PD17 Automating The Impact Reporting Of NICE Guidance. (23rd December 2022)

• Record Type: Journal Article
• Authors: Rowark, Shaun; Jonsson, Pall; Kent, Seamus
• Is Part Of: International journal of technology assessment in health care. Volume 38(2022)Supplement 1
• Page Start: S96
• Page End: S96
• Publication Date: 2022-12-23
• Subjects: Medical technology -- Periodicals; Technology assessment -- Periodicals; 610.28
• DOI: 10.1017/S0266462322002793
• Languages: English
• ISSNs: 0266-4623

Abstract

Abstract : Introduction: The National Institute for Health and Care Excellence (NICE) intends to automate the way it monitors the uptake, impact, and value of its guidance. Traditionally this has been done by developing impact reports, long documents that, while well received, are time consuming to develop and can quickly become outdated. Methods: We focused on a novel topic that would benefit from new data sources to examine its impact: a rapid guideline for managing the long-term effects of coronavirus disease 2019 (COVID-19). We shortlisted "measurable" recommendations within the guideline that were likely to be captured in data collections. We then reviewed available data sources that included relevant up-to-date data. Finally, we explored what existing methods were available to NICE for automating impact reporting. Results: For long COVID-19 we accessed OpenSAFELY, a secure, transparent software platform for primary care COVID-19 data that was developed in response to the pandemic. This captured data on the management of long COVID-19 in primary care as well as onward referral to specialist clinics. In addition, we accessed data from the CVD-COVID-UK/COVID-IMPACT Consortium, which links general practice records with primary care dispensing data. This enabled us to analyze the impact of the pandemic on the prescribing and dispensing of cardiovascular disease medications. Working with our digital team we developed an automated impact reporting dashboard using Google's data studio. This enabled different views of the data, for example by region or socioeconomic status, to be presented in an automated way. Conclusions: Automating the impact reporting of NICE guidance provides up-to-date information on its value to the health system. While we were able to collect new sources of data and automate some aspects of how these were viewed, full automation requires several enablers. These include an application programming interface between the data sources and NICE, and ensuring that NICE guidance is computer readable so that its measurement is practical in healthcare systems.