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Abstract

Analytics is the most advanced component of business intelligence. An analytic capability enables fact-based decisions using quantitative models. These models draw on statistical and quantitative analysis of large data repositories. An analytic capability is especially critical in healthcare because lives are at stake and there is intense pressure to reduce costs and improve efficiency. This study proposes antecedents and catalysts for developing an analytic capability based on an in-depth study of the cardiac surgical programs of the Veterans Health Administration (VHA). The VHA has developed an analytic capability for patient treatment and administrative decision-making. The models rely on the input of clinical data from multiple facilities. However, a diversity of standards, infrastructure, staff and patient mix result in misunderstood data definitions, errors in data entry, incomplete data sets, and conflicts between multiple systems. Consequently, data aggregation and data interoperability at both the systemic and semantic levels are challenging. Catalysts for developing an analytic capability, derived from the VHA case study, include a community of practice and patient case reassessment practices. Antecedents of an analytic capability include robust data aggregation and cleaning practices and establishment of data standards followed by judicious tailoring of analytic outputs to decision making needs.

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