No abstract

Prediction models using electronic clinical data accurately identified patients with elevated risk for hospitalization or death. This information can enhance the coordination of care for patients with complex clinical conditions.

Health care has lagged behind other industries in its use of advanced analytics. The Veterans Health Administration (VHA) has three decades of experience collecting data about the veterans it serves nationwide through locally developed information systems that use a common electronic health record. In 2006 the VHA began to build its Corporate Data Warehouse, a repository for patient-level data aggregated from across the VHA's national health system. This article provides a high-level overview of the VHA's evolution toward "big data," defined as the rapid evolution of applying advanced tools and approaches to large, complex, and rapidly changing data sets. It illustrates how advanced analysis is already supporting the VHA's activities, which range from routine clinical care of individual patients--for example, monitoring medication administration and predicting risk of adverse outcomes--to evaluating a systemwide initiative to bring the principles of the patient-centered medical home to all veterans. The article also shares some of the challenges, concerns, insights, and responses that have emerged along the way, such as the need to smoothly integrate new functions into clinical workflow. While the VHA is unique in many ways, its experience may offer important insights for other health care systems nationwide as they venture into the realm of big data.

Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions.

Corticosteroids are often used in the outpatient treatment of acute exacerbation of chronic obstructive pulmonary disease (COPD). To date, there are few data documenting the benefit of this practice. The objective of this randomized, double-blind, placebo-controlled trial was to assess the efficacy of corticosteroids in the outpatient treatment of COPD exacerbations. Twenty-seven patients presenting with acute COPD exacerbation were studied. In addition to continuing their previous medications and increasing their use of beta-agonists, patients were randomized to receive a 9-d tapering dose of either oral prednisone or placebo. Treatment with prednisone rather than placebo resulted in a more rapid improvement in arterial PO2 (PaO2) (1.12 mm Hg/d versus -0.03 mm Hg/day; p = 0.002), alveolar-arterial oxygen gradient (A-aDO2) (-1.16 mm Hg/d versus -0.03 mm Hg/day; p = 0.04), FEV1 (0.05 L/d versus 0.00 L/d; p = 0.006), and peak expiratory flow (PEF) (0.15 L/s/d versus 0.04 L/s/d; p = 0.009). Prednisone also resulted in fewer treatment failures (p = 0.002) and in a trend toward more rapid improvement in dyspnea scale scores. Outpatient treatment of acute COPD exacerbation with prednisone accelerates recovery of PaO2, A-aDO2, FEV1, and PEF, reduces the treatment failure rate, and improves subjective dyspnea.