Interoperability Maturity Model: Orchestrator Tool for Platform Ecosystems

The orchestration of platform ecosystems is becoming increasingly complex due to the growing number of players, complementary services and technological innovations. Interoperability is an important prerequisite for convincing customer journeys as well as functional and quality-assured data exchange and offers increasing potential for automation, especially with the help of machine learning or artificial intelligence. The interoperability maturity model developed in this study can be used as a conceptual framework to measure the interoperability of current and future platform ecosystem components and complements. The model, developed as an artifact of design science research, was evaluated using an iterative approach with orchestrators of health data platforms and their ecosystem. The results suggest that it can contribute to achieving and sustaining integrated value chains with multiple actors and diverse technologies, and can be used to assess the interoperability of care chains (e.g., care scenarios such as diabetes or cardiac insufficiency) and guide future interoperability considerations

Implementation of e-health interoperability in developing country contexts : the case of Zimbabwe

The provision of information technology-enabled healthcare services (e-health) has been adopted by numerous public and private facilities in both developing nations and advanced nations. However, one of the obstacles to the adoption of health information systems has been cited as their lack of interoperability resulting in their reduced effectiveness. In view of this, the study sought to explore the interoperability of health information systems employed in the country and then propose a framework to direct the process of implementing e-health interoperability. The study’s methodology was qualitative and a case study was undertaken. Semi-structured interviews were employed to gather data from e-health stakeholders in state-owned institutions and private enterprises. Document review was also conducted to substantiate findings from interviews. Data was analysed using thematic analysis and NVivo 12 software. The study’s findings revealed that several health information systems were implemented and their interoperability was low. Technological, terminology, organizational as well as regulatory and legal barriers were identified as hindrances to interoperability. The enablers for implementing e-health interoperability also revealed by this study include: development of re-usable software components, train the trainer approach to transfer of skills and regional conformance testing. The consequences of lack of interoperability among health information systems reported by this study include: burden on the worker, wastage of resources and high cost. The study also proposed a dual framework to guide the implementation of e-health interoperability. The study’s recommendations include the development of an e-health policy, an e-health strategy and the upgrade of ICT and telecommunication infrastructure to facilitate health information exchange.School of ComputingD. Phil. (Information Systems

DESIGN AND EXPLORATION OF NEW MODELS FOR SECURITY AND PRIVACY-SENSITIVE COLLABORATION SYSTEMS

Collaboration has been an area of interest in many domains including education, research, healthcare supply chain, Internet of things, and music etc. It enhances problem solving through expertise sharing, ideas sharing, learning and resource sharing, and improved decision making. To address the limitations in the existing literature, this dissertation presents a design science artifact and a conceptual model for collaborative environment. The first artifact is a blockchain based collaborative information exchange system that utilizes blockchain technology and semi-automated ontology mappings to enable secure and interoperable health information exchange among different health care institutions. The conceptual model proposed in this dissertation explores the factors that influences professionals continued use of video- conferencing applications. The conceptual model investigates the role the perceived risks and benefits play in influencing professionals’ attitude towards VC apps and consequently its active and automatic use

DETAILED CLINICAL MODELS AND THEIR RELATION WITH ELECTRONIC HEALTH RECORDS

Tesis por compendio[EN] Healthcare domain produces and consumes big quantities of people's health data. Although data exchange is the norm rather than the exception, being able to access to all patient data is still far from achieved. Current developments such as personal health records will introduce even more data and complexity to the Electronic Health Records (EHR). Achieving semantic interoperability is one of the biggest challenges to overcome in order to benefit from all the information contained in the distributed EHR. This requires that the semantics of the information can be understood by all involved parties. It has been stablished that three layers are needed to achieve semantic interoperability: Reference models, clinical models (archetypes), and clinical terminologies. As seen in the literature, information models (reference models and clinical models) are lacking methodologies and tools to improve EHR systems and to develop new systems that can be semantically interoperable. The purpose of this thesis is to provide methodologies and tools for advancing the use of archetypes in three different scenarios: - Archetype definition over specifications with no dual model architecture native support. Any EHR architecture that directly or indirectly has the notion of detailed clinical models (such as HL7 CDA templates) can be potentially used as a reference model for archetype definition. This allows transforming single-model architectures (which contain only a reference model) into dual-model architectures (reference model with archetypes). A set of methodologies and tools has been developed to support the definition of archetypes from multiple reference models. - Data transformation. A complete methodology and tools are proposed to deal with the transformation of legacy data into XML documents compliant with the archetype and the underlying reference model. If the reference model is a standard then the transformation is a standardization process. The methodologies and tools allow both the transformation of legacy data and the transformation of data between different EHR standards. - Automatic generation of implementation guides and reference materials from archetypes. A methodology for the automatic generation of a set of reference materials is provided. These materials are useful for the development and use of EHR systems. These reference materials include data validators, example instances, implementation guides, human-readable formal rules, sample forms, mindmaps, etc. These reference materials can be combined and organized in different ways to adapt to different types of users (clinical or information technology staff). This way, users can include the detailed clinical model in their organization workflow and cooperate in the model definition. These methodologies and tools put clinical models as a key part of the system. The set of presented methodologies and tools ease the achievement of semantic interoperability by providing means for the semantic description, normalization, and validation of existing and new systems.[ES] El sector sanitario produce y consume una gran cantidad de datos sobre la salud de las personas. La necesidad de intercambiar esta información es una norma más que una excepción, aunque este objetivo está lejos de ser alcanzado. Actualmente estamos viviendo avances como la medicina personalizada que incrementarán aún más el tamaño y complejidad de la Historia Clínica Electrónica (HCE). La consecución de altos grados de interoperabilidad semántica es uno de los principales retos para aprovechar al máximo toda la información contenida en las HCEs. Esto a su vez requiere una representación fiel de la información de tal forma que asegure la consistencia de su significado entre todos los agentes involucrados. Actualmente está reconocido que para la representación del significado clínico necesitamos tres tipos de artefactos: modelos de referencia, modelos clínicos (arquetipos) y terminologías. En el caso concreto de los modelos de información (modelos de referencia y modelos clínicos) se observa en la literatura una falta de metodologías y herramientas que faciliten su uso tanto para la mejora de sistemas de HCE ya existentes como en el desarrollo de nuevos sistemas con altos niveles de interoperabilidad semántica. Esta tesis tiene como propósito proporcionar metodologías y herramientas para el uso avanzado de arquetipos en tres escenarios diferentes: - Definición de arquetipos sobre especificaciones sin soporte nativo al modelo dual. Cualquier arquitectura de HCE que posea directa o indirectamente la noción de modelos clínicos detallados (por ejemplo, las plantillas en HL7 CDA) puede ser potencialmente usada como modelo de referencia para la definición de arquetipos. Con esto se consigue transformar arquitecturas de HCE de modelo único (solo con modelo de referencia) en arquitecturas de doble modelo (modelo de referencia + arquetipos). Se han desarrollado metodologías y herramientas que faciliten a los editores de arquetipos el soporte a múltiples modelos de referencia. - Transformación de datos. Se propone una metodología y herramientas para la transformación de datos ya existentes a documentos XML conformes con los arquetipos y el modelo de referencia subyacente. Si el modelo de referencia es un estándar entonces la transformación será un proceso de estandarización de datos. La metodología y herramientas permiten tanto la transformación de datos no estandarizados como la transformación de datos entre diferentes estándares. - Generación automática de guías de implementación y artefactos procesables a partir de arquetipos. Se aporta una metodología para la generación automática de un conjunto de materiales de referencia de utilidad en el desarrollo y uso de sistemas de HCE, concretamente validadores de datos, instancias de ejemplo, guías de implementación , reglas formales legibles por humanos, formularios de ejemplo, mindmaps, etc. Estos materiales pueden ser combinados y organizados de diferentes modos para facilitar que los diferentes tipos de usuarios (clínicos, técnicos) puedan incluir los modelos clínicos detallados en el flujo de trabajo de su sistema y colaborar en su definición. Estas metodologías y herramientas ponen los modelos clínicos como una parte clave en el sistema. El conjunto de las metodologías y herramientas presentadas facilitan la consecución de la interoperabilidad semántica al proveer medios para la descripción semántica, normalización y validación tanto de sistemas nuevos como ya existentes.[CA] El sector sanitari produeix i consumeix una gran quantitat de dades sobre la salut de les persones. La necessitat d'intercanviar aquesta informació és una norma més que una excepció, encara que aquest objectiu està lluny de ser aconseguit. Actualment estem vivint avanços com la medicina personalitzada que incrementaran encara més la grandària i complexitat de la Història Clínica Electrònica (HCE). La consecució d'alts graus d'interoperabilitat semàntica és un dels principals reptes per a aprofitar al màxim tota la informació continguda en les HCEs. Açò, per la seua banda, requereix una representació fidel de la informació de tal forma que assegure la consistència del seu significat entre tots els agents involucrats. Actualment està reconegut que per a la representació del significat clínic necessitem tres tipus d'artefactes: models de referència, models clínics (arquetips) i terminologies. En el cas concret dels models d'informació (models de referència i models clínics) s'observa en la literatura una mancança de metodologies i eines que en faciliten l'ús tant per a la millora de sistemes de HCE ja existents com per al desenvolupament de nous sistemes amb alts nivells d'interoperabilitat semàntica. Aquesta tesi té com a propòsit proporcionar metodologies i eines per a l'ús avançat d'arquetips en tres escenaris diferents: - Definició d'arquetips sobre especificacions sense suport natiu al model dual. Qualsevol arquitectura de HCE que posseïsca directa o indirectament la noció de models clínics detallats (per exemple, les plantilles en HL7 CDA) pot ser potencialment usada com a model de referència per a la definició d'arquetips. Amb açò s'aconsegueix transformar arquitectures de HCE de model únic (solament amb model de referència) en arquitectures de doble model (model de referència + arquetips). S'han desenvolupat metodologies i eines que faciliten als editors d'arquetips el suport a múltiples models de referència. - Transformació de dades. Es proposa una metodologia i eines per a la transformació de dades ja existents a documents XML conformes amb els arquetips i el model de referència subjacent. Si el model de referència és un estàndard llavors la transformació serà un procés d'estandardització de dades. La metodologia i eines permeten tant la transformació de dades no estandarditzades com la transformació de dades entre diferents estàndards. - Generació automàtica de guies d'implementació i artefactes processables a partir d'arquetips. S'hi inclou una metodologia per a la generació automàtica d'un conjunt de materials de referència d'utilitat en el desenvolupament i ús de sistemes de HCE, concretament validadors de dades, instàncies d'exemple, guies d'implementació, regles formals llegibles per humans, formularis d'exemple, mapes mentals, etc. Aquests materials poden ser combinats i organitzats de diferents maneres per a facilitar que els diferents tipus d'usuaris (clínics, tècnics) puguen incloure els models clínics detallats en el flux de treball del seu sistema i col·laborar en la seua definició. Aquestes metodologies i eines posen els models clínics com una part clau del sistemes. El conjunt de les metodologies i eines presentades faciliten la consecució de la interoperabilitat semàntica en proveir mitjans per a la seua descripció semàntica, normalització i validació tant de sistemes nous com ja existents.Boscá Tomás, D. (2016). DETAILED CLINICAL MODELS AND THEIR RELATION WITH ELECTRONIC HEALTH RECORDS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/62174TESISCompendi

Requirements engineering for electronic healthcare records

This thesis investigates requirements engineering methods based on process modelling for Electronic Healthcare Record (EHR) systems. The relation between software requirements and user workflows is essential in healthcare settings: EHRs are expected to improve clinical and administrative workflows. In turn, the new workflows are expected to satisfy a number of business goals. If a new software system does not support the desired clinical workflows or patient journeys, then its value and benefits are often disputed by stakeholders. Our hypothesis is that requirements engineering methods based on process models will contribute to the overall success of EHR projects in the industry. By success, we mean software systems that are in use and meet the business benefits expected of them. The experiments presented in this thesis are aimed to develop and evaluate a method that allows business analysts to make use of process models during requirements engineering for EHRs. The goal of the method is to ensure the software specification is aligned to and supports the user workflows. Each of the four experiments addresses a specific research objective, and thus the findings from each experiment constitute the basis for one of our four contributions to science. / Experiment 1: Relating Goal Oriented Requirements Engineering and Process Modelling: This experiment investigates the design of a common framework for describing process models and software requirements. It relates the KAOS framework for goal oriented requirements engineering and the Business Process Modelling Notation (BPMN). Our goal is to facilitate requirements elicitation. Specifically, business analysts using our framework should be able to reason about the alignment of the software specification to the business processes, and identify specific changes that improve this alignment (either changes in the design of the system, or changes in the business processes). This first experiment was conducted as part of the WellbeingUCL project, supported by Boots. / Experiment 2: Inferring Goal Models from Process Models: The second experiment investigates a method for business analysts to derive software requirements from process models. The purpose for defining such a method is to provide sufficient guidance to business analysts, during requirements elicitation. Our aim is to help business analysts elicit meaningful goal models and shape the design of the system-to-be, in light of these goals. A number of heuristics to facilitate requirements elicitation are proposed and evaluated, considering the trade-offs between a fully automated and a human driven process. / Experiment 3: Electronic Healthcare Record for Bupa: The third experiment evaluates the requirements engineering method during an EHR implementation for a chronic condition management service delivered by Bupa nurses in South West England. Action research is used to assess the impact and fit of the requirements elicitation process, in relation to the current work practices of business analysts in the industry. The extended KAOS framework and goal inference heuristics have been used to inform the final software specification, guide the workflow redesign and clarify the business benefits. From a project management perspective, this experiment evaluates how the KAOS method aligns with the Agile and Lean methodologies used in Bupa. The project has delivered an EHR system actively used to support the care of 2,600 patients. / Experiment 4: Personal Health Record for Nuffield Health: The fourth experiment evaluates the extended KAOS framework when developing a new digital customer proposition with an underlying EHR system. It investigates how consumer journeys can be modelled as KAOS process models. Of specific interest is the ability of the framework to clarify the responsibility assignments among the different agents (i.e. system components) that need to collaborate to deliver the end to end customer journey. The experiment was run as an action research project, in partnership with Nuffield Health. The results have informed the architecture of an open source personal health record for lifestyle data. / Contributions to science: This thesis advances the field of requirements engineering by introducing and evaluating a requirements elicitation method based on business process models. It also presents new evidence into the use of goal oriented requirements engineering for the design and implementation of EHR systems in the industry. Our four contributions to science directly follow from the results of the four experiments conducted as part of this research. Our first two contributions cover the conceptual framework and our proposed method for requirement elicitation based on process models. Our last two contributions present evidence for the practical use and benefits of our goal oriented requirements engineering method in industry based projects. First, we present an extension of the KAOS requirements engineering framework which includes a business process view with clearly defined syntax and execution semantic. This approach ensures process models and goal models have a shared semantic. A new concept, that of Intentional Fragment, captures the explicit relation between fragments of a process model and a specific goal. We also define additional consistency rules, to clarify how the process view relates with other KAOS models: object, agent and operation model. Secondly, we present a set of goal inference techniques to help analysts build goal models starting from process models. In effect, analysts can start from the artefacts that are most familiar to them (i.e. the workflow models) and gradually derive a goal model for the system-to-be. A set of 12 heuristics have been fully defined and integrated into a semi-structured method for goal elicitation. Our third contribution is an evaluation of how the goal oriented requirements engineering method (incorporating workflow analysis) supports the design and deployment of a EHR system in a clinical setting. The project was representative for the challenges faced by healthcare organisations wishing to deploy EHRs: quality of care standards that impose constraints on process redesign; legacy systems that have shaped the workflow; organisational complexity and competing stakeholder interests. We show that by methodically applying our goal inference techniques we were able to produce a valid goal model starting from models of the nurses workflows. The resulting goal model was used to reason about alternative design options in the system-to-be, and to clarify the benefit case in deploying the EHR system. Fourth, we examine the requirements engineering process for an EHR system meant to support a new customer proposition. This project was representative for the challenges faced in the digital health industry: a target consumer journey driven by user experience research; many different systems required to collaborate; focus on the architectural design of the system. We show that we can apply our goal inference techniques to customer journey maps and produce a meaningful goal model. This has been used to shape the architecture of the EHR system and reason about integration requirements. We also argue that our goal inference techniques complement agile development practices used within the organisation