Indiana University-Purdue University Indianapolis (IUPUI) / In the age of big data, better use of large, real-world datasets is needed, especially ultra-large databases that leverage health information exchange (HIE) systems to gather data from multiple sources. Promising as this process is, there have been challenges analyzing big data in healthcare due to big data attributes, mainly regarding volume, variety, and velocity. Thus, these health data require not only computational approaches but also context-based controls.In this research, we systematically examined associations among select neural and dermal conditions in an ultra-large healthcare database derived from an HIE, in which computational approaches with epidemiological measures were used. After a systematic cleaning, a binary logistic model-based methodology was used to search for associations, controlling for race and gender. Age groups were chosen using an algorithm to find the highest incidence rates for each condition pair. A binomial test was conducted to check for significant temporal direction among conditions to infer cause and effect. Gene-disease association data were used to evaluate the association among the conditions and assess the shared genetic background. The results were adjusted for multiple testing, and network graphs of significant associations were created. Findings among methodologies were compared to each other and with prior studies in the literature. In the results, seemingly distant neural and dermal conditions had an extensive number of associations. Controlling for race and gender tightened these associations, especially for racial factors affecting dermal conditions, like melanoma, and gender differences on conditions like migraine. Temporal and gene associations helped explain some of the results, but not all. Network visualizations summarized results, highlighting central conditions and stronger associations. Healthcare data are confounded by many factors that hide associations of interest. Triangulating associations with separate analyses helped with the interpretation of results. There are still numerous confounders in these data that bias associations. Aside from what is known, our approach with limited variables may inform hypothesis generation. Using additional variables with controlled-computational methods that require minimal external input may provide results that can guide healthcare, health policy, and further research.

Sverige är ett av de mest framträdande digitaliserade länderna inom EU. Men vissa sektorer har hamnat efter i digitaliseringsprocessen, en av dem är sjukvården. Sjukvården är en av de mest informationsintensiva sektorerna i det svenska samhället, det är kritiskt att IT-systemen är sammanhållna och kommunicerande med varandra, s.k. interoperabla. Just där brister sjukvårdens IT-system idag, men sjukvården som organisation brister också i att ha någon form av enhetlig standard för hur vårdinformation ska dokumenteras. Dessa brister leder till försämrad vårdkvalitet och arbetsmiljö för vårdpersonalen. Syftet med denna studie är att utveckla en artefakt för hur blockkedjeteknikens egenskaper kan användas för att förbättra interoperabiliteten i de svenska hälso- och sjukvårdssystemen. Vi har genomfört studien med en designbaserad metod, där vi tar fram en modell baserat på blockkedjans egenskaper och presenterade problem utifrån sex intervjuer av personer som arbetar med IT i vården. Vårt resultat visar att blockkedjan har egenskaper som kan stödja interoperabilitet i sjukvården. Resultatet visar också det krävs en balans mellan säkerhet och flexibilitet samt någon form av standard för hur vårdinformation ska dokumenteras, antingen på nationell eller regional nivå, för att skapa interoperabilitet. / Sweden is one of the most prominent digitized countries within the European Union. But some sectors have fallen behind in the digitizing process; one of them is the healthcare sector. The healthcare sector is one of the most information intensive fields in the Swedish society, where it is critical that the IT-systems are integrated and communicative with each other, so-called interoperable. Today's IT systems in healthcare are failing in terms of interoperability, but the healthcare itself as an organisation also fails to have some sort of uniform standard for documenting health data. These deficiencies lead to an impaired quality of care for the patients but also a worsened environment for the healthcare professionals. The purpose of this study is to develop an artefact for how the capabilities of the blockchain technology can be used to improve interoperability within the Swedish healthcare systems. We’ve conducted this paper by using a design-science based method, where we have developed a model based on the capabilities of blockchain technology and issues presented based on interviews with six people working with IT within healthcare. Our findings show that the blockchain technology has capabilities that can support interoperability within the healthcare systems. Our findings also show that to achieve interoperability there is a need to balance security and flexibility as well as some form of unified standard for how healthcare data is to be documented, on either a national or regional level.

A dissertation submitted to the Faculty of Arts in fulfilment of the requirements for the Degree of Doctor of Philosophy (Library and Information Studies) in the Department of Information Studies at the University Of Zululand, 2017 / This study examined access and use of clinical informatics among medical doctors at University College Hospital, Nigeria and King Edward VIII Hospital, South Africa. The specific objectives of the study were to explain the purposes of using clinical informatics; determine the benefits of using clinical informatics in the selected teaching hospitals; ascertain the availability of clinical informatics infrastructure in the selected teaching hospitals; identify the clinical informatics facilities that are accessible to medical doctors in the selected teaching hospitals; determine the factors that influence the behavioural intention to use clinical informatics by medical doctors in the selected teaching hospitals; determine the policies that guide the effective accessibility and utilisation of clinical informatics among medical doctors in the selected teaching hospitals; and investigate the challenges that faced both the access to and the use of clinical informatics among medical doctors in the selected teaching hospitals. The study adopted the post-positivist paradigm which combines both qualitative and quantitative research methods. The study largely used a survey design. The sample for the study was drawn from medical doctors in two purposively selected teaching hospitals in Nigeria and South Africa. The teaching hospitals were King Edward V111 hospital, Durban, South Africa and University College Hospital, Ibadan, Nigeria. The two teaching hospitals were selected because they belong to the first generation of teaching hospitals in Nigeria and South Africa, among other reasons. It was believed that they would be well established in terms of funding towards infrastructure and human development in their respective countries. Convenience sampling was used to select the respondents for the study. The questionnaire was administered to 413 medical doctors, 258 (63%) of whom returned the questionnaire. Interviews were also conducted with the heads of the ICT units at the University College Hospital in Ibadan, Nigeria, and King Edward VIII Hospital in Durban, South Africa. The quantitative data aspect of the study was analysed using descriptive statistics and Statistical Package for Social Sciences (SPSS), while the qualitative aspect of the data was analysed through the use of qualitative contents analysis. The study was guided by the Unified theory of acceptance and use of technology (UTAUT). The essence of using this theory is to identify the factors that influence the use of clinical informatics. The finding of the study reveals that there was an association between the demographic variables and the use of clinical informatics. It was established that there was a significant association between the medical department and the use of electronic medical records. An assessment of the socio-demographic characteristics and the use of the Clinical Decision Support System revealed that there was a significant association between the years of medical practice and the use of Clinical Decision Support System. The finding also revealed that social demographic variables such as age, years of practice and position were all significant related with the use of diagnostic image archiving. Furthermore, the surveyed medical doctors stated that their main purpose of using clinical informatics is for medical diagnosis. It was also discovered that there is association between the teaching hospitals and the use of clinical informatics for knowledge sharing. In addition, clinical informatics was found to influence the spirit of team work amongst the medical doctors through knowledge sharing with their professional colleagues and their medical students. Similarly, there were association between the teaching hospitals treatment of patients and effective healthcare delivery. In addition, the major benefit of using clinical informatics in the two hospitals was to reduce medical errors. The most available clinical informatics tools in the selected teaching hospitals were the Diagnosis Image Archiving and Clinical Decision Support System. Performance expectancy and effort expectancy were identified as the factors from the UTAUT that influenced the medical doctors’ behavioural intention to use clinical informatics resources in the selected teaching hospitals. The non-availability of clinical informatics resources was identified as the main challenge facing the effective access to and use of clinical informatics. In addition, the two hospitals relied on the ICT policies of other institutions and did not have their own ICT policies, which was problematic. The study concluded that the clinical informatics environments in the two teaching hospitals are inadequate and there is poor access to clinical informatics resources among medical doctors in the selected teaching hospitals. Major recommendations of the study include the need to establish ICT policies and increase investment in clinical informatics resources at the surveyed teaching hospitals in order to promote effective and value-based healthcare delivery. In addition, the hospital management should create awareness on the importance and benefits of clinical informatics particularly for the medical doctors through informal and continuing education and training such as workshops and short courses. Moreover, the hospital managements need to partner with relevant stakeholders such as government, corporate bodies, and departments of health. This is for the provision of adequate and suitable environment to support the access and use of clinical informatics. Further studies on the various types of health informatics such as nursing informatics, pharmacy informatics and veterinary informatics are recommended. It is also suggested that the study should be extended to other regions of Africa. The study is significant and makes tangible contributions to technology acceptance and use in clinical medicine from developing country contexts such as Nigeria and South Africa giving the increasing role of information and communication technology in diagnosis, prescription, treatment, monitoring and overall management of patient care in an environment characterized by complex diseases. The study has the potential to inform policy, practises, and also contribute to this research in the general area of social information in Africa.

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Indiana University-Purdue University Indianapolis (IUPUI) / Between 3.2 and 5.3 million U.S. civilians live with traumatic brain injury (TBI)-related disabilities. Although the post-acute phase of TBI has been recognized as both a discrete disease process and risk factor for chronic conditions, TBI is not recognized as a chronic disease. TBI epidemiology draws upon untimely, incomplete, cross-sectional, administrative datasets. The adoption of electronic health records (EHR) may supplement traditional datasets for public health surveillance and research. Methods Indiana constructed a state-wide clinical TBI registry from longitudinal (2004-2018) EHRs. This dissertation includes three distinct studies to enhance, evaluate, and apply the registry: 1) development and evaluation of a natural language processing algorithm for identification of TBI severity within free-text notes; 2) evaluation and comparison of the performance of the ICD-9-CM and ICD-10-CM surveillance definitions; and 3) estimating the effect of mild TBI (mTBI) on the risk of post-acute chronic conditions compared to individuals without mTBI. Results Automated extraction of Glasgow Coma Scale from clinical notes was feasible and demonstrated balanced recall and precision (F-scores) for classification of mild (99.8%), moderate (100%), and severe (99.9%) TBI. We observed poor sensitivity for ICD-10-CM TBI surveillance compared to ICD-9-CM (0.212 and 0.601, respectively), resulting in potentially 5-fold underreporting. ICD-10-CM was not statistically equivalent to ICD-9-CM for sensitivity (𝑑𝑑𝑑𝑑̂=0.389, 95% CI [0.388,0.405]) or positive predictive value (𝑑𝑑𝑑𝑑̂=-0.353, 95% CI [-0.362,-0.344]). Compared to a matched cohort, individuals with mTBI were more likely to be diagnosed with mental health, substance use, neurological, cardiovascular, and endocrine conditions. Conclusion ICD-9-CM and ICD-10-CM surveillance definitions were not equivalent, and the transition resulted in a underreporting incidence for mTBI. This has direct implications on existing and future TBI registries and the Report to Congress on Traumatic Brain Injury in the United States. The supplementation of state-based trauma registries with structured and unstructured EHR data is effective for studying TBI outcomes. Our findings support the classification of TBI as a chronic disease by funding bodies, which may improve public funding to replace legacy systems to improve standardization, timeliness, and completeness of the epidemiology and post-acute outcomes of TBI.

This dissertation develops a comprehensive statistical learning framework that is robust to (distributional) perturbations in the data using Distributionally Robust Optimization (DRO) under the Wasserstein metric. The learning problems that are studied include: (i) Distributionally Robust Linear Regression (DRLR), which estimates a robustified linear regression plane by minimizing the worst-case expected absolute loss over a probabilistic ambiguity set characterized by the Wasserstein metric; (ii) Groupwise Wasserstein Grouped LASSO (GWGL), which aims at inducing sparsity at a group level when there exists a predefined grouping structure for the predictors, through defining a specially structured Wasserstein metric for DRO; (iii) Optimal decision making using DRLR informed K-Nearest Neighbors (K-NN) estimation, which selects among a set of actions the optimal one through predicting the outcome under each action using K-NN with a distance metric weighted by the DRLR solution; and (iv) Distributionally Robust Multivariate Learning, which solves a DRO problem with a multi-dimensional response/label vector, as in Multivariate Linear Regression (MLR) and Multiclass Logistic Regression (MLG), generalizing the univariate response model addressed in DRLR. A tractable DRO relaxation for each problem is being derived, establishing a connection between robustness and regularization, and obtaining upper bounds on the prediction and estimation errors of the solution. The accuracy and robustness of the estimator is verified through a series of synthetic and real data experiments. The experiments with real data are all associated with various health informatics applications, an application area which motivated the work in this dissertation. In addition to estimation (regression and classification), this dissertation also considers outlier detection applications.

Yes / National audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet). Realist evaluation, which involves building, testing and refining theories of how an intervention works, provides an overall framework for this feasibility study. Realist hypotheses that describe how, in what contexts, and why QualDash is expected to provide benefit will be tested across five hospitals. A controlled interrupted time series analysis, using key MINAP and PICANet measures, will provide preliminary evidence of the impact of QualDash, while ethnographic observations and interviews over 12 months will provide initial insight into contexts and mechanisms that lead to those impacts. Feasibility outcomes include the extent to which MINAP and PICANet data are used, data completeness in the audits, and the extent to which participants perceive QualDash to be useful and express the intention to continue using it after the study period. The study has been approved by the University of Leeds School of Healthcare Research Ethics Committee. Study results will provide an initial understanding of how, in what contexts, and why quality dashboards lead to improvements in care quality. These will be disseminated to academic audiences, study participants, hospital IT departments and national audits. If the results show a trial is feasible, we will disseminate the QualDash software through a stepped wedge cluster randomised trial.

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This study is the first report of Saudi patients in the literature on electronic personal health records (ePHRs). It investigates patients’ attitudes and expectations regarding ePHRs in Saudi Arabia. It also gives insights about addressing the gap between the interest and the utilization of ePHRs by presenting information about patients’ preferences for ePHR features and activities. The findings show higher interest rates in ePHR use compared to other studies with similar sample frame in developed countries. They also indicate high levels of perceived usefulness of ePHRs on patients’ health and healthcare. More research is needed to explore the ePHR privacy concerns of patients and the key factors in improving the use of ePHRs among specific populations such as the elderly and those patients with chronic disease. / Thesis / Master of Science (MSc) / This study is the first report of Saudi patients in the literature on electronic personal health records (ePHRs). It investigates patients’ attitudes and expectations regarding ePHRs in Saudi Arabia. It also gives insights about addressing the gap between the interest and the utilization of ePHRs by presenting information about patients’ preferences for ePHR features and activities. More research is needed to explore the ePHR privacy concerns of patients and the key factors in improving the use of ePHRs among specific populations.