Journal:Learning health systems need to bridge the "two cultures" of clinical informatics and data science
| Full article title | Learning health systems need to bridge the "two cultures" of clinical informatics and data science |
|---|---|
| Journal | Journal of Innovation in Health Informatics |
| Author(s) | Scott, Philip J.; Dunscombe, Rachel; Evans, David; Mukherjee, Mome; Wyatt, Jeremy C. |
| Author affiliation(s) | University of Portsmouth, Salford Royal NHS Foundation Trust, British Computer Society, University of Edinburgh, University of Southampton |
| Primary contact | Email: Philip dot scott at port dot ac dot uk |
| Year published | 2018 |
| Volume and issue | 25(2) |
| Page(s) | 126–31 |
| DOI | 10.14236/jhi.v25i2.1062 |
| ISSN | 1687-8035 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.hindawi.com/journals/abi/2018/4059018/ |
| Download | http://downloads.hindawi.com/journals/abi/2018/4059018.pdf (PDF) |
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Abstract
Background: United Kingdom (U.K.) 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 also 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 U.K., 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 U.K. 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 recognize that the full social and economic benefits of digital health and data science can only be realized by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.
Keywords: big data, health informatics, bioinformatics, evidence-based practice, health policy, program evaluation, education, learning health systems
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Notes
This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.
