Risk-Adjusted Cumulative Sum for Early Detection of Hospitals With Excess Perioperative Mortality

Author:

Chen Vivi W.12,Chidi Alexis P.3,Dong Yongquan1,Richardson Peter A.14,Axelrod David A.5,Petersen Laura A.14,Massarweh Nader N.678

Affiliation:

1. Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas

2. Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas

3. Department of Thoracic and Cardiovascular Surgery, University of Texas MD Anderson Cancer Center, Houston

4. Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Texas

5. Division of Transplantation, Department of Surgery, University of Iowa, Iowa City

6. Surgical and Perioperative Care, Atlanta VA Health Care System, Decatur, Georgia

7. Division of Surgical Oncology, Department of Surgery, Emory University School of Medicine, Atlanta, Georgia

8. Department of Surgery, Morehouse School of Medicine, Atlanta, Georgia

Abstract

ImportanceNational surgical quality improvement programs lack tools for early detection of quality or safety concerns, which risks patient safety because of delayed recognition of poor performance.ObjectiveTo compare the risk-adjusted cumulative sum (CUSUM) with episodic evaluation for early detection of hospitals with excess perioperative mortality.Design, Setting, and ParticipantsNational, observational, hospital-level, comparative effectiveness study of 697 566 patients. Identification of hospitals with excess, risk-adjusted, quarterly 30-day mortality using observed to expected ratios (ie, current criterion standard in the Veterans Affairs Surgical Quality Improvement Program) was compared with the risk-adjusted CUSUM. Patients included in the study underwent a noncardiac operation at a Veterans Affairs hospital, had a record in the Veterans Affairs Surgical Quality Improvement Program (January 1, 2011, through December 31, 2016), and were aged 18 years or older.Main Outcome and MeasureNumber of hospitals identified as having excess risk-adjusted 30-day mortality.ResultsThe cohort included 697 566 patients treated at 104 hospitals across 24 quarters. The mean (SD) age was 60.9 (13.2) years, 91.4% were male, and 8.6% were female. For each hospital, the median number of quarters detected with observed to expected ratios, at least 1 CUSUM signal, and more than 1 CUSUM signal was 2 quarters (IQR, 1-4 quarters), 8 quarters (IQR, 4-11 quarters), and 3 quarters (IQR, 1-4 quarters), respectively. During 2496 total quarters of data, outlier hospitals were identified 33.3% of the time (830 quarters) with at least 1 CUSUM signal within a quarter, 12.5% (311 quarters) with more than 1 CUSUM signal, and 11.0% (274 quarters) with observed to expected ratios at the end of the quarter. The CUSUM detection occurred a median of 49 days (IQR, 25-63 days) before observed to expected ratio reporting (1 signal, 35 days [IQR, 17-54 days]; 2 signals, 49 days [IQR, 26-61 days]; 3 signals, 58 days [IQR, 44-69 days]; ≥4 signals, 49 days [IQR, 42-69 days]; trend test, P < .001). Of 274 hospital quarters detected with observed to expected ratios, 72.6% (199) were concurrently detected by at least 1 CUSUM signal vs 42.7% (117) by more than 1 CUSUM signal. There was a dose-response relationship between the number of CUSUM signals in a quarter and the median observed to expected ratio (0 signals, 0.63; 1 signal, 1.28; 2 signals, 1.58; 3 signals, 2.08; ≥4 signals, 2.49; trend test, P < .001).ConclusionsThis study found that with CUSUM, hospitals with excess perioperative mortality can be identified well in advance of standard end-of-quarter reporting, which suggests episodic evaluation strategies fail to detect out-of-control processes and place patients at risk. Continuous performance evaluation tools should be adopted in national quality improvement programs to prevent avoidable patient harm.

Publisher

American Medical Association (AMA)

Subject

Surgery

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