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Learning health systems need to bridge the 'two cultures' of clinical informatics and data science

Research output: Contribution to journalArticlepeer-review

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Learning health systems need to bridge the 'two cultures' of clinical informatics and data science. / Scott, Philip J.; Dunscombe, Rachel; Evans, David; Mukherjee, Mome; Wyatt, Jeremy C.

In: Journal of Innovation in Health Informatics, Vol. 25, No. 2, 15.06.2018, p. 126-131.

Research output: Contribution to journalArticlepeer-review

Harvard

Scott, PJ, Dunscombe, R, Evans, D, Mukherjee, M & Wyatt, JC 2018, 'Learning health systems need to bridge the 'two cultures' of clinical informatics and data science', Journal of Innovation in Health Informatics, vol. 25, no. 2, pp. 126-131. https://doi.org/10.14236/jhi.v25i2.1062

APA

Scott, P. J., Dunscombe, R., Evans, D., Mukherjee, M., & Wyatt, J. C. (2018). Learning health systems need to bridge the 'two cultures' of clinical informatics and data science. Journal of Innovation in Health Informatics, 25(2), 126-131. https://doi.org/10.14236/jhi.v25i2.1062

Vancouver

Scott PJ, Dunscombe R, Evans D, Mukherjee M, Wyatt JC. Learning health systems need to bridge the 'two cultures' of clinical informatics and data science. Journal of Innovation in Health Informatics. 2018 Jun 15;25(2):126-131. https://doi.org/10.14236/jhi.v25i2.1062

Author

Scott, Philip J. ; Dunscombe, Rachel ; Evans, David ; Mukherjee, Mome ; Wyatt, Jeremy C. / Learning health systems need to bridge the 'two cultures' of clinical informatics and data science. In: Journal of Innovation in Health Informatics. 2018 ; Vol. 25, No. 2. pp. 126-131.

Bibtex

@article{e5885bc3a0244e8e83ef2f8aaf420a66,
title = "Learning health systems need to bridge the 'two cultures' of clinical informatics and data science",
abstract = "Background - UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational 'Big Data'. Learning health systems require not only data, but feedback loops of knowledge into changed practice. This depends on knowledge management and application, which in turn depends upon effective system design and implementation. Biomedical informatics is the interdisciplinary field at the intersection of health science, social science and information science and technology that spans this entire scope. Issues - In the UK, the separate worlds of health data science (bioinformatics, 'Big Data') and effective healthcare system design and implementation (clinical informatics, 'Digital Health') have operated as 'two cultures'. Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on 'data cleansing' or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. Recommendation - The UK needs increased clinical informatics research and education capacity and capability at much greater scale and ambition to be able to meet policy expectations, address the fundamental gaps in the discipline's evidence base and mitigate the absence of regulation. Independent evaluation of digital health interventions should be the norm, not the exception. Conclusions - Policy makers and research funders need to acknowledge the existing gap between the 'two cultures' and recognise that the full social and economic benefits of digital health and data science can only be realised by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.",
keywords = "Big data, Bioinformatics, Education, Evidence-based practice, Health informatics, Health policy, Learning health systems, Programme evaluation",
author = "Scott, {Philip J.} and Rachel Dunscombe and David Evans and Mome Mukherjee and Wyatt, {Jeremy C.}",
year = "2018",
month = jun,
day = "15",
doi = "10.14236/jhi.v25i2.1062",
language = "English",
volume = "25",
pages = "126--131",
journal = "Journal of Innovation in Health Informatics",
issn = "2058-4555",
publisher = "BCS, The Chartered Institute for IT",
number = "2",

}

RIS

TY - JOUR

T1 - Learning health systems need to bridge the 'two cultures' of clinical informatics and data science

AU - Scott, Philip J.

AU - Dunscombe, Rachel

AU - Evans, David

AU - Mukherjee, Mome

AU - Wyatt, Jeremy C.

PY - 2018/6/15

Y1 - 2018/6/15

N2 - Background - UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational 'Big Data'. Learning health systems require not only data, but feedback loops of knowledge into changed practice. This depends on knowledge management and application, which in turn depends upon effective system design and implementation. Biomedical informatics is the interdisciplinary field at the intersection of health science, social science and information science and technology that spans this entire scope. Issues - In the UK, the separate worlds of health data science (bioinformatics, 'Big Data') and effective healthcare system design and implementation (clinical informatics, 'Digital Health') have operated as 'two cultures'. Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on 'data cleansing' or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. Recommendation - The UK needs increased clinical informatics research and education capacity and capability at much greater scale and ambition to be able to meet policy expectations, address the fundamental gaps in the discipline's evidence base and mitigate the absence of regulation. Independent evaluation of digital health interventions should be the norm, not the exception. Conclusions - Policy makers and research funders need to acknowledge the existing gap between the 'two cultures' and recognise that the full social and economic benefits of digital health and data science can only be realised by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.

AB - Background - UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational 'Big Data'. Learning health systems require not only data, but feedback loops of knowledge into changed practice. This depends on knowledge management and application, which in turn depends upon effective system design and implementation. Biomedical informatics is the interdisciplinary field at the intersection of health science, social science and information science and technology that spans this entire scope. Issues - In the UK, the separate worlds of health data science (bioinformatics, 'Big Data') and effective healthcare system design and implementation (clinical informatics, 'Digital Health') have operated as 'two cultures'. Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on 'data cleansing' or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. Recommendation - The UK needs increased clinical informatics research and education capacity and capability at much greater scale and ambition to be able to meet policy expectations, address the fundamental gaps in the discipline's evidence base and mitigate the absence of regulation. Independent evaluation of digital health interventions should be the norm, not the exception. Conclusions - Policy makers and research funders need to acknowledge the existing gap between the 'two cultures' and recognise that the full social and economic benefits of digital health and data science can only be realised by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.

KW - Big data

KW - Bioinformatics

KW - Education

KW - Evidence-based practice

KW - Health informatics

KW - Health policy

KW - Learning health systems

KW - Programme evaluation

UR - http://www.scopus.com/inward/record.url?scp=85048995502&partnerID=8YFLogxK

U2 - 10.14236/jhi.v25i2.1062

DO - 10.14236/jhi.v25i2.1062

M3 - Article

AN - SCOPUS:85048995502

VL - 25

SP - 126

EP - 131

JO - Journal of Innovation in Health Informatics

JF - Journal of Innovation in Health Informatics

SN - 2058-4555

IS - 2

ER -

ID: 10924844