Anesthesia complications as a childbirth patient safety indicator

The Agency for Healthcare Research and Quality (AHRQ) has established multiple sets of indicators for quality monitoring and improvement. One such set is the patient safety indicators (PSIs), which focuses on potentially preventable hospital complications after surgeries, procedures, and childbirth. Our objective in this study was to determine the prevalence of childbirth-related anesthesia complications by method of delivery and to evaluate the variation in complication rates across hospitals using the AHRQ PSI methodology and a modification specific to childbirth with the goal of determining the relevance of tracking anesthesia complications as a potential PSI for childbirth.

The technical specifications of the experimental Anesthesia Complication Quality Indicator, one of the PSI defined by AHRQ, were modified to create a childbirth-specific indicator that included all childbirth admissions (vaginal and cesarean deliveries) and complications from general and neuraxial anesthesia/analgesia. Using California hospital discharge data, we calculated hospital-specific rates, adjusting for age, race/ethnicity, and pregnancy complications.

A total of 508,842 deliveries occurred in 254 hospitals in California in 2009. Hospitals with <200 annual deliveries (N = 12) were excluded from analyses. Among 242 hospitals, the rate of anesthesia complications was 0.13% for the standard AHRQ study population (adult surgical admissions, which included cesarean deliveries). The childbirth-specific rate of anesthesia complications was 0.31%. When stratified by method of delivery, complication rates were 0.49% for cesarean delivery and 0.22% for vaginal delivery (P < 0.0001). The unadjusted mean (SD) was 0.34% (0.34%), with range (0%-2.46%). The rates of 13 hospitals (including their 95% confidence limits) remained in the upper quartile as outliers, with adjusted rates from 0.52% to 2.13%.

Rates of childbirth-related anesthesia complications may provide an opportunity to identify hospitals with extreme rates that may provide insights into systematic ways to improve patient safety.