Data

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

Monash University
Ahmad Reza Pourghaderi (Aggregated by) Arul Earnest (Aggregated by) Jessy Hansen (Aggregated by) Susannah Ahern (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26180/28665671.v1&rft.title=Guidelines for benchmarking and outlier detection in clinical quality registries - simulation and model build code&rft.identifier=https://doi.org/10.26180/28665671.v1&rft.publisher=Monash University&rft.description=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:guidelines_data_preparation.do 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. sim_extra_sum.dtaSummary performance dataset containing the average accuracy of outlier detection methods for simulations of clinical quality registry data of varied data parameters.guidelines_model_build.RR code for developing generalised linear models for predicting the accuracy of outlier detection based on registry data parameters.&rft.creator=Ahmad Reza Pourghaderi&rft.creator=Arul Earnest&rft.creator=Jessy Hansen&rft.creator=Susannah Ahern&rft.date=2025&rft_rights=CC-BY-4.0&rft_subject=Clinical registries&rft_subject=Simulation study&rft_subject=Guidelines for methods&rft_subject=Outlier detection&rft_subject=Epidemiological methods&rft_subject=Biostatistics&rft.type=dataset&rft.language=English Access the data
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Full description

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:

  • guidelines_data_preparation.do
    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.
  • sim_extra_sum.dta
    Summary performance dataset containing the average accuracy of outlier detection methods for simulations of clinical quality registry data of varied data parameters.
  • guidelines_model_build.R
    R code for developing generalised linear models for predicting the accuracy of outlier detection based on registry data parameters.


Issued: 2025-03-26

Created: 2025-03-26

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Subjects
Biostatistics | Clinical registries | Epidemiological methods | Guidelines for methods | Outlier detection | Simulation study |

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ACN 633 798 857