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CLINICAL DECISION SUPPORT: WHAT WILL HAPPEN IN THE 2020S?
Clinical decision support may be defined as ‘a process for enhancing health-related decisions and actions with pertinent, organized, clinical knowledge, and patient information to improve health and healthcare delivery’.1 The aim is to assist when even relatively simple problems (such as the management of chest pain after coronary artery bypass surgery) are in fact enormously complex for most humans to deal with.2 Clinical decision support has changed substantially over the past 20 years and no doubt will continue to change in the 2020s. However, it is unclear to what extent it will change and exactly what new directions this field will take. Some think that there will be a dramatic change. They think that drivers of this transformational change will be data, evidence from both research and databases, algorithms, patient-specific guidance and artificial intelligence that will enable information technologies to learn from outcomes and continually improve.3–5 This may all be correct—but the extent to which it is really new is questionable. Online clinical decision support has been around since the internet has been around. One of the earliest papers that attempted to predict the future of online clinical decision support was published in 1998: it is ‘Online practice guidelines: issues, obstacles, and future prospects’ by Rita Zielstorff.6 And what does this paper predict? It suggests that the future will be about ‘data mining’, ‘algorithms and decision tables’, ‘patient-specific decision support’ and patient outcomes that ‘can be facilitated by the clinical information system, providing the means to refine the guideline and improve practice still further’. The words and phrases are slightly different from those that we use today, but the ideas are largely the same. The most striking difference from papers of the past few years is the absence of hype.
It seems that patient-specific decision support …
Contributors Both authors made substantial contributions to the conception and design of the work; both revised it critically for important intellectual content, and approved the final version to be published.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests KW and CW work for BMJ which produces the clinical decision support tool BMJ Best Practice. CW is also a member of the SMART Health IT Advisory Committee.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.