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Inter-Unit Reliability for Quality Measure Testing.

Kevin He1, John D Kalbfleisch1, Yuan Yang1

  • 1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, United States.

Journal of Hospital Administration
|April 13, 2019
PubMed
Summary
This summary is machine-generated.

Determining the minimum number of dialysis facilities needed for quality measure testing is crucial. This study uses inter-unit reliability (IUR) and confidence intervals to ensure precise quality assessments for dialysis patient care.

Keywords:
IURMedical ProfilingPowerReliabilityUFR

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Area of Science:

  • Health Services Research
  • Biostatistics
  • Nephrology Quality Improvement

Background:

  • Facility-specific quality measures are essential for monitoring dialysis centers.
  • Preliminary evaluations often involve recruiting a subset of facilities to test and validate these measures.
  • Determining the minimum number of facilities is key to ensuring the precision of quality measures.

Purpose of the Study:

  • To propose a method for determining the minimum number of facilities required for quality measure development and validation.
  • To utilize inter-unit reliability (IUR) and its confidence intervals to assess the precision of quality measures.
  • To inform the recruitment process for facility-specific quality measure testing.

Main Methods:

  • Proposed a method based on inter-unit reliability (IUR) to determine the minimum number of facilities.
  • Calculated confidence intervals for the IUR, using interval width as a measure of precision.
  • Conducted a simulation study to evaluate the performance of estimated IUR with varying numbers of facilities.

Main Results:

  • The study demonstrates how to use IUR confidence intervals to assess measure precision.
  • Simulation results help in understanding the relationship between the number of facilities and measure reliability.
  • The developed method aids in establishing the minimum facility sample size for quality measure testing.

Conclusions:

  • The proposed method using IUR provides a framework for determining the optimal number of facilities for quality measure validation.
  • Accurate precision in quality measures is achievable by recruiting an adequate number of facilities.
  • This approach supports the development of robust quality measures, such as one for high ultrafiltration rates in End-Stage Renal Disease patients.