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
- Milestone pig kidney transplant offers hope amid ethical, safety questions
- Fitch Ratings: Hospital credit outlook improves amid stabilizing margins
- Annual Leapfrog Group awards recognize top hospitals, ASCs
- US obesity rates decline for first time in a decade
- Study: Active monitoring without surgery safe for certain low-risk DCIS patients
- Data support option to skip sentinel lymph node biopsy in early breast cancer
- Surveyed nurses, physicians likely to quit
- Costs drop, access expands for GLP-1 weight loss drugs
- Q&A: Perioperative immunotherapy advances for early-stage NSCLC
- Proposals close December 16: Present at the 2025 OR Manager Conference
© Access Intelligence, LLC. All rights reserved. |
Privacy Policy |
Cookie Settings |
Diversity, Equity, Inclusion & Belonging |
Accessibility Statement