Doctor of Philosophy

dissertationLogical Observation Identifiers Names and Codes (LOINC®) was developed in 1994 to provide a universal vocabulary for reporting laboratory and clinical observations. This dissertation was aimed at determining whether LOINC is meeting its goal when it is used in the real world. Three institutions, Associated and Regional University Pathologist (ARUP), Intermountain Healthcare, and Regenstrief Institute, were invited to participate in this research. These institutions represented three of the seven institutions that provided their catalogue of laboratory test names for creating the first version of laboratory LOINC codes. After obtaining IRB approval, each institution provided 5 years (2003-2007) of laboratory data and their associated local codes and LOINC code mappings. Extensional definitions (EDs) were used to characterize the laboratory data reported by a specific LOINC code. EDs included frequency of testing, mean and standard deviation of the result values, coded variables, etc. To reduce privacy concerns, we distributed parsing and processing programs to each institution and the initial processing of the raw results occurred within the local systems, and only the deidentified EDs were sent to the primary investigator for combined analysis. We used the EDs to evaluate the coverage, correctness, consistency and competence of LOINC. For coverage, we analyzed how many laboratory tests being routinely tested in daily operations could be assigned a correct LOINC code. For correctness, we verified the accuracy of LOINC mappings to local codes. For consistency and usefulness, we detected any inconsistencies in LOINC design and measured the degree of semantic interoperability that could be achieved using LOINC. Besides auditing LOINC code use, we also analyzed the result values that were associated with the LOINC results (i.e. characteristics like the type of result (number, coded value), units of measure, answer set (positive/negative) etc.). We also found that consistent use of result values was important in achieving semantic interoperability when exchanging laboratory data. Our analysis produced the following results: 1. Completeness: LOINC can provide 99% coverage rate for the results in two typical health care institutions and 79% coverage for results from a reference laboratory. 2. Correctness: An error rate of 4.5% existed in mappings at the three institutions. 3. Consistency and usefulness: Several complicated or inconsistent designs for LOINC usage were found, which reduced the semantic interoperability of LOINC

A corpus-based approach for automated LOINC mapping

Objective To determine whether the knowledge contained in a rich corpus of local terms mapped to LOINC (Logical Observation Identifiers Names and Codes) could be leveraged to help map local terms from other institutions. Methods We developed two models to test our hypothesis. The first based on supervised machine learning was created using Apache's OpenNLP Maxent and the second based on information retrieval was created using Apache's Lucene. The models were validated by a random subsampling method that was repeated 20 times and that used 80/20 splits for training and testing, respectively. We also evaluated the performance of these models on all laboratory terms from three test institutions. Results For the 20 iterations used for validation of our 80/20 splits Maxent and Lucene ranked the correct LOINC code first for between 70.5% and 71.4% and between 63.7% and 65.0% of local terms, respectively. For all laboratory terms from the three test institutions Maxent ranked the correct LOINC code first for between 73.5% and 84.6% (mean 78.9%) of local terms, whereas Lucene's performance was between 66.5% and 76.6% (mean 71.9%). Using a cut-off score of 0.46 Maxent always ranked the correct LOINC code first for over 57% of local terms. Conclusions This study showed that a rich corpus of local terms mapped to LOINC contains collective knowledge that can help map terms from other institutions. Using freely available software tools, we developed a data-driven automated approach that operates on term descriptions from existing mappings in the corpus. Accurate and efficient automated mapping methods can help to accelerate adoption of vocabulary standards and promote widespread health information exchange

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

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

Uma rede telemática para a prestação regional de cuidados de saúde

Doutoramento em Engenharia InformáticaAs tecnologias de informação e comunicação na área da saúde não são só um instrumento para a boa gestão de informação, mas antes um fator estratégico para uma prestação de cuidados mais eficiente e segura. As tecnologias de informação são um pilar para que os sistemas de saúde evoluam em direção a um modelo centrado no cidadão, no qual um conjunto abrangente de informação do doente deve estar automaticamente disponível para as equipas que lhe prestam cuidados, independentemente de onde foi gerada (local geográfico ou sistema). Este tipo de utilização segura e agregada da informação clínica é posta em causa pela fragmentação generalizada das implementações de sistemas de informação em saúde. Várias aproximações têm sido propostas para colmatar as limitações decorrentes das chamadas “ilhas de informação” na saúde, desde a centralização total (um sistema único), à utilização de redes descentralizadas de troca de mensagens clínicas. Neste trabalho, propomos a utilização de uma camada de unificação baseada em serviços, através da federação de fontes de informação heterogéneas. Este agregador de informação clínica fornece a base necessária para desenvolver aplicações com uma lógica regional, que demostrámos com a implementação de um sistema de registo de saúde eletrónico virtual. Ao contrário dos métodos baseados em mensagens clínicas ponto-a-ponto, populares na integração de sistemas em saúde, desenvolvemos um middleware segundo os padrões de arquitetura J2EE, no qual a informação federada é expressa como um modelo de objetos, acessível através de interfaces de programação. A arquitetura proposta foi instanciada na Rede Telemática de Saúde, uma plataforma instalada na região de Aveiro que liga oito instituições parceiras (dois hospitais e seis centros de saúde), cobrindo ~350.000 cidadãos, utilizada por ~350 profissionais registados e que permite acesso a mais de 19.000.000 de episódios. Para além da plataforma colaborativa regional para a saúde (RTSys), introduzimos uma segunda linha de investigação, procurando fazer a ponte entre as redes para a prestação de cuidados e as redes para a computação científica. Neste segundo cenário, propomos a utilização dos modelos de computação Grid para viabilizar a utilização e integração massiva de informação biomédica. A arquitetura proposta (não implementada) permite o acesso a infraestruturas de e-Ciência existentes para criar repositórios de informação clínica para aplicações em saúde.Modern health information technology is not just a supporting instrument to good information management but a strategic requirement to provide more efficient and safer health care. Health information technology is a cornerstone to build the future patient-centric health care systems in which a comprehensive set of patient data will be available to the relevant care teams, in spite of where (system or service point) it was generated. Such secure and efficient use of clinical data is challenged by the existing fragmentation of health information systems implementation. Several approaches have been proposed to address the limitations of the so called “information silos” in healthcare, ranging from full centralization (a single system) to full-decentralized clinical message exchange networks. In this work we advocate the use of a service-based unification layer, by federating distributed heterogeneous information sources. This clinical information hub provides the basis to build regional-level applications, which we have demonstrated by implementing a virtual Electronic Health Record system. Unlike the message-driven, point-to-point approaches popular in health care systems integration, we developed a middleware layer, using J2EE architectural patterns, in which the common information is represented as an object model, accessible through programming interfaces. The proposed architecture was instantiated in the Rede Telemática da Saúde network, a platform deployed in the region of Aveiro connecting eight partner institutions (two hospitals and six primary care units), covering ~ 350,000 citizens, indexing information on more than 19,000,000 episodes of care and used by ~350 registered professionals. In addition to the regional health information collaborative platform (RTSys), we introduce a second line of research towards bridging the care networks and the science networks. In the later scenario, we propose the use of Grid computing to enable the massive use and integration of biomedical information. The proposed architecture (not implemented) enables to access existing e-Science infrastructures to create clinical information repositories for health applications

Quality framework for semantic interoperability in health informatics: definition and implementation

Aligned with the increased adoption of Electronic Health Record (EHR) systems, it is recognized that semantic interoperability provides benefits for promoting patient safety and continuity of care. This thesis proposes a framework of quality metrics and recommendations for developing semantic interoperability resources specially focused on clinical information models, which are defined as formal specifications of structure and semantics for representing EHR information for a specific domain or use case. This research started with an exploratory stage that performed a systematic literature review with an international survey about the clinical information modelling best practice and barriers. The results obtained were used to define a set of quality models that were validated through Delphi study methodologies and end user survey, and also compared with related quality standards in those areas that standardization bodies had a related work programme. According to the obtained research results, the defined framework is based in the following models: Development process quality model: evaluates the alignment with the best practice in clinical information modelling and defines metrics for evaluating the tools applied as part of this process. Product quality model: evaluates the semantic interoperability capabilities of clinical information models based on the defined meta-data, data elements and terminology bindings. Quality in use model: evaluates the suitability of adopting semantic interoperability resources by end users in their local projects and organisations. Finally, the quality in use model was implemented within the European Interoperability Asset register developed by the EXPAND project with the aim of applying this quality model in a broader scope to contain any relevant material for guiding the definition, development and implementation of interoperable eHealth systems in our continent. Several European projects already expressed interest in using the register, which will now be sustained by the European Institute for Innovation through Health Data

Informatics for Health 2017 : advancing both science and practice

Conference report, The Informatics for Health congress, 24-26 April 2017, in Manchester, UK.Introduction : The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress. Discussion : The twin programmes of “Big Data” and “Digital Health” are not always joined up by coherent policy and investment priorities. Substantial global investment in health IT and data science has led to sound progress but highly variable outcomes. Society needs an approach that brings together the science and the practice of health informatics. The goal is multi-level Learning Health Systems that consume and intelligently act upon both patient data and organizational intervention outcomes. Conclusions : Informatics for Health demonstrated the art of the possible, seen in the breadth and depth of our contributions. We call upon policy makers, research funders and programme leaders to learn from this joined-up approach.Publisher PDFPeer reviewe