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Development and Validation of a Methodology to Reduce Mortality Using the Veterans Affairs Surgical Quality

Deborah S Keller1, Donald Kroll2, Harry T Papaconstantinou3

  • 1Department of Surgery, Baylor University Medical Center, Dallas, TX.

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A new method using the Veterans Affairs Surgical Quality Improvement Program (VASQIP) Risk Calculator effectively identifies high-risk surgical patients for tertiary care referral, significantly reducing 30-day mortality rates.

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Area of Science:

  • Surgical Quality Improvement
  • Health Services Research
  • Patient Outcomes

Background:

  • Developing methods to identify patients at high risk of 30-day mortality after elective surgery is crucial for optimizing tertiary care referrals.
  • The Veterans Affairs Surgical Quality Improvement Program (VASQIP) Risk Calculator offers a potential tool for this purpose.
  • The study aimed to develop and validate an institution-specific process using the VASQIP calculator to improve patient outcomes.

Purpose of the Study:

  • To develop and validate a methodology for identifying patients who may benefit from tertiary care referral based on surgical risk.
  • To hypothesize that this process could optimize referrals and reduce mortality.
  • To evaluate the effectiveness of the developed methodology in a real-world clinical setting.

Main Methods:

  • A VASQIP risk score was calculated for all patients undergoing elective noncardiac surgery at a single Veterans Affairs (VA) facility.
  • A threshold of 3.3% predicted mortality was established for referral to a tertiary care center.
  • The study compared actual vs. predicted referrals and mortality rates at referring and receiving facilities.

Main Results:

  • The validation included 565 patients, with 90 (16%) identified for referral based on a VASQIP risk score >3.3%.
  • For referred patients, predicted mortality was 27% (16 patients), but actual deaths were significantly lower at 4 (p=0.007).
  • For patients not indicated for referral, predicted mortality was 1% (4 patients), with no actual deaths observed (p=0.1241).

Conclusions:

  • The validated methodology effectively identifies patients for higher-level care referral, leading to reduced mortality at referring institutions.
  • This approach optimizes patient care decisions and significantly improves patient outcomes.
  • Further application and studies are warranted to explore the broader impact of this methodology.