Modelling clinical narrative as computable knowledge: The NICE computable implementation guidance project

Author:

Scott Philip1ORCID,Heigl Michaela2,McCay Charles34,Shepperdson Polly5,Lima‐Walton Elia6,Andrikopoulou Elisavet7,Brunnhuber Klara6,Cornelius Gary8,Faulding Susan2,McAlister Ben910,Rowark Shaun2,South Matthew1112ORCID,Thomas Mark R.12,Whatling Justin213,Williams John14,Wyatt Jeremy C.15ORCID,Greaves Felix2

Affiliation:

1. Institute of Management & Health University of Wales Trinity Saint David Carmarthen Wales UK

2. NICE Manchester UK

3. Ramsey Systems Shrewsbury UK

4. Professional Record Standards Body London UK

5. First Data Bank UK Ltd Exeter UK

6. Elsevier Ltd London UK

7. School of Computing University of Portsmouth Portsmouth UK

8. Computer & Information Sciences University of Strathclyde Glasgow Scotland UK

9. HL7 UK Whitchurch UK

10. Oracle Health London UK

11. Open Clinical CIC Loughton UK

12. Institute of Applied Health Research University of Birmingham Birmingham UK

13. Palantir Technologies Inc. Denver Colorado USA

14. Faculty of Clinical Informatics London UK

15. University of Southampton Southampton UK

Abstract

AbstractIntroductionTranslating narrative clinical guidelines to computable knowledge is a long‐standing challenge that has seen a diverse range of approaches. The UK National Institute for Health and Care Excellence (NICE) Content Advisory Board (CAB) aims ultimately to (1) guide clinical decision support and other software developers to increase traceability, fidelity and consistency in supporting clinical use of NICE recommendations, (2) guide local practice audit and intervention to reduce unwarranted variation, (3) provide feedback to NICE on how future recommendations should be developed.ObjectivesThe first phase of work was to explore a range of technical approaches to transition NICE toward the production of natively digital content.MethodsFollowing an initial ‘collaborathon’ in November 2022, the NICE Computable Implementation Guidance project (NCIG) was established. We held a series of workstream calls approximately fortnightly, focusing on (1) user stories and trigger events, (2) information model and definitions, (3) horizon‐scanning and output format. A second collaborathon was held in March 2023 to consolidate progress across the workstreams and agree residual actions to complete.ResultsWhile we initially focussed on technical implementation standards, we decided that an intermediate logical model was a more achievable first step in the journey from narrative to fully computable representation. NCIG adopted the WHO Digital Adaptation Kit (DAK) as a technology‐agnostic method to model user scenarios, personae, processes and workflow, core data elements and decision‐support logic. Further work will address indicators, such as prescribing compliance, and implementation in document templates for primary care patient record systems.ConclusionsThe project has shown that the WHO DAK, with some modification, is a promising approach to build technology‐neutral logical specifications of NICE recommendations. Implementation of concurrent computable modelling by multidisciplinary teams during guideline development poses methodological and cultural questions that are complex but tractable given suitable will and leadership.

Publisher

Wiley

Subject

Health Information Management,Public Health, Environmental and Occupational Health,Health Informatics

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