What can hospitalized patients tell us about adverse events? Learning from patient-reported incidents

J Gen Intern Med. 2005 Sep;20(9):830-6. doi: 10.1111/j.1525-1497.2005.0180.x.


Purpose: Little is known about how well hospitalized patients can identify errors or injuries in their care. Accordingly, the purpose of this study was to elicit incident reports from hospital inpatients in order to identify and characterize adverse events and near-miss errors.

Subjects: We conducted a prospective cohort study of 228 adult inpatients on a medicine unit of a Boston teaching hospital.

Methods: Investigators reviewed medical records and interviewed patients during the hospitalization and by telephone 10 days after discharge about "problems,""mistakes," and "injuries" that occurred. Physician investigators classified patients' reports. We calculated event rates and used multivariable Poisson regression models to examine the factors associated with patient-reported events.

Results: Of 264 eligible patients, 228 (86%) agreed to participate and completed 528 interviews. Seventeen patients (8%) experienced 20 adverse events; 1 was serious. Eight patients (4%) experienced 13 near misses; 5 were serious or life threatening. Eleven (55%) of 20 adverse events and 4 (31%) of 13 near misses were documented in the medical record, but none were found in the hospital incident reporting system. Patients with 3 or more drug allergies were more likely to report errors compared with patients without drug allergies (incidence rate ratio 4.7, 95% CI 1.7, 13.4).

Conclusion: Inpatients can identify adverse events affecting their care. Many patient-identified events are not captured by the hospital incident reporting system or recorded in the medical record. Engaging hospitalized patients as partners in identifying medical errors and injuries is a potentially promising approach for enhancing patient safety.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Boston
  • Female
  • Health Care Surveys
  • Hospitals, Teaching / standards*
  • Humans
  • Interviews as Topic
  • Male
  • Medical Errors / classification
  • Medical Errors / statistics & numerical data*
  • Medication Errors / statistics & numerical data
  • Middle Aged
  • Patient Satisfaction / statistics & numerical data*
  • Process Assessment, Health Care
  • Prospective Studies