Compliance with established pneumonia core measures at MD Anderson Cancer Center in the emergency center.

Abstract

189 Background: Pneumonia is the major cause of death due to infectious diseases in the United States. In the cancer patient, pneumonia is the overall leading infectious cause of death. Pneumonia Core Measures (PCM) and Clinical Pathways are frequently used by healthcare organizations to ensure the delivery of high-quality care and pathogen-directed therapy. A multidisciplinary team was organized at the University of Texas MD Anderson Cancer Center (MDACC) Emergency Center (EC) into a Pneumonia Team to optimize care and to enhance compliance with current PCM. Methods: A retrospective review of EC patients during pneumonia season was completed. Results: Three areas for improvement in the EC were identified. The areas include lack of EC staff’s knowledge on PCM, lack of standardized order-sets for pathogen-directed treatment, and cancer patients presenting with pneumonia syndromes that fall outside established Community-Acquired Pneumonia (CAP) guidelines. The identified problems were addressed through three strategies: Intense EC staff education initially and yearly prior to pneumonia season (September-March). Microbiologic analysis of the pathogens responsible for the pneumonias in our unique cancer population at MDACC. Development and implementation of an institutional pneumonia algorithm and an order-set. The Pneumonia Team also identified a gap between our patient population and the current PCM. Pneumonia patients at MDACC EC are divided into two distinct groups, solid tumor and hematologic cancers. The microbiology analyzed in both groups is consistent with Healthcare-Associated Pneumonia (HCAP) and not CAP. Microbiology analysis identified gram positive, gram negative, fungal, viral and multi-drug resistant organisms. The initial analysis demonstrated that 87% of our patients met criteria for HCAP and only 12% met CAP. Based on this percentage, antibiotic selection for our CAP patients comprises a small portion of our total population. Conclusions: Our current algorithm and order-set optimize care and minimize variation to match our patient population. These findings provide important considerations for policy makers in regard to pneumonia measurements in a cancer setting.