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      Digital innovation evaluation: user perceptions of innovation readiness, digital confidence, innovation adoption, user experience and behaviour change

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          Abstract

          Background

          Innovation spread is a key policy objective for health systems world-wide, but adoption success varies enormously. We have developed a set of short generic user-reported measures to help understand how and why healthcare innovations spread. This work builds on the literature and on practical experience in developing and using patient-reported outcome measures.

          Measures

          The Innovation Readiness Score measures user perceptions of how much they are open to and up-to-date with new ideas, and whether their organisations are receptive to and capable of innovation. It is based on Rogers’ classification of innovativeness (innovator, early adopter, early majority, etc).

          The Digital Confidence Score rates users’ digital literacy and confidence to use digital products, with dimensions of familiarity, social pressure, support and digital self-efficacy.

          The Innovation Adoption Score rates the adoption process in terms of coherence and reflective thought before, during and after implementation. It is based on Normalisation Process Theory.

          The User Satisfaction measure assesses a digital product in terms of usefulness, ease of use, support and satisfaction.

          The Behaviour Change measure covers user perceptions of their capability, opportunity and motivation to change behaviour, based on the COM-B model.

          These measures have been mapped onto Greenhalgh’s NASSS Framework (non-adoption, abandonment and challenges to scale-up, spread and sustainability of health and care technologies).

          Conclusion

          These tools measure different aspects of digital health innovations and may help predict the success of innovation dissemination, diffusion and spread programmes.

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          Most cited references6

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          Assessment of Remote Heart Rhythm Sampling Using the AliveCor Heart Monitor to Screen for Atrial Fibrillation

          Asymptomatic atrial fibrillation (AF) is increasingly common in the aging population and implicated in many ischemic strokes. Earlier identification of AF with appropriate anticoagulation may decrease stroke morbidity and mortality.
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            Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework

            Background Failures and partial successes are common in technology-supported innovation programmes in health and social care. Complexity theory can help explain why. Phenomena may be simple (straightforward, predictable, few components), complicated (multiple interacting components or issues) or complex (dynamic, unpredictable, not easily disaggregated into constituent components). The recently published NASSS framework applies this taxonomy to explain Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability. This paper reports the first empirical application of the NASSS framework. Methods Six technology-supported programmes were studied using ethnography and action research for up to 3 years across 20 health and care organisations and 10 national-level bodies. They comprised video outpatient consultations, GPS tracking technology for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organising software and integrated case management via data warehousing. Data were collected at three levels: micro (individual technology users), meso (organisational processes and systems) and macro (national policy and wider context). Data analysis and synthesis were guided by socio-technical theories and organised around the seven NASSS domains: (1) the condition or illness, (2) the technology, (3) the value proposition, (4) the adopter system (professional staff, patients and lay carers), (5) the organisation(s), (6) the wider (institutional and societal) system and (7) interaction and mutual adaptation among all these domains over time. Results The study generated more than 400 h of ethnographic observation, 165 semi-structured interviews and 200 documents. The six case studies raised multiple challenges across all seven domains. Complexity was a common feature of all programmes. In particular, individuals’ health and care needs were often complex and hence unpredictable and ‘off algorithm’. Programmes in which multiple domains were complicated proved difficult, slow and expensive to implement. Those in which multiple domains were complex did not become mainstreamed (or, if mainstreamed, did not deliver key intended outputs). Conclusion The NASSS framework helped explain the successes, failures and changing fortunes of this diverse sample of technology-supported programmes. Since failure is often linked to complexity across multiple NASSS domains, further research should systematically address ways to reduce complexity and/or manage programme implementation to take account of it.
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              A short generic patient experience questionnaire: howRwe development and validation

              Background Patient experience is a key quality outcome for modern health services, but most existing survey methods are long and setting-specific. We identified the need for a short generic questionnaire for tracking patient experience. Methods We describe the development and validation of the howRwe questionnaire. This has two items relating to clinical care (treat you kindly; listen and explain) and two items relating to the organisation of care (see you promptly; well organised) as perceived by patients. Each item has four responses (excellent, good, fair and poor). The questionnaire was trialled in 828 patients in an orthopaedic pre-operative assessment clinic (PAC). Results The howRwe questionnaire is shorter (29 words) and more readable (Flesch-Kincaid grade score 2.2) than other questionnaires with broadly similar objectives. Psychometric properties in this sample are good with Cronbach’s α=0.82. Following a change to the appointments system in the clinic, howRwe showed improvement in promptness and organisation, but not in kindness and communication, showing that it can distinguish between the clinical and organisational aspects of patient experience. Conclusions howRwe meets the criteria for a short generic patient experience questionnaire that is suitable for frequent use. In the validation study of PAC patients, it showed good psychometric properties and concurrent, construct and discriminant validity.
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                Author and article information

                Journal
                BMJ Health Care Inform
                BMJ Health Care Inform
                bmjhci
                bmjhci
                BMJ Health & Care Informatics
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2632-1009
                2019
                17 April 2019
                : 26
                : 1
                : e000018
                Affiliations
                [1 ] R-Outcomes Ltd , Newbury, UK
                [2 ] UCL Institute of Health Informatics , London, UK
                Author notes
                [Correspondence to ] Tim Benson, R-Outcomes Ltd, Hermitage, Thatcham RG18 9WL, UK; tim.benson@ 123456r-outcomes.com
                Article
                bmjhci-2019-000018
                10.1136/bmjhci-2019-000018
                7062319
                31039121
                6f5d7a98-a0fd-4d58-b2d4-33d7d0c46c5a
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0

                History
                : 19 August 2018
                : 02 March 2019
                : 13 March 2019
                Categories
                Original Research
                1506
                Custom metadata
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                innovation diffusion,computer literacy,consumer behaviour,program evaluation,behaviour change

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