Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review

Scheibner, James; Sleigh, Joanna; Ienca, Marcello

doi:10.1093/jamia/ocab096

Cited by 34 publications

(16 citation statements)

References 83 publications

(92 reference statements)

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“…They also favor eHealth technology that enables shared decision-making, physical exercise training, socializing, and booking health examinations [ 62 , 66 , 67 , 92 , 93 ]. In addition, users find convenient and easy-to-use eHealth to be more attractive, suggesting that usability and technology acceptance should be taken into consideration when designing and implementing technology for eHealth, which is consistent with the literature [ 86 , 94 - 103 ].…”

Section: Discussionsupporting

confidence: 84%

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Xie¹,

Chen²,

Or³

2022

J Med Internet Res

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Background Despite the great potential of eHealth, substantial costs are involved in its implementation, and it is essential to know whether these costs can be justified by its benefits. Such needs have led to an increased interest in measuring the benefits of eHealth, especially using the willingness to pay (WTP) metric as an accurate proxy for consumers’ perceived benefits of eHealth. This offered us an opportunity to systematically review and synthesize evidence from the literature to better understand WTP for eHealth and its influencing factors. Objective This study aimed to provide a systematic review of WTP for eHealth and its influencing factors. Methods This study was performed and reported as per the Cochrane Collaboration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, CINAHL Plus, Cochrane Library, EconLit, and PsycINFO databases were searched from their inception to April 19, 2022. We conducted random-effects meta-analyses to calculate WTP values for eHealth (at 2021 US dollar rates) and meta-regression analyses to examine the factors affecting WTP. Results A total of 30 articles representing 35 studies were included in the review. We found that WTP for eHealth varied across studies; when expressed as a 1-time payment, it ranged from US $0.88 to US $191.84, and when expressed as a monthly payment, it ranged from US $5.25 to US $45.64. Meta-regression analyses showed that WTP for eHealth was negatively associated with the percentages of women (β=−.76; P<.001) and positively associated with the percentages of college-educated respondents (β=.63; P<.001) and a country’s gross domestic product per capita (multiples of US $1000; β=.03; P<.001). Compared with eHealth provided through websites, people reported a lower WTP for eHealth provided through asynchronous communication (β=−1.43; P<.001) and a higher WTP for eHealth provided through medical devices (β=.66; P<.001), health apps (β=.25; P=.01), and synchronous communication (β=.58; P<.001). As for the methods used to measure WTP, single-bounded dichotomous choice (β=2.13; P<.001), double-bounded dichotomous choice (β=2.20; P<.001), and payment scale (β=1.11; P<.001) were shown to obtain higher WTP values than the open-ended format. Compared with ex ante evaluations, ex post evaluations were shown to obtain lower WTP values (β=−.37; P<.001). Conclusions WTP for eHealth varied significantly depending on the study population, modality used to provide eHealth, and methods used to measure it. WTP for eHealth was lower among certain population segments, suggesting that these segments may be at a disadvantage in terms of accessing and benefiting from eHealth. We also identified the modalities of eHealth that were highly valued by consumers and offered suggestions for the design of eHealth interventions. In addition, we found that different methods of measuring WTP led to significantly different WTP estimates, highlighting the need to undertake further methodological explorations of approaches to elicit WTP values.

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Section: Discussionsupporting

confidence: 84%

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Xie¹,

Chen²,

Or³

2022

J Med Internet Res

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“…There is also a lack of eHealth regulations, which is a major barrier to the development of eHealth [ 76 ]. The most common regulations used in eHealth implementation are national data and privacy protection laws and regulations, as well as national EHR and health financing legislation [ 77 ]. Health financing legislation is critical to ensure the continued sustainability and support of eHealth.…”

Section: Discussionmentioning

confidence: 99%

Effectiveness of eHealth Self-management Interventions in Patients With Heart Failure: Systematic Review and Meta-analysis

Liu¹,

Li²,

Wan³

et al. 2022

J Med Internet Res

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Background Heart failure (HF) is a common clinical syndrome associated with substantial morbidity, a heavy economic burden, and high risk of readmission. eHealth self-management interventions may be an effective way to improve HF clinical outcomes. Objective The aim of this study was to systematically review the evidence for the effectiveness of eHealth self-management in patients with HF. Methods This study included only randomized controlled trials (RCTs) that compared the effects of eHealth interventions with usual care in adult patients with HF using searches of the EMBASE, PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL databases from January 1, 2011, to July 12, 2022. The Cochrane Risk of Bias tool (RoB 2) was used to assess the risk of bias for each study. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria were used to rate the certainty of the evidence for each outcome of interest. Meta-analyses were performed using Review Manager (RevMan v.5.4) and R (v.4.1.0 x64) software. Results In total, 24 RCTs with 9634 participants met the inclusion criteria. Compared with the usual-care group, eHealth self-management interventions could significantly reduce all-cause mortality (odds ratio [OR] 0.83, 95% CI 0.71-0.98, P=.03; GRADE: low quality) and cardiovascular mortality (OR 0.74, 95% CI 0.59-0.92, P=.008; GRADE: moderate quality), as well as all-cause readmissions (OR 0.82, 95% CI 0.73-0.93, P=.002; GRADE: low quality) and HF-related readmissions (OR 0.77, 95% CI 0.66-0.90, P<.001; GRADE: moderate quality). The meta-analyses also showed that eHealth interventions could increase patients’ knowledge of HF and improve their quality of life, but there were no statistically significant effects. However, eHealth interventions could significantly increase medication adherence (OR 1.82, 95% CI 1.42-2.34, P<.001; GRADE: low quality) and improve self-care behaviors (standardized mean difference –1.34, 95% CI –2.46 to –0.22, P=.02; GRADE: very low quality). A subgroup analysis of primary outcomes regarding the enrolled population setting found that eHealth interventions were more effective in patients with HF after discharge compared with those in the ambulatory clinic setting. Conclusions eHealth self-management interventions could benefit the health of patients with HF in various ways. However, the clinical effects of eHealth interventions in patients with HF are affected by multiple aspects, and more high-quality studies are needed to demonstrate effectiveness.

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“…The recent COVID-19 pandemic and the subsequent need for online digital resources revealed a window of opportunity to harness the paper-based TIR digitally to provide better ease of use and incorporate project management functionality (48-50). The health bene ts of digital tools are widely noted in the literature (51,52), including user accessibility, learnability, navigation, control and input, and data collection (40) and are amenable to the integration of emerging evidence and tools over time (53). Some e-health technologies have emerged in recent years to support implementation, but they are population or disease-speci c. For example, The Implementation Pain Practice Change (ImPaC) Resource is an evidence-based online and interactive resource that guides healthcare teams through a practice change speci c to improving infant pain assessment and management in the NICU (54).…”

Section: The Pivot To Digitalmentioning

confidence: 99%

The Implementation Playbook: study protocol for the development and feasibility evaluation of a digital tool for effective implementation of evidence-based innovations

Barwick

Brown²,

Petricca

et al. 2023

Preprint

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Background Evidence-based innovations can improve health outcomes, but only if successfully implemented. Implementation can be complex, highly susceptible to failure, costly and resource intensive. Internationally, there is an urgent need to improve the implementation of effective innovations. Successful implementation is best guided by implementation science, but organizations lack implementation know-how and have difficulty applying it. Implementation support is typically shared in static, non-interactive, overly academic guides and is rarely evaluated. In-person implementation facilitation is often soft-funded, costly, and scarce. This study seeks to improve effective implementation by (1) developing a first-in-kind digital tool to guide pragmatic, empirically based and self-directed implementation planning in real-time; and (2) exploring the tool’s feasibility in six health organizations implementing different innovations. Methods Ideation emerged from a paper-based resource, The Implementation Game©, and a revision called The Implementation Roadmap©; both integrate core implementation components from evidence, models and frameworks to guide structured, explicit, and pragmatic planning. Prior funding also generated user personas and high-level product requirements. This study will design, develop, and evaluate the feasibility of a digital tool called The Implementation Playbook©. In Phase 1, user-centred design and usability testing will inform tool content, visual interface, and functions to produce a minimum viable product. Phase 2 will explore the Playbook’s feasibility in six purposefully selected health organizations sampled for maximum variation. Organizations will use the Playbook for up to 24 months to implement an innovation of their choosing. Mixed methods will gather: (i) field notes from implementation team check-in meetings; (ii) interviews with implementation teams about their experience using the tool; (iii) user free-form content entered into the tool as teams work through implementation planning; (iv) Organizational Readiness for Implementing Change questionnaire; (v) System Usability Scale; and (vi) tool metrics on how users progressed through activities and the time required to do so. Discussion Effective implementation of evidence-based innovations is essential for optimal health. We seek to develop a prototype digital tool and demonstrate its feasibility and usefulness across organizations implementing different innovations. This technology could fill a significant need globally, be highly scalable, and potentially valid for diverse organizations implementing various innovations.

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Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review

Cited by 34 publications

References 83 publications

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Effectiveness of eHealth Self-management Interventions in Patients With Heart Failure: Systematic Review and Meta-analysis

The Implementation Playbook: study protocol for the development and feasibility evaluation of a digital tool for effective implementation of evidence-based innovations

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