Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

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.Publisher's Versio

Design, implementation and usability analysis of patient empowerment in ADLIFE project via patient reported outcome measures and shared decision making

Introduction: This paper outlines the design, implementation, and usability study results of the patient empowerment process for chronic disease management, using Patient Reported Outcome Measurements and Shared Decision-Making Processes. Background: The ADLIFE project aims to develop innovative, digital health solutions to support personalized, integrated care for patients with severe long-term conditions such as Chronic Obstructive Pulmonary Disease, and/or Chronic Heart Failure. Successful long-term management of patients with chronic conditions requires active patient self-management and a proactive involvement of patients in their healthcare and treatment. This calls for a patient-provider partnership within an integrated system of collaborative care, supporting self-management, shared-decision making, collection of patient reported outcome measures, education, and follow-up. Methods: ADLIFE follows an outcome-based and patient-centered approach where PROMs represent an especially valuable tool to evaluate the outcomes of the care delivered. We have selected 11 standardized PROMs for evaluating the most recent patients’ clinical context, enabling the decision-making process, and personalized care planning. The ADLIFE project implements the "SHARE approach’ for enabling shared decision-making via two digital platforms for healthcare professionals and patients. We have successfully integrated PROMs and shared decision-making processes into our digital toolbox, based on an international interoperability standard, namely HL7 FHIR. A usability study was conducted with 3 clinical sites with 20 users in total to gather feedback and to subsequently prioritize updates to the ADLIFE toolbox. Results: User satisfaction is measured in the QUIS7 questionnaire on a 9-point scale in the following aspects: overall reaction, screen, terminology and tool feedback, learning, multimedia, training material and system capabilities. With all the average scores above 6 in all categories, most respondents have a positive reaction to the ADLIFE PEP platform and find it easy to use. We have identified shortcomings and have prioritized updates to the platform before clinical pilot studies are initiated. Conclusions: Having finalized design, implementation, and pre-deployment usability studies, and updated the tool based on further feedback, our patient empowerment mechanisms enabled via PROMs and shared decision-making processes are ready to be piloted in clinal settings. Clinical studies will be conducted based at six healthcare settings across Spain, UK, Germany, Denmark, and Israel

From Raw Data to FAIR Data: The FAIRification Workflow for Health Research

BackgroundFAIR (findability, accessibility, interoperability, and reusability) guidingprinciples seek the reuse of data and other digital research input, output, and objects(algorithms, tools, and workflows that led to that data) making themfindable, accessible,interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governedinitiative-defined a seven-step FAIRificationprocessfocusingondata,butalsoindicatingtherequired work for metadata. This FAIRification process aims at addressing the translation ofraw datasets into FAIR datasets in a general way, without considering specific requirementsand challenges that may arise when dealing with some particular types of data.This work was performed in the scope of FAIR4Healthproject. FAIR4Health has received funding from the European Union’s Horizon 2020 research and innovationprogramme under grant agreement number 824666

The design of a mobile platform providing personalized assistance to older multimorbid patients with mild dementia or mild cognitive impairment (MCI)

Management of multiple chronic conditions introduces demanding challenges for patients. This situation becomes more complex when multimorbidity is associated with dementia. In this paper, we present the design of a mobile Patient Empowerment Platform that enables older multimorbid patients with mild dementia or mild cognitive impairment (MCI) to easily follow their complex care plans and increase their adherence. We focus on the presentation of the human-centered design process that we have followed with the involvement of patients, informal caregivers, and healthcare professionals via the clinical pilot sites of the CAREPATH project. We elaborate the design challenges we have faced and present the iterative mock-ups that have been created in cooperation with end users to address these challenges and the final PEP design

Localisation, personalisation and delivery of best practice guidelines on an integrated care and cure cloud architecture : the C3-cloud approach to managing multimorbidity

Background: C3-Cloud is an integrated care ICT infrastructure offering seamless patient-centered approach to managing multimorbidity, deployed in three European pilot sites. Challenge: The digital delivery of best practice guidelines unified for multimorbidity, customized to local practice, offering the capability to improve patient personalization and benefit. Method: C3-Cloud has adopted a co-production approach to developing unified multimorbidity guidelines, by collating and reconciling best practice guidelines for each condition. Clinical and technical teams at pilot sites and the C3-Cloud consortium worked in tandem to create the specification and technical implementation. Results: C3-Cloud offers CDSS for diabetes, renal failure, depression and congenital heart failure, with over 300 rules and checks that deliver four best practice guidelines in parallel, customized for each pilot site. Conclusions: The process provided a traceable, maintainable and audited digitally delivered collated and reconciled guidelines

A collaborative platform for management of chronic diseases via guideline-driven individualized care plans

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. We also report the results of usability studies carried out in four pilot sites by patients and clinicians

Protocol for creating a single, holistic and digitally implementable consensus clinical guideline for multiple multi-morbid conditions

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

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains

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

Adverse Drug Event Notification System Reusing clinical patient data for semi-automatic ADE detection

Adverse drug events (ADEs) are common, costly and a public health issue. Today, their detection relies on medical chart review and spontaneous reports, but this is known to be rather ineffective. Along with the increasing availability of clinical patient data in electronic health records (EHRs), a computer-based ADE detection has a tremendous potential to contribute to patient safety. Current ADE detection systems are very specific, usually built directly on top of clinical information systems through proprietary interfaces. Thus, it is not possible to run different ADE detection tools on top of already existing systems in an ad-hoc manner. The European project "SALUS" aims at providing the necessary infrastructure and toolset for accessing and analyzing clinical patient data of heterogeneous clinical information systems. This paper highlights the SALUS ADE notification system as the key tool to enable a semi-automatic ADE detection and notification. In contrast to previous work, the ADE notification system is not restricted to a specific clinical environment. It can be run on different clinical data models with different levels of data quality. The system is equipped with innovative features, building up an intelligent, comprehensive ADE detection and notification system that promises a profound impact in the domain of computer-based ADE detection