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Guidelines for benchmarking and outlier detection in clinical quality registries - simulation and model build code

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DataCite Commons2025-03-26 更新2025-04-16 收录
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https://bridges.monash.edu/articles/dataset/Guidelines_for_benchmarking_and_outlier_detection_in_clinical_quality_registries_-_simulation_and_model_build_code/28665671/1
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资源简介:
Contains the summary dataset, simulation Stata code and model build R code for the study titled "Benchmarking methods for detection of underperforming healthcare providers in clinical quality registries – implementation guidelines".Contains:<b>guidelines_data_preparation.do </b><br>Stata code for running the simulations (using the user written hiersim command available at https://doi.org/10.26180/24480889) and preparing the summary performance dataset. <b>sim_extra_sum.dta</b><br>Summary performance dataset containing the average accuracy of outlier detection methods for simulations of clinical quality registry data of varied data parameters.<b>guidelines_model_build.R</b><br>R code for developing generalised linear models for predicting the accuracy of outlier detection based on registry data parameters.<br>
提供机构:
Monash University
创建时间:
2025-03-26
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