The measurement of inpatient complications has received substantial attention in recent years because mortality rates and other outcome measures often appear unable to discriminate superior from inferior hospital care. Complication measurement holds out the promise of being more sensitive to variations in patient care because complications occur more frequently than do mortalities, and because complications are more direct consequences of the process of care.
The authors developed a new measure of complications that seeks to give insight into the patient care given by different hospitals or physicians by using commonly available data. Specifically, this measure is based on a decision-theoretic model that estimates the probability of a complication for combinations of admitting and secondary International Classification of Diseases, 9th Revision, Clinical Modification diagnoses. The measure can be evaluated at the patient level, or aggregated and risk-adjusted for the population of a given care provider (eg, physician or hospital). When applied to a set of patient-level UB-82/92§ data, this measure estimates the risk of complication for any member of a population, controlling for comorbidity, and hence is designated comorbidity-adjusted complication risk (CACR).
The authors describe the development of CACR and its testing and validation using data acquired from the states of Pennsylvania, California, and Florida, as well as facility data obtained directly from hospitals. The data set includes 480,000 patients from 50 Pennsylvania hospitals, 300,000 patients from 33 Florida hospitals, 370,000 patients from 35 California hospitals, and 37,000 patients from six validation hospitals. Comorbidity-adjusted complication risk is constructed from widely available data common to most patient cases. Comorbidity-adjusted complication risk can be adjusted for its case mix, but such risk adjustment has much less effect on CACR than on other adverse outcomes such as mortality and morbidity. Comorbidity-adjusted complication risk varies widely across the hospitals in this sample, yet it is stable across time and is correlated with other known quality outcomes, including such accepted “gold standards” as hospital-documented adverse event rates and chart review determinations of complications.