Abstract

The delivery of health care involves a myriad of stakeholders, including patients, direct health care providers, researchers, managed care organizations, and third-party payers. These stakeholders often have considerable differences in objectives, concerns, priorities and constraints, making data management in health care organizations a challenging endeavor. The planning, management, and delivery of health care services is now dependent on effective data management strategies, from both the business and clinical perspectives. As health care costs have once again started to rise steeply, efficiencies in administrative and clinical information processing offer one area of potential benefits. The Data Management in Health Care Minitrack focuses on the evolution of the database infrastructure required for handling clinical, managerial, and population-based data in the health care arena. The adoption of electronic commerce models in health care is making data management technologies even more critical. The ability to support both business-to-business and business-toconsumer efforts often rests on a foundation of database systems, along with evolving standards and networking infrastructures. This year, we have accepted three papers from among seven submissions dealing with a cross section of data management topics. The first paper, “Examining Quality of Care – How Poor Information Flow can Impact on Hospital Workflow and Effect Patient Outcomes” by Reeva Lederman and Iain Morrison, casts a critical eye on hospital workflows and the use of information technology to improve the situation. The particular area of focus is in neurology and concerns the efficient delivery of patient images based on MRI (Medical Resonance Imaging), PET (Positron Emission Tomography), and other techniques. Clearly, delayed or missing information in such a context can affect the quality of patient care. The authors take a comprehensive approach, using patient surveys, staff

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