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Due to population ageing and medical advances, people with advanced chronic diseases (ACD) live longer. Such patients are even more likely to face either temporary or permanent reduced functional reserve, which typically further increases their healthcare resource use and the burden of care on their caregiver(s). Accordingly, these patients and their caregiver(s) may benefit from integrated supportive care provided via digitally supported interventions. This approach may either maintain or improve their quality of life, increase their independence, and optimize the healthcare resource use from early stages. ADLIFE is an EU-funded project, aiming to improve the quality of life of older people with ACD by providing integrated personalized care via a digitally enabled toolbox. Indeed, the ADLIFE toolbox is a digital solution which provides patients, caregivers, and health professionals with digitally enabled, integrated, and personalized care, supporting clinical decisions, and encouraging independence and self-management. Here we present the protocol of the ADLIFE study, which is designed to provide robust scientific evidence on the assessment of the effectiveness, socio-economic, implementation, and technology acceptance aspects of the ADLIFE intervention compared to the current standard of care (SoC) when applied in real-life settings of seven different pilot sites across six countries. A quasi-experimental trial following a multicenter, non-randomized, non-concurrent, unblinded, and controlled design will be implemented. Patients in the intervention group will receive the ADLIFE intervention, while patients in the control group will receive SoC. The assessment of the ADLIFE intervention will be conducted using a mixed-methods approach.

Chronic diseases introduce challenges for the patients to manage the changing requirements of the disease. Patient empowerment activities are a critical component to assist patients in their long-term care journey. In order to be effective, patient empowerment tools need to be well-integrated with the chronic disease management tools used at the clinical sites. This paper explores and analyzes the exploitation of HL7 FHIR to design and implement an interoperable patient empowerment platform that can be seamlessly integrated with external chronic disease management and Electronic Health Record (EHR) systems

Introduction Persons with Advanced Chronic Diseases can greatly benefit from digitally supported interventions to improve or maintain their health, avoid unnecessary deterioration, extend their independence and optimize health resources utilization. Digitalisation is expected to lead a profound transformation of health services. It is important to evaluate its impact. The coronavirus disease (COVID-19) pandemic has pushed forward the paradigm shift towards telehealth, highlighting the need worldwide for enabling and promoting digital care. Theory/Methods The project ADLIFE (H2020, SC1-DTH-11-2019, 875209) aims to provide innovative integrated intelligent personalized care to aged patients with complex chronic diseases. Care will be supported by an ICT solution, the ADLIFE Toolbox. The target population is senior (55+) patients with severe Heart failure and/or COPD. In total in the seven pilot sites, 882 patients, 1243 caregivers and 577 healthcare professionals from specialized and primary care services will be involved in pilot operation and evaluation activities. Care delivery models, level of integration, scope and content of the Clinical Decision Support Services (CDSS) and health outcomes has been explored and defined involving relevant stakeholders at each pilot site. Results and Discussion Each pilot has identified improvement areas required to enable the delivery of care proposed in ADLIFE. A conceptual framework has been developed to that includes and categorize health outcomes. Data will be used for evaluation and CDSS. A set of PROMs has been proposed to capture the information on the effectiveness and the quality of the care delivered as perceived by the patients. CDSS are based on computable flowcharts as defined in evidence based clinical guidelines (single disease and reconciled for multimorbidity). AI algorithms will be developed and trained to identify Potentially Preventable Situations. Conclusions (comprising key findings) The project seeks to demonstrate that a personalized care model that integrates clinical and patient stakeholders´ analysis with ICT tools is effective and flexible and can be deployed and replicated in different health care systems. Lessons learned Assessing care models and having trusted personalised digital solutions are key for ADLIFE implementation and operation in the seven ICT health systems. Limitations Multimorbidity covers a wide range of conditions. ADLIFE focuses on COPD and/or Heart Failure with or without co morbidities. Further analytical and development work will be needed to be done. Suggestions for future research The effectiveness and efficiency of deploying digitally enabled holistic and integrated supportive care will be assessed by evaluating health gain, quality of life, use of resources and economic costs. The authors are on behalf of the ADLIFE Consortium. The ADLIFE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875209.

Supported by the European Commission under Horizon 2020, mHealth4Afrika is co-designing and validating a modular, multilingual, state-of-the-art health information system addressing primary healthcare requirements in resource constrained environments. mHealth4Afrika has co-designed a comprehensive range of functionality and medical programs in partnership with Ministries of Health, district health officers, clinic managers and primary healthcare workers from urban, rural and deep rural health facilities in Ethiopia, Kenya, Malawi and South Africa. This paper provides insights into how mHealth4Afrika is leveraging HL7 FHIR to support standards-based data exchange and interoperability between Electronic Medical Records and DHIS2. This work is currently being validated in the field.

mHealth4Afrika has introduced the use of CE approved medical sensors at the point of care in primary healthcare facilities in Africa as part of an integrated platform supporting primary health care services. This paper shares insights into the standards-based architecture and HL7 FHIR service developed to support data transfer from sensors with proprietary standards to populate the mHealth4Afrika electronic patient record via custom Android and Windows applications. The current iteration is being validated in healthcare facilities in Ethiopia, Kenya, Malawi and South Africa.

Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans.

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

Graphical abstractDisplay Omitted We model and implement a framework for managing disparate Common Data Elements.Maintaining metadata within Linked Data cloud facilitates semantic interoperability.Federated semantic metadata registry framework links clinical research and care.Clinical research applications can access heterogeneous patient data automatically.Secondary use of electronic health records is achieved for safety studies. In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems.

Use of medical terminologies and mappings across them are considered to be crucial pre-requisites for achieving interoperable eHealth applications. Built upon the outcomes of several research projects, we introduce a framework for evaluating and utilizing terminology mappings that offers a platform for i) performing various mappings strategies, ii) representing terminology mappings together with their provenance information, and iii) enabling terminology reasoning for inferring both new and erroneous mappings. We present the results of the introduced framework from SALUS project where we evaluated the quality of both existing and inferred terminology mappings among standard terminologies.

CAREPATH project is focusing on providing an integrated solution for sustainable care for multimorbid elderly patients with dementia or mild cognitive impairment. The project has a digitally enhanced integrated patient-centered care approach clinical decision and associated intelligent tools with the aim to increase patients’ independence, quality of life and intrinsic capacity. In this paper, the conceptual aspects of the CAREPATH project, in terms of technical and clinical requirements and considerations, are presented.

Introduction: The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. C3-Cloud project aims to build an integrated care platform for addressing the growing demand for improved health outcomes of multimorbid and long-term care patients. Theory/Methods: C3-Cloud has established an ICT infrastructure enabling continuous coordination of patient-centred care activities by a multidisciplinary care team MDT and patients/informal care givers. The Coordinated Care and Cure Delivery Platform C3DP allows, collaborative creation and execution of personalised care plans for multi-morbid patients through systematic and semi-automatic reconciliation of clinical guidelines. Clinical decision support CDS systems implementing flowcharts from evidence based clinical guidelines are integrated to present suggestions for treatment goal and activities e.g. medications, follow-up appointments, diet, exercise, lab tests. Pilot site local care systems are integrated with the C3DP via the technical and semantic interoperability platform to facilitate informed decision making. Active patient involvement is realized through a Patient Empowerment Platform presenting personalized care plan to the patient and establishing a continuous bi-way communication with the patient to collect patient observations, questionnaire responses, symptoms and feedback about care plan goals and activities. Results: The following research results have been achieved to enable guideline enabled personalised care plan management for addressing the needs of multi-morbidity: 43 logical flowcharts were designed out of 4 disease guidelines Type 2 Diabetes, Heart Failure, Renal Failure and Depression. 181 CDS rules assessing 166 patient criteria and recommending 154 goal/activity suggestions were implemented as CDS services in GDL covering T2D and RF. 52 reconciliation rules were designed for eliminating contradicting guideline recommendations due to multi-morbidity. 23 HL7 FHIR profiles were defined for representing care plan and patient data. C3DP has been integrated with these CDS services via CDS-Hooks specification to recommend personalised care plan goals and activities. Discussions: In this research, we have successfully implemented an ICT infrastructure enabling guideline-driven integrated care for multi-morbid patients. Although our ICT solution covers all the technical requirements identified by clinical partners, effective implementation of integrated care in real-life care setting requires major changes in organisational responsibilities and care pathways. Conclusions: User-centred design and usability testing have successfully been completed. C3-Cloud pilot application will now be operated in 3 European pilot sites with the participation of 62 MDT members and 1200 multi-morbid patients for 15 months. Lessons learned: There are two main research lines for reconciliation of contradicting guideline recommendations: 1 fully-automated reconciliation via ontology reasoning, 2 manually-crafted reconciliation rules by clinical expert groups. Although first approach is more dynamic, research results are still for very primitive cases and not clinically validated. As we are targeting an industry-ready solution after piloting in real-life settings, we have opted for the second option. Limitations: When a new chronic disease is to be addressed within our platform, reconciliation rules covering all disease combinations have to be re-assessed by the clinical expert group. Suggestions for future research: Fully-automated reconciliation approaches need to be further studied and validated in real-life settings.

Introduction: The C3-Cloud project http://c3-cloud.eu/ aims to enable the development of personalised care plans for multi-morbid conditions, supported by innovative ICT components, to improve delivery of integrated and patient-centred care. This is achieved through the coordination by a multidisciplinary care team MDT. To demonstrate feasibility, pilot studies will be conducted in 3 European regions: Region Jamtland Harjedalen RJH, Sweden, South Warwickshire SWFT, UK and Basque Country BC, Spain. Short description of practice: We describe the pre-implementation phase to support the implementation of the C3-Cloud care model during the pilot study. The results comprise of prototypes that will be tested in each site. They include: i organizational model description in C3-Cloud scenario, ii key factors at system level and care coordination iii relation between actors, activities and C3-Cloud solutions. Aim and theory of change: The aim is to define organizational prototypes in each site. The theory of change is based on the identification of the organizational model changes required for C3-Cloud solutions to work consistently across different organizational settings and population groups, accordingly to C3-Cloud care model. Targeted population and stakeholders: Multimorbid patients who are 65+ and have at least two or more of diabetes, heart failure, renal failure and depression. 600 intervention and 600 control patients and 62 MDT members. MDT is comprised of health professionals, social care workers and homecare providers. Timeline: The study is divided into a pre-study phase, a study phase and a post-study. This work has been developed in pre-study phase. Highlights: The analyses of system factors have shown differences among the three sites, in various domains, as the resources of the community. The implementation of C3-Cloud speeds up communication among actors. The patients participate in a higher number of activities and the teamwork is strengthened. C3-Cloud supports the formal introduction of all actors in the preparation of the work plan and increases patient involvement. Sustainability: We will use the human resources available in the settings and the technological resources generated along the project, facilitating subsequent deployments. Transferability: It will be supported by the development of guidelines for any organisation to implement the necessary changes. Conclusions: The three pilot sites have good health systems that comply with most of the organizational model prototype requirements. Organizational and geographical settings and place of service for interventions are defined. Care coordination actors, activities and interpersonal communication are in place. However, several areas as alignment of incentives and patient involvement require further research for C3-Cloud care model. Discussion: With the information collated to date, pilot sites are carrying out further work to develop the capability identified infrastructure, skills and organizational practices to provide the C3-Cloud model care. The aim is to implement the suggested changes to adequately deploy the pilot phase of the project in the three environments. Lessons learned: The contribution of MDT members and patients has been crucial. The involvement of the patient in all aspects of care is key for successful care. Change management has to consider what is currently possible for integrated multi-morbidity care pathway adoption.