Patient misidentification in the neonatal intensive care unit: quantification of risk.

OBJECTIVE: To quantify the potential for misidentification among NICU patients resulting from similarities in patient names or hospital medical record numbers (MRNs). METHODS: A listing of all patients who received care in 1 NICU during 1 calendar year was obtained from the unit's electronic medical record system. A patient day was considered at risk for misidentification when the index patient shared a surname, similar-sounding surname, or similar MRN with another patient who was cared for in the NICU on that day. RESULTS: During the 1-year study period, 12186 days of patient care were provided to 1260 patients. The unit's average daily census was 33.4; the maximum census was 48. Not a single day was free of risk for patient misidentification. The mean number of patients who were at risk on any given day was 17 (range: 5-35), representing just over 50% of the average daily census. During the entire calendar year, the risk ranged from 20.6% to a high of 72.9% of the average daily census. The most common causes of misidentification risk were similar-appearing MRNs (44% of patient days). Identical surnames were present in 34% of patient days, and similar-sounding names were present in 9.7% of days. Twins and triplets contributed one third of patient days in the NICU. After these multiple births were excluded from analysis, 26.3% of patient days remained at risk for misidentification. Among singletons, the contribution to misidentification risk of similar-sounding surnames was relatively unchanged (9.1% of patient days), whereas that of similar MRNs and identical surnames decreased (17.6% and 1.0%, respectively). CONCLUSIONS: NICU patients are frequently at risk for misidentification errors as a result of similarities in standard identifiers. This risk persists even after exclusion of multiple births and is substantially higher than has been reported in other hospitalized populations.

Voluntary anonymous reporting of medical errors for neonatal intensive care.

OBJECTIVES: Medical errors cause significant morbidity and mortality in hospitalized patients. Specialty-based, voluntary reporting of medical errors by health care providers is an important strategy that may enhance patient safety. We developed a voluntary, anonymous, Internet-based reporting system for medical errors in neonatal intensive care, evaluated its feasibility, and identified errors that affect high-risk neonates and their families. METHODS: Health professionals (n = 739) from 54 hospitals in the Vermont Oxford Network received access to a secure Internet site for anonymous reporting of errors, near-miss errors, and adverse events. Reports used free-text entry in phase 1 (17 months) and a structured form in phase 2 (10 months). The number and types of reported events and factors that contributed to the events were measured. RESULTS: Of 1230 reports--522 in phase 1 (17 months) and 708 in phase 2 (10 months)--the most frequent event categories were wrong medication, dose, schedule, or infusion rate (including nutritional agents and blood products; 47%); error in administration or method of using a treatment (14%); patient misidentification (11%); other system failure (9%); error or delay in diagnosis (7%); and error in the performance of an operation, procedure, or test (4%). The most frequent contributory factors were failure to follow policy or protocol (47%), inattention (27%), communications problem (22%), error in charting or documentation (13%), distraction (12%), inexperience (10%), labeling error (10%), and poor teamwork (9%). In 24 reports, family members assisted in discovery, contributed to the cause, or themselves were victims of the error. Serious patient harm was reported in 2% and minor harm in 25% of phase 2 events. CONCLUSIONS: Specialty-based, voluntary, anonymous Internet reporting by health care professionals identified a broad range of medical errors in neonatal intensive care and promoted multidisciplinary collaborative learning. Similar specialty-based systems have the potential to enhance patient safety in a variety of clinical settings.