Sarah N. Lim Choi Keung

Purpose: The European funded project ADLIFE focuses on the application of digitally enabled integrated care for people with advanced chronic diseases. The implementation of the ADLIFE intervention required a robust practical tool that would be common to all pilot sites while allowing flexibility for local variations as well as the ability to adapt to unanticipated changes and problems.Design/methodology/approach: The ADLIFE project combined the concepts of implementation research and formative evaluation with the standardized operating procedures (SOP) methodology. The ADLIFE project significantly modified the SOP approach and used it as a means to not only to define and organize the tasks that needed to be performed in preparing and implementing the ADLIFE intervention but also to create a deeper understanding of the unique challenges faced in each site, as well as a method for achieving a consensus.Findings: The ADLIFE SOPs were developed by a dedicated working group, and they encompassed the preparatory phase leading up to implementation of the intervention. The SOP was also the basis for monitoring the implementation, and this created a structure for the dynamic ongoing tactical and even strategic changes necessitated by local diversity as well as many unanticipated changes.Originality/value: The SOP methodology was useful in supporting the development of the ADLIFE SOP, which was a consensus-based approach to guide for managing the implementation process, both at project and local levels. It has supported continuous improvement and learning throughout the project. Both the process and the SOP produced by the process can be readily adapted and used in other similar projects.

Introduction: The ADLIFE project aims to improve the quality of life of older people with advanced chronic diseases by providing integrated intelligent personalised care via a digitally enabled holistic and integrated supportive care ICT Toolbox. The two interlinked user-facing tools are firstly, a Personalised Care Plan Management Platform (PCPMP) used by healthcare professionals; and secondly, a Patient Empowerment Platform (PEP) that patients and their informal caregivers use to promote patient self-management. The impact of the ADLIFE digital tools will be explored in a 12-month pilot study conducted across 7 clinical sites in 6 countries to evaluate their impact on a range of health-related, implementation and socio-economic outcomes. The development of digital tools needs to be done in continuous collaboration with target end-users. Feedback from prototype testing with typical user scenarios is crucial to identify any remaining issues to resolve ahead of the deployment of such tools. We present the findings from a pre-deployment usability study conducted on the ADLIFE Toolbox. Methods: Pilot sites recruited 3-5 participants for their feedback on the PCPMP and PEP tools. Usability data was collected using a standardised Questionnaire for User Interface Satisfaction (QUIS), administered online, following a training workshop and testing by the participants. One site collected feedback via a Patient and Public Involvement (PPI) approach for the PEP tool as an option for the activity timeline. The questionnaire responses were analysed to identify the key areas of improvement. The analysis includes a standard scoring system giving an indication of users’ satisfaction with each facet of interest. These scores identify specific features of the ADLIFE tools that have lower usability scores, allowing useful improvements to be made before deployment in the main ADLIFE pilot study. Additional free text comments are used to complement the QUIS scores and provide greater depth of understanding around specific usability issues. PPI responses were analysed separately as the group did not test the tool directly. Results: 13 responses were received for PCPMP and 18 for PEP. Overall, the study participants (excluding 10 PPI participants) scored both tools above average, with scores over 66% on average in all questionnaire categories (scores of over 6 out of 9, average score on this scale is 4.5). Some areas of usability scored lower, such as task progression and highlighting where input is required. Together with comments elaborating on scores given, those areas are being assessed further for prioritising updates to the tools and also to be considered in the study planning, such as training materials and communication channels. The PPI feedback provided insight into how ADLIFE tools can fit within the wider context of healthcare and technology. Conclusions: The usability studies have provided an opportunity to get feedback from participants similar to the ADLIFE study participants and make improvements to the ADLIFE tools, training and communication ahead of the pilot study start. Acknowledgements: ADLIFE has received funding from the EU Horizon 2020 research and innovation programme under grant agreement no. 875209. The authors thank all partners within ADLIFE for their cooperation and valuable contribution.

CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists in dealing with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alert physicians of treatment change plans. The aim of this systematic review is to identify various CDSSs that are used in brain tumour diagnosis and prognosis and rely on data captured by any imaging modality. Based on the 2020 preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. Different types of CDSSs identified through this review include Curiam BT, FASMA, MIROR, HealthAgents, and INTERPRET, among others. This review also examines various CDSS tool types, system features, techniques, accuracy, and outcomes, to provide the latest evidence available in the field of neuro-oncology. An overview of such CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with their benefits, challenges, and future perspectives has been provided. Although a CDSS improves diagnostic capabilities and healthcare delivery, there is lack of specific evidence to support these claims. The absence of empirical data slows down both user acceptance and evaluation of the actual impact of CDSS on brain tumour management. Instead of emphasizing the advantages of implementing CDSS, it is important to address its potential drawbacks and ethical implications. By doing so, it can promote the responsible use of CDSS and facilitate its faster adoption in clinical settings.

Technical and semantic interoperability are broadly used components of interoperability technology in healthcare. Technical Interoperability provides interoperability interfaces to enable data exchange within different healthcare systems, despite any underlying heterogeneity. Semantic interoperability make different healthcare systems understand and interpret the meaning of the data that is exchanged, by using and mapping standardized terminologies, coding systems, and data models to describe the concept and structure of data. We propose a solution using Semantic and Structural Mapping techniques within CAREPATH; a research project designed to develop ICT solutions for the care management of elderly multimorbid patients with mild cognitive impairment or mild dementia. Our technical interoperability solution supplies a standard-based data exchange protocol to enable information exchange between local care systems and CAREPATH components. Our semantic interoperability solution supplies programmable interfaces, in order to semantically mediate different clinical data representation formats and incorporating data format and terminology mapping features. The solution offers a more reliable, flexible and resource efficient method across EHRs.

The abnormal accumulation of cells in the human brain, if left untreated, may cause brain damage. Management and treatment of these tumours require an early and accurate diagnosis, while their prognostic characterisation can also be beneficial in the choice of care planning for the patient. CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists to deal with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alerting physicians of requirement of change in treatment plans. The aim of this systematic review is to identify various CDSSs used in brain tumour diagnosis and prognosis, that rely on data captured by any imaging modality. Based on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. This review examines various CDSS tool types, system features, techniques used, accuracy, and outcome, to provide the latest evidence available in the field of neuro-oncology. An overview of different types of CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with highlighting their benefits, challenges, and future perspectives has been provided.

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.

The process of developing a computer interpretable, integrated clinical guideline requires multiple considerations and decisions. As part of the CAREPATH project, a holistic approach to comorbidity has been adopted using an integrated clinical guideline for the management of multimorbid patients with mild cognitive impairment or mild dementia. The project’s clinical and technical teams would later interpret and implement the integrated clinical guideline into the CAREPATH holistic computer interpretable guideline. Three phases should be completed to accomplish the patient-centered computer interpretable guideline modelling, which include the conceptual modelling, interpretable modelling and localization phases, respectively. This paper describes the methodological viewpoints of this process and the relevant considerations.

Delivery of future healthcare information systems requires systems to support patients with multi-morbidity. Current approaches to computer interoperable guidelines typically consider only a single clinical guideline for a single condition. There is a need to establish a robust protocolized approach to the development of holistic consensus computer interoperable guidelines in the context of multi-morbidity. The presence of mild cognitive impairment (MCI) and dementia adds an additional challenge to the delivery of effective digital health solutions. CAREPATH proposes an ICT-based solution for the optimization of clinical practice in the treatment and management of multi-morbid older adults with mild cognitive impairment or mild dementia. In this manuscript, we present an evidence-based protocol for the development of a single computer interoperable holistic guideline for a collection of multi-morbid conditions. To the best of our knowledge, this is the first published protocol for the production of a consensus interoperable clinical guideline for people with multi-morbidity, with special focus on older adults with MCI or mild dementia. This addresses a still unmet need for such processes which are expected to play a central role for future integrated healthcare information systems.

Background: There is an increasing need to organize the care around the patient and not the disease, while considering the complex realities of multiple physical and psychosocial conditions, and polypharmacy. Integrated patient-centered care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced information and communication technology solutions for semiautomated clinical decision support. Objective: The Collaborative Care and Cure Cloud project (C3-Cloud) has developed 2 collaborative computer platforms for patients and members of the multidisciplinary team (MDT) and deployed these in 3 different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients with 2 or more chronic conditions (diabetes mellitus type 2, heart failure, kidney failure, depression), their informal caregivers, health care professionals, and, to some extent, health care systems. Methods: This paper describes the protocol for conducting an evaluation of user experience, acceptability, and usefulness of the platforms. For this, 2 “testing and evaluation” phases have been defined, involving multiple qualitative methods (focus groups and surveys) and advanced impact modeling (predictive modeling and cost-benefit analysis). Patients and health care professionals were identified and recruited from 3 partnering regions in Spain, Sweden, and the United Kingdom via electronic health record screening. Results: The technology trial in this 4-year funded project (2016-2020) concluded in April 2020. The pilot technology trial for evaluation phases 3 and 4 was launched in November 2019 and carried out until April 2020. Data collection for these phases is completed with promising results on platform acceptance and socioeconomic impact. We believe that the phased, iterative approach taken is useful as it involves relevant stakeholders at crucial stages in the platform development and allows for a sound user acceptance assessment of the final product. Conclusions: Patients with multiple chronic conditions often experience shortcomings in the care they receive. It is hoped that personalized care plan platforms for patients and collaboration platforms for members of MDTs can help tackle the specific challenges of clinical guideline reconciliation for patients with multimorbidity and improve the management of polypharmacy. The initial evaluative phases have indicated promising results of platform usability. Results of phases 3 and 4 were methodologically useful, yet limited due to the COVID-19 pandemic. Trial Registration: ClinicalTrials.gov NCT03834207; https://clinicaltrials.gov/ct2/show/NCT03834207 International Registered Report Identifier (IRRID): RR1-10.2196/21994