An Interoperable eHealth Reference Architecture for Primary Care

eHealth is still not widely used in primary care, because barriers still exist around integrated and interoperable technological infrastructures for eHealth. This paper describes the design of an interoperable eHealth reference architecture for primary care and its evaluation with experts. This reference architecture aims to facilitate IT specialists in setting up interoperable eHealth infrastructures within primary healthcare organizations. The design of the reference architecture was based on the results of 14 working sessions with 10 eHealth Small and Medium sized Enterprises (SMEs) and the theory behind the Refined eHealth European Interoperability Framework (ReEIF). The evaluation with experts revealed additional conditions that – next to the reference architecture – are needed before interoperable eHealth in primary care can actually be achieved

Technology-supported shared decision-making in chronic conditions:a systematic review of randomized controlled trials

Objectives: To describe the role of patients with a chronic disease, healthcare professionals (HCPs) and technology in shared decision making (SDM) and the use of clinical decision support systems (CDSSs), and to evaluate the effectiveness of SDM and CDSSs interventions. Methods: Randomized controlled studies published between 2011 and 2021 were identified and screened independently by two reviewers, followed by data extraction and analysis. SDM elements and interactive styles were identified to shape the roles of patients, HCPs and technology. Results: Forty-three articles were identified and reported on 21 SDM-studies, 15 CDSS-studies, 2 studies containing both an SDM-tool and a CDSS, and 5 studies with other decision support components. SDM elements were mostly identified in SDM-tools and interactions styles were least common in the other decision support components. Conclusions: Patients within the included RCTs mainly received information from SDM-tools and occasionally CDSSs when it concerns treatment strategies. HCPs provide and clarify information using SDM-tools and CDSSs. Technology provides interactions, which can support more active SDM. SDM-tools mostly showed evidence for positive effects on SDM outcomes, while CDSSs mostly demonstrated positive effects on clinical outcomes. Practice implications: Technology-supported SDM has potential to optimize SDM when patients, HCPs and technology collaborate well together.</p

Game-based design for eHealth in practice

Background: Games are increasingly used in eHealth as a strategy for user engagement. While these game-based applications receive attention in literature, there is an enormous diversity of end users and objectives targeted by eHealth. Identifying game content that drives and sustains engagement is therefore challenging. Future developments would benefit from more openness on the game design process and motivational strategies applied. Objective: Our objective was to provide insight in our approach in the development of game-based eHealth in practice. By means of a case study, PERSSILAA, we elaborate the entire game design process and show the motivational strategies applied, to aid researchers and designers of future game-based applications. PERSSILAA is a self-management platform which aims to counter frailty by offering older adults training modules in the domains of healthy nutrition, physical and cognitive training to maintain a healthy lifestyle. Methods: We introduce four phases in the process towards game-based eHealth: 1) end-user research, 2) conceptualisation, 3) creative design and 4) refinement. Results: A total number of 168 participants participated in end-user research (1), resulting in an overview of their preferences for game content and a set of game design recommendations. We found that conventional games currently popular among older adults do not necessarily translate well into engaging concepts for eHealth. Recommendations include: focusing game concepts on thinking, problem solving, variation, discovery and achievement, using high quality aesthetics. Stakeholder sessions with developing partners resulted in strategies for long-term engagement (2), using indicators of user performance on the platform's training modules. These performance indicators, e.g. completed training sessions or exercises, form the basis for game progression. Results from prior phases were used in creative design (3) to create the game "Stranded!". The user plays a shipwrecked person who has to gather parts for a life raft by completing in-game objectives. Iterative prototyping (4) resulted in the final prototype of the game-based application. A total number of 35 end users participated using simulated training modules. The online game-based application was used without reported errors for a six weeks. End users scored appreciation (74/100), ease of use (73/100), expected effectivity and motivation (62/100), fun and pleasantness of using the application (75/100) and intended future use (66/100) which implicates that the application is ready for use by a larger population. Conclusions: The study resulted in a game-based application for which the entire game design process within eHealth was transparently documented. We believe we have contributed to the transfer of knowledge on game design that supports engagement in eHealth applications. Our user evaluations indicate that results from end-user research and consequential strategies for long-term engagement led to game content that is engaging to the older adult end user.</p

Lessons learned from a living lab on the broad adoption of eHealth in primary health care

Background: Electronic health (eHealth) solutions are considered to relieve current and future pressure on the sustainability of primary health care systems. However, evidence of the effectiveness of eHealth in daily practice is missing. Furthermore, eHealth solutions are often not implemented structurally after a pilot phase, even if successful during this phase. Although many studies on barriers and facilitators were published in recent years, eHealth implementation still progresses only slowly. To further unravel the slow implementation process in primary health care and accelerate the implementation of eHealth, a 3-year Living Lab project was set up. In the Living Lab, called eLabEL, patients, health care professionals, small- and medium-sized enterprises (SMEs), and research institutes collaborated to select and integrate fully mature eHealth technologies for implementation in primary health care. Seven primary health care centers, 10 SMEs, and 4 research institutes participated. Objective: This viewpoint paper aims to show the process of adoption of eHealth in primary care from the perspective of different stakeholders in a qualitative way. We provide a real-world view on how such a process occurs, including successes and failures related to the different perspectives. Methods: Reflective and process-based notes from all meetings of the project partners, interview data, and data of focus groups were analyzed systematically using four theoretical models to study the adoption of eHealth in primary care. Results: The results showed that large-scale implementation of eHealth depends on the efforts of and interaction and collaboration among 4 groups of stakeholders: patients, health care professionals, SMEs, and those responsible for health care policy (health care insurers and policy makers). These stakeholders are all acting within their own contexts and with their own values and expectations. We experienced that patients reported expected benefits regarding the use of eHealth for self-management purposes, and health care professionals stressed the potential benefits of eHealth and were interested in using eHealth to distinguish themselves from other care organizations. In addition, eHealth entrepreneurs valued the collaboration among SMEs as they were not big enough to enter the health care market on their own and valued the collaboration with research institutes. Furthermore, health care insurers and policy makers shared the ambition and need for the development and implementation of an integrated eHealth infrastructure. Conclusions: For optimal and sustainable use of eHealth, patients should be actively involved, primary health care professionals need to be reinforced in their management, entrepreneurs should work closely with health care professionals and patients, and the government needs to focus on new health care models stimulating innovations. Only when all these parties act together, starting in local communities with a small range of eHealth tools, the potential of eHealth will be enforced

Back-UP:Personalised Prognostic Models To Improve Well-Being And return To Work After Neck and Low Back Pain

Patients with Neck and/or Low Back Pain (NLBP) constitute a heterogeneous group with the prognosis and precise mix of factors involved varying substantially between individuals. This means that a one-size-fits-all approach is not recommended, but methods to tailor treatment to the individual needs are still relatively under-developed. Moreover, the fragmentation of disciplines involved in its study hampers achieving sound answers to clinical questions. Data mining techniques open new horizons by combining data from existing datasets, in order to select the best treatment at each moment in time to a patient based on the individual characteristics. Within the Back-UP project (H2020 #777090) a multidisciplinary consortium is creating a prognostic model to support more effective and efficient management of NLBP, based on the digital representation of multidimensional clinical information. Patient-specific models provide a personalized evaluation of the patient case, using multidimensional health data from the following sources: (1) psychological, behavioral, and socioeconomic factors, (2) biological patient characteristics, including musculoskeletal structures and function, and molecular data, (3) workplace and lifestyle risk factors. The Back-UP system leverages shared-decision making, not only by enabling interoperability between all professionals involved in the care trajectory, but also empowering the patient in the decisions related to his/her care path. Furthermore, dynamic intervention models ensure that the patient receives the most beneficial treatment at each moment in time, having into account the current position of the patient in the care path (i.e. within clinical rehabilitation, in return-to-work process or through motivational strategies that support self-management in daily life)

eLabel: living labs for implementation and evaluation of integrated technology in primary care

In order to implement integrated eHealth technology in primary care, and to study implementation plans, and uptake and effect of these applications, we will establish ten living labs in the Netherlands. Together, these living labs make up the ‘eLabEL project’. For these ten living labs, we will determine where eHealth technology can provide added value, and, together with companies, we will implement relevant applications. Next, patients’ and caregivers’ view on care with and without technology will be investigated, as well as the use and usefulness of technology for specific target populations in primary care (e.g., COPD patients). A special focus will also be placed on developing decision support tools for caregivers. Finally, we will study optimal implementation strategies throughout the project. After three years a durable living lab infrastructure should be established in which companies and research organizations can develop and test eHealth innovations for primary care. This paper aims to spark the discussion on how to set up these kinds of Living Labs

Requirements for and barriers towards interoperable ehealth technology in primary care

Despite eHealth technology's rapid growth, eHealth applications are rarely embedded within primary care, mostly because systems lack interoperability. This article identifies requirements for, and barriers towards, interoperable eHealth technology from healthcare professionals' perspective -- the people who decide when (and which) patients use the technology. After distributing surveys and performing interviews, the authors coded the data and applied thematic analyses. They subdivided results according to levels of interoperability, as workflow process, information, applications, and IT infrastructure. They found that implementing interoperable eHealth technology in primary care succeeds only when all identified levels of interoperability are taken into account

E-Supporter: Personalized Technology Supported Coaching of Patients with Chronic Diseases

A serious challenge in current Western societies is the increasing number of patients with chronic diseases due to unhealthy lifestyle and the growing number of older people. Currently, more than 52% of the Dutch people have a chronic disease of which at least 33% have multiple diseases. Unfortunately, the number of people with a chronic disease is expected just to increase leading to a higher pressure on the quality of healthcare and rising healthcare costs. Personalised coaching to support patients’ self-efficacy on self-management could be a key solution to address these problems. In the last decade, innovative technologies have been developed that focus on self-management of patients. However, this support cannot be fully tailored to the patient as these apps usually do not take into account patients’ behaviour. Therefore, the development of e-supporter has been started in September 2018. E-supporter is an element of the Centre for Care Technology Research (CCTR) e-manager project that aims to improve the quality of life and perceived quality of care in patients with chronic conditions. The concept of e-supporter has been based on literature research, expert meetings and pilot studies. E-supporter will integrate various e-coaching apps that help patients with COPD, asthma and diabetes mellitus type 2 (DM2) to self-manage their disease. These apps have been developed by Maastricht University Medical Centre (MUMC+), TNO, University of Twente and commercial parties. E-supporter will promote pursuing a personalised treatment plan in daily life by using an intelligent interface that uses information from the ABCC tool, the various integrated e-coaching apps and daily health behaviour, thoughts and moods of the patient. The ABCC tool assesses the disease state, disease burden, and personalized goals that the patient has set together with the healthcare professional during consultation. Tailored coaching content will be developed based on the I-Change model and prediction models that inform the patient of expected consequences and benefits of their behaviour. In addition, e-supporter also helps healthcare professionals to be better informed about patients to enhance personalised care. This all will lead to healthcare that is more efficient, cost-effective, sustainable and of high quality

Clinical decision support systems for primary care: the identification of promising application areas and an initial design of a CDSS for lower back pain

Decision support technology has the potential to change the way professionals treat patients for the better. We questioned thirty-three healthcare professionals on their view about the usage of eHealth technology within their daily practice, and areas in which decision support can play a role, to lower healthcare professionals’ workload. Qualitative analysis resulted in an overview of desired eHealth functionalities and promising areas for decision support technology within primary care. Based on these results, we discuss future work in which we will focus on the development, and evaluation of a clinical decision support system (CDSS) for advising patients with physical complaints on whether they should see a healthcare professional or can perform self-care. Next, the CDSS should advise healthcare professionals in selecting relevant training exercises for a specific patient. In first instance, this CDSS is focused on diagnostic triaging and selection of training exercises for patients with nonspecific lower back pain