Temporal trends in rates of patient harm resulting from medical care

N Engl J Med. 2010 Nov 25;363(22):2124-34. doi: 10.1056/NEJMsa1004404.

Abstract

Background: In the 10 years since publication of the Institute of Medicine's report To Err Is Human, extensive efforts have been undertaken to improve patient safety. The success of these efforts remains unclear.

Methods: We conducted a retrospective study of a stratified random sample of 10 hospitals in North Carolina. A total of 100 admissions per quarter from January 2002 through December 2007 were reviewed in random order by teams of nurse reviewers both within the hospitals (internal reviewers) and outside the hospitals (external reviewers) with the use of the Institute for Healthcare Improvement's Global Trigger Tool for Measuring Adverse Events. Suspected harms that were identified on initial review were evaluated by two independent physician reviewers. We evaluated changes in the rates of harm, using a random-effects Poisson regression model with adjustment for hospital-level clustering, demographic characteristics of patients, hospital service, and high-risk conditions.

Results: Among 2341 admissions, internal reviewers identified 588 harms (25.1 harms per 100 admissions; 95% confidence interval [CI], 23.1 to 27.2) [corrected]. Multivariate analyses of harms identified by internal reviewers showed no significant changes in the overall rate of harms per 1000 patient-days (reduction factor, 0.99 per year; 95% CI, 0.94 to 1.04; P=0.61) or the rate of preventable harms. There was a reduction in preventable harms identified by external reviewers that did not reach statistical significance (reduction factor, 0.92; 95% CI, 0.85 to 1.00; P=0.06), with no significant change in the overall rate of harms (reduction factor, 0.98; 95% CI, 0.93 to 1.04; P=0.47).

Conclusions: In a study of 10 North Carolina hospitals, we found that harms remain common, with little evidence of widespread improvement. Further efforts are needed to translate effective safety interventions into routine practice and to monitor health care safety over time. (Funded by the Rx Foundation.).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Hospitals / statistics & numerical data*
  • Hospitals / trends
  • Humans
  • Medical Errors / classification
  • Medical Errors / trends*
  • Multivariate Analysis
  • North Carolina
  • Retrospective Studies
  • Risk Adjustment