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The Vision for eHealth infers that Sweden should be best in the world to utilize the opportunities of the digitization by 2025. One of three particularly important areas of action to realize the vision is standardization of e.g. exchange of information. HL7 FHIR is a modern standard for interoperability within e-health. HL7 FHIR enables the exchange of information between different healthcare information systems in an easy way. The basic building blocks in HL7 FHIR are called resources. These represent healthcare entities of some kind, e.g. Patient, Medication, Care plan, and Device. A base set of resources should either together, or by themselves, be able to satisfy the most common use cases in healthcare. A set of rules about a resource's content is called a profile, which is used for defining extensions and constraints on a resource. Profiles can be used to customize the standard to everything from a small local use-case to characteristics common for a whole country, so-called national profiles. This master thesis project sought to investigate the opportunities and restrictions with HL7 FHIR profiling by mapping the outlook of e-health stakeholders in Sweden. The project conducted a mixed method approach. Surveys were sent out to regions, county councils and private caregivers and interviews were held with national stakeholders, industry suppliers, HL7 Sweden and subject experts. The qualitative data was processed through a thematic analysis and the quantitative data was processed through a descriptive analysis. The results showed that there were positive views on governing and maintaining HL7 FHIR and FHIR profiling on a national level and to the establishment of national FHIR profiles. However, questions remain on how it shold be done. Among caregivers there were in general positive attitudes towards HL7 FHIR as a standard for interoperability and towards a possible implementation. However, the implementation level was low and specific knowledge of HL7 FHIR profiles is yet needed. / Vision e-Hälsa 2025 innebär att Sverige ska vara bäst i världen på att utnyttja möjligheterna med digitaliseringen år 2025. Ett av tre särskilt viktiga handlingsområden för att förverkliga visionen är standardisering, t.ex. av utbyte av information. HL7 FHIR är en modern standard för interoperabilitet inom e-hälsa och möjliggör utbyte av information mellan olika hälsoinformationssystem på ett enkelt sätt. De grundläggande byggstenarna i HL7 FHIR kallas resurser. Dessa representerar hälso- och sjukvårdsentiteter av något slag, t.ex. Patient, Medicin, Vårdplan och Apparat. En basuppsättning av resurser ska antingen tillsammans eller i sig själva kunna tillgodose de vanligaste användningsfallen inom hälso- och sjukvård. En uppsättning regler om en resurs innehåll kallas för profil och används för att definiera tillägg och begränsningar på en resurs. Profiler kan användas för att anpassa standarden till allt från ett litet lokalt användningsfall till egenskaper som är gemensamma för ett helt land, så kallade nationella profiler. Detta masterexamensarbete ämnade undersöka möjligheter och begränsningar med HL7 FHIR-profilering genom att kartlägga utsikterna för ehälso-aktörer i Sverige. I projektet genomfördes en mixad metodinriktning, i vilken enkäter skickades ut till regioner, landsting och privata vårdgivare och intervjuer hölls med nationella intressenter, leverantörer, HL7 Sverige och ämnesexperter. Kvalitativ data genomgick en tematisk analys och kvantitativ data genomgick en deskriptiv analys. Resultatet visade på en generellt positiv attityd gentemot ett framtagande och förvaltande av HL7 FHIR och FHIR-profiler på nationell nivå och införande av nationella FHIR-profiler. Däremot kvarstår frågor om hur det ska realiseras. Bland vårdgivare var det generellt positiva attityder gentemot HL7 FHIR som en standard för interoperabilitet och en eventuell implementation. Däremot var den generella implementationsnivån låg och ytterligare kunskap om HL7 FHIR-profiler behövs.

För att svenska vårdsystem skall kunna kommunicera med varandra har Inera som ägs av Sveriges Kommuner och Landsting (SKL) utformat en standard för hur vårdinformation skall struktureras. Denna standard kallas Regelverk för interoperabilitet inom vård och omsorg – tekniska anvisningar (RIVTA) och består av en uppsättning regler, så kallade tjänstekontrakt. Problemet med RIVTA är att det inte sträcker sig utanför Sveriges gränser. Därför är regioner (f.d. landsting) och kommuner intresserade av en ny internationell standard som kallas Fast Healthcare Interoperability Resources (FHIR). Studiens uppdragsgivare Nordic Medtest, är ett företag som testar och kvalitetssäkrar mjukvara inom svensk vård och omsorg. Nordic Medtest vill därför ligga i framkant gällande FHIR och skapa en miljö där deras kunder kan testa sina system.   Målet med denna studie är att översätta en delmängd av information i två tjänstekontrakt för RIVTA, som tillhandahållits av uppdragsgivaren på Nordic Medtest tjänstekontrakten getObservations och getActivities till motsvarande standarden för FHIR. Tillsammans med detta skall en testmiljö för dessa två översatta tjänstekontrakt tas fram. En användare skall kunna efterfråga de två översatta kontrakten via ett gränssnitt där de sedan presenteras på skärmen för användaren. I samband med översättningen av tjänstekontrakten och utvecklingen av testmiljön ska en teststrategi tas fram vars mål är att säkerställa en korrekt översättning och en kvalitetssäkrad testmiljö. / In order for Swedish healthcare systems to communicate, Inera, a company owned by the Swedish Municipalities and County Council (SKL), has formed a standard on how care information should be structured. This standard is called Rules for interoperability in health and care - technical instructions (RIVTA) and consists of a set of service contracts. The weakness of with RIVTA is that it does not extend beyond Sweden's borders. Therefore, regions (former county councils) and municipalities look at a new international standard called Fast Healthcare Interoperability Resources (FHIR). The study's client Nordic Medtest is a company that tests and quality-assures software in Swedish healthcare and care. Nordic Medtest wants to be at the forefront of FHIR and wants to create an environment where their clients can test their systems. The goal of this study is to translate a limited amount of two service contracts for RIVTA, the contracts getObservations and getActivities to corresponding structures in FHIR. In parallel with this a test environment for these two translated service contracts will be developed. A user will have the ability to request the two translated contracts through an interface which will present the information in the requested contracts. Together with the translation of the two service contracts and test environment development a testing strategy will be developed with the aim to ensure a correct translation and a quality safe test environment.

[pt] Este trabalho apresenta uma proposta de implementação de uma blockchain privada gerenciada por agentes de software para armazenar dados de sáude. A tecnologia blockchain está mudando a maneira com que dados privados são armazenados. Agora é possível compartilhar informações sem revelar quem é o dono da informação. Este trabalho apresenta um sistema que permite que usuários armazenagem dados de saúde em uma blockchain gerenciada por agentes de software. Pesquisas revelaram que dados de saúde devem ser armazenado em blockchains privadas, pois são privadas e não devem ser acessíveis para qualquer pessoa como em blockchains públicas. Técnicas de engenharia de software foram utilizadas para desenvolver a arquitetura proposta. O resultado é uma blockchain privada capaz de manipular dados no padrão HL7 e armazena-los de forma anônima e privada. Agentes de software foram utilizados para realizar todo o processo de recebimento, validação e inserção de dados no blockchain. / [en] This paper presents an implementation approach for a private blockchain that is managed by software agents for healthcare data storage. Blockchain technology is changing the way we store private information. Now, it is possible to share private information while not revealing its owner s identity. This paper presents a solution, which enables users to store medical data by using blockchains along with software agents. Further research work has shown that healthcare data, as sensitive information, should be stored in private blockchains through the use of appropriate methods. Software engineering techniques have been used to achieve the proposed solution. The result is a private blockchain that is suitable for manipulating HL7 data, ensuring anonymity and privacy. This can be achieved through software agents that act as regulatory controls for the private blockchains.

An average of 3 million deaths occurs each year in high-income countries due to unsafe care, with causes including diagnostic and communication failures. These failures are related to clinical information overload, the extraction of essential unstructured data, and complex health data analytics for deriving insights. The use case of this dissertation focuses on emergency room (ER) physicians, as they are the initial point of contact for patients, and time-sensitive situations occur frequently in the ER. The goal is to develop an intelligent clinical information platform (ICIP) for ER physicians, assisting patients’ care pathways using machine learning (ML). This platform provides a new, multidimensional view to represent patients’ medical conditions, focused on heart diseases. To achieve the platform’s implementation, three technical components are developed and published within this dissertation: first, a component for data extraction from remote video consultations via WebRTC; second, a data classification component using a Faster Region-Based Convolutional Neural Network (R-CNN) model together with active learning (AL); and third, a data search component with an implemented Elasticsearch pipeline and data storage unified in the FHIR standard. The research for a newly developed clinical platform is practically and industrially based on building a future clinical product. For this product, ML models are developed to analyze data from past clinical treatments using an R-CNN model for text classification and to access verbal audio data through a speech-to-text (STT) engine employing an RNN TensorFlow model and a large language model (LLM) from NLP.js. Additionally, JSON object-based rule-based reasoning from FHIR is used. It has been demonstrated that a three-tier architecture (AngularJS, Java Spring Boot, and PostgreSQL), consisting of components involving neural networks such as R-CNN, RNN (recurrent neural network), and LLM, can be implemented as a data platform for assisting heart disease care pathways. This allows physicians to interpret patients’ vital parameters, pathways, and timelines via diagrams presented in widgets on the AngularJS frontend.

Background: In the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium, an IT-based clinical trial recruitment support system was developed based on the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Currently, OMOP CDM is populated with German Fast Healthcare Interoperability Resources (FHIR) using an Extract-Transform-Load (ETL) process, which was designed as a bulk load. However, the computational effort that comes with an everyday full load is not efficient for daily recruitment. Objective: The aim of this study is to extend our existing ETL process with the option of incremental loading to efficiently support daily updated data. Methods: Based on our existing bulk ETL process, we performed an analysis to determine the requirements of incremental loading. Furthermore, a literature review was conducted to identify adaptable approaches. Based on this, we implemented three methods to integrate incremental loading into our ETL process. Lastly, a test suite was defined to evaluate the incremental loading for data correctness and performance compared to bulk loading. Results: The resulting ETL process supports bulk and incremental loading. Performance tests show that the incremental load took 87.5% less execution time than the bulk load (2.12 min compared to 17.07 min) related to changes of 1 day, while no data differences occurred in OMOP CDM. Conclusions: Since incremental loading is more efficient than a daily bulk load and both loading options result in the same amount of data, we recommend using bulk load for an initial load and switching to incremental load for daily updates. The resulting incremental ETL logic can be applied internationally since it is not restricted to German FHIR profiles.