Comparative study of healthcare messaging standards for interoperability in ehealth systems

Advances in the information and communication technology have created the field of "health informatics," which amalgamates healthcare, information technology and business. The use of information systems in healthcare organisations dates back to 1960s, however the use of technology for healthcare records, referred to as Electronic Medical Records (EMR), management has surged since 1990’s (Net-Health, 2017) due to advancements the internet and web technologies. Electronic Medical Records (EMR) and sometimes referred to as Personal Health Record (PHR) contains the patient’s medical history, allergy information, immunisation status, medication, radiology images and other medically related billing information that is relevant. There are a number of benefits for healthcare industry when sharing these data recorded in EMR and PHR systems between medical institutions (AbuKhousa et al., 2012). These benefits include convenience for patients and clinicians, cost-effective healthcare solutions, high quality of care, resolving the resource shortage and collecting a large volume of data for research and educational needs. My Health Record (MyHR) is a major project funded by the Australian government, which aims to have all data relating to health of the Australian population stored in digital format, allowing clinicians to have access to patient data at the point of care. Prior to 2015, MyHR was known as Personally Controlled Electronic Health Record (PCEHR). Though the Australian government took consistent initiatives there is a significant delay (Pearce and Haikerwal, 2010) in implementing eHealth projects and related services. While this delay is caused by many factors, interoperability is identified as the main problem (Benson and Grieve, 2016c) which is resisting this project delivery. To discover the current interoperability challenges in the Australian healthcare industry, this comparative study is conducted on Health Level 7 (HL7) messaging models such as HL7 V2, V3 and FHIR (Fast Healthcare Interoperability Resources). In this study, interoperability, security and privacy are main elements compared. In addition, a case study conducted in the NSW Hospitals to understand the popularity in usage of health messaging standards was utilised to understand the extent of use of messaging standards in healthcare sector. Predominantly, the project used the comparative study method on different HL7 (Health Level Seven) messages and derived the right messaging standard which is suitable to cover the interoperability, security and privacy requirements of electronic health record. The issues related to practical implementations, change over and training requirements for healthcare professionals are also discussed

Web application of physiological data based on FHIR

This paper works toward implementing a prototype demonstrating some of the capabilities of the FHIR specification. The specification requires a clear understanding of its different components in order to be successfully implemented, therefore the primary concern of this work is to understand and analyse FHIR’s concepts. The research conducted in this work revealed that FHIR is a well-designed specification, based on a powerful data model and technologies. Therefore, it sould help solving the interoperability issues of the healthcare eco-system. It has also been pointed that since FHIR is a recent standard, many of its uses and benefits are still to be discovered. Moreover, FHIR integrates well in the current health information technology context since it can be used in addition to existing standards

FUTURE-ORIENTED AND PATIENT-CENTRIC? A QUALITATIVE ANALYSIS OF DIGITAL THERAPEUTICS AND THEIR INTEROPERABILITY

This paper focuses on the integration of digital therapeutics (DTx) into future-oriented and patient-centric care pathways. Based on a workshop series and problem-centered interviews in Germany, the current state-of-the-art of regulatory and technical integration of DTx was mapped as a landscape of DTx interoperability. The results focus on key interfaces of DTx, namely with Electronic Health Records (EHRs), devices, and other digital health innovations such as telemedicine, and highlight current challenges and potentials for future development. On a broader level, the results point to unresolved issues of care coordination, the optional role of the EHRs as regulated platforms for care, and the importance of integrating DTx data into public data spaces for research

Desenvolvimento de uma Infraestrutura baseada em HL7® FHIR® para Interoperabilidade Clínica

Throughout the years, the healthcare business knowledge, requirements, and the number of patients seeking medical attention has grown tremendously to a point where sensitive cases needed the input from multiple healthcare institutions in order to track the patient’s medical history and make the most adequate decisions for each situation. Technology and digital information fulfils a great role in addressing these problems and improving healthcare provision. However, due to the immense number of organizations and systems in this business, sharing a patient’s clinical information can be a major problem if the systems are not capable of understanding the data sent to each other. Ensuring interoperability between systems is crucial to guarantee the continuous flow of a patient’s clinical history transmission and to improve the health professionals’ work. As a company working in the field of healthcare, ALERT’s main goal is to help organizations improve in their health business and to help prolong life, by providing the necessary technology that is capable of benefiting the health professional’s work management and sharing the necessary information with other organizations. Thus, the company seeks to constantly improve its product suite, ALERT®, by meeting the worldwide organizations requirements and assuring interoperability based on the existing health standards in the market. This way, the company wants to add in the ALERT suite the latest standard, Fast Healthcare Interoperability Resources (FHIR ® ), which brings great technological innovations for interoperability’s improvement, provided by the standards developing organization, Health Level Seven International (HL7), being also considered to be a suitable standard for mobile applications thanks to its capabilities and ease of implementation. Herewith, thisthesis presents a development and architectural approach to apply FHIR features in the product suite, along with the problem and solution analysis, including the evaluation of suitable frameworks for the implementation phase. Considering the experiments’ results, the implemented FHIR services actually improved the product’s performance, and thanks to the standard’s specification, the implementation of its core features proved to be simple and straightforward while respecting the key criteria for some of the developed services.Ao longo dos anos, o conhecimento, as exigências, e o número de pacientes à procura de cuidados médicos na área de negócio de cuidados de saúde, tem vindo a aumentar drasticamente ao ponto de ser necessária a opinião de outras instituições para casos de maior sensibilidade, de modo a que o historial médico do paciente fosse acompanhado e que servisse para tomar as decisões mais adequadas para o problema em questão. A tecnologia e a informação digital representam um grande papel na resolução de problemas e promoção de entrega de cuidados de saúde. No entanto, devido à imensa quantidade de organizações e sistemas nesta área de negócio, a partilha de informação clínica relativa a um paciente pode vir a ser um grave problema caso os sistemas não sejam capazes de compreender os dados que estão a ser transmitidos entre eles. Deste modo, assegurar interoperabilidade entre sistemas é crucial para garantir um fluxo contínuo de transmissão de informação relativa ao historial clínico de um paciente, e para melhorar o trabalho dos profissionais de saúde. Sendo uma empresa que trabalha na área de cuidados de saúde, a ALERT tem como principal objetivo ajudar as organizações a melhorar o seu negócio de saúde e ajudar a prolongar a vida, fornecendo a tecnologia necessária que beneficie a gestão de trabalho dos profissionais de saúde e que partilhe informação com outras organizações. Portanto, a empresa procura constantemente melhorar o seu produto ALERT®, procurando cumprir com os requisitos de organizações globais e garantindo interoperabilidade baseada nos standards de saúde existentes no mercado. Assim, a empresa pretende adotar o último standard lançado, Fast Healthcare Interoperability Resources (FHIR®), que traz grandes inovações tecnológicas para o aperfeiçoamento da interoperabilidade, fornecida pela organização de desenvolvimento de standards, Health Level Seven International (HL7), sendo também considerado um standard adequado para aplicações móveis graças às suas capacidades e facilidade de implementação. Com isto, esta tese apresenta uma abordagem arquitetural e de desenvolvimento para a aplicação de funcionalidades FHIR no produto, juntamente com a análise do problema e da solução, incluindo a avaliação de ferramentas adequadas para a fase de implementação. Os resultados de teste obtidos para os serviços FHIR implementados, demonstraram uma melhoria na performance do produto, e graças à especificação do standard, a implementação das principais funcionalidades provou ser simples e direta, respeitando os principais critérios para os serviços desenvolvidos

Emerging and Established Trends to Support Secure Health Information Exchange

This work aims to provide information, guidelines, established practices and standards, and an extensive evaluation on new and promising technologies for the implementation of a secure information sharing platform for health-related data. We focus strictly on the technical aspects and specifically on the sharing of health information, studying innovative techniques for secure information sharing within the health-care domain, and we describe our solution and evaluate the use of blockchain methodologically for integrating within our implementation. To do so, we analyze health information sharing within the concept of the PANACEA project that facilitates the design, implementation, and deployment of a relevant platform. The research presented in this paper provides evidence and argumentation toward advanced and novel implementation strategies for a state-of-the-art information sharing environment; a description of high-level requirements for the transfer of data between different health-care organizations or cross-border; technologies to support the secure interconnectivity and trust between information technology (IT) systems participating in a sharing-data “community”; standards, guidelines, and interoperability specifications for implementing a common understanding and integration in the sharing of clinical information; and the use of cloud computing and prospectively more advanced technologies such as blockchain. The technologies described and the possible implementation approaches are presented in the design of an innovative secure information sharing platform in the health-care domain

Health systems data interoperability and implementation

Objective The objective of this study was to use machine learning and health standards to address the problem of clinical data interoperability across healthcare institutions. Addressing this problem has the potential to make clinical data comparable, searchable and exchangeable between healthcare providers. Data sources Structured and unstructured data has been used to conduct the experiments in this study. The data was collected from two disparate data sources namely MIMIC-III and NHanes. The MIMIC-III database stored data from two electronic health record systems which are CareVue and MetaVision. The data stored in these systems was not recorded with the same standards; therefore, it was not comparable because some values were conflicting, while one system would store an abbreviation of a clinical concept, the other would store the full concept name and some of the attributes contained missing information. These few issues that have been identified make this form of data a good candidate for this study. From the identified data sources, laboratory, physical examination, vital signs, and behavioural data were used for this study. Methods This research employed a CRISP-DM framework as a guideline for all the stages of data mining. Two sets of classification experiments were conducted, one for the classification of structured data, and the other for unstructured data. For the first experiment, Edit distance, TFIDF and JaroWinkler were used to calculate the similarity weights between two datasets, one coded with the LOINC terminology standard and another not coded. Similar sets of data were classified as matches while dissimilar sets were classified as non-matching. Then soundex indexing method was used to reduce the number of potential comparisons. Thereafter, three classification algorithms were trained and tested, and the performance of each was evaluated through the ROC curve. Alternatively the second experiment was aimed at extracting patient’s smoking status information from a clinical corpus. A sequence-oriented classification algorithm called CRF was used for learning related concepts from the given clinical corpus. Hence, word embedding, random indexing, and word shape features were used for understanding the meaning in the corpus. Results Having optimized all the model’s parameters through the v-fold cross validation on a sampled training set of structured data ( ), out of 24 features, only ( 8) were selected for a classification task. RapidMiner was used to train and test all the classification algorithms. On the final run of classification process, the last contenders were SVM and the decision tree classifier. SVM yielded an accuracy of 92.5% when the and parameters were set to and . These results were obtained after more relevant features were identified, having observed that the classifiers were biased on the initial data. On the other side, unstructured data was annotated via the UIMA Ruta scripting language, then trained through the CRFSuite which comes with the CLAMP toolkit. The CRF classifier obtained an F-measure of 94.8% for “nonsmoker” class, 83.0% for “currentsmoker”, and 65.7% for “pastsmoker”. It was observed that as more relevant data was added, the performance of the classifier improved. The results show that there is a need for the use of FHIR resources for exchanging clinical data between healthcare institutions. FHIR is free, it uses: profiles to extend coding standards; RESTFul API to exchange messages; and JSON, XML and turtle for representing messages. Data could be stored as JSON format on a NoSQL database such as CouchDB, which makes it available for further post extraction exploration. Conclusion This study has provided a method for learning a clinical coding standard by a computer algorithm, then applying that learned standard to unstandardized data so that unstandardized data could be easily exchangeable, comparable and searchable and ultimately achieve data interoperability. Even though this study was applied on a limited scale, in future, the study would explore the standardization of patient’s long-lived data from multiple sources using the SHARPn open-sourced tools and data scaling platformsInformation ScienceM. Sc. (Computing

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication