Electronic prescription systems in Greece: a large-scale survey of healthcare professionals' perceptions.

BACKGROUND: The national e-prescription system in Greece is one of the most important achievements in the e-health sector. Healthcare professionals' feedback is essential to ensure the introduced system tends to their needs and reduces their everyday workload. The number of surveys collecting the users' views is limited, while the existing studies include only a small number of participants. METHODS: In this study, healthcare professionals' perceptions on e-prescription are explored. For this, a questionnaire was distributed online, containing closed- and open-ended questions aiming to address strengths and identify drawbacks in e-prescription. Answers were collected from primary health care physicians, specialized medical doctors and pharmacists. RESULTS: In total, 430 answers were collected (129 from primary health care physicians, 164 responses from specialized medical doctors and 137 pharmacists). Analysis of the collected answers reveals that the views of the three groups of healthcare professionals mostly converge. The positive impact e-prescribing systems have on the overall prescribing procedure in preventing errors and providing automation is commented. Among gaps identified and proposed improvements, health care professionals note the need for access to information on adverse drug reactions, side effects, drug-to-drug interactions and allergies. Flexible interaction with Therapeutic Prescription Protocols is desired to ameliorate monitoring and decision-making, while drug dosing features, and simplified procedures for copying, repeating, canceling a prescription, are perceived as useful to incorporate. CONCLUSIONS: Collecting healthcare professionals' feedback is important, as their views can be transcribed to system requirements, to further promote e-prescribing and improve the provided health care services by facilitating decision making through safer and more efficient e-prescription. Introduction of the identified improvements can simplify the everyday workflow of healthcare professionals. To the best of our knowledge, a survey with more than 400 answered questionnaires on the use of e-prescription systems by healthcare professionals has never been conducted in Greece before.

Evaluation of an electronic prescription platform: Clinicians' feedback on three distinct services aiming to facilitate clinical decision and safer e-prescription.

BACKGROUND: Health Care Professionals (HCPs) are the main end-users of digital clinical tools such as electronic prescription systems. For this reason, it is of high importance to include HCPs throughout the design, development and evaluation of a newly introduced system to ensure its usefulness, as well as confirm that it tends to their needs and can be integrated in their everyday clinical practice. METHODS: In the context of the PrescIT project, an electronic prescription platform with three services was developed (i.e., Prescription Check, Prescription Suggestion, Therapeutic Prescription Monitoring). To allow an iterative process of discovery through user feedback, design and implementation, a two-phase evaluation was carried out, with the participation of HCPs from three hospitals in Northern Greece. The two-phase evaluation included presentations of the platform, followed by think-aloud sessions, individual platform testing and the collection of qualitative as well as quantitative feedback, through standard questionnaires (e.g., SUS, PSSUQ). RESULTS: Twenty one HCPs (8 in the first, 18 in the second phase, and five present in both) participated in the two-phase evaluation. HCPs comprised clinicians varying in their specialty and one pharmacist. Clinicians' feedback during the first evaluation phase already deemed usability as "excellent" (with SUS scores ranging from 75 to 95/100, showing a mean value of 86.6 and SD of 9.2) but also provided additional user requirements, which further shaped and improved the services. In the second evaluation phase, clinicians explored the system's usability, and identified the services' strengths and weaknesses. Clinicians perceived the platform as useful, as it provides information on potential adverse drug reactions, drug-to-drug interactions and suggests medications that are compatible with patients' comorbidities and current medication. CONCLUSIONS: The developed PrescIT platform aims to increase overall safety and effectiveness of healthcare services. Therefore, including clinicians in a two-phase evaluation confirmed that the introduced system is useful, tends to the users' needs, does not create fatigue and can be integrated in their everyday clinical practice to support clinical decision and e-prescribing.

Applying Digital Health in Cancer and Palliative Care in Europe: Policy Recommendations from an International Expert Workshop (MyPal Project).

Background: Digital health interventions are becoming increasingly important for adults, children, and young people with cancer and palliative care needs, but there is little research to guide policy and practice. Objectives: To identify recommendations for policy development of digital health interventions in cancer and palliative care. Design: Expert elicitation workshop. Setting: European clinical (cancer and palliative care, adult and pediatric), policy, technical, and research experts attended a one-day workshop in London, England, in October 2022, along with MyPal research consortium members. Methods: As part of the European Commission-funded MyPal project, we elicited experts' views on global, national, and institutional policies within structured facilitated groups, and conducted qualitative analysis on these discussions. Results/Implementation: Thirty-two experts from eight countries attended. Key policy drivers and levers in digital health were highlighted. Global level: global technology regulation, definitions, access to information technology, standardizing citizens' rights and data safety, digital infrastructure and implementation guidance, and incorporation of technology into existing health systems. National level: country-specific policy, compatibility of health apps, access to digital infrastructure including vulnerable groups and settings, development of guidelines, and promoting digital literacy. Institutional level: undertaking a needs assessment of service users and clinicians, identifying best practice guidelines, providing education and training for clinicians on digital health and safe digital data sharing, implementing plans to minimize barriers to accessing digital health care, minimizing bureaucracy, and providing technical support. Conclusions: Developers and regulators of digital health interventions may find the identified recommendations useful in guiding policy making and future research initiatives. MyPal child study Clinical Trial Registration NCT04381221; MyPal adult study Clinical Trial Registration NCT04370457.

Use of Real-World Data to Support Adverse Drug Reactions Prevention During ePrescription.

Adverse Drug Reactions (ADRs) are a crucial public health issue due to the significant health and monetary burden that they can impose. Real-World Data (RWD), e.g., Electronic Health Records, claims data, etc., can support the identification of potentially unknown ADRs and thus, they could provide raw data to mine ADR prevention rules. The PrescIT project aims to create a Clinical Decision Support System (CDSS) for ADR prevention during ePrescription and uses OMOP-CDM as the main data model to mine ADR prevention rules, based on the software stack provided by the OHDSI initiative. This paper presents the deployment of OMOP-CDM infrastructure using the MIMIC-III as a testbed.

Questionnaire to Capture the Over Time User Preference During the Comparison of Pharmacovigilance Software Systems.

The study aimed to assess the usability of the PVClinical platform, which is designed for detecting and managing Adverse Drug Reactions (ADRs). A "slider" type comparative questionnaire was designed to capture the preferences of six end-users over time between PVC clinical platform and the established clinical and pharmaceutical ADR detection software tools. The results of the questionnaire were cross-examined with the results of the usability study. The questionnaire was a quick preference-capturing tool over time and provided impactful insights. Coherence in participants' preferences for PVClinical platform was observed, but further research is needed to establish the effectiveness of the questionnaire as a preference-capturing tool.

Physician-Reported Experience and Usability of the MyPal Platform: A Palliative Care Digital Health Intervention.

There is a lack of research focusing on the physician-end, their experiences, and their perception of usability with an eHealth intervention. The aim of this study was to evaluate physician satisfaction, and perception of usability following the use of the MyPal platform, a digital health intervention to foster palliative care for hematological cancer patients. Participants were healthcare professionals active in the project's multinational randomized clinical trial evaluating the impact of the MyPal platform. A post-study electronic questionnaire was administered comprised of; 2 standardized questionnaires (PSSUQ, UEQ) and a feature satisfaction questionnaire, and an open ended question. All questionnaire scores were relatively high and the platform was more than marginally accepted by all participants.

A Platform Promoting Inter-Physician Interaction to Support the Management of Adverse Drug Reactions for CLL Patients.

Adverse Drug Reactions (ADRs) cause significant impact for patients' Quality of Life (QoL) and vastly increase costs, especially regarding chronic diseases. To this end, we propose a platform that aims at supporting the management of patients with Chronic Lymphocytic Leukemia (CLL), via an eHealth platform facilitating inter-physician interaction and the provision of treatment consultation by a specialized ADR management team comprised of CLL experts.

Transfer Learning for Early Prediction of Adverse Drug Reactions: Docetaxel and Alopecia in Breast Cancer as a Case Study.

Transfer Learning (TL) is an approach which has not yet been widely investigated in healthcare, mostly applied in image data. This study outlines a TL pipeline leveraging Individual Case Safety reports (ICSRs) and Electronic Health Records (EHR), applied for the early detection Adverse Drug Reactions (ADR), evaluated using of alopecia and docetaxel on breast cancer patients as use case.

The PrescIT Knowledge Graph: Supporting ePrescription to Prevent Adverse Drug Reactions.

Adverse Drug Reactions (ADRs) are an important public health issue as they can impose significant health and monetary burdens. This paper presents the engineering and use case of a Knowledge Graph, supporting the prevention of ADRs as part of a Clinical Decision Support System (CDSS) developed in the context of the PrescIT project. The presented PrescIT Knowledge Graph is built upon Semantic Web technologies namely the Resource Description Framework (RDF), and integrates widely relevant data sources and ontologies, i.e., DrugBank, SemMedDB, OpenPVSignal Knowledge Graph and DINTO, resulting in a lightweight and self-contained data source for evidence-based ADRs identification.

Benchmarking of Machine Learning classifiers on plasma proteomic for COVID-19 severity prediction through interpretable artificial intelligence.

The SARS-CoV-2 pandemic highlighted the need for software tools that could facilitate patient triage regarding potential disease severity or even death. In this article, an ensemble of Machine Learning (ML) algorithms is evaluated in terms of predicting the severity of their condition using plasma proteomics and clinical data as input. An overview of AI-based technical developments to support COVID-19 patient management is presented outlining the landscape of relevant technical developments. Based on this review, the use of an ensemble of ML algorithms that analyze clinical and biological data (i.e., plasma proteomics) of COVID-19 patients is designed and deployed to evaluate the potential use of AI for early COVID-19 patient triage. The proposed pipeline is evaluated using three publicly available datasets for training and testing. Three ML "tasks" are defined, and several algorithms are tested through a hyperparameter tuning method to identify the highest-performance models. As overfitting is one of the typical pitfalls for such approaches (mainly due to the size of the training/validation datasets), a variety of evaluation metrics are used to mitigate this risk. In the evaluation procedure, recall scores ranged from 0.6 to 0.74 and F1-score from 0.62 to 0.75. The best performance is observed via Multi-Layer Perceptron (MLP) and Support Vector Machines (SVM) algorithms. Additionally, input data (proteomics and clinical data) were ranked based on corresponding Shapley additive explanation (SHAP) values and evaluated for their prognosticated capacity and immuno-biological credence. This "interpretable" approach revealed that our ML models could discern critical COVID-19 cases predominantly based on patient's age and plasma proteins on B cell dysfunction, hyper-activation of inflammatory pathways like Toll-like receptors, and hypo-activation of developmental and immune pathways like SCF/c-Kit signaling. Finally, the herein computational workflow is corroborated in an independent dataset and MLP superiority along with the implication of the abovementioned predictive biological pathways are corroborated. Regarding limitations of the presented ML pipeline, the datasets used in this study contain less than 1000 observations and a significant number of input features hence constituting a high-dimensional low-sample (HDLS) dataset which could be sensitive to overfitting. An advantage of the proposed pipeline is that it combines biological data (plasma proteomics) with clinical-phenotypic data. Thus, in principle, the presented approach could enable patient triage in a timely fashion if used on already trained models. However, larger datasets and further systematic validation are needed to confirm the potential clinical value of this approach. The code is available on Github: https://github.com/inab-certh/Predicting-COVID-19-severity-through-interpretable-AI-analysis-of-plasma-proteomics.

Hellenic registry of patients with home mechanical ventilation (HR-HMV): profiling sleep Apnea-Hypopnea syndrome patients across Greece.

BACKGROUND: Chronic respiratory conditions are a prominent public health issue and thus, building a patient registry might facilitate both policy decision making and improvement of clinical management processes. Hellenic Registry of patients with Home Mechanical Ventilation (HR-HMV) was initiated in 2017 and a web-based platform is used to support patient data collection. Eighteen hospital departments (including sleep labs) across Greece participate in this initiative, focusing on recording data for both children and adult patients supported by mechanical ventilation at home, including patients with Sleep Apnea-Hypopnea Syndrome (SAHS) under Positive Airway Pressure (PAP) therapy. METHODS: The HR-HMV initiative ultimately aims to provide a database for evidence-based care and policy making in this specific domain. To this end, a web information system was developed and data were manually collected by clinics and hospital departments. Legal and privacy issues (such as General Data Protection Rule compliance and technical information security measures) have been considered while designing the web application. Based on the collected data, an exploratory statistical report of SAHS patients in Greece is presented. RESULTS: Eleven out of the eighteen participating clinics and hospital departments have contributed with data by the time of the current study. More than 5000 adult and children patient records have been collected so far, the vast majority of which (i.e., 4900 patients) diagnosed with SAHS. CONCLUSION: The development and maintenance of patient registries is a valuable tool for policy decision making, observational/epidemiological research and beyond (e.g., health technology assessment procedures). However, as all data collection and processing approaches, registries are also related with potential biases. Along these lines, strengths and limitations must be considered when interpreting the collected data, and continuous validation of the collected clinical data per se should be emphasized. Especially for Greece, where the lack of national registries is eminent, we argue that HR-HMV could be a useful tool for the development and the update of related policies regarding the healthcare services for patients with home mechanical ventilation support and SAHS patients, which could be useful for related initiatives at a European level as well.

Exploiting Social Media for Active Pharmacovigilance: The PVClinical Social Media Workspace.

The value of social media data for Adverse Drug Reaction (ADR) monitoring is actively investigated. While social media provide a vast amount of data, these data are hard to analyse due to their unstructured nature and lack of credibility. Despite these challenges, social media have been identified as a potentially useful data source, potentially able to "strengthen" the evidence for new ADRs. To this end, PVClinical project aims to build a platform facilitating the investigation of multiple heterogeneous data sources, including social media, to support pharmacovigilance (PV) processes, both in the clinical environment and beyond. In this study, we present the PVClinical Twitter workspace, also highlighting the rationale behind the main design choices, while also discussing the respective challenges.

Privacy-Preserving Partner Notification Service to Control Sexually Transmitted Infections.

Partner Notification (PN) processes are typically part of wider combination prevention efforts and focus on the notification of sexual partners to prevent Sexually Transmitted Infections (STIs), including Human Immunodeficiency Viruses and viral hepatitis. We present a free, voluntary, anonymous and GDPR-compliant Partner Notification service that offers enhanced security and privacy through a web and mobile application via a unique random codes.

Ethical Principles in Digital Palliative Care for Children: The MyPal Project and Experiences Made in Designing a Trustworthy Approach.

This paper explores the ethical dimension of the opportunity to offer improved electronic patient-reported outcome (ePRO) systems addressing personal needs of pediatric cancer patients, their parents and caregivers, with regard to technological advance of digital health. This opportunity has been explored in the MyPal research project, which aims to assess a patient-centered service for palliative care relying on the adaptation and extension of digital health tools and concepts available from previous projects. Development and implementation of ePROs need to take place in a safe, secure and responsible manner, preventing any possible harm and safeguarding the integrity of humans. To that end, although the final results will be published at the end of the project, this paper aims to increase awareness of the ethical ramifications we had to address in the design and testing of new technologies and to show the essentiality of protection and promotion of privacy, safety and ethical standards. We have thus reached a final design complying with the following principles: (a) respect for the autonomy of participants, especially children, (b) data protection and transparency, (c) fairness and non-discrimination, (d) individual wellbeing of participants in relation to their physical and psychological health status and e) accessibility and acceptability of digital health technologies for better user-engagement. These principles are adapted from the Ethics Guidelines for a trustworthy Artificial Intelligence (AI) which provide the framework for similar interventions to be lawful, complying with all applicable laws and regulations, ethical, ensuring compliance to ethical principles and values and robust, both from a technical and social perspective.

A GDPR-Compliant Partner Notification Service.

Partner Notification processes focus on the notification of sexual partners to prevent the transmission of Sexually Transmitted Infections (STIs). The INTEGRATE Joint Action provides an integrated platform called RiskRadar, for combination prevention activities targeting STIs, including an anonymous, free and voluntary Partner Notification service. The presented service information flow ensures privacy, security and GDPR compliance which were identified as vital with similar tools. The service is available via web and mobile interfaces using a unique random code provided from authorised healthcare professionals to support privacy.

AquaScouts: ePROs Implemented as a Serious Game for Children With Cancer to Support Palliative Care.

MyPal is a European initiative focusing on the use of the electronic patient reported outcome (ePRO) measures to enhance patient engagement in palliative cancer care via digital self-reporting palliative care for patients with cancer. As a part of its approach, MyPal also focuses on pediatric patients, implementing a specific digital health platform including a serious game to facilitate the reporting of the symptoms and overall status regarding their quality of life (QoL). To this end, the reduction of psychological burden related to frequent reporting, a.k.a. as "reporting fatigue" has been identified as a priority. In this study, we present the MyPal-CHILD platform, emphasizing on the serious game named AquaScouts and its key design decisions, while also emphasizing on the respective challenges. More specifically, we provide insights on the participatory design approach applied during the design of the platform and the high-level goals defined based on end-user input. In addition, the validation process applied before the use of the platform under real-world conditions is also presented. Finally, we discuss a number of challenges and the prospects of deploying eHealth interventions to support palliative care.

MyPal ADULT study protocol: a randomised clinical trial of the MyPal ePRO-based early palliative care system in adult patients with haematological malignancies.

INTRODUCTION: The systematic collection of electronic patient-reported outcome (ePRO) in the routine care of patients with chronic haematological malignancies such as chronic lymphocytic leukaemia (CLL) and myelodysplasia syndromes (MDS) can constitute a very ambitious but worthwhile challenge. MyPal is a Horizon 2020 Research & Innovation Action aiming to meet this challenge and foster palliative care for patients with CLL or MDS by leveraging ePRO systems to adapt to the personal needs of patients and caregiver(s). METHODS AND ANALYSIS: In this interventional randomised trial, 300 patients with CLL or MDS will be recruited across Europe. Patients will be randomly allocated to early palliative care using the MyPal system (n=150) versus standard care including general palliative care if needed (n=150). Patients in the experimental arm will be given access to the MyPal digital health platform which consists of purposely designed software available on smartphones and/or tablets. The platform entails different functionalities including physical and psychoemotional symptom reporting via regular questionnaire completion, spontaneous self-reporting, motivational messages, medication management and a personalised search engine for health information. Data on patients' activity (daily steps and sleep quality) will be automatically collected via wearable devices. ETHICS AND DISSEMINATION: The integration of ePROs via mobile applications has raised ethical concerns regarding inclusion criteria, information provided to participants, free and voluntary consent, and respect for their autonomy. These have been carefully addressed by a multidisciplinary team. Data processing, dissemination and exploitation of the study findings will take place in full compliance with European Union data protection law. A participatory design was adopted in the development of the digital platform involving focus groups and discussions with patients to identify needs and preferences. The protocol was approved by the ethics committees of San Raffaele (8/2020), Thessaloniki 'George Papanikolaou' Hospital (849), Karolinska Institutet (20.10.2020), University General Hospital of Heraklion (07/15.4.2020) and University of Brno (01-120220/EK). TRIAL REGISTRATION NUMBER: NCT04370457.

Identifying Actionability as a Key Factor for the Adoption of 'Intelligent' Systems for Drug Safety: Lessons Learned from a User-Centred Design Approach.

INTRODUCTION: Information technology (IT) plays an important role in the healthcare landscape via the increasing digitization of medical data and the use of modern computational paradigms such as machine learning (ML) and knowledge graphs (KGs). These 'intelligent' technical paradigms provide a new digital 'toolkit' supporting drug safety and healthcare processes, including 'active pharmacovigilance'. While these technical paradigms are promising, intelligent systems (ISs) are not yet widely adopted by pharmacovigilance (PV) stakeholders, namely the pharma industry, academia/research community, drug safety monitoring organizations, regulatory authorities, and healthcare institutions. The limitations obscuring the integration of ISs into PV activities are multifaceted, involving technical, legal and medical hurdles, and thus require further elucidation. OBJECTIVE: We dissect the abovementioned limitations by describing the lessons learned during the design and implementation of the PVClinical platform, a web platform aiming to support the investigation of potential adverse drug reactions (ADRs), emphasizing the use of knowledge engineering (KE) as its main technical paradigm. RESULTS: To this end, we elaborate on the related 'business processes' (i.e. operational processes) and 'user goals' identified as part of the PVClinical platform design process based on Design Thinking principles. We also elaborate on key challenges restricting the adoption of such ISs and their integration in the clinical setting and beyond. CONCLUSIONS: We highlight the fact that beyond providing analytics and useful statistics to the end user, 'actionability' has emerged as the operational priority identified through the whole process. Furthermore, we focus on the needs for valid, reproducible, explainable and human-interpretable results, stressing the need to emphasize on usability.

RiskRadar: development and pilot results of a technical intervention targeting combination prevention regarding HIV, viral hepatitis, sexually transmitted infections and tuberculosis.

BACKGROUND: The HIV pandemic impacts the lives of millions and despite the global coordinated response, innovative actions are still needed to end it. A major challenge is the added burden of coinfections such as viral hepatitis, tuberculosis and various sexually transmitted infections in terms of prevention, treatment and increased morbidity in individuals with HIV infection. A need for combination prevention strategies, tailored to high-risk key populations arises and technology-based interventions can be a valuable asset. The COVID-19 pandemic challenged the delivery of existing services and added stress to existing public health and clinical structures but also highlighted the potential of exploiting technical solutions for interventions regarding infectious diseases. In this paper we report the design process, results and evaluation findings from the pilots of 'RiskRadar'-a web and mobile application aiming to support combination prevention, testing and linkage to care for HIV, viral hepatitis, various sexually transmitted infections and tuberculosis. METHODS: RiskRadar was developed for the INTEGRATE Joint Action's aim to improve, adapt and pilot innovative digital tools for combination prevention. RiskRadar was designed iteratively using informed end-user-oriented approaches. Emphasis was placed on the Risk Calculator that enables users to assess their risk of exposure to one or more of the four disease areas, make informed decisions to seek testing or care and adjust their behaviours ultimately aiming to harm/risk reduction. RiskRadar has been piloted in three countries, namely Croatia, Italy and Lithuania. RESULTS: RiskRadar has been used 1347 times across all platforms so far. More than 90% of users have found RiskRadar useful and would use it again, especially the Risk Calculator component. Almost 49.25% are men and 29.85% are in the age group of 25-34. The application has scored 5.2/7 in the User Experience Questionnaire, where it is mainly described as "supportive" and "easy-to-use". The qualitative evaluation of RiskRadar also yielded positive feedback. CONCLUSIONS: Pilot results demonstrate above average satisfaction with RiskRadar and high user-reported usability scores, supporting the idea that technical interventions could significantly support combination prevention actions on Sexually Transmitted Infections.

Developing an infrastructure for secure patient summary exchange in the EU context: Lessons learned from the KONFIDO project.

BACKGROUND: The increase of healthcare digitalization comes along with potential information security risks. Thus, the EU H2020 KONFIDO project aimed to provide a toolkit supporting secure cross-border health data exchange. METHODS: KONFIDO focused on the so-called "User Goals", while also identifying barriers and facilitators regarding eHealth acceptance. Key user scenarios were elaborated both in terms of threat analysis and legal challenges. Moreover, KONFIDO developed a toolkit aiming to enhance the security of OpenNCP, the reference implementation framework. RESULTS: The main project outcomes are highlighted and the "Lessons Learned," the technical challenges and the EU context are detailed. CONCLUSIONS: The main "Lessons Learned" are summarized and a set of recommendations is provided, presenting the position of the KONFIDO consortium toward a robust EU-wide health data exchange infrastructure. To this end, the lack of infrastructure and technical capacity is highlighted, legal and policy challenges are identified and the need to focus on usability and semantic interoperability is emphasized. Regarding technical issues, an emphasis on transparent and standards-based development processes is recommended, especially for landmark software projects. Finally, promoting mentality change and knowledge dissemination is also identified as key step toward the development of secure cross-border health data exchange services.