Postoperative Delirium as a Target for Surgical Quality Improvement

Julia R Berian, Lynn Zhou, Marcia M. Russell, Melissa A. Hornor, Mark E. Cohen, Emily Finlayson, Clifford Y. Ko, Ronnie A. Rosenthal, Thomas N. Robinson

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Objective: To explore hospital-level variation in postoperative delirium using a multi-institutional data source. Background: Postoperative delirium is closely related to serious morbidity, disability, and death in older adults. Yet, surgeons and hospitals rarely measure delirium rates, which limits quality improvement efforts. Methods: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Geriatric Surgery Pilot (2014 to 2015) collects geriatric-specific variables, including postoperative delirium using a standardized definition. Hierarchical logistic regression models, adjusted for case mix [Current Procedural Terminology (CPT) code] and patient risk factors, yielded risk-adjusted and smoothed odds ratios (ORs) for hospital performance. Model performance was assessed with Hosmer-Lemeshow (HL) statistic and c-statistics, and compared across surgical specialties. Results: Twenty thousand two hundred twelve older adults (≥65 years) underwent inpatient operations at 30 hospitals. Postoperative delirium occurred in 2427 patients (12.0%) with variation across specialties, from 4.7% in gynecology to 13.7% in cardiothoracic surgery. Hierarchical modeling with 20 risk factors (HL = 9.423, P = 0.31; c-statistic 0.86) identified 13 hospitals as statistical outliers (5 good, 8 poor performers). Per hospital, the median risk-adjusted delirium rate was 10.4% (range 3.2% to 27.5%). Operation-specific risk and preoperative cognitive impairment (OR 2.9, 95% confidence interval 2.5-3.5) were the strongest predictors. The model performed well across surgical specialties (orthopedic, general surgery, and vascular surgery). Conclusion: Rates of postoperative delirium varied 8.5-fold across hospitals, and can feasibly be measured in surgical quality datasets. The model performed well with 10 to 12 variables and demonstrated applicability across surgical specialties. Such efforts are critical to better tailor quality improvement to older surgical patients.

Original languageEnglish (US)
Pages (from-to)93-99
Number of pages7
JournalAnnals of surgery
Issue number1
StatePublished - Jul 1 2018

Bibliographical note

Funding Information:
From the *American College of Surgeons, Division of Research and Optimal Patient Care, Chicago, IL; †University of Chicago Medical Center, Department of Surgery, Chicago, IL; zUniversity of California, Los Angeles, Department of Surgery, Los Angeles, CA; §University of California, San Francisco, Department of Surgery, San Francisco, CA; ôYale University, Department of Surgery, New Haven, CT; and ||University of Colorado, Denver, Department of Surgery, Aurora, CO. This project is funded in part by a grant from the John A. Harford Foundation. The authors declare no conflict of interests. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site ( Reprints: Julia R. Berian, MD, MS, University of Chicago Medical Center, Department of Surgery, 5841 S. Maryland Ave, O-217 MC6040, Chicago IL 60637. E-mail: Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved. ISSN: 0003-4932/17/26801-0093 DOI: 10.1097/SLA.0000000000002436

Publisher Copyright:
© 2017 Wolters Kluwer Health, Inc. All rights reserved.


  • aging
  • cognitive impairment
  • elderly
  • geriatric surgery
  • outcomes
  • patient-centered
  • postoperative delirium
  • quality improvement
  • surgical quality


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