The large amounts of clinical data generated by electronic health record systems are an underutilized resource, which, if tapped, has enormous potential to improve health care. Since the majority of this data is in the form of unstructured text, which is challenging to analyze computationally, there is a need for sophisticated clinical language processing methods. Unsupervised methods that exploit statistical properties of the data are particularly valuable due to the limited availability of annotated corpora in the clinical domain. Information extraction and natural language processing systems need to incorporate some knowledge of semantics. One approach exploits the distributional properties of language – more specifically, term co-occurrence information – to model the relative meaning of terms in high-dimensional vector space. Such methods have been used with success in a number of general language processing tasks; however, their application in the clinical domain has previously only been explored to a limited extent. By applying models of distributional semantics to clinical text, semantic spaces can be constructed in a completely unsupervised fashion. Semantic spaces of clinical text can then be utilized in a number of medically relevant applications. The application of distributional semantics in the clinical domain is here demonstrated in three use cases: (1) synonym extraction of medical terms, (2) assignment of diagnosis codes and (3) identification of adverse drug reactions. To apply distributional semantics effectively to a wide range of both general and, in particular, clinical language processing tasks, certain limitations or challenges need to be addressed, such as how to model the meaning of multiword terms and account for the function of negation: a simple means of incorporating paraphrasing and negation in a distributional semantic framework is here proposed and evaluated. The notion of ensembles of semantic spaces is also introduced; these are shown to outperform the use of a single semantic space on the synonym extraction task. This idea allows different models of distributional semantics, with different parameter configurations and induced from different corpora, to be combined. This is not least important in the clinical domain, as it allows potentially limited amounts of clinical data to be supplemented with data from other, more readily available sources. The importance of configuring the dimensionality of semantic spaces, particularly when – as is typically the case in the clinical domain – the vocabulary grows large, is also demonstrated. / De stora mängder kliniska data som genereras i patientjournalsystem är en underutnyttjad resurs med en enorm potential att förbättra hälso- och sjukvården. Då merparten av kliniska data är i form av ostrukturerad text, vilken är utmanande för datorer att analysera, finns det ett behov av sofistikerade metoder som kan behandla kliniskt språk. Metoder som inte kräver märkta exempel utan istället utnyttjar statistiska egenskaper i datamängden är särskilt värdefulla, med tanke på den begränsade tillgången till annoterade korpusar i den kliniska domänen. System för informationsextraktion och språkbehandling behöver innehålla viss kunskap om semantik. En metod går ut på att utnyttja de distributionella egenskaperna hos språk – mer specifikt, statistisk över hur termer samförekommer – för att modellera den relativa betydelsen av termer i ett högdimensionellt vektorrum. Metoden har använts med framgång i en rad uppgifter för behandling av allmänna språk; dess tillämpning i den kliniska domänen har dock endast utforskats i mindre utsträckning. Genom att tillämpa modeller för distributionell semantik på klinisk text kan semantiska rum konstrueras utan någon tillgång till märkta exempel. Semantiska rum av klinisk text kan sedan användas i en rad medicinskt relevanta tillämpningar. Tillämpningen av distributionell semantik i den kliniska domänen illustreras här i tre användningsområden: (1) synonymextraktion av medicinska termer, (2) tilldelning av diagnoskoder och (3) identifiering av läkemedelsbiverkningar. Det krävs dock att vissa begränsningar eller utmaningar adresseras för att möjliggöra en effektiv tillämpning av distributionell semantik på ett brett spektrum av uppgifter som behandlar språk – både allmänt och, i synnerhet, kliniskt – såsom hur man kan modellera betydelsen av flerordstermer och redogöra för funktionen av negation: ett enkelt sätt att modellera parafrasering och negation i ett distributionellt semantiskt ramverk presenteras och utvärderas. Idén om ensembler av semantisk rum introduceras också; dessa överträffer användningen av ett enda semantiskt rum för synonymextraktion. Den här metoden möjliggör en kombination av olika modeller för distributionell semantik, med olika parameterkonfigurationer samt inducerade från olika korpusar. Detta är inte minst viktigt i den kliniska domänen, då det gör det möjligt att komplettera potentiellt begränsade mängder kliniska data med data från andra, mer lättillgängliga källor. Arbetet påvisar också vikten av att konfigurera dimensionaliteten av semantiska rum, i synnerhet när vokabulären är omfattande, vilket är vanligt i den kliniska domänen. / High-Performance Data Mining for Drug Effect Detection (DADEL)

Implementation of electronic health records (EHRs) is a driver for the improvement of health care and the reduction of health care costs. Developing countries face substantial challenges in adopting EHRs. The complex adaptive system conceptual framework was used to guide this single case study to explore strategies that health care leaders used to successfully implement the EHR system. Data were collected from 6 health care leaders from an island in the Caribbean using a semistructured interview technique. Data were analyzed using the Bengtsson's 4-stage data analysis process, which includes decontextualization, recontextualization, categorization, and compilation. The results of the study yielded 5 main themes: training, increased staffing, monitoring, identifying organizational gaps, and time. The implications of the study for positive social change include the potential to improve the standards of care provided to promote improved patient outcomes by using the strategies identified in this study to successfully implement the EHR system.

A new hospital in United Arab Emirates (UAE) plans to adopt health information technology (HIT) and become fully digitalized once operational. The hospital has identified a need to assess basic computer literacy of new employees prior to offering them training on various HIT applications. Lack of research in identifying an accurate assessment method for basic computer literacy among health care professionals led to this explanatory correlational research study, which compared self-assessment scores and a simulated actual computer skills test to find an appropriate tool for assessing computer literacy. The theoretical framework of the study was based on constructivist learning theory and self-efficacy theory. Two sets of data from 182 hospital employees were collected and analyzed. A t test revealed that scores of self-assessment were significantly higher than they were on the actual test, which indicated that hospital employees tend to score higher on self-assessment when compared to actual skills test. A Pearson product moment correlation revealed a statistically weak correlation between the scores, which implied that self-assessment scores were not a reliable indicator of how an individual would perform on the actual test. An actual skill test was found to be the more reliable tool to assess basic computer skills when compared to self-assessment test. The findings of the study also identified areas where employees at the local hospital lacked basic computer skills, which led to the development of the project to fill these gaps by providing training on basic computer skills prior to them getting trained on various HIT applications. The findings of the study will be useful for hospitals in UAE who are in the process of adopting HIT and for health information educators to design appropriate training curricula based on assessment of basic computer literacy.

La France connaît un vieillissement de sa population sans précédent. La part des séniors s’accroît et notre société se doit de repenser son organisation pour tenir compte de ce changement et mieux connaître cette population.De nombreuses cohortes de personnes âgées existent déjà à travers le monde dont quatre en France et, bien que la part de cette population vivant dans des structures d’hébergement collectif (EHPAD, cliniques de soins de suite) augmente, la connaissance de ces seniors reste lacunaire.Aujourd’hui les groupes privés de maisons de retraite et d’établissements sanitaires comme Korian ou Orpéa s’équipent de grandes bases de données relationnelles permettant d’avoir de l’information en temps réel sur leurs patients/résidents. Depuis 2010 les dossiers de tous les résidents Korian sont dématérialisés et accessibles par requêtes. Ils comprennent à la fois des données médico-sociales structurées décrivant les résidents et leurs traitements et pathologies, mais aussi des données textuelles explicitant leur prise en charge au quotidien et saisies par le personnel soignant.Au fil du temps et alors que le dossier résident informatisé (DRI) avait surtout été conçu comme une application de gestion de base de données, il est apparu comme une nécessité d’exploiter cette mine d’informations et de construire un outil d’aide à la décision destiné à améliorer l’efficacité des soins. L’Institut du Bien Vieillir IBV devenu entretemps la Fondation Korian pour le Bien Vieillir a alors choisi, dans le cadre d’un partenariat Public/Privé de financer un travail de recherche destiné à mieux comprendre le potentiel informatif de ces données, d’évaluer leur fiabilité et leur capacité à apporter des réponses en santé publique. Ce travail de recherche et plus particulièrement cette thèse a alors été pensée en plusieurs étapes.- D’abord l’analyse de contenu du data warehouse DRI, l’objectif étant de construire une base de données recherche, avec un versant social et un autre de santé. Ce fut le sujet du premier article.- Ensuite, par extraction directe des informations socio-démographiques des résidents dès leur entrée, de leurs hospitalisations et décès puis, par un processus itératif d’extractions d’informations textuelles de la table des transmissions et l’utilisation de la méthode Delphi, nous avons généré vingt-quatre syndromes, ajouté les hospitalisations et les décès et construit une base de données syndromique, la Base du Bien Vieillir (BBV) . Ce système d’informations d’un nouveau type a permis la constitution d’une cohorte de santé publique à partir de la population des résidents de la BBV et l’organisation d’un suivi longitudinal syndromique de celle-ci. La BBV a également été évaluée scientifiquement dans un cadre de surveillance et de recherche en santé publique au travers d’une analyse de l’existant : contenu, périodicité, qualité des données. La cohorte construite a ainsi permis la constitution d’un outil de surveillance. Cet échantillon de population a été suivi en temps réel au moyen des fréquences quotidiennes d’apparitions des 26 syndromes des résidents. La méthodologie d’évaluation était celle des systèmes de surveillance sanitaire proposée par le CDC d’Atlanta et a été utilisée pour les syndromes grippaux et les gastro entérites aiguës. Ce fut l’objet du second article.- Enfin la construction d’un nouvel outil de santé publique : la distribution de chacun des syndromes dans le temps (dates de transmissions) et l’espace (les EHPAD de transmissions) a ouvert le champ de la recherche à de nouvelles méthodes d’exploration des données et permis d’étudier plusieurs problématiques liées à la personne âgée : chutes répétées, cancer, vaccinations et fin de vie. / French population is rapidly aging. Senior citizens ratio is increasing and our society needs to rethink its organization, taking into account this change, better knowing this fast growing population group.Even if numerous cohorts of elderly people already exist worldly with four in France and, even as they live in growing numbers in nursing homes and out-patient treatment clinics, knowledge of this population segment is still missing.Today several health and medico-social structures groups as Korian and Orpéa invest in big relational data bases enabling them to get real-time information about their patients/residents. Since 2010 all Korian residents’ files are dematerialized and accessible by requests. They contain at the same time, structured medico-social data describing the residents as well as their treatments and pathologies, but also free-textual data detailing their daily care by the medical staff.Through time and as the computerized resident file (DRI) was mainly conceived as a data base management application, it appeared essential to mine these data and build a decision-making tool intended to improve the care efficiency. The Ageing Well Institute becoming meanwhile the Korian Ageing Well Foundation chose then, working in a private/public partnership, to finance a research work intented to better understand these datas’ informative potential, to assess their reliability and response to public health threats. This research work and this thesis were then designed in several steps:- First, a content analysis of the data warehouse DRI, the objective being to build a research data base, with a social side and a health side. This was the first paper subject.- Then, by direct extraction of the residents’ socio-demographic information at nursing home (NH) entry, adding hospitalizations and deaths, and finally, by an iterative textual extraction process of the transmissions data and by using the Delphi method, we created twenty-four syndromes, added hospitalizations and deaths and built a syndromic data base, the Ageing Well data base. This information system of a new kind, allowed the constitution of a public health cohort for elderly people from the BBV residents’population and its syndromic longitudinal follow-up. The BBV was also scientifically assessed for surveillance and public health research through present situation analysis: content, periodicity and data quality. This cohort then gave us the opportunity to build a surveillance tool and follow the residents’ population in real-time by watching their 26 daily frequency syndromic distributions. The methodology for that assessment, Atlanta CDCs’ health surveillance systems method, was used for flu and acute gastro enteritis syndroms and was the second paper subject.- Finally, the building of a new public health tool: each syndrom’s distribution through time (transmissions dates) and space (transmissions NH ids) opened the research field to new data exploration methods. I used these to study different health problems afflicting senior citizens: frequent falls, cancer, vaccinations and the end of life.

Indiana University-Purdue University Indianapolis (IUPUI) / Public health agencies protect the health and safety of populations. A key function of public health agencies is surveillance or the ongoing, systematic collection, analysis, interpretation, and dissemination of data about health-related events. Recent public health events, such as the H1N1 outbreak, have triggered increased funding for and attention towards the improvement and sustainability of public health agencies’ capacity for surveillance activities. For example, provisions in the final U.S. Centers for Medicare and Medicaid Services (CMS) “meaningful use” criteria ask that physicians and hospitals report surveillance data to public health agencies using electronic laboratory reporting (ELR) and syndromic surveillance functionalities within electronic health record (EHR) systems. Health information exchange (HIE), organized exchange of clinical and financial health data among a network of trusted entities, may be a path towards achieving meaningful use and enhancing the nation’s public health surveillance infrastructure. Yet the evidence on the value of HIE, especially in the context of public health surveillance, is sparse. In this research, the value of HIE to the process of public health surveillance is explored. Specifically, the study describes the real and perceived completeness and usefulness of HIE in public health surveillance activities. To explore the real value of HIE, the study examined ELR data from two states, comparing raw, unedited data sent from hospitals and laboratories to data enhanced by an HIE. To explore the perceived value of HIE, the study examined public health, infection control, and HIE professionals’ perceptions of public health surveillance data and information flows, comparing traditional flows to HIE-enabled ones. Together these methods, along with the existing literature, triangulate the value that HIE does and can provide public health surveillance processes. The study further describes remaining gaps that future research and development projects should explore. The data collected in the study show that public health surveillance activities vary dramatically, encompassing a wide range of paper and electronic methods for receiving and analyzing population health trends. Few public health agencies currently utilize HIE-enabled processes for performing surveillance activities, relying instead on direct reporting of information from hospitals, physicians, and laboratories. Generally HIE is perceived well among public health and infection control professionals, and many of these professionals feel that HIE can improve surveillance methods and population health. Human and financial resource constraints prevent additional public health agencies from participating in burgeoning HIE initiatives. For those agencies that do participate, real value is being added by HIEs. Specifically, HIEs are improving the completeness and semantic interoperability of ELR messages sent from clinical information systems. New investments, policies, and approaches will be necessary to increase public health utilization of HIEs while improving HIEs’ capacity to deliver greater value to public health surveillance processes.

Bakgrund  Användningen av den elektroniska journalen (e-journalen) har sedan år 2020 ökatexceptionellt, delvis till följd av Covid-19 pandemin. Legitimerad hälso- och sjukvårdpersonal är enligt lag skyldiga att dokumentera vårdbesök. E-journalen är ett verktyg för alla som medverkar kring patientens vård och är ett sätt att dela vårdinformation med andra vårdgivare vilket bidrar till en bättre och säkrare vård. Syfte Syftet var att beskriva patienters upplevelser av att ha tillgång till egen e-journal. Metod Icke-systematisk litteraturöversikt som baserats på 15 vetenskapliga originalartiklar med kvantitativ, kvalitativ och mixad metod. PubMed och CINHAL användes som databaser för sökningen som utfördes med hjälp av indexord i kombination med fritextsökningar. Artiklarna genomgick en kvalitetsgranskning baserad på Sophiahemmet Högskolas bedömningsunderlag för vetenskaplig klassificering. Resultatet sammanställdes och analyserades utifrån en integrerad dataanalys. Resultat Resultatet sammanställdes i två huvudkategorier och fem underkategorier. Huvudkategorierna var: Upplevda fördelar av tillgången till e-journalen och Upplevda nackdelar av tillgången till e-journalen. Resultatet visade att de upplevda fördelarna bland annat var en upplevd förbättrad kommunikation mellan vårdpersonal och patienter och en känsla av delaktighet hos patienten. Andra upplevda fördelar var en ökad kunskap för sin sjukdom och sin vård samt en förbättrad möjlighet till egenvård. Upplevda nackdelar anspelar på patientens upplevelse av rädsla och oro kring e-journalen samt språkliga och tekniska svårigheter ett internetbeserat verktyg kan ge.  Slutsats Tillgången till e-journalen upplevs i helhet som positiv av patienter. E-journalen kan ses som ett verktyg för dem att bli mer delaktiga i sin vård, få en bättre kunskap om sin vård samt öka sin förmåga till egenvård. Dock framkom även negativa aspekter, så som oro samt språkliga och tekniska svårigheter som inte bör ignoreras. Hälso-och sjukvårdspersonal bör ha insikt i dessa upplevda för-och nackdelar för att kunna stärka de positiva upplevelserna samt förebygga och förhindra de negativa utfallen av e-journalen. / Background Since 2020, the use of the e-journal has increased exceptionally, partly as a result of the Covid-19 pandemic. All licensed healthcare professionals are obliged by law to document healthcare visits. Electric health records (EHR) can be used by all involved in a patient’s care and is a way to share information between healthcare professionals. This in turn provides safer and better healthcare. Aim The aim was to describe patients' experiences of having access to their electronic health records. Method Non-systematic literature review based on 15 original scientific articles using quantitative and qualitative methods. PubMed and CINHAL were used as databases for the search, which was performed using index words in combination with free text searches. The articles underwent a quality review based on Sophiahemmet University's assessment documents for scientific classification and quality regarding studies with a quantitative and qualitative method approach. The results were compiled and analyzed based on integrated data analysis. Results The results were compiled into two main categories and five subcategories. The main categories were: Perceived benefits of access to EHRs and Perceived disadvantages of access to EHRs. The result showed that perceived benefits were improved communication between healthcare professionals and patients and an improved feeling of participation for the patient. Other perceived benefits were the patients’ understanding of the illness and their care, as well as improving the patients’ opportunities for self-care. Perceived obstacles and disadvantages allude to the patients’ experience of fear and anxiety around EHR as well as the difficulties in language and technical obstacles an internet-based tool can cause. Conclusions Access to EHR is generally perceived as positive by patients. EHRs can be seen as a tool for them to become more involved in their care, gain a better knowledge of their care and increase their ability to self-care. However, negative aspects also emerged, such as anxiety and linguistic and technical difficulties that should not be ignored. Healthcare professionals should have insight into these perceived benefits as well as perceived obstacles to strengthen the positive experiences as well as prevent the negative outcomes of EHRs.

Implementation of electronic health records by the Health Information Technology for Economic and Clinical Health has led to the implementation of electronic dental records (EDRs) and digital radiography in dental offices. The purpose of this study was to determine the state of the implementation and usage of EDRs and digital radiographs by the private general and pediatric dental practices in Mississippi as well as reasons why the dental practices are not moving forward with the advanced technology. A survey was emailed to 712 dental practices: 116 responded (16% response rate), and 104 consented to participate (89.66%). Results indicated dental practices in Mississippi using EDRs was 46.07%, EDRs with paper records was 42.70%, and only paper records was 11.24%. Results indicated dental practices using digital radiography was 76.40%, conventional radiography was 13.48%, and both was 10.11%. Common reasons for not advancing were cost, insufficient training, computer/software issues, and “too old.”

The use of Electronic Health Records (EHR) for reporting patient data has been widely adopted by healthcare providers. This data can encompass many forms of medical information such as disease symptoms, results from laboratory tests, ICD-10 classes and other information from patients. Structured EHR data is often high-dimensional and contain many missing values, which impose a complication to many computing problems. Detecting meaningful structures in EHR data could provide meaningful insights in diagnose detection and in development of medical decision support systems. In this work, a subset of EHR data from patient questionnaires is explored through two well-known clustering algorithms: K-Means and Agglomerative Hierarchical. The algorithms were tested on different types of data, primarily raw data and data where missing values have been imputed using different imputation techniques. The primary evaluation index for the clustering algorithms was the silhouette value using euclidean and cosine distance measures. The result showed that natural groupings most likely exist in the data set. Hierarchical clustering created higher quality clusters than k-means, and the cosine measure yielded a good interpretation of distance. The data imputation imposed large effects to the data and likewise to the clustering results, and other or more sophisticated techniques are needed for handling missing values in the data set. / Användandet av digitala journaler för att rapportera patientdata har ökat i takt med digitaliseringen av vården. Dessa data kan innehålla många typer av medicinsk information så som sjukdomssymptom, labbresultat, ICD-10 diagnoskoder och annan patientinformation. EHR data är vanligtvis högdimensionell och innehåller saknade värden, vilket kan leda till beräkningssvårigheter i ett digitalt format. Att upptäcka grupperingar i sådana patientdata kan ge värdefulla insikter inom diagnosprediktion och i utveckling av medicinska beslutsstöd. I detta arbete så undersöker vi en delmängd av digital patientdata som innehåller patientsvar på sjukdomsfrågor. Detta dataset undersöks genom att applicera två populära klustringsalgoritmer: k-means och agglomerativ hierarkisk klustring. Algoritmerna är ställda mot varandra och på olika typer av dataset, primärt rådata och två dataset där saknade värden har ersatts genom imputationstekniker. Det primära utvärderingsmåttet för klustringsalgoritmerna var silhuettvärdet tillsammans med beräknandet av ett euklidiskt distansmått och ett cosinusmått. Resultatet visar att naturliga grupperingar med stor sannolikhet finns att hitta i datasetet. Hierarkisk klustring visade på en högre klusterkvalitet än k-means, och cosinusmåttet var att föredra för detta dataset. Imputation av saknade data ledde till stora förändringar på datastrukturen och således på resultatet av klustringsexperimenten, vilket tyder på att andra och mer avancerade dataspecifika imputationstekniker är att föredra.

Clinical research based on data from patient or study data management systems plays an important role in transferring basic findings into the daily practices of physicians. To support study recruitment, diagnostic processes, and risk factor evaluation, search queries for such management systems can be used. Typically, the query syntax as well as the underlying data structure vary greatly between different data management systems. This makes it difficult for domain experts (e.g., clinicians) to build and execute search queries. In this work, the Core Ontology of Phenotypes is used as a general model for phenotypic knowledge. This knowledge is required to create search queries that determine and classify individuals (e.g., patients or study participants) whose morphology, function, behaviour, or biochemical and physiological properties meet specific phenotype classes. A specific model describing a set of particular phenotype classes is called a Phenotype Specification Ontology. Such an ontology can be automatically converted to search queries on data management systems. The methods described have already been used successfully in several projects. Using ontologies to model phenotypic knowledge on patient or study data management systems is a viable approach. It allows clinicians to model from a domain perspective without knowing the actual data structure or query language.

Bakgrund: Malnutrition hos geriatriska patienter är vanligt och ger negativa hälsoeffekter som genererar ökade vårdbehov. Sjuksköterskor har en nyckelfunktion i behandlingen. Syfte: Syftet var att kartlägga omvårdnadsdokumentationen kring nutrition hos geriatriska patienter på ett länssjukhus. Metod: En retrospektiv, kvantitativ tvärsnittsstudie genomfördes där 37 journaler inkluderades och granskades. Urvalet var konsekutivt. Resultat: Samtliga journaler innehöll någon form av grundläggande information i status. Strukturerade riskbedömningar och generella vårdplaner vid bedömd risk fanns i majoriteten av journalerna. Alla vårdplaner innehöll åtgärder men många saknade kompletterande information om huruvida åtgärden sedan genomförts eller ej. Åtgärderna i den generella vårdplanen var allmänt uttryckta och det var oklart vad patienten i praktiken fått för åtgärd. I 35 % av vårdplanerna fanns en diskrepans mellan dokumenterad måluppfyllelse och övrig dokumentation. Epikrisen innehöll i 51% av journalerna brister som innebär att den inte motsvarar en sammanfattning av given vård och/eller fortsatt behov av åtgärder. Konklusion: Resultatet tyder på att det finns en medvetenhet kring nutrition som omvårdnadsområde med riskbedömning och behov av åtgärder vid risk för malnutrition. Kvaliteten på dokumentationen minskar dock för varje led i omvårdnadsprocessen och behov av förbättringar föreligger både på IT-systemnivå och individ/vårdenhetsnivå hos sjuksköterskorna. / Background: Malnutrition in geriatric patients is common and causes negative health effects that increases further need of care. Nurses have a crucial part of its treatment. Purpose: The purpose was to survey the nutritional documentation of geriatric patients in a county hospital. Method: A retrospective, quantitative cross-sectional study was performed where 37 records where included and reviewed. A consecutive sampling method was used. Results: All records contained some sort of basic nutritional information.  Structured risk assessment and general care plans at assessed risk, was to be found within the majority of the records. All care plans contained planned treatments, but many lacked supplementary information on whether the endeavor was fulfilled or not. The treatments in the care plans were generally expressed and therefore lacks the ability to tell what kind of treatment the patient had received. A discrepancy was found in 35% of the care plans between the reported achievements and other recordings.  Of the epicrisis, 51% did not correspond to delivered care and/or further need of intervention. Conclusion: The result indicates an awareness of the nutritional role in the field of nursing and the importance of risk assessments as well as the need of treatment in patients at risk of malnutrition. The quality of the documentation is successively decreasing in every step of the nursing process. There is a need of improvement in the IT systems as well as the performance of nurses and care settings routines.