Studies estimate that 6% to 27% of deaths in hospitals might be prevented with higher quality care. These estimates may be inaccurate because they fail to account for the uncertainty associated with classifying preventability. The purpose of this study was to measure the prevalence of preventable deaths, accounting for the uncertainty in preventability ratings.
We created standardized structured case abstracts for all deaths at a multisite academic teaching hospital over a 3-month period. Each case abstract was evaluated independently by 4 reviewers who rated death preventability on a 100-point scale ranging from 0 (“Definitely not preventable”) to 100 (“Definitely preventable”). Ratings were categorized into a 4-level ordinal scale and latent class analysis was used to measure the prevalence of each preventability class and estimate the probability that deaths in each class were preventable.
There were 480 deaths (3.4% of all admissions) during the study period. The latent class model (LCM) found that 91.6% (95% CI: 88.4–94.8%) of deaths were “nonpreventable” and 8.4% (5.2–11.6%) were “possibly preventable.” “Possibly preventable” deaths could be identified with 90% certainty, but due to error in reviewer ratings, a “possibly preventable” death had a 50% probability of being receiving a rating of less than 25/100 by any single reviewer. Only 5 of 31 deaths classified as a “possibly preventable” (1.0% of all deaths) were judged to likely be alive in 3 months with perfect care.
After accounting for uncertainty associated with rating the preventability of hospital deaths, we found that 8.4% of deaths were deemed possibly preventable. There was only moderate probability that these deaths were truly preventable.