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Do complication screening programs detect complications present at admission?

James M Naessens1, Christopher G Scott, Todd R Huschka

  • 1Divisions of Health Care Policy & Research and Biostatistics, Mayo Clinic, Rochester, Minnesota, USA. naessens@mayo.edu

Joint Commission Journal on Quality and Safety
|March 23, 2004
PubMed
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Computer algorithms using administrative data accurately identify hospital complications, but require a present-on-admission flag to reduce coding noise and enable reliable hospital comparisons.

Area of Science:

  • Health Informatics
  • Medical Record Analysis
  • Hospital Quality Improvement

Background:

  • Administrative data and computer algorithms are increasingly used to identify hospital complications.
  • Assessing algorithm accuracy requires differentiating hospital-acquired conditions from pre-existing comorbidities.

Purpose of the Study:

  • To verify the accuracy of computer algorithms in identifying hospital complications using administrative data.
  • To evaluate the effectiveness of a medical records indicator in distinguishing hospital-acquired conditions.

Main Methods:

  • Applied indicators to secondary diagnoses for all 1997-1998 discharges to differentiate conditions.
  • Analyzed cases to identify complications and their acquired status.

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Main Results:

  • Algorithms identified 71 different complications, with 69 having cases coded as acquired.
  • Thirty-five complications had at least 30 cases flagged as acquired.
  • Hospital complications like postoperative septicemia significantly increase costs, length of stay, and mortality.

Conclusions:

  • Current algorithms incorrectly flag pre-existing conditions as hospital-acquired, complicating inter-hospital comparisons.
  • Coding variability between institutions further hinders accurate complication monitoring.
  • Implementing a present-on-admission flag is crucial for reducing noise and improving complication rate monitoring.