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      The NICE Evidence Standards Framework for digital health and care technologies – Developing and maintaining an innovative evidence framework with global impact

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          Abstract

          Objective

          In 2018, the UK National Institute for Health and Care Excellence (NICE), in partnership with Public Health England, NHS England, NHS Improvement and others, developed an evidence standards framework (ESF) for digital health and care technologies (DHTs). The ESF was designed to provide a standardised approach to guide developers and commissioners on the levels of evidence needed for the clinical and economic evaluation of DHTs by health and care systems.

          Methods

          The framework was developed using an agile and iterative methodology that included a literature review of existing initiatives and comparison of these against the requirements set by NHS England; iterative consultation with stakeholders through an expert working group and workshops; and questionnaire-based stakeholder input on a publicly available draft document.

          Results

          The evidence standards framework has been well-received and to date the ESF has been viewed online over 55,000 times and downloaded over 19,000 times.

          Conclusions

          In April 2021 we published an update to the ESF. Here, we summarise the process through which the ESF was developed, reflect on its global impact to date, and describe NICE’s ongoing work to maintain and improve the framework in the context for a fast moving, innovative field.

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          Most cited references21

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          Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

          Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.
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            Evaluating Digital Health Interventions: Key Questions and Approaches.

            Digital health interventions have enormous potential as scalable tools to improve health and healthcare delivery by improving effectiveness, efficiency, accessibility, safety, and personalization. Achieving these improvements requires a cumulative knowledge base to inform development and deployment of digital health interventions. However, evaluations of digital health interventions present special challenges. This paper aims to examine these challenges and outline an evaluation strategy in terms of the research questions needed to appraise such interventions. As they are at the intersection of biomedical, behavioral, computing, and engineering research, methods drawn from all of these disciplines are required. Relevant research questions include defining the problem and the likely benefit of the digital health intervention, which in turn requires establishing the likely reach and uptake of the intervention, the causal model describing how the intervention will achieve its intended benefit, key components, and how they interact with one another, and estimating overall benefit in terms of effectiveness, cost effectiveness, and harms. Although RCTs are important for evaluation of effectiveness and cost effectiveness, they are best undertaken only when: (1) the intervention and its delivery package are stable; (2) these can be implemented with high fidelity; and (3) there is a reasonable likelihood that the overall benefits will be clinically meaningful (improved outcomes or equivalent outcomes at lower cost). Broadening the portfolio of research questions and evaluation methods will help with developing the necessary knowledge base to inform decisions on policy, practice, and research.
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              Deriving a practical framework for the evaluation of health apps

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                Author and article information

                Journal
                Digit Health
                Digit Health
                DHJ
                spdhj
                Digital Health
                SAGE Publications (Sage UK: London, England )
                2055-2076
                24 June 2021
                Jan-Dec 2021
                : 7
                : 20552076211018617
                Affiliations
                [1 ]Department of Computer Science, University of Liverpool, UK
                [2 ]Centre for Health Technology Evaluation, NICE, Manchester, UK
                [3 ]Digital, Information and Technology Directorate, NICE, Manchester, UK
                [4 ]Health and Social Care Directorate, NICE, Manchester, UK
                [5 ]MedCity, London, UK
                [6 ]Science, Evidence and Analytics Directorate, NICE, Manchester, UK
                [7 ]NHSx, London, UK
                [8 ]Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
                Author notes
                [*]Harriet Unsworth, University of Liverpool, Liverpool, UK. Email: h.unsworth@ 123456liverpool.ac.uk
                Author information
                https://orcid.org/0000-0002-1427-6783
                https://orcid.org/0000-0002-7909-3769
                https://orcid.org/0000-0003-4226-4349
                https://orcid.org/0000-0002-8055-3873
                Article
                10.1177_20552076211018617
                10.1177/20552076211018617
                8236783
                34249371
                8984d420-c1b2-4583-aabd-7645f97e30f1
                © The Author(s) 2021

                Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License ( https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 7 December 2020
                : 24 April 2021
                Categories
                Policy and Practice
                Custom metadata
                January-December 2021
                ts2

                health economics,health technology assessment,digital health,general,clinical evidence

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