Scaling Digital Health Innovation: Developing a New ‘Service Readiness Level’ Framework of Evidence

Janette Hughes, Marilyn Lennon, Robert J. Rogerson and George Crooks
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Janette Hughes: Digital Health & Care Innovation Centre, University of Strathclyde, Inovo Building, 121 George Street, Glasgow G1 1RD, UK
Marilyn Lennon: Department of Computing & Information Science, Livingstone Tower, University of Strathclyde, Glasgow G1 1XQ, UK
Robert J. Rogerson: Technology & Innovation Centre, Institute for Future Cities, University of Strathclyde, 99 George Street, Glasgow G1 1RD, UK
George Crooks: Digital Health & Care Innovation Centre, University of Strathclyde, Inovo Building, 121 George Street, Glasgow G1 1RD, UK

IJERPH, 2021, vol. 18, issue 23, 1-19

Abstract: Digital innovation has scaled exponentially in many sectors including tourism, banking, and retail. It is well cited that the health sector is slower to embrace digital health innovations (DHI) beyond the pilot stage and consequently, many successful DHI pilot projects have failed to scale up. Such failure arises in part from a knowledge gap around what type and level of evidence are needed to convince implementers and decision makers to fund, endorse, or adopt new innovations into care delivery systems and sustainable practice. Much is known about the range of DHI evaluation methods used; however, less is published on the evidence that decision makers need to move innovations to scale. This paper draws on interviews (N = 18) with decision makers/project leads engaged in DHI in Scotland to identify what evidence matters when making DHI adoption/scale decisions. The results are used to present a heuristic service readiness level (SRL) framework that captures the changing nature of the evidence base required over a project lifecycle for progression to scale. We utilise this framework to discuss ‘what evidence’ is required and ‘how data accumulate’ over time to assist project teams to build a ‘DHI case for scale’.

Keywords: service innovation; service readiness; scaling; digital health innovation; evidence; evaluation methods; case for scale (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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