Application of an Automated Surveillance System to Evaluate Outpatient Care of Pneumonia

With economic pressures to shift the care of community-acquired pneumonia (CAP) to the ambulatory setting, there is a need to ensure safety of outpatients with CAP. The use of claims data alone remains the primary strategy for identifying these patients, but billing information often does not match the clinical diagnosis and does not have the ability to find unrecognized cases. In our previous work, an automated pneumonia case detection algorithm (CDA) was able to detect cases of CAP with positive predictive value of 71%. For this study, we begin to illustrate how this type of surveillance system may assist in evaluating the quality of outpatient care for CAP.