Can data from an electronic medical record identify which patients with pneumonia have Pneumocystis carinii Infection?

BACKGROUND: Pneumocystis carinii is the leading opportunistic pulmonary infection in HIV-infected patients. Invasive diagnostic procedures might be avoided if available electronic data can accurately identify patients with Pneumocystis pneumonia (PCP). METHODS: We extracted data from electronic hospital records, emergency department records, and a pathology database for 299 HIV-infected patients with pneumonia who underwent bronchoscopy. We identified independent indicators of confirmed PCP using logistic regression analysis on a random half of the patients and validated the predictive power of the resulting model on the other half. RESULTS: Bronchoscopy confirmed pneumocystis carinii in 111 patients (37%). Five of the seven significant independent predictors of PCP came from patients' electronic medical records: infiltrate on chest radiograph, male gender, lower red cell distribution width, lower serum creatinine, and a prior positive HIV test. The other two (duration of illness and presence of dyspnea) came from the emergency department record. A simple index found 43% of patients at low risk (18% with pneumocystis), 37% at moderate risk (36% with pneumocystis), and 20% at high risk (74% with pneumocystis). CONCLUSIONS: Data from electronic medical records can help quantify the risk of PCP among HIV-infected patients. However, the model failed to identify 18% of patients with PCP in the low risk group, and empiric therapy would erroneously treat 26% of patients classified as high risk. Bronchoscopy is needed to accurately diagnose PCP among HIV-infected patients with pneumonia. However, if bronchoscopy is not available, the model can help with initial decisions about antibiotic therapy.

Structure, functions, and activities of a research support informatics section.

The authors describe a research group that supports the needs of investigators seeking data from an electronic medical record system. Since its creation in 1972, the Regenstrief Medical Records System has captured and stored more than 350 million discrete coded observations on two million patients. This repository has become a central data source for prospective and retrospective research. It is accessed by six data analysts--working closely with the institutional review board--who provide investigators with timely and accurate data while protecting patient and provider privacy and confidentiality. From January 1, 1999, to July 31, 2002, data analysts tracked their activities involving 47,559 hours of work predominantly for physicians (54%). While data retrieval (36%) and analysis (25%) were primary activities, data analysts also actively collaborated with researchers. Primary objectives of data provided to investigators were to address disease-specific (35.4%) and drug-related (12.2%) questions, support guideline implementation (13.1%), and probe various aspects of clinical epidemiology (5.7%). Outcomes of these endeavors included 117 grants (including 300,000 US dollars per year salary support for data analysts) and 139 papers in peer-reviewed journals by investigators who rated the support provided by data analysts as extremely valuable.