Selection of criteria for a telemedicine framework for designing, implementing, monitoring and evaluating telemedicine interventions: Validation using a modified Delphi process.

Objectives: The call to scale up telemedicine services globally as part of the digital health transformation lacks an agreed-upon set of constructs to guide the implementation process. A lack of guidance hinders the development, consolidation, sustainability and optimisation of telemedicine services. The study aims to reach consensus among telemedicine experts on a set of implementation constructs to be developed into an evidence-based support tool. Methods: A modified Delphi study was conducted to evaluate a set of evidence-informed telemedicine implementation constructs comprising cores, domains and items. The study evaluated the constructs consisting of five cores: Assessment of the Current Situation, Development of a Telemedicine Strategy, Development of Organisational Changes, Development of a Telemedicine Service, and Monitoring, Evaluation and Optimisation of Telemedicine Implementation; seven domains: Individual Readiness, Organisational Readiness, Clinical, Economic, Technological and Infrastructure, Regulation, and Monitoring, Evaluation and Optimisation; divided into 53 items. Global telemedicine specialists (n = 247) were invited to participate and evaluate 58 questions. Consensus was set at ≥70%. Results: Forty-five experts completed the survey. Consensus was reached on 78% of the constructs evaluated. Regarding the core constructs, Monitoring, Evaluation and Optimisation of Telemedicine Implementation was determined to be the most important one, and Development of a Telemedicine Strategy the least. As for the domains, the Clinical one had the highest level of consensus, and the Economic one had the lowest. Conclusions: This research advances the field of telemedicine, providing expert consensus on a set of implementation constructs. The findings also highlight considerable divergence in expert opinion on the constructs of reimbursement and incentive mechanisms, resistance to change, and telemedicine champions. The lack of agreement on these constructs warrants attention and may partly explain the barriers that telemedicine services continue to face in the implementation process.

Knowledge management tools and mechanisms for evidence-informed decision-making in the WHO European Region: a scoping review.

BACKGROUND: Knowledge management (KM) emerged as a strategy to promote evidence-informed decision-making. This scoping review aims to map existing KM tools and mechanisms used to promote evidence-informed health decision-making in the WHO European Region and identify knowledge gaps. METHODS: Following the Joanna Briggs Institute (JBI) guidance for conducting scoping reviews, we searched Medline, PubMed, EMBASE, the Cochrane library, and Open Grey. We conducted a descriptive analysis of the general characteristics of the included papers and conducted narrative analysis of the included studies and categorized studies according to KM type and phase. RESULTS: Out of 9541 citations identified, we included 141 studies. The KM tools mostly assessed are evidence networks, surveillance tools, observatories, data platforms and registries, with most examining KM tools in high-income countries of the WHO European region. Findings suggest that KM tools can identify health problems, inform health planning and resource allocation, increase the use of evidence by policymakers and stimulate policy discussion. CONCLUSION: Policymakers and funding agencies are called to support capacity-building activities, and future studies to strengthen KM in the WHO European region particularly in Eastern Europe and Central Asia. An updated over-arching strategy to coordinate KM activities in the WHO European region will be useful in these efforts.

Digital Health Reimbursement Strategies of 8 European Countries and Israel: Scoping Review and Policy Mapping.

BACKGROUND: The adoption of digital health care within health systems is determined by various factors, including pricing and reimbursement. The reimbursement landscape for digital health in Europe remains underresearched. Although various emergency reimbursement decisions were made during the COVID-19 pandemic to enable health care delivery through videoconferencing and asynchronous care (eg, digital apps), research so far has primarily focused on the policy innovations that facilitated this outside of Europe. OBJECTIVE: This study examines the digital health reimbursement strategies in 8 European countries (Belgium, France, Germany, Italy, the Netherlands, Poland, Sweden, and the United Kingdom) and Israel. METHODS: We mapped available digital health reimbursement strategies using a scoping review and policy mapping framework. We reviewed the literature on the MEDLINE, Embase, Global Health, and Web of Science databases. Supplementary records were identified through Google Scholar and country experts. RESULTS: Our search strategy yielded a total of 1559 records, of which 40 (2.57%) were ultimately included in this study. As of August 2023, digital health solutions are reimbursable to some extent in all studied countries except Poland, although the mechanism of reimbursement differs significantly across countries. At the time of writing, the pricing of digital health solutions was mostly determined through discussions between national or regional committees and the manufacturers of digital health solutions in the absence of value-based assessment mechanisms. Financing digital health solutions outside traditional reimbursement schemes was possible in all studied countries except Poland and typically occurs via health innovation or digital health-specific funding schemes. European countries have value-based pricing frameworks that range from nonexistent to embryonic. CONCLUSIONS: Studied countries show divergent approaches to the reimbursement of digital health solutions. These differences may complicate the ability of patients to seek cross-country health care in another country, even if a digital health app is available in both countries. Furthermore, the fragmented environment will present challenges for developers of such solutions, as they look to expand their impact across countries and health systems. An increased emphasis on developing a clear conceptualization of digital health, as well as value-based pricing and reimbursement mechanisms, is needed for the sustainable integration of digital health. This study can therein serve as a basis for further, more detailed research as the field of digital health reimbursement evolves.

Barriers and facilitators to utilizing digital health technologies by healthcare professionals.

Digital technologies change the healthcare environment, with several studies suggesting barriers and facilitators to using digital interventions by healthcare professionals (HPs). We consolidated the evidence from existing systematic reviews mentioning barriers and facilitators for the use of digital health technologies by HP. Electronic searches were performed in five databases (Cochrane Database of Systematic Reviews, Embase®, Epistemonikos, MEDLINE®, and Scopus) from inception to March 2023. We included reviews that reported barriers or facilitators factors to use technology solutions among HP. We performed data abstraction, methodological assessment, and certainty of the evidence appraisal by at least two authors. Overall, we included 108 reviews involving physicians, pharmacists, and nurses were included. High-quality evidence suggested that infrastructure and technical barriers (Relative Frequency Occurrence [RFO] 6.4% [95% CI 2.9-14.1]), psychological and personal issues (RFO 5.3% [95% CI 2.2-12.7]), and concerns of increasing working hours or workload (RFO 3.9% [95% CI 1.5-10.1]) were common concerns reported by HPs. Likewise, high-quality evidence supports that training/educational programs, multisector incentives, and the perception of technology effectiveness facilitate the adoption of digital technologies by HPs (RFO 3.8% [95% CI 1.8-7.9]). Our findings showed that infrastructure and technical issues, psychological barriers, and workload-related concerns are relevant barriers to comprehensively and holistically adopting digital health technologies by HPs. Conversely, deploying training, evaluating HP's perception of usefulness and willingness to use, and multi-stakeholders incentives are vital enablers to enhance the HP adoption of digital interventions.

The global effect of digital health technologies on health workers' competencies and health workplace: an umbrella review of systematic reviews and lexical-based and sentence-based meta-analysis.

Systematic reviews have quantified the effectiveness, feasibility, acceptability, and cost-effectiveness of digital health technologies (DHTs) used by health-care workers. We aimed to collate available evidence on technologies' effect on health-care workers' competencies and performance. We searched the Cochrane Database of Systematic Reviews, Embase, MEDLINE, Epistemonikos, and Scopus for reviews published from database inception to March 1, 2023. Studies assessing the effects of DHTs on the organisational, socioeconomic, clinical, and epidemiological levels within the workplace, and on health-care workers' performance parameters, were included. Data were extracted and clustered into 25 domains using vote counting based on the direction of effect. The relative frequency of occurrence (RFO) of each domain was estimated using R software. AMSTAR-2 tool was used to appraise the quality of reporting, and the Confidence in the Evidence from Reviews of Qualitative research approach developed by Grading of Recommendations Assessment, Development and Evaluation was used to analyse the certainty of evidence among included studies. The 12 794 screened reviews generated 132 eligible records for assessment. Top-ranked RFO identifiers showed associations of DHT with the enhancement of health-care workers' performance (10·9% [95% CI 5·3-22·5]), improvement of clinical practice and management (9·8% [3·9-24·2]), and improvement of care delivery and access to care (9·2% [4·1-20·9]). Our overview found that DHTs positively influence the daily practice of health-care workers in various medical specialties. However, poor reporting in crucial domains is widely prevalent in reviews of DHT, hindering our findings' generalisability and interpretation. Likewise, most of the included reviews reported substantially more data from high-income countries. Improving the reporting of future studies and focusing on low-income and middle-income countries might elucidate and answer current knowledge gaps.

Utility of Telehealth Platforms Applied to Burns Management: A Systematic Review.

The financial burden of burn injuries has a considerable impact on patients and healthcare systems. Information and Communication Technologies (ICTs) have demonstrated their utility in the improvement of clinical practice and healthcare systems. Because referral centres for burn injuries cover large geographic areas, many specialists must find new strategies, including telehealth tools for patient evaluation, teleconsultation, and remote monitoring. This systematic review was performed according to PRISMA guidelines. PubMed, Cochrane, Medline, IBECS, and LILACS were the search engines used. Systematic reviews, meta-analyses, clinical trials, and observational studies were included in the study search. The protocol was registered in PROSPERO with the number CRD42022361137. In total, 37 of 185 studies queried for this study were eligible for the systematic review. Thirty studies were comparative observational studies, six were systematic reviews, and one was a randomised clinical trial. Studies suggest that telehealth allows better perception of triage, more accurate estimation of the TBSA, and resuscitation measures in the management of acute burns. In addition, some studies assess that TH tools are equivalent to face-to-face outpatient visits and cost-efficient because of transport savings and unnecessary referrals. However, more studies are required to provide significant evidence. However, the implementation of telehealth should be specifically adapted to each territory.

Methodological and Quality Flaws in the Use of Artificial Intelligence in Mental Health Research: Systematic Review.

BACKGROUND: Artificial intelligence (AI) is giving rise to a revolution in medicine and health care. Mental health conditions are highly prevalent in many countries, and the COVID-19 pandemic has increased the risk of further erosion of the mental well-being in the population. Therefore, it is relevant to assess the current status of the application of AI toward mental health research to inform about trends, gaps, opportunities, and challenges. OBJECTIVE: This study aims to perform a systematic overview of AI applications in mental health in terms of methodologies, data, outcomes, performance, and quality. METHODS: A systematic search in PubMed, Scopus, IEEE Xplore, and Cochrane databases was conducted to collect records of use cases of AI for mental health disorder studies from January 2016 to November 2021. Records were screened for eligibility if they were a practical implementation of AI in clinical trials involving mental health conditions. Records of AI study cases were evaluated and categorized by the International Classification of Diseases 11th Revision (ICD-11). Data related to trial settings, collection methodology, features, outcomes, and model development and evaluation were extracted following the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) guideline. Further, evaluation of risk of bias is provided. RESULTS: A total of 429 nonduplicated records were retrieved from the databases and 129 were included for a full assessment-18 of which were manually added. The distribution of AI applications in mental health was found unbalanced between ICD-11 mental health categories. Predominant categories were Depressive disorders (n=70) and Schizophrenia or other primary psychotic disorders (n=26). Most interventions were based on randomized controlled trials (n=62), followed by prospective cohorts (n=24) among observational studies. AI was typically applied to evaluate quality of treatments (n=44) or stratify patients into subgroups and clusters (n=31). Models usually applied a combination of questionnaires and scales to assess symptom severity using electronic health records (n=49) as well as medical images (n=33). Quality assessment revealed important flaws in the process of AI application and data preprocessing pipelines. One-third of the studies (n=56) did not report any preprocessing or data preparation. One-fifth of the models were developed by comparing several methods (n=35) without assessing their suitability in advance and a small proportion reported external validation (n=21). Only 1 paper reported a second assessment of a previous AI model. Risk of bias and transparent reporting yielded low scores due to a poor reporting of the strategy for adjusting hyperparameters, coefficients, and the explainability of the models. International collaboration was anecdotal (n=17) and data and developed models mostly remained private (n=126). CONCLUSIONS: These significant shortcomings, alongside the lack of information to ensure reproducibility and transparency, are indicative of the challenges that AI in mental health needs to face before contributing to a solid base for knowledge generation and for being a support tool in mental health management.

Leaving no one behind: prioritising digital health equity across the WHO European Region

The 2023 World Health Organization (WHO) report on digital health for the WHO European Region demonstrates the accelerated progress in the adoption of digital health technologies (DHT) in recent years. However, there are growing concerns about the digital divide resulting from inequitable access and utilisation of DHT, particularly among older people and marginalised communities. This article sheds light on the advancements made by WHO Europe Member States and underscores the necessity to ensure access to devices and stable internet connection, as well as promoting digital literacy and user engagement, to overcome this digital divide.

The Current Status of Telemedicine Technology Use Across the World Health Organization European Region: An Overview of Systematic Reviews.

BACKGROUND: Several systematic reviews evaluating the use of telemedicine by clinicians, patients, and health authorities to improve the delivery of care in the 53 member states of the World Health Organization (WHO) European Region have been conducted in recent years. However, a study summarizing the findings of these reviews has not been conducted. OBJECTIVE: This overview of systematic reviews aimed to summarize findings regarding the use of telemedicine across the 53 member states and identify the medical fields and levels of care in and at which the effectiveness, feasibility, and applicability of telemedicine have been demonstrated. The barriers to and facilitators of telemedicine use were also evaluated and collated to help with the design and implementation of telemedicine interventions. METHODS: Through a comprehensive systematic evaluation of the published and unpublished literature, we extracted clinical, epidemiological, and technology-related data from each review included in the study. We focused on evaluating the barriers to and facilitators of the use of telemedicine apps across the 53 member states considered. We rated the methodological quality of each of the included reviews based on A Measurement Tool to Assess Systematic Review 2 approach and judged the overall certainty of evidence by using the Grading of Recommendations, Assessment, Development, and Evaluations methodology. The entire process was performed by 2 independent authors. RESULTS: This overview drew on data from >2239 primary studies, with >20,000 enrolled patients in total, within the WHO European Region. On the basis of data from randomized trials, observational studies, and economic evaluations from several countries, the results show a clear benefit of telemedicine technologies in the screening, diagnosis, management, treatment, and long-term follow-up of a series of chronic diseases. However, we were unable to pool the results into a reliable numeric parameter because of the high heterogeneity of intervention methodologies, scheduling, primary study design discrepancies, settings, and geographical locations. In addition to the clinical outcomes of the interventions, the social and economic outcomes are highlighted. CONCLUSIONS: The application of telemedicine is well established across countries in the WHO European Region; however, some countries could still benefit from the many uses of these digital solutions. Barriers related to users, technology, and infrastructure were the largest. Conversely, the provision of health services using technological devices was found to significantly enhance patients' clinical outcomes, improve the long-term follow-up of patients by medical professionals, and offer logistical benefits for both patients and health workers. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42022309375; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=309375.

Infodemics and health misinformation: a systematic review of reviews.

Objective: To compare and summarize the literature regarding infodemics and health misinformation, and to identify challenges and opportunities for addressing the issues of infodemics. Methods: We searched MEDLINE®, Embase®, Cochrane Library of Systematic Reviews, Scopus and Epistemonikos on 6 May 2022 for systematic reviews analysing infodemics, misinformation, disinformation and fake news related to health. We grouped studies based on similarity and retrieved evidence on challenges and opportunities. We used the AMSTAR 2 approach to assess the reviews' methodological quality. To evaluate the quality of the evidence, we used the Grading of Recommendations Assessment, Development and Evaluation guidelines. Findings: Our search identified 31 systematic reviews, of which 17 were published. The proportion of health-related misinformation on social media ranged from 0.2% to 28.8%. Twitter, Facebook, YouTube and Instagram are critical in disseminating the rapid and far-reaching information. The most negative consequences of health misinformation are the increase of misleading or incorrect interpretations of available evidence, impact on mental health, misallocation of health resources and an increase in vaccination hesitancy. The increase of unreliable health information delays care provision and increases the occurrence of hateful and divisive rhetoric. Social media could also be a useful tool to combat misinformation during crises. Included reviews highlight the poor quality of published studies during health crises. Conclusion: Available evidence suggests that infodemics during health emergencies have an adverse effect on society. Multisectoral actions to counteract infodemics and health misinformation are needed, including developing legal policies, creating and promoting awareness campaigns, improving health-related content in mass media and increasing people's digital and health literacy.

The experiences of 33 national COVID-19 dashboard teams during the first year of the pandemic in the World Health Organization European Region: A qualitative study.

Background: Governments across the World Health Organization (WHO) European Region have prioritised dashboards for reporting COVID-19 data. The ubiquitous use of dashboards for public reporting is a novel phenomenon. Objective: This study explores the development of COVID-19 dashboards during the first year of the pandemic and identifies common barriers, enablers and lessons from the experiences of teams responsible for their development. Methods: We applied multiple methods to identify and recruit COVID-19 dashboard teams, using a purposive, quota sampling approach. Semi-structured group interviews were conducted from April to June 2021. Using elaborative coding and thematic analysis, we derived descriptive and explanatory themes from the interview data. A validation workshop was held with study participants in June 2021. Results: Eighty informants participated, representing 33 national COVID-19 dashboard teams across the WHO European Region. Most dashboards were launched swiftly during the first months of the pandemic, February to May 2020. The urgency, intense workload, limited human resources, data and privacy constraints and public scrutiny were common challenges in the initial development stage. Themes related to barriers or enablers were identified, pertaining to the pre-pandemic context, pandemic itself, people and processes and software, data and users. Lessons emerged around the themes of simplicity, trust, partnership, software and data and change. Conclusions: COVID-19 dashboards were developed in a learning-by-doing approach. The experiences of teams reveal that initial underpreparedness was offset by high-level political endorsement, the professionalism of teams, accelerated data improvements and immediate support with commercial software solutions. To leverage the full potential of dashboards for health data reporting, investments are needed at the team, national and pan-European levels.

Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews.

BACKGROUND: Artificial intelligence is fueling a new revolution in medicine and in the healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there are several aspects that limit the measure of its impact in people's health. It is necessary to assess the current status on the application of AI towards the improvement of people's health in the domains defined by WHO's Thirteenth General Programme of Work (GPW13) and the European Programme of Work (EPW), to inform about trends, gaps, opportunities, and challenges. OBJECTIVE: To perform a systematic overview of systematic reviews on the application of artificial intelligence in the people's health domains as defined in the GPW13 and provide a comprehensive and updated map on the application specialties of artificial intelligence in terms of methodologies, algorithms, data sources, outcomes, predictors, performance, and methodological quality. METHODS: A systematic search in MEDLINE, EMBASE, Cochrane and IEEEXplore was conducted between January 2015 and June 2021 to collect systematic reviews using a combination of keywords related to the domains of universal health coverage, health emergencies protection, and better health and wellbeing as defined by the WHO's PGW13 and EPW. Eligibility criteria was based on methodological quality and the inclusion of practical implementation of artificial intelligence. Records were classified and labeled using ICD-11 categories into the domains of the GPW13. Descriptors related to the area of implementation, type of modeling, data entities, outcomes and implementation on care delivery were extracted using a structured form and methodological aspects of the included reviews studies was assessed using the AMSTAR checklist. RESULTS: The search strategy resulted in the screening of 815 systematic reviews from which 203 were assessed for eligibility and 129 were included in the review. The most predominant domain for artificial intelligence applications was Universal Health Coverage (N = 98) followed by Health Emergencies (N = 16) and Better Health and Wellbeing (N = 15). Neoplasms area on Universal Health Coverage was the disease area featuring most of the applications (21.7 %, N = 28). The reviews featured analytics primarily over both public and private data sources (67.44 %, N = 87). The most used type of data was medical imaging (31.8 %, N = 41) and predictors based on regions of interest and clinical data. The most prominent subdomain of Artificial Intelligence was Machine Learning (43.4 %, N = 56), in which Support Vector Machine method was predominant (20.9 %, N = 27). Regarding the purpose, the application of Artificial Intelligence I is focused on the prediction of the diseases (36.4 %, N = 47). With respect to the validation, more than a half of the reviews (54.3 %, N = 70) did not report a validation procedure and, whenever available, the main performance indicator was the accuracy (28.7 %, N = 37). According to the methodological quality assessment, a third of the reviews (34.9 %, N = 45) implemented methods for analysis the risk of bias and the overall AMSTAR score below was 5 (4.01 ± 1.93) on all the included systematic reviews. CONCLUSION: Artificial intelligence is being used for disease modelling, diagnose, classification and prediction in the three domains of GPW13. However, the evidence is often limited to laboratory and the level of adoption is largely unbalanced between ICD-11 categoriesand diseases. Data availability is a determinant factor on the developmental stage of artificial intelligence applications. Most of the reviewed studies show a poor methodological quality and are at high risk of bias, which limits the reproducibility of the results and the reliability of translating these applications to real clinical scenarios. The analyzed papers show results only in laboratory and testing scenarios and not in clinical trials nor case studies, limiting the supporting evidence to transfer artificial intelligence to actual care delivery.

Data gaps towards health development goals, 47 low- and middle-income countries.

OBJECTIVE: To assess the availability and gaps in data for measuring progress towards health-related sustainable development goals and other targets in selected low- and middle-income countries. METHODS: We used 14 international population surveys to evaluate the health data systems in the 47 least developed countries over the years 2015-2020. We reviewed the survey instruments to determine whether they contained tools that could be used to measure 46 health-related indicators defined by the World Health Organization. We recorded the number of countries with data available on the indicators from these surveys. FINDINGS: Twenty-seven indicators were measurable by the surveys we identified. The two health emergency indicators were not measurable by current surveys. The percentage of countries that used surveys to collect data over 2015-2020 were lowest for tuberculosis (2/47; 4.3%), hepatitis B (3/47; 6.4%), human immunodeficiency virus (11/47; 23.4%), child development status and child abuse (both 13/47; 27.7%), compared with safe drinking water (37/47; 78.7%) and births attended by skilled health personnel (36/47; 76.6%). Nineteen countries collected data on 21 or more indicators over 2015-2020 while nine collected data on no indicators; over 2018-2020 these numbers reduced to six and 20, respectively. CONCLUSION: Examining selected international surveys provided a quick summary of health data available in the 47 least developed countries. We found major gaps in health data due to long survey cycles and lack of appropriate survey instruments. Novel indicators and survey instruments would be needed to track the fast-changing situation of health emergencies.

Health Information Systems in the COVID-19 Pandemic: A Short Survey of Experiences and Lessons Learned From the European Region.

Introduction: The COVID-19 crisis provides an opportunity to reflect on what worked during the pandemic, what could have been done differently, and what innovations should become part of an enhanced health information system in the future. Methods: An online qualitative survey was designed and administered online in November 2020 to all the 37 Member States that are part of the WHO European Health Information Initiative and the WHO Central Asian Republics Information Network. Results: Nineteen countries responded to the survey (Austria, Belgium, Croatia, Czech Republic, Finland, Greece, Iceland, Ireland, Israel, Italy, Kazakhstan, Latvia, Lithuania, Romania, Russian Federation, Sweden, Turkey, United Kingdom, and Uzbekistan). The COVID-19 pandemic required health information systems (HIS) to rapidly adapt to identify, collect, store, manage, and transmit accurate and timely COVID-19 related data. HIS stakeholders have been put to the test, and valuable experience has been gained. Despite critical gaps such as under-resourced public health services, obsolete health information technologies, and lack of interoperability, most countries believed that their information systems had worked reasonably well in addressing the needs arising during the COVID-19 pandemic. Conclusion: Strong enabling environments and advanced and digitized health information systems are vital to controlling epidemics. Sustainable finance and government support are required for the continued implementation and enhancement of HIS. It is important to promote digital solutions beyond the COVID-19 pandemic. Now is the time to discuss potential solutions to obtain timely, accurate, and reliable health information and steer policy-making while protecting privacy rights and meeting the highest ethical standards.