Association Between Hospital Staffing Models and Failure to Rescue

Ann Surg. 2019 Jul;270(1):91-94. doi: 10.1097/SLA.0000000000002744.


Objective: To identify hospital staffing models associated with failure to rescue (FTR) rates at low- and high-performing hospitals.

Background: FTR is an important quality measure in surgical safety and is a metric that hospitals are seeking to improve. Specific unit-level determinants of FTR, however, remain unknown.

Methods: Retrospective, observational study using data from the Michigan Quality Surgical Collaborative, which is a prospectively collected and clinically audited database in the state of Michigan. We identified 44,567 patients undergoing major general or vascular surgery from 2008 to 2012. Our main outcome measures were mortality, complications, and FTR rates.

Results: Hospital rates of FTR across low, middle, and high tertiles were 8.9%, 16.5%, and 19.9%, respectively (P < 0.001). Low FTR hospitals tended to have a closed intensive care unit staffing model (56% vs 20%, P < 0.001) and a higher proportion of board-certified intensivists (88% vs 60%, P < 0.001) when compared to high FTR hospitals. There was also significantly more staffing of low FTR hospitals by hospitalists (85% vs 20%, P < 0.001) and residents (62% vs 40%, P < 0.01). Low FTR hospitals were noted to have more overnight coverage (75% vs 45%, P < 0.001) as well as a dedicated rapid response team (90% vs 60%, P < 0.001).

Conclusions: Low FTR hospitals had significantly more staffing resources than high FTR hospitals. Although hiring additional staff may be beneficial, there remain significant financial limitations for many hospitals to implement robust staffing models. Thus, our ongoing work seeks to improve rescue and implement effective staffing strategies within these constraints.

Publication types

  • Observational Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Clinical Audit
  • Cross-Sectional Studies
  • Failure to Rescue, Health Care / statistics & numerical data*
  • Female
  • Health Workforce / statistics & numerical data*
  • Hospital Mortality
  • Humans
  • Male
  • Michigan
  • Middle Aged
  • Patient Safety / statistics & numerical data*
  • Personnel Staffing and Scheduling / organization & administration
  • Personnel Staffing and Scheduling / statistics & numerical data*
  • Personnel, Hospital / supply & distribution*
  • Postoperative Complications / epidemiology
  • Postoperative Complications / etiology
  • Quality Improvement / statistics & numerical data
  • Quality Indicators, Health Care / statistics & numerical data*
  • Retrospective Studies
  • Surgical Procedures, Operative