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      Consumer preference to utilise a mobile health app: A stated preference experiment

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      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          One prominent barrier faced by healthcare consumers when accessing health services is a common requirement to complete repetitive, inefficient paper-based documentation at multiple registration sites. Digital innovation has a potential role to reduce the burden in this area, through the collection and sharing of data between healthcare providers. While there is growing evidence for digital innovations to potentially improve the effectiveness and efficiency of health systems, there is less information on the willingness of healthcare consumers to embrace and utilise technology to provide data.

          Aim

          The study aims to improve understanding of consumers’ preference for utilising a digital health administration mobile app.

          Methods

          The online study used a stated preference experiment design to explore aspects of consumers’ preference for a mobile health administration app and its impact on the likelihood of using the app. The survey was answered by a representative sample (by age and gender) of Australian adults, and sociodemographic factors were also recorded for analysis. Each participant answered eight choice sets in which a hypothetical app (defined by a set of dimensions and levels) was presented and the respondent was asked if they would be willing to provide data using that app. Analysis was conducted using bivariate logistic regression.

          Results

          For the average respondent, the two most important dimensions were the time it took to register on the app and the electronic governance arrangements around their personal information. Willingness to use any app was found to differ based on respondent characteristics: people with higher education, and women, were relatively more willing to utilise the mobile health app.

          Conclusion

          This study investigated consumers’ willingness to utilise a digital health administration mobile app. The identification of key characteristics of more acceptable apps provide valuable insight and recommendations for developers of similar digital health administration technologies. This would increase the likelihood of achieving successful acceptance and utilisation by consumers. The results from this study provide evidence-based recommendations for future research and policy development, planning and implementation of digital health administration mobile applications in Australia.

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          Most cited references29

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          A systematic review of patient acceptance of consumer health information technology.

          A systematic literature review was performed to identify variables promoting consumer health information technology (CHIT) acceptance among patients. The electronic bibliographic databases Web of Science, Business Source Elite, CINAHL, Communication and Mass Media Complete, MEDLINE, PsycArticles, and PsycInfo were searched. A cited reference search of articles meeting the inclusion criteria was also conducted to reduce misses. Fifty-two articles met the selection criteria. Among them, 94 different variables were tested for associations with acceptance. Most of those tested (71%) were patient factors, including sociodemographic characteristics, health- and treatment-related variables, and prior experience or exposure to computer/health technology. Only ten variables were related to human-technology interaction; 16 were organizational factors; and one was related to the environment. In total, 62 (66%) were found to predict acceptance in at least one study. Existing literature focused largely on patient-related factors. No studies examined the impact of social and task factors on acceptance, and few tested the effects of organizational or environmental factors on acceptance. Future research guided by technology acceptance theories should fill those gaps to improve our understanding of patient CHIT acceptance, which in turn could lead to better CHIT design and implementation.
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            Systematic review of approaches to using patient experience data for quality improvement in healthcare settings

            Objectives Explore how patient-reported experience measures (PREMs) are collected, communicated and used to inform quality improvement (QI) across healthcare settings. Design Systematic review. Setting Various primary and secondary care settings, including general practice, and acute and chronic care hospitals. Participants A full range of patient populations from (children through to the elderly) and staff (from healthcare practitioners to senior managers). Methods Scientific databases were searched (CINAHL, PsycINFO, MEDLINE and Cochrane Libraries) as was grey literature. Qualitative and quantitative studies describing collection of PREM data and subsequent QI actions in any healthcare setting were included. Risk of bias was assessed using established criteria. Of 5312 initial hits, 32 full texts were screened, and 11 were included. Results Patient experience data were most commonly collected through surveys and used to identify small areas of incremental change to services that do not require a change to clinician behaviour (eg, changes to admission processes and producing educational materials). While staff in most studies reported having made effective improvements, authors struggled to identify what those changes were or the impact they had. Conclusions Findings suggest there is no single best way to collect or use PREM data for QI, but they do suggest some key points to consider when planning such an approach. For instance, formal training is recommended, as a lack of expertise in QI and confidence in interpreting patient experience data effectively may continue to be a barrier to a successful shift towards a more patient-centred healthcare service. In the context of QI, more attention is required on how patient experience data will be used to inform changes to practice and, in turn, measure any impact these changes may have on patient experience.
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              The effectiveness of internet-based e-learning on clinician behavior and patient outcomes: a systematic review protocol.

              The objective of this systematic review is to identify, appraise and synthesize the best available evidence for the effectiveness of internet-based e-learning programs on health care professional behavior and patient outcomes.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Supervision
                Role: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                21 February 2020
                2020
                : 15
                : 2
                : e0229546
                Affiliations
                [001]School of Public Health, Curtin University, Perth, Australia
                University of Ghana College of Health Sciences, GHANA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-8732-4320
                Article
                PONE-D-19-28394
                10.1371/journal.pone.0229546
                7034842
                32084250
                c395170d-5b95-4811-972a-136348370a9f
                © 2020 Lim et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 October 2019
                : 8 February 2020
                Page count
                Figures: 2, Tables: 2, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Computer and Information Sciences
                Computer Software
                Apps
                Medicine and Health Sciences
                Health Care
                Health Services Administration and Management
                Research and Analysis Methods
                Research Design
                Survey Research
                Surveys
                Medicine and Health Sciences
                Health Care
                Health Care Policy
                Engineering and Technology
                Management Engineering
                Risk Management
                Insurance
                Medicine and Health Sciences
                Health Care
                Health Care Providers
                Research and Analysis Methods
                Research Design
                Experimental Design
                Computer and Information Sciences
                Data Management
                Custom metadata
                All three data files are available from the Research Data Australia database. Available at http://dx.doi.org/10.25917/5e256ca31c855.

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                Uncategorized

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