodological challenges.Outlier classification performance of risk adjustment methods when profiling multiple providers.Comparing clinical data with administrative data for producing acute myocardial infarction report cardsThe Impact of Unmeasured Clinical Variables on the Accuracy of Hospital Report Cards: A Monte Carlo StudyOptimal Statistical Decisions for Hospital Report Cards
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The Use of Fixed-and Random-Effects Models for Classifying Hospitals as Mortality Outliers: A Monte Carlo Assessment
description
article
@en
im November 2003 veröffentlichter wissenschaftlicher Artikel
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wetenschappelijk artikel
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наукова стаття, опублікована в листопаді 2003
@uk
name
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
@en
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
@nl
type
label
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
@en
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
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prefLabel
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
@en
The Use of Fixed-and Random-Ef ...... iers: A Monte Carlo Assessment
@nl
P2860
P356
P1476
The use of fixed- and random-e ...... iers: a Monte Carlo assessment
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P2093
David A Alter
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P304
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10.1177/0272989X03258443
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2003-11-01T00:00:00Z