医疗管理的医疗保健分析

Vinay Kommera
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引用次数: 0

摘要

医疗机构需要一个强大的系统来帮助他们维持一个健康的环境,包括不断努力通过提供正确的治疗来改善病人的护理。为了实现这一目标,医疗保健分析用于系统地管理大量电子收集的医疗保健数据,目的是改善患者的医疗保健,降低成本,并通过与相关医生联系,在适当的时间采取必要的行动,以确保适当的治疗,从而优先考虑挽救患者的生命。医疗保健分析(也称为大数据分析)不仅仅是关于管理大量和不断增长的数据。它还涉及从医疗保健数据库中发现的模式中提取见解。分析深入挖掘实时数据中的意义;对未来做出预测,为成功铺平道路。明智地实施医疗保健分析可以改变医疗保健行业的运营方式,这意味着它只会导致有利的方向,例如它可以帮助医疗保健提供商减少欺诈、浪费和滥用,从而推动业务增长、提高生产力、改善患者护理、降低医疗费用、提高账单透明度、减少不必要的医疗测试以及比您想象的更多。最重要的是,使用分析可以改善医疗保健部门的工作流程。医疗保健行业要达到更高的高度,需要对庞大且不断流动的数据库实施医疗保健分析,以产生最佳结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Healthcare Analytics for Medical Management
Healthcare organizations need a powerful system that can help them maintain a healthy environment which involves constantly striving to improve patient care by delivering the right kind of treatment. To achieve this Healthcare Analytics is used to manage huge healthcare data systematically, that is collected electronically, the purpose being improve patient healthcare, reduce cost, and give top priority to save the patient's life by taking necessary action at the right time by connecting with the concerned physician who can assure proper treatment. Healthcare Analytics also referred to as big data analytics is not only about managing massive and ever-growing data. It's also about extracting insights from patterns found in the healthcare database. Analytics dives deep to explore meaning in the realtime data; make predictions about future which can pave the way to the path of success. Implementing Healthcare Analytics wisely can change the way healthcare sectors operate, meaning it can only lead to advantageous direction like it can help healthcare providers reduce fraud, waste and abuse which in turn can drive to business growth, improve productivity, improve patient care, cut down medical expenses, transparency in billing, reduce unnecessary medical tests and much more than you can imagine. Most importantly using analytics can improve workflow across healthcare sectors. Healthcare industry to reach great heights needs to enforce Healthcare Analytics to the huge and everflowing database to produce the best consequences.
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