Synergy-COPD: a systems approach for understanding and managing chronic diseases.

Chronic diseases (CD) are generating a dramatic societal burden worldwide that is expected to persist over the next decades. The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems. We hypothesized that the development of a systems approach to understand CD together with the generation of an ecosystem to transfer the acquired knowledge into the novel healthcare scenario may contribute to a cost-effective enhancement of health outcomes. To this end, we designed the Synergy-COPD project wherein the heterogeneity of chronic obstructive pulmonary disease (COPD) was addressed as a use case representative of CD. The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span. Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COP

Predictive medicine: outcomes, challenges and opportunities in the Synergy-COPD project

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a major challenge for healthcare. Heterogeneities in clinical manifestations and in disease progression are relevant traits in COPD with impact on patient management and prognosis. It is hypothesized that COPD heterogeneity results from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering. OBJECTIVES: To assess the potential of systems medicine to better understand non-pulmonary determinants of COPD heterogeneity. To transfer acquired knowledge to healthcare enhancing subject-specific health risk assessment and stratification to improve management of chronic patients. METHOD: Underlying mechanisms of skeletal muscle dysfunction and of co-morbidity clustering in COPD patients were explored with strategies combining deterministic modelling and network medicine analyses using the Biobridge dataset. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was done (ICD9-CM data from Medicare, 13 million people). A targeted network analysis using the two studies: skeletal muscle dysfunction and co-morbidity clustering explored shared pathways between them. RESULTS: (1) Evidence of abnormal regulation of pivotal skeletal muscle biological pathways and increased risk for co-morbidity clustering was observed in COPD; (2) shared abnormal pathway regulation between skeletal muscle dysfunction and co-morbidity clustering; and, (3) technological achievements of the projects were: (i) COPD Knowledge Base; (ii) novel modelling approaches; (iii) Simulation Environment; and, (iv) three layers of Clinical Decision Support Systems. CONCLUSIONS: The project demonstrated the high potential of a systems medicine approach to address COPD heterogeneity. Limiting factors for the project development were identified. They were relevant to shape strategies fostering 4P Medicine for chronic patients. The concept of Digital Health Framework and the proposed roadmap for its deployment constituted relevant project outcomes

Protocol for regional implementation of collaborative lung function testing

The potential of forced spirometry (FS) testing for diagnosis, monitoring and management of chronic respiratory patients is well established1-3 such that FS is a pivotal test in both respiratory medicine and primary care. Moreover, it also shows potential in the informal care scenario: that is, in pharmacy offices for case-finding purposes4,5 and for self-management in selected patients.6,7 We acknowledge that well-designed studies8 have failed to show practical benefits of FS for asthma and COPD diagnosis and management in primary care. However, it has been demonstrated that historical limitations for extensive use of FS in primary care, because of suboptimal quality of testing, can be overcome by offline remote support by specialised professionals.9,10 Large-scale deployment of this type of setting has generated evidence of cost-effectiveness.

Health outcomes from home hospitalization: multisource predictive modeling

Background: Home hospitalization is widely accepted as a cost-effective alternative to conventional hospitalization for selected patients. A recent analysis of the home hospitalization and early discharge (HH/ED) program at Hospital Clínic de Barcelona over a 10-year period demonstrated high levels of acceptance by patients and professionals, as well as health value-based generation at the provider and health-system levels. However, health risk assessment was identified as an unmet need with the potential to enhance clinical decision making. Objective: The objective of this study is to generate and assess predictive models of mortality and in-hospital admission at entry and at HH/ED discharge. Methods: Predictive modeling of mortality and in-hospital admission was done in 2 different scenarios: at entry into the HH/ED program and at discharge, from January 2009 to December 2015. Multisource predictive variables, including standard clinical data, patients' functional features, and population health risk assessment, were considered. Results: We studied 1925 HH/ED patients by applying a random forest classifier, as it showed the best performance. Average results of the area under the receiver operating characteristic curve (AUROC; sensitivity/specificity) for the prediction of mortality were 0.88 (0.81/0.76) and 0.89 (0.81/0.81) at entry and at home hospitalization discharge, respectively; the AUROC (sensitivity/specificity) values for in-hospital admission were 0.71 (0.67/0.64) and 0.70 (0.71/0.61) at entry and at home hospitalization discharge, respectively. Conclusions: The results showed potential for feeding clinical decision support systems aimed at supporting health professionals for inclusion of candidates into the HH/ED program, and have the capacity to guide transitions toward community-based care at HH discharge

Protocol for regional implementation of collaborative self-management services to promote physical activity

Background: Chronic diseases are generating a major health and societal burden worldwide. Healthy lifestyles, including physical activity (PA), have proven efficacy in the prevention and treatment of many chronic conditions. But, so far, national PA surveillance systems, as well as strategies for promotion of PA, have shown low impact. We hypothesize that personalized modular PA services, aligned with healthcare, addressing the needs of a broad spectrum of individual profiles may show cost-effectiveness and sustainability. Methods: The current manuscript describes the protocol for regional implementation of collaborative self-management services to promote PA in Catalonia (7.5 M habitants) during the period 2017-2019. The protocols of three implementation studies encompassing a broad spectrum of individual needs are reported. They have a quasi-experimental design. That is, a non-randomized intervention group is compared to a control group (usual care) using propensity score methods wherein age, gender and population-based health risk assessment are main matching variables. The principal innovations of the PA program are: i) Implementation of well-structured modular interventions promoting PA; ii) Information and communication technologies (ICT) to facilitate patient accessibility, support collaborative management of individual care plans and reduce costs; and iii) Assessment strategies based on the Triple Aim approach during and beyond the program deployment. Discussion: The manuscript reports a precise roadmap for large scale deployment of community-based ICT-supported integrated care services to promote healthy lifestyles with high potential for comparability and transferability to other sites. Trial registration: This study protocol has been registered at ClinicalTrials.org ( NCT02976064 ). Registered November 24th, 2016

Biomedical research in a digital health framework

This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements--data and tools--of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform

Context-aware quality of life telemonitoring for a novel healthcare paradigm

Els nostres sistemes de salut estan veient qüestionada la seva sostenibilitat arran del canvi demogràfic d'una societat en la qual augmenta la prevalença de cronicitat i discapacitat. El nou model de salut es basa en la Medicina 4P. Una tecnologia clau per a la Medicina 4P és el telemonitoratge, és a dir, les TIC per conèixer l'estat de salut d'un pacient a distància i prendre decisions 4P. Un repte ambiciós és el telemonitoratge de la Qualitat de Vida (QoL) basat en el coneixement del context. Proposem una metodologia formal per avaluar la QoL mitjançant la categorització de dades d'entrada i sortida i tècniques de fusió de dades. Hem dissenyat i desenvolupat un Sistema de Telemonitoratge i Suport Domiciliari (TMHSS) que implementa aquesta metodologia, integrat al sistema BackHome per un Cas d'Ús concret, el de persones amb discapacitats severes que utilitzen Interfícies Cervell Ordinador (BCI) com a Tecnologia Assistencial (AT) en entorns reals. Hem aplicat Disseny Centrat en l'Usuari amb la finalitat de traslladar els BCIs des del laboratori fins a l'ús domèstic independent. El sistema BackHome ha assolit cinc innovacions fonamentals: (i) una arquitectura que satisfà els requisits d'un BCI multifuncional i amb suport remot; (ii) un dispositiu de BCI lleuger, autònom, còmode i fiable; (iii) un programari fàcil d'utilitzar per a manegar diverses aplicacions d'autonomia física i social; (iv) Un TMHSS per fer efectiu l'ús independent dels BCIs a la llar; i (v) una estació clínica per a la gestió remota de serveis terapèutics. Hem avaluat el sistema BackHome amb usuaris finals a casa seva, aprenent de la perspectiva de terapeutes i cuidadors no experts amb resultats que mostren bona acceptació i nivells d'usabilitat, satisfacció de l'usuari i nivells de control que demostren que el BCI pugui ja considerar-se una AT alternativa. Hem emprat el TMHSS de BackHome per reconèixer activitats i hàbits dels usuaris a partir de l'anàlisi de dades de sensors, per detectar per exemple si l'usuari està a casa o fora, o si ha rebut una visita. També hem avaluat a continuació amb bona precisió elements de la Qualitat de Vida, com ara mobilitat, son, o estat d'ànim, a partir de les activitats de l'usuari prèviament detectades.Our healthcare systems are facing sustainability challenges caused by a demographic shift with ageing, chronicity and disability growing in our society. A novel healthcare paradigm should be founded on 4P medicine: Preventive, Predictive, Personalized, and Participatory medicine needs new methodologies and tools enabled by Information and Communication Technologies (ICTs). One of the key technology enablers for 4P medicine is telemonitoring, i.e. ICTs to monitor the health status of a patient from a distance, which may trigger 4P decision making. A new generation of telemonitoring tools allow prescription and follow-up around the main chronic care strategies, namely, therapeutic adherence and healthy habits promotion. A broader and more ambitious challenge is Quality of Life (QoL) telemonitoring based on the knowledge of context. We are proposing a formal methodology to provide Context-aware QoL assessment, categorizing data inputs, defining outputs, and exploring data fusion techniques. A Telemonitoring and Home Support System (TMHSS) which implements that methodology has been designed, developed and integrated to the BackHome system for a particular Use Case, i.e. severely disabled people using Brain Computer Interfaces (BCI) as an assistive technology (AT) at home. We have applied User Centred Design throughout all development stages of a multi-functional BCI, in order to move BCIs from the lab towards independent home use. The BackHome system has achieved five key innovations: (i) an architecture able to meet the requirements of BCI multifunctionality and remote home support; (ii) a light, autonomous, comfortable and reliable BCI equipment; (iii) an easy-to-use software to control multiple purpose applications; (iv) a TMHSS for BCI independent home use; and (v) a Therapist station to manage and monitor BCI-based remote services. We have evaluated the BackHome system with end-users at home, also taking the therapists' and non-expert caregivers' perspective into account. The results show good acceptance, usability levels, user satisfaction and levels of control, which demonstrate that BCI can already be considered as an alternative AT. We used the TMHSS of BackHome to recognize activities and habits of users based on the analysis of sensors' data, in order to detect for example whether the user is at home or away or whether has received a visit at home or not. Similarly, and consequently from the previous analysis, results show good accuracies in assessing items of QoL such as Mobility, Sleep, or Mood, based on measures and fusion of detected activities from the user. The assessment of the overall wellbeing of an individual with a multidimensional perspective through processing of data gathered from environmental and personal sensors in a broad and non-intrusive way, will become of great interest to healthcare professionals, policy makers and also for citizens which are called to co-produce and lead the new paradigm of care