医疗数据分析在减少医疗欺诈和改善临床和财务结果方面的作用

R. B. Rao
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引用次数: 13

摘要

考虑以下医疗保健趋势:(1)由于医疗保健IT技术的进步和医疗改革立法的推动,电子形式的患者、生命科学和流程数据的数量急剧增加。(2)医学信息(如循证知识)和已发表知识的数量据说每隔几年就翻一番。(3)可用于病人护理的治疗方法和诊断选择的数量呈爆炸式增长,通常能够针对疾病状况进行精确的治疗。在这次演讲中,我们将讨论这些趋势,以及尽管取得了这些进步,医疗保健仍面临危机的一些原因:即,医疗费用持续增长,而患者的治疗效果却没有相应改善。我们相信,对临床、生命科学和医疗过程数据的分析可以在应对这些基本挑战方面发挥关键作用。特别是两项技术进步可以发挥关键作用:云计算和移动性将使分析大量数据成为可能,并在影响最大的时候迅速向临床医生、消费者和研究人员提供有用的信息。其中一些已经在今天发生,通过分析医疗记录来减少欺诈、浪费和滥用,改善患者的治疗效果,并改善对护理标准和政策指导方针的遵守。我们以对未来医疗系统可以不断分析以优化医疗成本和结果的一瞥来结束谈话。
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The role of medical data analytics in reducing health fraud and improving clinical and financial outcomes
Consider the following healthcare trends: (1) There is a tremendous increase in the amount of patient, life sciences and process data in electronic form, fueled by advances in healthcare IT technology, and health reform legislation. (2) The amount of medical information (e.g., evidence-based knowledge) and published knowledge is said to be doubling every few years. (3) There is an explosion in the number of available therapies and diagnostic options for patient care, often enabling precise targeting of therapy to disease conditions. In this talk we will discuss these trends and some of the reasons why, despite these advances, healthcare is facing a crisis: namely, there is a steady unsustainable increase in medical costs without a corresponding improvement of patient outcomes. We believe that analysis of clinical, life sciences and medical process data can play a key role in tackling these fundamental challenges. Two technology advances, in particular, can play a key role: cloud computing and mobility will make it possible to analyze vast amounts of data and quickly deliver useful information to clinicians, consumers and researchers at the point where it can have the most impact. Some of this is already happening today, with medical records being analyzed to reduce fraud, waste and abuse, improve patient outcomes, and to improve compliance with standards of care and policy guidelines. We conclude the talk with a glimpse of a future where medical systems could be continually analyzed for optimizing healthcare costs and outcomes.
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