Todd Oliver M, Burton Jennifer K, Dodds Richard M, Hollinghurst Joe, Lyons Ronan A, Quinn Terence J, Schneider Anna, Walesby Katherine E, Wilkinson Chris, Conroy Simon, Gale Chris P, Hall Marlous, Walters Kate, Clegg Andrew P
Academic Unit of Elderly Care and Rehabilitation, Bradford Teaching Hospitals NHS Trust, University of Leeds, Bradford, UK.
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Age Ageing. 2020 Aug 24;49(5):716-722. doi: 10.1093/ageing/afaa018.
The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people.
在过去三十年中，常规收集的健康和社会护理数据的可用性以及分析这些数据的处理能力一直在稳步提高。这些发展为老龄化研究带来了重大机遇，特别是通过整合跨越健康和社会护理传统界限的不同数据集，进行预后研究以及对具有代表性的老年人群体的干预措施进行新颖评估。然而，在编码、数据分析以及将研究结果应用于日常护理等层面使用常规数据存在相当大的挑战。在老龄化研究中应用常规数据来探究新问题的新视野需要临床医生、数据科学家、生物统计学家、流行病学家和试验方法学家之间采取协作方法。这需要在这一重要领域培养下一代研究领导者的能力。有必要针对与老年人相关的常见病症和结局制定共识编码列表以及标准化、经过验证的算法，以最大限度地发挥该群体常规数据研究的潜力。最后，我们必须通过开发利用常规数据基础设施评估干预措施的新方法，推动常规数据的应用以改善老年人的护理。我们相信，利用常规数据有助于填补患有多种疾病和身体虚弱的老年人的知识空白，并设计干预措施和护理途径，以解决我们在照顾老年人时面临的复杂健康问题。
