Reducing Unnecessary Preoperative Cardiology Referral and Cost in Patients Undergoing Bariatric Surgery

Andrew Deak1, Lauren E Tragesser1, Kaitlyn D Ibrahim2

  • 1Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania; Department of Internal Medicine, Temple University Hospital, Philadelphia, Pennsylvania.

Insights

A new algorithm using cardiac risk factors can reduce unnecessary cardiology referrals for bariatric surgery patients, saving costs and resources without impacting patient safety.

Area of Science:

  • Cardiology
  • Bariatric Surgery
  • Healthcare Management

Background:

  • Metabolic and bariatric surgery (MBS) candidates have high cardiovascular disease (CVD) risk.
  • Current guidelines lack clear criteria for preoperative cardiac risk stratification in MBS patients.
  • This increases surgical risk and potentially leads to unnecessary healthcare utilization.

Purpose of the Study:

  • To develop and test a novel referral algorithm for preoperative cardiac risk stratification in MBS candidates.
  • To assess the algorithm's impact on reducing unnecessary cardiology referrals and associated costs.
  • To evaluate the algorithm's effect on patient safety and postoperative cardiac complications.

Main Methods:

  • Retrospective analysis of 1,528 MBS patients (2014-2023).
  • Calculation of Revised Cardiac Risk Index (RCRI) scores.
  • Development of a novel referral algorithm incorporating RCRI, smoking history, age, and METS.
  • Simulation of referral patterns and cost savings based on the algorithm.

Main Results:

  • 56% of MBS patients were referred to cardiology preoperatively.
  • A standardized algorithm could have reduced referrals by 30% (255 patients), identifying low-risk individuals.
  • Estimated cost savings of approximately $28,000 from reduced unnecessary consultations and testing.
  • No postoperative cardiac complications were observed in the study cohort.

Conclusions:

  • A novel referral algorithm, integrating RCRI and other CVD risk factors, can optimize preoperative cardiac risk stratification for MBS candidates.
  • Implementation may significantly decrease unnecessary cardiology referrals, leading to reduced resource utilization and cost savings.
  • The proposed algorithm shows potential for improving healthcare efficiency without compromising patient safety in the context of bariatric surgery.

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