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首页> 外文期刊>Journal of health services research & policy >Predictive risk modelling using routine data: Underexploited potential to benefit patients
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Predictive risk modelling using routine data: Underexploited potential to benefit patients

机译:使用常规数据预测风险建模:潜在的潜在潜力益处患者

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摘要

Huge amounts of data on individuals are now routinely collected electronically in the public sector in the UK. The NHS, as a single payer, can mandate data collection with a degree of consistency for almost the whole population of the UK, and creates one of the best sources of routinely collected data on health care in the world. These data are best for patient encounters in inpatient, outpatient and A& E settings, as well as the comprehensive coverage of people registered in general practice. As they have unique identifiers, with the right security mechanism in place to protect confidentiality, it is possible to link records over time and across services. These can be augmented at a local level by data on social care and, sometimes, community health services. These data receive an enormous boost in April 2013 in England when anonymized person level data on use of primary care by all people registered with a general practice will become available.
机译:现在常规地在英国的公共部门内常规地收集有关个人数据。 NHS作为单一付款人,可以使用英国的整个人口的几乎全部人口一致,并创造了常规收集了世界的最佳资料之一。 这些数据对于住院病人,门诊和A&E设置中的患者最适合患者,以及在一般练习中注册的人们的全面覆盖范围。 由于它们具有唯一的标识符,具有正确的安全机制来保护机密性,可以随时间和跨服务链接记录。 这些可以通过社会护理数据的数据在地方一级增强,有时是社区卫生服务。 这些数据于2013年4月在英格兰获得了巨大的提升,当时所有在一般惯例中注册的所有人员使用初级保健的匿名人员级数据将获得。

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