The focus of this thesis is to utilize many of today’s current technologies to design a communication protocol that allows different devices to be incorporated into a system that can facilitate the flow of information between a user and a world of digital data. The protocol will take advantage of individual benefits from NFC, Bluetooth and cloud computing in its design to make the underlying complexity as transparent to the user as possible. Some of the main problems, such as security and reliability, are discussed and how they are incorporated into the core design of the protocol. The protocol is then applied to a case study to see how it can be utilized to create an integrity preserving system for managing medical records in a healthcare environment. The results from the case study gives merit to guidelines provided by the protocol specifications, making a system implementation based on the protocol theoretically possible. A real system implementation is required to verify the results extracted from the case study. / Denna uppsats fokuserar på att använda många av dagens teknologier för att konstruera ett kommunikationsprotokoll som möjliggör för olika enheter att inkorporeras i ett system som underlättar informationsflödet mellan en användare och en värld av digital data. Protokollet utnyttjar olika individuella fördelar hos NFC, Bluetooth and molntjänster i dess design för att göra den underliggande komplexiteten så transparant som möjligt för användaren. Några av de främsta problemen, så som säkerhet och tillförlitlighet, diskuteras och hur de inkorporeras i hjärtat av protokollet. Protokollet appliceras sedan i en fallstudie för att se hur det kan användas för att skapa ett system för sjukjournaler som bevarar integriteten hos patienter. Resultatet från fallstudien pekar mot att de riktlinjer som gavs av protokollspecifikationerna fungerar för att göra en systemimplementation på en teoretisk nivå. En verklig systemimplementation skulle behövas för att verifiera de resultat som framgår ur fallstudien.

The expectation of graduating nurses today is to be knowledgeable and responsive to rapidly changing technology in the health care environment. Although federal mandates, Institute of Medicine (IOM) recommendations, and nursing program accreditation initiatives are pushing an "informatics" healthcare agenda by promoting the implementation of electronic health record (EHR) systems by 2014 in all healthcare facilities, very few US nursing schools provide students with access and training in, EHR systems. In addition, nursing faculty may not have a clear understanding of healthcare informatics; the use of information and technology to communicate, manage knowledge, mitigate error, and support decision-making. Nursing education must address faculty issues related to this innovative paradigm in order to keep pace and participate as co-creators of relevant informatics technology curriculum that prepares graduates for real life workforce. Understanding the challenges, concerns, and successes in implementing informatics may help nurse educators as they develop curriculum and teach in this environment. This case study explores and describes, with nursing faculty of a small liberal arts college, faculty knowledge, skills, and attitudes (KSAs) as they participate in an action research framed curriculum development program for informatics academic EHR (AEHR) integration. The research question:What is the experience of nursing educators and nursing faculty members involved in the integration of an AEHR project framed in the Learning by Developing model at a small liberal arts college school of nursing? Significant insights as participants in the study influenced nurse educators' ideas regarding collaborative curricular design, meaningful assignments, and the importance of feedback.

Blockkedjetekniken inom sjukvård är ett välutforskat område där journalsystem, spårning av medicin, patientövervakning endast är ett fåtal områden där forskare lyfter blockkedjans relevans. För att undersöka etiska dilemman i samband med blockkedjan undersöker studien specifikt journalsystem där känsliga personliga data hanteras och tittar på hur detta förändras med implementationen av blockkedjetekniken. Studien använder sig av ACTIVE-ramverket för att kunna kategorisera olika etiska dilemman. Studien använder sig av en semi-systematisk litteraturstudiemetodik med en tematisk analys för att besvara forskningsfrågan: Vilka kategorier av etiska dilemman lyfter litteraturen med blockkedjetekniken inom journalsystem? Resultatet av studien sammanfattar de etiska dilemman som litteraturen lyfter och visar även på att texter som är kritiska till blockkedjan är underrepresenterat vilket öppnar upp för vidare forskning. / Blockchain in the health care sector is a well-researched domain where electronic medical records (EMR), tracking of medicine and patient monitoring are a few of the domains where researchers propose blockchain solutions. This study focuses on EMR’s which handle sensitive personal data and research the impact that blockchain technology has on the system to better understand what ethical dilemmas can occur. The study uses the ACTIVE-framework to categorize ethical dilemmas. A semi-systematic literature review in combination with a thematic analysis is used to answer the research question: What categories of ethical dilemmas does the literature raise with the blockchain technology within record systems? The study's findings summarize the ethical dilemmas addressed in the literature and also indicate an underrepresentation of critical texts on blockchain, which calls for further research.

The implementation of E-health innovations varies between countries. An E-health innovation that has had a big impact on healthcare is the electronic patient medical record. Electronic patient medical records contribute to better communication between caregivers and to a better operation by providing caregivers the right information at the right time. The European Commission writes that digital solutions in healthcare can improve the overall health for European citizens. E-health innovations and the access to Electronic Patient Medical Records differs in Europe. While some countries have fully developed Electronic Patient Medical Records, some have not even started. Bosnia & Herzegovina is striving for EU-membership and is yet under implementation of Electronic patient medical records. The aim of this study is to improve the understanding of what socio-technical challenges and opportunities Bosnia and Herzegovina is facing when implementing electronic patient medical records. The method used to answer the research question is a qualitative method using a purposeful sampling by interviewing healthcare professionals in Bosnia & Herzegovina. Six semi-structured interviews were carried out with the help of a translator. The data was analyzed using an inductive content analysis enabling to distinguish challenges and possibilities with the implementation of electronic patient medical records at the hospital in Bosnia and Herzegovina. The result of the study indicates that Bosnia & Herzegovina are facing challenges such as lack of IT-skills, troubles with accessing the electronic patient medical records during power outs or system crashes and the system not fully supporting the way the doctors want to document. The opportunities listed are a better ability to provide patients with quality care, a greater access to information and the possibility to further implement E-health innovations.

During the last few years, there has been increasing interest in making medical records more centered around patients. Empowering the patient more in the care process has proven to increase the quality of care. It can also enable increased data sharing among different actors, where today patient health data is locked into thousands of separate data silos. Meanwhile, growth in portable medical devices and patient-generated health data (PGHD) poses a new source of valuable data which today has limited utilization in clinical settings. In solving these issues of data availability without compromising the privacy of patients, blockchain has been suggested to play an important role through a more patient-centric model of controlling information. The purpose of this study is to investigate how blockchain can solve data availability and security issues in the healthcare system. We explore the research question from a Sweden-specific context by first defining the current state of the Swedish health data ecosystem, and then analyzing how blockchain helps in increasing the availability and security of personal health data. Qualitative methods were used, and data was collected through both a literature review and an interview study where 16 semi-structured interviews were conducted with Swedish governmental agencies, EMR providers, informaticians, as well as blockchain experts. The current issues in data availability and security in the Swedish healthcare system were identified together with the benefits of using blockchain in this context. Our findings suggest that Sweden has already solved many of the problems other countries face, limiting the marginal benefit of using blockchain. However, problems of sharing raw data persist and blockchain has benefits in managing accesses to health data from both regulatory and privacy perspectives. There are also benefits of using the technology for ensuring the quality of PGHD as well as providing increased security for health data. Lastly, we propose and discuss three separate blockchainbased solutions to be used in healthcare. A major contribution to literature lies in finding that system barriers in form of legislation and technical and semantic interoperability are issues that first need to be resolved in order to harvest the full value of using blockchain technology - issues often understated in other papers. We call for future studies to investigate practical use-cases such as small-scale consortiums addressing specific data sets or patient groups to provide proof-of-concept on how the technology performs in terms of cost, integrity, security, and scalability in for personal health data. / Patientdata är i dagsläget spridd i tusentals data-silos i sjukvården. Att involvera patienten i vårdprocessen har visat sig förbättra vårdresultatet, vilket senaste åren ökat diskussioner om att göra hälsodata mer tillgänglig och centrerad kring patienten. Samtidigt växer användandet av portabla medicinska apparater och patient-genererad information snabbt, och utgör nu en ny datakälla som i dagsläget i princip inte utnyttjas i den kliniska kontexten. För att lösa dessa problem och öka tillgängligheten av data utan att äventyra patientens integritet har blockkedjeteknologi föreslagits spela en viktig roll genom en mer patientcentrerad modell av informationsdelning. Syftet med denna studie är att undersöka hur blockkedjor kan lösa problemen med tillgänglighet av sjukvårdsdata inom vårdsystemet. Vi undersöker frågeställningen utifrån en svensk kontext genom att först definiera de existerande problem relaterade till datatillgänglighet och säkerhet i det svenska vårdsystemet, för att sedan analysera blockkedjans roll för att lösa dessa problem. Studien är av kvalitativ natur där datainsamling gjorts genom dels en litteraturstudie, och dels genom en intervjustudie, där 16 semistrukturerade intervjuer genomförts med svenska myndigheter, journalsystems-leverantörer, informatiker samt blockkedje-experter. Nuvarande problem inom datatillgänglighet och datasäkerhet identifierades tillsammans med de fördelar som finns av att använda blockkedjor i sammanhanget. Våra resultat visar att Sverige redan har löst många av de problem många andra länder idag möter, vilket potentiellt minskar den marginella nyttan av att använda blockkedjor. Dock existerar fortfarande problem när det gäller delning av digitala kopior av journaler mellan aktörer, och en blockkedjelösning har fördelar ur både regulatoriska perspektiv och integritetsperspektiv. Vidare finner vi fördelar av att använda blockkedjor för att försäkra kvaliteten av patient-genererad hälsodata, samt för att öka säkerheten i arkitekturer som möjliggör datadelnin. Slutligen föreslår vi och diskuterar tre olika blockkedjelösningar för den svenska sjukvårdssektorn. Ett av huvudbidragen till litteraturen ligger i att identifiera systembarriärer i form av legislativa åtgärder samt teknisk och semantisk interoperabilitet - problem som måste lösas för att till fullo kunna åtnjuta fördelarna av en blockkedjelösning. Vi uppmanar framtida studier att undersöka praktiska användningsområden såsom småskaliga konsortium för att vidare bidra med hur tekniken levererar på frågor kopplade till kostnad, integritet, säkerhet och skalbarhet för personlig hälsodata.

Bien qu'il s'agisse d'une maladie évitable par la vaccination, la grippe cause annuellement environ 3 à 5 millions de cas de maladie grave et environ 290 000 à 650 000 décès dans le monde. Pour prévenir l'infection et ses complications, la vaccination antigrippale est généralement recommandée pour toutes les personnes de 6 mois et plus. La vaccination annuelle est nécessaire en raison des perpétuels changements antigéniques des virus de la grippe; par conséquent, les souches incluses dans les vaccins antigrippaux sont régulièrement mises à jour. Ainsi, l'efficacité de terrain des vaccins antigrippaux (EV) varie d'une saison à l'autre, ce qui nécessite une surveillance constante pour évaluer l'impact des programmes de vaccination contre la grippe saisonnière au fil du temps. Les données médico-administratives sont une riche source d'informations qui pourraient être exploitées pour estimer l'efficacité réelle des vaccins antigrippaux. De plus, des études récentes ont rapporté que la réponse immunitaire à l'infection grippale et à la vaccination peut être altérée par des expositions antérieures, ce qui pourrait affecter l’efficacité de terrain des vaccins antigrippaux. Cette thèse visait à déterminer si les données médico-administratives fournissent des estimations valables de l'EV et à évaluer l'impact de la vaccination répétée et d’une infection antérieure par les virus de la grippe sur l'EV contre le syndrome d’allure grippale (SAG). Nous avons d'abord effectué une revue systématique de la littérature pour évaluer l'impact de la vaccination antigrippale sur la réduction des visites médicales pour un SAG, des hospitalisations pour un SAG, des hospitalisations pour la grippe confirmée en laboratoire (LCI) et des hospitalisations toutes causes confondues. Nous avons identifié que la spécificité des résultats joue un rôle crucial dans l'estimation de l'EV et que la propension à utiliser des soins de santé peut introduire un biais dans les études d'EV si la propension à consulter pour un SAG est influencée par le statut vaccinal, mais également si la capacité à capturer le statut vaccinal et l’issue (SAG) est tributaire de la propension à consulter. Par la suite, nous avons constaté que les courbes d'incidence des consultations médicales liées à un SAG spécifique, dérivées des codes de diagnostic clinique spécifiques à l'infection grippale, étaient très similaires aux données de surveillance des Centers for Disease Control and Prevention (CDC) des États-Unis pour le LCI, suggérant ainsi qu'il est plus approprié d'utiliser la définition de SAG spécifique à l’infection grippale pour une surveillance des cas de grippe plutôt qu'une définition large du SAG, lorsque seuls les codes de diagnostic clinique sont disponibles pour l'évaluation de l’infection grippale. Ensuite, l'efficacité de terrain des vaccins antigrippaux de 2018-2019 à prévenir les consultations médicales pour un SAG (spécifique à l’infection grippale) a été évaluée dans une cohorte d'individus américains ayant au moins un enregistrement pertinent par année, entre 2015 et 2019, dans leur dossier de santé électronique (DSE). Les rapports de cotes ajustés (aOR) ont été dérivés de modèles de régression logistique multivariés et les EVs ajustées ont été calculées à l'aide de 100x(1-aOR). Les estimations d’EVs dérivées des données médico-administratives étaient toutes plus petites que celles rapportées par les CDC américains, suggérant ainsi que l’utilisation secondaire de ces données médico-administratives a mené à une sous-estimation de l’EV probablement due à des biais de détection et de mauvaise classification corrélés avec la propension à utiliser des soins de santé. Lorsque les EVs sont stratifiées sur le nombre de visites médicales, les estimations d'EVs et la couverture vaccinale augmentent avec le nombre de visites médicales, atteignant des estimations similaires à celles obtenues par les CDC américains et la couverture vaccinale nationale des États-Unis pour les personnes ayant au moins 6 visites médicales lors des 12 mois précédents. Les résultats suggèrent ainsi que l'utilisation secondaire des données médico-administratives ne permet pas de produire des estimations valables de l’efficacité de terrain des vaccins antigrippaux, et ce, en l’absence de données complètes sur la vaccination et l'infection grippale. Cependant, ces données médico-administratives ont le potentiel d'évaluer l'efficacité de terrain des vaccins antigrippaux dans les populations considérées à haut risque de complications à la suite de l'infection, ce qui est difficile à faire avec une surveillance active, ainsi que dans les populations ayant des conditions de santé nécessitant un suivi médical soutenu; car la probabilité que le statut vaccinal et/ou l’infection grippale soient déclarés dans les données médico-administratives augmente avec le nombre de contacts avec le système de santé. Enfin, l'efficacité de terrain des vaccins antigrippaux de 2018-2019 à prévenir le SAG a été estimée en fonction de l’historique de la vaccination antigrippale et des antécédents de SAG chez les utilisateurs fréquents de soins de santé. Bien que l'EV semble diminuer avec l’augmentation du nombre de vaccinations précédentes, la vaccination antigrippale lors de la saison en cours offre probablement une protection contre le SAG, quels que soient les antécédents de vaccination, en particulier chez les enfants. Néanmoins, les antécédents de SAG pourraient atténuer l'effet négatif d'une vaccination antérieure sur l'EV, probablement en raison d’une immunité naturelle liée à l’infection grippale. Même si une vaccination antérieure peut atténuer l'EV de la saison en cours dans certaines circonstances, cet effet d'interférence est imprévisible et les antécédents de vaccination ou d'infection ne devraient pas influencer la décision de se faire vacciner contre la grippe. Jusqu'à ce que des vaccins antigrippaux universels efficaces soient disponibles et éliminent la nécessité d'une vaccination annuelle, la recommandation actuelle de la vaccination annuelle contre la grippe reste un bon moyen de se protéger et ainsi protéger les autres de l’infection et de ses complications, principalement pour les personnes à haut risque de complications. / Although a vaccine-preventable disease, influenza causes annually approximately 3 to 5 million cases of severe illness and about 290 000 to 650 000 deaths worldwide. To prevent the infection and its complications, influenza vaccination is recommended for all individuals 6 months and older. Annual vaccination is necessary because of continual antigenic changes of influenza viruses; hence, vaccine compositions are regularly updated. Consequently, vaccine effectiveness (VE) varies between seasons requiring ongoing measurement to assess the impact of seasonal influenza vaccination programs over time. Administrative healthcare databases are a rich source of information that could be leveraged to estimate real-world influenza VE. Recent studies have reported that immunologic response to influenza infection and vaccination may be altered by previous exposures. This thesis aimed to determine if administrative healthcare data provide accurate VE estimates and to evaluate the impact of repeated vaccination and previous infection on VE against medically attended influenza-like illness (MA-ILI). We first performed a systematic review of the literature to evaluate the impact of influenza vaccination to reduce outpatient visits for influenza-like illness (ILI), hospitalization for ILI, hospitalization for lab-confirmed influenza (LCI) and all-cause hospitalization. We identified that outcome specificity plays a crucial role in VE estimate and healthcare seeking behaviour can bias VE estimates if the propensity to seek care for ILI is influenced by vaccination status, but also if the ability to capture patients’ vaccination status and/or ILI is dependent on their propensity to seek care. Subsequently, we found that the incidence curves of influenza-related medical encounters, derived from clinical diagnostic codesspecific to influenza infection, were very similar to the United States (U.S.) Centers for Disease Control and Prevention (CDC) surveillance data for LCI; suggesting that it is more appropriate to use influenza case definition for specific surveillance rather than a broad ILI definition, when only clinical diagnostic codes are available for the evaluation of influenza. Then, the 2018-2019 influenza vaccine effectiveness against medically attended influenza-like illness (MA-ILI) was evaluated in a cohort of U.S. individuals who had at least one relevant record per year between 2015 and 2019 in their electronic medical record (EMR). Adjusted odds ratios (aORs) were derived from multivariate logistic regression models and adjusted VE (aVEs) were calculated using 100x(1-aORs). Estimated aVEs derived from administrative healthcare data were all lower than CDC-reported VE; results suggested that the secondary use of these administrative healthcare data led to an underestimation of influenza VE, likely due to detection and misclassification biases, correlated with healthcare seeking behaviour. When stratified by the number of primary care visits, aVE estimates and vaccine coverage increased with the number of primary care visits, reaching estimates similar to those obtained by the U.S. CDC and U.S. national vaccination coverage among those with at least 6 primary care visits in the previous 12 months. Results suggested that the secondary use of these administrative healthcare data cannot produce accurate influenza VE without comprehensive influenza vaccination and infection data. However, these databases have the potential to assess influenza VE in populations considered at high risk of complications following the infection, which is not easily achievable with active surveillance, as well as in populations with health conditions requiring constant medical follow-up since probabilities that vaccination and/or infection status are reported in administrative healthcare data increase with the number of contacts with the healthcare system. Finally, the 2018-2019 aVE against MA-ILI was estimated by previous vaccination status and previous history of MA-ILI in frequent healthcare users. Although VE appeared to decrease in relation to increasing numbers of previous influenza vaccinations, current season vaccination likely provides protection against MA-ILI regardless of vaccination history, especially in children. Nevertheless, previous MA-ILI could mitigate the negative effect of prior influenza vaccination on VE likely via infection-induced immunity. Even if prior influenza vaccination may attenuate current season VE in some circumstances, this interference effect is unpredictable and previous vaccination or infection history should not influence the decision to get vaccinated against influenza. Until effective universal influenza vaccines are available and eliminate the need for annual vaccination, the current recommendation for annual influenza vaccination remains important to protect ourselves and others from influenza infection and its complications, particularly in at-risk populations.

No description available.

The overarching goal of this dissertation is to integrate heterogeneous data for the estimation of disease coheritability and subtyping. Chapter 2 focuses on the significance and estimation of heritability and coheritability, which quantify the proportion of phenotypic variation attributable to genetic factors and the genetic correlations between different traits, respectively. To achieve this, we develop robust statistical methods based on estimating equations that account for familial correlations and the computational challenges posed by large pedigrees and extensive datasets. Our methods are evaluated through simulations, demonstrating satisfactory consistency and robust inference properties. Compared to simpler methods performing separate trait analysis, our approaches show a greater power through joint analysis of multiple traits. An application to the analysis of heritability and coheritability in electronic health record (EHR) data reveals substantial genetic correlations between mental disorders and metabolic/endocrine measurements, suggesting shared genetic influences that warrant further investigation. These findings have implications for understanding these conditions' etiology, diagnosis, and treatment. Chapters 3 and 4 focus on the importance of patient subtyping for personalized mental health care, particularly relevant to the substantial variability observed in mental disorders. Chapter 3 develops methods for subtyping patients with mental disorders using various data modalities and variational inference. We propose latent mixture models inspired by the Item Response Theory to handle both binary and continuous data. We also introduce Black Box Variational Inference (BBVI) algorithms to overcome the challenges of numeric integration in nonlinear models. Our numerical experiments validate the proposed methods, demonstrating that variance-controlling techniques improve convergence speed and reduce iteration variance. However, the proposed algorithm encounters limitations with latent mixture models containing binary modalities due to approximations used in non-conjugate posterior distributions resulting from the non-exponential family likelihood function. Chapter 4 investigates multi-modal integration techniques for subtyping patients using data from the Adolescent Brain Cognitive Development (ABCD) study. We introduce a Bayesian hierarchical joint model with latent variables and utilize Pólya-Gamma augmentation for posterior approximation, which enables efficient Gibbs sampling and accurate estimation of model parameters. Extensive simulations confirm the consistency of estimators and the prediction accuracy of our method. Applying these methods to patient clustering in the ABCD study provides information for identifying potential clinical subtypes within mental health, which can inform the development of targeted psychological and educational interventions, ultimately improving mental health outcomes. Keywords: latent mixture model, integrative analysis, coheritability, multi-modality, disease subtyping, variational inference, Pólya-Gamma

No / AIMS: The aims of this study were to determine the recording of drug sensitivities of elderly care home residents, to describe the nature of sensitivities and to identify and describe discrepancies in the documentation of drug sensitivity status in general practices, pharmacies and care homes. METHODS: A random sample of residents within a purposive sample of care homes (nursing and residential) was selected. A clinical pharmacist inspected the GP medical record, the medicines administration record, and the care home record for each resident to identify drug sensitivities and discrepancies between records and to describe the nature of the recorded sensitivities. RESULTS: The records of 121 residents in 31 care homes were studied. Thirty-one (26%) residents had at least one documented drug sensitivity in one of the sources inspected, with 48 sensitivities in total recorded. There was no description of the nature of the sensitivities recorded in 39/48 (81%) cases. The number of sensitivities recorded on the medicines administration record, care home record and the GP record were 3 (6%), 29 (60%) and 35 (73%), respectively. Only two sensitivities were simultaneously recorded on all three records. CONCLUSIONS: It was of concern that over 90% of drug sensitivities were not recorded on the medicines administration record which is the final checking document when administering medication. The reason for this was that the dispensing pharmacy was responsible for generating the medicines administration record; however, drug sensitivity status is seldom shared between the GP and the dispensing pharmacy. Printing sensitivities on prescriptions would help to resolve this.

No / To assess the reliability of duration of treatment time measured by physiotherapy staff in early-stage stroke patients. DESIGN: Comparison of physiotherapy staff's recording of treatment sessions and video recording. SETTING: Rehabilitation stroke unit in a general hospital. SUBJECTS: Thirty-nine stroke patients without trunk control or who were unable to stand with an erect trunk without the support of two therapists recruited to a randomized trial evaluating the Oswestry Standing Frame. Twenty-six physiotherapy staff who were involved in patient treatment. MAIN MEASURES: Contemporaneous recording by physiotherapy staff of treatment time (in minutes) compared with video recording. STATISTICAL ANALYSIS: Intraclass correlation with 95% confidence interval and the Bland and Altman method for assessing agreement by calculating the mean difference (standard deviation; 95% confidence interval), reliability coefficient and 95% limits of agreement for the differences between the measurements. RESULTS: The mean duration (standard deviation, SD) of treatment time recorded by physiotherapy staff was 32 (11) minutes compared with 25 (9) minutes as evidenced in the video recording. The mean difference (SD) was -6 (9) minutes (95% confidence interval (CI) -9 to -3). The reliability coefficient was 18 minutes and the 95% limits of agreement were -24 to 12 minutes. Intraclass correlation coefficient for agreement between the two methods was 0.50 (95% CI 0.12 to 0.73). CONCLUSIONS: Physiotherapy staff's recording of duration of treatment time was not reliable and was systematically greater than the video recording.