New Horizons in the use of routine data for ageing research.
10 February 2020
This article looks at new horizons in the use of routine data for ageing research. This includes prognostic research, clinical trials, and service evaluations. The authors highlight the need for multidisciplinary collaboration. They identify three key areas where the application of routine data has major benefits for research in ageing - prediction (developing prediction tools to identify levels of future risk of outcomes thereby helping in decision making), clinical trials (routine data can help extend participation in clinical trials), and service evaluation (understanding performance of clinical services by measuring outcomes in routine data).
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Todd OM, Burton JK, Dodds RM, Hollinghurst J, Lyons RA, Quinn TJ, Schneider A, Walesby KE, Wilkinson C, Conroy S, Gale CP, Hall M, Walters K, Clegg AP.
British Geriatrics Society, (2020) pg 1-7
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.