Surveillance based on hospitalization discharge data overestimates disease burden

Most discharge data include repeat hospitalizations, skewing estimates of disease rates.

Estimates of disease prevalence based on the total number of people hospitalized for a given condition overstate the actual number of people affected, report researchers from California State University and CDC. That's because most hospitalization data include repeat hospitalizations, counting the same individual patients more than once.

Using 2011 data from 10,384,306 hospital discharges in 12 states, based on State Inpatient Databases (SID) of the Agency for Healthcare Research and Quality (AHRQ), the researchers tracked hospitalization rates, including repeat hospitalizations, on diabetes and selected causes. They discovered that hospitalization rates that include repeat hospitalizations overestimate the true burden of various diabetes-related diseases - and that this overestimation is especially pronounced for some causes. However, the inclusion of repeat hospitalizations had little impact on comparing disease rates between people with and without diabetes.

"To our knowledge, ours is the first study to quantify the overestimation of hospitalization rates for common diabetes-related causes because of the inclusion of repeat hospitalizations, and to determine whether this affects comparisons of diabetes to non-diabetes rates," the researchers conclude.