July 22, 2020
Data mining yields tool to predict OR staffing needs
Staffing to a block duration can be inefficient. Uncontrolled variables such as increased case complexity and unexpected staff absences can cause chaos. Leaders from Penn Medicine—Pennsylvania Hospital in Philadelphia used data analytics to measure the efficiency of matching staffing against an optimized OR schedule, which allowed them to predict staffing hours to case hours and determine a productivity score. By matching staff to case demand, they realized a 6.4% labor savings and improved productivity.
Free Daily News
- Catheter sterility concerns prompt Class 1 FDA recall for surgery trays
- Large amounts of personal data possibly stolen in Change Healthcare cyberattack
- AI model helps predict patient decline, drive collaborative care
- One patient’s recovery highlights benefits of outpatient endoscopic spine surgery
- Getting ready for the OAS CAHPS Survey 2025 requirement
- Contribute to perioperative education with the 2024 OR Manager Salary/Career Survey
- Supply chain stability improves, but threats remain
- Private equity healthcare ownership draws new scrutiny
- Share your expertise! Topics, speakers sought for 2025 ORBMC
- FDA approves imaging drug for detecting cancer after lumpectomy
© Access Intelligence, LLC. All rights reserved. | Privacy Policy | Diversity, Equity, Inclusion & Belonging