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Related Experiment Videos

Procedure to normalize data for benchmarking.

Robert L Chatburn1, Richard M Ford

  • 1Respiratory Care Department, University Hospitals of Cleveland, Cleveland, Ohio 44106, USA. robert.chatburn@uhhs.com

Respiratory Care
|January 31, 2006
PubMed
Summary
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Accurate hospital benchmarking requires precise conversion of procedure-hours to procedure-days. A new regression method significantly reduces conversion errors compared to simple division, improving data reliability for benchmarking efforts.

Area of Science:

  • Health Services Research
  • Healthcare Administration
  • Biostatistics

Background:

  • Hospital billing systems are primary sources for activity counts used in benchmarking.
  • Benchmarking data often uses procedure-days, procedure-shifts, or procedure-hours.
  • Simple division for normalization from hourly to daily billing underestimates procedure-days due to rounding conventions.

Purpose of the Study:

  • To simulate data and quantify errors in converting procedure-hours to procedure-days using simple division.
  • To develop an accurate procedure for normalizing benchmarking data.
  • To compare the novel normalization procedure against simple division using simulated and real-world data.

Main Methods:

  • Generated simulated patient data (5,000 patients) with random start times and procedure durations.

Related Experiment Videos

  • Employed a resampling procedure to simulate benchmarking data across various sample sizes.
  • Utilized linear regression to derive a conversion procedure from procedure-hours to procedure-days, validated with actual patient data.

    • Main Results:

    • Simple division resulted in significant conversion errors: +/-16% (hourly), +/-11% (8-hr shifts), +/-8% (12-hr shifts) for 100 samples.
    • Regression-based conversion significantly reduced errors: +/-1% (hourly), +/-0.2% (8-hr shifts), +/-0.2% (12-hr shifts) for 100 samples.
    • Regression equations derived from simulated data outperformed those from actual data (median error 0.39 vs. +/-2.92, p=0.013).

    Conclusions:

    • Simple division underestimates procedure-days when converting from hourly or shift-based billing data.
    • A regression-based normalization procedure offers a more accurate method for converting procedure-hours/shifts to procedure-days.
    • The improved normalization enhances the reliability of hospital benchmarking data.