Some hospital leaders lack the technical expertise to implement electronic health records (EHRs) even though the healthcare industry has a government mandate. The purpose of this single case study was to explore strategies healthcare executives use to develop and implement information technology systems for processing EHRs. The target population consisted of healthcare leaders and managers successful in implementing EHR systems in a healthcare organization. Lewin's 3-step change theory was used as the conceptual framework for this study with data collected from observations (5), semistructured interviews (5), and organizational documents. Descriptive coding was used to identify 3 themes that emerged from observations, document analysis, recording and analyzing the interview transcripts of research participants. The themes included communication and management plan for EHR implementation, information technology EHR vendor selection, and EHR implementation technical support strategy. The findings benefit both the patients and clinicians with the potential to improve healthcare service delivery utilizing electronic technology for documenting physician visits. Study results may assist healthcare providers with identifying implementation strategies successful for EHR adoption and assisting with speeding the process. The research findings may contribute to social change through increasing patient access to treatment along with community engagement in using EHRs by information sharing to reduce healthcare cost.

Over 700,000 adverse drug events (ADEs) result in emergency hospital visits annually, and many of these ADEs are preventable through the use of health information technology in hospitals. However, only 12.6% of U.S. hospitals have developed the capacity to adopt closed-loop electronic medical records (EMR). Organizational complexity may be a major factor influencing hospitals' adoption of closed-loop EMR. This quantitative study explored how organizational complexity influenced hospitals' adoption of closed-loop EMR. Diffusion of innovation theory was the foundation for this study. Logistic regression was used to establish possible relationships between organizational complexity and hospitals' adoption of EMR for closed-loop medication therapy management. Secondary data from Health Information and Management Systems Society were examined to explore the relationship between organization complexity and hospitals' adoption of EMR for closed-loop medication therapy. The research questions explored whether vendor selection strategy, structural complexity, and management structure influence hospitals' adoption of EMR for closed-loop medication therapy management. The results indicated that all three variables, vendor selection strategy, structural complexity, and management structure, are statistically significant predictors of hospitals' adoption of EMR for closed-loop medication therapy management. Results from this study may promote positive social change by enhancing hospitals' adoption of EMR for closed-loop medication therapy management, which may therefore help improve the quality, efficiency, and safety of health care delivery in U.S. hospitals.

Information contained in the free text of health records is useful for the immediate care of patients as well as for medical knowledge creation. Advances in clinical language processing have made it possible to automatically extract this information, but most research has, until recently, been conducted on clinical text written in English. In this thesis, however, information extraction from Swedish clinical corpora is explored, particularly focusing on the extraction of clinical findings. Unlike most previous studies, Clinical Finding was divided into the two more granular sub-categories Finding (symptom/result of a medical examination) and Disorder (condition with an underlying pathological process). For detecting clinical findings mentioned in Swedish health record text, a machine learning model, trained on a corpus of manually annotated text, achieved results in line with the obtained inter-annotator agreement figures. The machine learning approach clearly outperformed an approach based on vocabulary mapping, showing that Swedish medical vocabularies are not extensive enough for the purpose of high-quality information extraction from clinical text. A rule and cue vocabulary-based approach was, however, successful for negation and uncertainty classification of detected clinical findings. Methods for facilitating expansion of medical vocabulary resources are particularly important for Swedish and other languages with less extensive vocabulary resources. The possibility of using distributional semantics, in the form of Random indexing, for semi-automatic vocabulary expansion of medical vocabularies was, therefore, evaluated. Distributional semantics does not require that terms or abbreviations are explicitly defined in the text, and it is, thereby, a method suitable for clinical corpora. Random indexing was shown useful for extending vocabularies with medical terms, as well as for extracting medical synonyms and abbreviation dictionaries.

Thesis (MScEng)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: The various applications of Information and Communication Technologies (ICTs) in healthcare are increasingly effective to improve the cost-effectiveness and quality of healthcare service delivery. Telemedicine is such an application, using ICTs to provide health services over a distance. Since 1997, the South African Department of Health has invested large amounts of capital to implement telemedicine systems in South Africa. Unfortunately, telemedicine programs have had little success since, leading to many workstations standing dormant. Telemedicine implementation decision making that is based on insufficient evidence is identified as one of the underlying problems that cause telemedicine programs to fail. It is proposed that implementation decisions should be based on quantifiable evidence regarding the potential benefits of telemedicine. A decision support system is developed that can be used to quantify potential benefits and plan telemedicine implementation programs accordingly. The decision support system is modelled and demonstrated using data from the Eastern Cape public health sector. The first phase of the system guides decision makers to identify potential telemedicine benefits as well as data sources that can be used to measure these benefits. The system is scoped to focus on the application of telemedicine to support patient referrals between hospitals. Data sources are considered accordingly, with electronic health record (EHR) data proving to be a feasible primary source for needs assessments, however limiting the benefits that can be quantified. The analysis of the needs assessment is included in the second phase of the decision support system. Data are extracted, transformed and loaded into a data warehouse from where it can be analysed. The system includes three analysis steps to: map referral patterns, analyse potential benefits of telemedicine programs and determine cost-effective telemedicine solutions by allocating equipment at different hospitals. Analysis techniques used in the system include Pareto analysis, economic analysis, linear programming and the use of a genetic algorithm. It is proposed that the potential benefit results and equipment allocation algorithm be used to plan telemedicine programs for continuous evaluation. The final phase of the system therefore guides decision makers to use the results for implementation planning as well as evaluability assessments, for future management and evaluation of telemedicine programs. The decision support system is validated using patient referral data from the Western Cape public health sector. The case study proved that the system is applicable to the real-world and could be a valuable tool for decision makers to base telemedicine implementation planning on quantifiable evidence. The limitation on size and quality of both the Eastern Cape and Western Cape data sets, caused that the full potential of the system could not be demonstrated and validated. It is recommended that the quality standards of EHR referral reports be improved, to ensure more accurate benefit results. Future work is recommended to include qualitative needs assessments in the scope of the decision support system, hereby increasing the amount of benefits to be assessed. Although it is expected that the developed system is capable to support even better resolution decisions with more detailed data sets, the system developed in this study proved already adequate for improved implementation decision making. This could lead to higher success rates of telemedicine programs and ultimately better quality healthcare for all. / AFRIKAANSE OPSOMMING: Die verskillende toepassings van Informasie en Kommunikasie Tegnologie (IKT) in gesondheidsorg, speel ʼn rol in toenemende doeltreffendheid om die koste-effektiwiteit en kwaliteit van gesondheidsorg dienslewering te verbeter. Tele-geneeskunde is een van hierdie toepassings, wat IKT gebruik om gesondheidsdienste oor ʼn afstand te kan voorsien. Die Suid-Afrikaanse Departement van Gesondheid belê sedert 1997, groot bedrae kapitaal in die implementering van tele-geneeskunde stelsels, in Suid-Afrika. Ongelukkig het tele-geneeskunde programme min sukses behaal sedertdien, wat veroorsaak dat vele werkstasies dormant is. Die basering van implementeringsbesluite op onvoldoende getuienis, is geïdentifiseer as een van die onderliggende probleme wat veroorsaak dat tele-geneeskunde programme misluk. Daar word voorgestel dat implementeringsbesluite gebaseer moet word op kwantifiseerbare getuienis ten opsigte van die potensiële voordele van telemedisyne. ʼn Besluitnemingsondersteuning stelsel is ontwikkel wat gebruik kan word om die potensiële voordele te kwantifiseer en dienooreenkomstig implementering van tele-geneeskunde programme te beplan. Die stelsel is gemodelleer en gedemonstreer aan die hand van data uit die Oos-Kaap publieke gesondheidsektor. Die eerste fase van die stelsel begelei besluitnemers om potensiële voordele van telegeneeskunde, sowel as data-bronne wat gebruik kan word om hierdie voordele te meet, te identifiseer. Die stelsel is beperk tot ʼn fokus op die ondersteuning wat tele-geneeskunde aan hospitaal pasiënt verwysingstelsels, kan bied. Data bronne is dienooreenkomstig oorweeg: elektroniese mediese rekords (EMR) word erken as ʼn gunstige primêre databron, maar veroorsaak egter beperkings op die aantal voordele wat gekwantifiseer kan word. Die behoeftebepaling word uitgevoer in die tweede fase van die besluitnemingsondersteuning stelsel. Data is onttrek, getransformeer is en gelaai in 'n data stoor, vanwaar dit ontleed kan word. Die stelsel sluit drie analisestappe in: verwysingspatroon analise, berekening van potensiële voordele vir tele-geneeskunde programme en die bepaling van koste-effektiewe oplossings deur toekenning van toerusting by verskillende hospitale. Die analise tegnieke wat in die stelsel gebruik word, sluit die volgende in: Pareto analise, ekonomiese analise, lineêre programmering en 'n genetiese algoritme. Die gebruik van potensiële voordeel resultate en die toerusting toekenning algoritme word voorgestel vir die beplanning vir deurlopende evaluering in tele-geneeskunde programme. Die finale fase van die stelsel is gestruktureer, om besluitnemers te begelei in die gebruik van analise resultate, vir implementering beplanning sowel as evalueerbaarheid studies, wat sodoende deurlopende evaluering en bestuur van tele-geneeskunde programme sal verbeter.Die besluitnemingsondersteuning stelsel is gevalideer deur pasiënt verwysings data van die Wes-Kaap publieke gesondheidsektor, te gebruik. Die gevallestudie het bewys dat die stelsel toepaslik is in die werklike wêreld en kan as ʼn waardevolle hulpmiddel vir besluitnemers dien om tele-geneeskunde implementering beplanning op kwantifiseerbare bewyse te baseer. Die beperkings op die grootte en gehalte van beide die Oos-Kaap en Wes-Kaap datastelle het veroorsaak dat die stelsel nie tot sy volle reg gedemonstreer en gevalideer kon word nie. Verbeterings in kwaliteit standaarde van EMR verwysing data word aanbeveel om meer akkurate resultate te bekom. Verdere studies wat die byvoeg van kwalitatiewe meetings in die stelsel ondersoek, sal die omvang van potensiële voordele verbeter en dus die algehele waarde van die stelsel verbeter. Alhoewel die ontwikkelde stelsel in staat is om beter resolusie besluite te kan ondersteun met meer gedetailleerde data, is dit bewys dat die huidige stelsel reeds voldoende is om besluitneming te verbeter. Beter besluitneming gevolglik lei tot hoër sukseskoerse van tele-geneeskunde programme en uiteindelik verbeterde gehalte gesondheidsorg vir almal.

Introdução: A utilização das ferramentas e instrumentos da informática no processo do atendimento de pacientes auxilia os profissionais da saúde, pois facilita a coleta e armazenamento das informações, proporcionando qualidade no atendimento e criando condições de enfrentamento dos desafios do mundo globalizado. Nesse contexto, a utilização de dados de prontuário eletrônico de pacientes vinculados à pesquisa clínica em um hospital universitário público pode auxiliar no aprimoramento da assistência à saúde, assim como subsidia dados de pesquisas no âmbito da saúde. Objetivos: Identificar e avaliar os registros provenientes de pesquisas clínicas postos nos sistemas coorporativos do Hospital de Clínicas de Porto Alegre (HCPA), no período de 2014 a 2016. Método: A pesquisa utilizou abordagem quantitativa e qualitativa, de análise de conteúdo de referências e de dados provenientes da rede de informação clínica e assistencial através do cruzamento de informações do sistema integrado Aplicativo para Gestão de Hospitais Universitários (AGHU) e pelo Grupo de Pesquisa e Pós-Graduação (GPPG) do Hospital de Clínicas de Porto Alegre, no período entre janeiro de 2014 e dezembro de 2016. Resultados: Entre os projetos, 58,6% encaminharam relatórios de pesquisa, sendo que somente 23,8% possuem registro de participantes de pesquisa. No entanto, apenas 10,3% dentre todos os estudos que indicaram utilizar pacientes no seu protocolo de pesquisa tem concordância de registro entre o GPPG8 e o AGHU. Cerca de 25,6% do total de relatórios de pesquisa encaminhados apresentam informações quanto aos seus produtos de pesquisa. As pesquisas com patrocínio privado demonstraram encaminhar mais relatórios de atualização dos projetos, porém com menor índice na apresentação dos produtos científicos (1,4%). Considerações finais: Potenciais limitações no uso dos registros existentes no AGHU foram identificadas para decisões terapêuticas pela equipe assistencial de maneira geral, tendo em vista a aparente subnotificação de informações relativas ao andamento e desfecho dos estudos desenvolvidos. Entretanto, não foi possível analisar as causas dos registros possivelmente inadequados ou incompletos, sugerindo-se pesquisas específicas com a incorporação de questionários ou entrevistas individuais para permitir maior aprofundamento na temática. Produtos: A pesquisa identificou a necessidade de três produtos derivados do estudo: (1) material explicativo para os pesquisadores informando a necessidade do registro apropriado dos participantes no sistema coorporativo; (2) modelo de relatório de pesquisa para encerramento de projeto, disponibilizado pelo GPPG, em formato online para pesquisadores responsáveis pelo projeto de pesquisa; e (3) sugestão de melhoria das informações disponibilizadas pela aba “Projetos de Pesquisa” no prontuário online dos pacientes que estão vinculados a projetos de pesquisa, informando os potenciais resultados de pesquisas envolvidas com estes à área assistencial. / Introduction: Using informatics tools on the medical care process for patients helps health professionals, makes easier to collect and to storage information, as well as exchange this information among professionals and institutions, offering quality of care and creating conditions to face challenges in a globalized world. In this context, using electronic medical records data of patients enrolled on clinical trials in a public hospital may help improving health care, as well as provide research health data. Objectives: To identify and evaluate records from clinical trials registered on corporative systems from Hospital de Clinicas de Porto Alegre (HCPA), from 2014 to 2016. Method: The research used quantitative and qualitative approach, analyzing references content and data from the network for clinical data, crossing information from Aplicativo para Gestão de Hospitais Universitários (AGHU) and Grupo de Pesquisa e Pós-Graduação (GPPG) of HCPA, from 2014 and 2016. Results: Among the projects 58,6% forwarded research reports, but just 23,8% with record of research participants. However, only 10,3% of studies that report participants enrolled in study protocol matched records in GPPG8 and AGHU. About 25,6% of total research reports informed research products. Researches with private sponsor showed more update reports, but with lower presentations of scientific products (1,4%). Final considerations: Potential limitations on using existent records on AGHU were identified for therapeutic decisions by clinical team in general, with apparent underreporting of information relate to development and closure for studies developed. However was not possible to analyze causes for possibly inaccurate or incomplete records, suggesting specific research with individual questionnaires or interviews in order to allow deepening the understanding on the theme. Products: The research identify the need for three product from the study: (1) a explicative material to researchers, informing an appropriate participant’s registration on the corporative system; (2) a model of research report for project termination, available on GPPG, online, to lead researchers in research projects; and (3) improvement suggestion on information available by “research projects” tab on the online medical records for patients enroll in research projects, informing potential results associated to medical care area.

Orientador: Rodrigo Jensen / Resumo: Introdução: O Conselho Federal de Enfermagem (COFEN), por meio da Resolução 358/2009, preconiza que a assistência de enfermagem deve ser sistematizada com a implementação do Processo de Enfermagem (PE). O PE direciona os julgamentos clínicos ao cuidado de enfermagem. Um dos desafios dos profissionais da enfermagem é o uso de um sistema de classificação na prática do cuidado, aliada a recursos tecnológicos disponibilizados pelos Registros Eletrônicos de Saúde (RES). Os RES estruturados a partir de um Conjunto de Dados Mínimos de Enfermagem (CDME) e sistemas de classificação de enfermagem podem contribuir à construção de Sistemas de Informação em Saúde de melhor qualidade. Objetivos: Construir um CDME para unidade de internação clínica. Métodos: Estudo metodológico desenvolvido em quatro etapas. Na primeira etapa, foi realizada a análise documental dos formulários e telas do sistema de informação, utilizados na unidade de clínica médica para registro de enfermagem, de um hospital público do interior do Estado de São Paulo. Na segunda etapa, foram realizadas oficinas com enfermeiros da unidade de clínica médica para determinar o conjunto de dados mínimos de enfermagem, relacionados aos elementos dos cuidados de enfermagem, elementos do paciente e elementos dos provedores de serviços, pertinentes à assistência de enfermagem, tendo como referenciais a classificação de diagnósticos de enfermagem NANDA Internacional (NANDA-I), a Classificação das Intervenções de Enfermagem (NIC) e a... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Introduction: By means of Resolution 358/2009, the Brazilian Nursing Federal Council (COFEN) recommends that the nursing care should be systematized through the implementation of the Nursing Process (NP). The NP guides the clinical judgments needed in nursing care. One of the greatest challenges faced by nursing professionals in this process is the use of a classification system in the practice of care, together with technological resources provided by the Electronic Health Records (EHR). These EHR, when structured from a Nursing Minimum Data Set (NMDS) and from nursing classification systems, can contribute to the quality development of Health Information Systems. Objectives: To develop a NMDS for clinical hospitalization units. Methods: Methodological study performed in four stages. At the first stage a documentary evaluation of the screens and forms of the information system used at the clinical unit to register nursing data in a public hospital of the State of São Paulo was conducted. At the second stage, workshops were held with nurses from the medical unit to determine the NMDS related to the nursing care elements, patient elements and to the service providers elements involved in nursing care. It was used as referential the nursing diagnoses classification NANDA International (NANDA-I), the Nursing Intervention Classification (NIC) and the nursing theory Basic Human Needs (BHN). At the third stage, a cross-mapping was made between the nursing prescriptions from the ins... (Complete abstract click electronic access below) / Mestre

Nurses are often the first members of the health care team with whom patients interact. The initial impression of the nurses’ receptiveness to the patients’ needs influences the patients’ views of their overall care. Researchers have suggested that understanding communication between individuals can provide the human link, or social element, to the successful implementation and use of electronic health records, including documentation (Lanham, Leykum, & McDaniel, 2012). Zadvinskis, Chipps, and Yen (2014) identified that the helpful features of bedside documentation systems were offset by the mismatch between the system and nurse’s workflow. The purpose of this micro-ethnography study was to explore the culture of nurse-patient interaction associated with electronic documentation at the bedside. Data were collected through passive participant observation, audio-taping of the nurse-patient interactions, and informal and semi-structured interviews with the nurses. A total of twenty-six observations were conducted on three nursing units at an urban healthcare facility in New England. These three units were occupied by similar patient populations and all patients required cardiac monitoring. Three themes consistently emerged from qualitative data analysis: the nurses paused during verbal communication, the nurses played a game of tag between the patient and the computer, and the nurses performed automatic or machine-like actions. The participants described these themes in the informal and semi-structured interviews. The nurses’ actions were observed during passive participant observation, and the audio-taped interactions supported these themes. Understanding the adaptation of caregiving necessitated by bedside electronic documentation will have a positive impact on developing systems that interface seamlessly with the nurses’ workflow and encourage patients’ active participation in their care.

Introdução: A utilização das ferramentas e instrumentos da informática no processo do atendimento de pacientes auxilia os profissionais da saúde, pois facilita a coleta e armazenamento das informações, proporcionando qualidade no atendimento e criando condições de enfrentamento dos desafios do mundo globalizado. Nesse contexto, a utilização de dados de prontuário eletrônico de pacientes vinculados à pesquisa clínica em um hospital universitário público pode auxiliar no aprimoramento da assistência à saúde, assim como subsidia dados de pesquisas no âmbito da saúde. Objetivos: Identificar e avaliar os registros provenientes de pesquisas clínicas postos nos sistemas coorporativos do Hospital de Clínicas de Porto Alegre (HCPA), no período de 2014 a 2016. Método: A pesquisa utilizou abordagem quantitativa e qualitativa, de análise de conteúdo de referências e de dados provenientes da rede de informação clínica e assistencial através do cruzamento de informações do sistema integrado Aplicativo para Gestão de Hospitais Universitários (AGHU) e pelo Grupo de Pesquisa e Pós-Graduação (GPPG) do Hospital de Clínicas de Porto Alegre, no período entre janeiro de 2014 e dezembro de 2016. Resultados: Entre os projetos, 58,6% encaminharam relatórios de pesquisa, sendo que somente 23,8% possuem registro de participantes de pesquisa. No entanto, apenas 10,3% dentre todos os estudos que indicaram utilizar pacientes no seu protocolo de pesquisa tem concordância de registro entre o GPPG8 e o AGHU. Cerca de 25,6% do total de relatórios de pesquisa encaminhados apresentam informações quanto aos seus produtos de pesquisa. As pesquisas com patrocínio privado demonstraram encaminhar mais relatórios de atualização dos projetos, porém com menor índice na apresentação dos produtos científicos (1,4%). Considerações finais: Potenciais limitações no uso dos registros existentes no AGHU foram identificadas para decisões terapêuticas pela equipe assistencial de maneira geral, tendo em vista a aparente subnotificação de informações relativas ao andamento e desfecho dos estudos desenvolvidos. Entretanto, não foi possível analisar as causas dos registros possivelmente inadequados ou incompletos, sugerindo-se pesquisas específicas com a incorporação de questionários ou entrevistas individuais para permitir maior aprofundamento na temática. Produtos: A pesquisa identificou a necessidade de três produtos derivados do estudo: (1) material explicativo para os pesquisadores informando a necessidade do registro apropriado dos participantes no sistema coorporativo; (2) modelo de relatório de pesquisa para encerramento de projeto, disponibilizado pelo GPPG, em formato online para pesquisadores responsáveis pelo projeto de pesquisa; e (3) sugestão de melhoria das informações disponibilizadas pela aba “Projetos de Pesquisa” no prontuário online dos pacientes que estão vinculados a projetos de pesquisa, informando os potenciais resultados de pesquisas envolvidas com estes à área assistencial. / Introduction: Using informatics tools on the medical care process for patients helps health professionals, makes easier to collect and to storage information, as well as exchange this information among professionals and institutions, offering quality of care and creating conditions to face challenges in a globalized world. In this context, using electronic medical records data of patients enrolled on clinical trials in a public hospital may help improving health care, as well as provide research health data. Objectives: To identify and evaluate records from clinical trials registered on corporative systems from Hospital de Clinicas de Porto Alegre (HCPA), from 2014 to 2016. Method: The research used quantitative and qualitative approach, analyzing references content and data from the network for clinical data, crossing information from Aplicativo para Gestão de Hospitais Universitários (AGHU) and Grupo de Pesquisa e Pós-Graduação (GPPG) of HCPA, from 2014 and 2016. Results: Among the projects 58,6% forwarded research reports, but just 23,8% with record of research participants. However, only 10,3% of studies that report participants enrolled in study protocol matched records in GPPG8 and AGHU. About 25,6% of total research reports informed research products. Researches with private sponsor showed more update reports, but with lower presentations of scientific products (1,4%). Final considerations: Potential limitations on using existent records on AGHU were identified for therapeutic decisions by clinical team in general, with apparent underreporting of information relate to development and closure for studies developed. However was not possible to analyze causes for possibly inaccurate or incomplete records, suggesting specific research with individual questionnaires or interviews in order to allow deepening the understanding on the theme. Products: The research identify the need for three product from the study: (1) a explicative material to researchers, informing an appropriate participant’s registration on the corporative system; (2) a model of research report for project termination, available on GPPG, online, to lead researchers in research projects; and (3) improvement suggestion on information available by “research projects” tab on the online medical records for patients enroll in research projects, informing potential results associated to medical care area.

abstract: Clinicians confront formidable challenges with information management and coordination activities. When not properly integrated into clinical workflow, technologies can further burden clinicians’ cognitive resources, which is associated with medical errors and risks to patient safety. An understanding of workflow is necessary to redesign information technologies (IT) that better support clinical processes. This is particularly important in surgical care, which is among the most clinical and resource intensive settings in healthcare, and is associated with a high rate of adverse events. There are a growing number of tools to study workflow; however, few produce the kinds of in-depth analyses needed to understand health IT-mediated workflow. The goals of this research are to: (1) investigate and model workflow and communication processes across technologies and care team members in post-operative hospital care; (2) introduce a mixed-method framework, and (3) demonstrate the framework by examining two health IT-mediated tasks. This research draws on distributed cognition and cognitive engineering theories to develop a micro-analytic strategy in which workflow is broken down into constituent people, artifacts, information, and the interactions between them. It models the interactions that enable information flow across people and artifacts, and identifies dependencies between them. This research found that clinicians manage information in particular ways to facilitate planned and emergent decision-making and coordination processes. Barriers to information flow include frequent information transfers, clinical reasoning absent in documents, conflicting and redundant data across documents and applications, and that clinicians are burdened as information managers. This research also shows there is enormous variation in how clinicians interact with electronic health records (EHRs) to complete routine tasks. Variation is best evidenced by patterns that occur for only one patient case and patterns that contain repeated events. Variation is associated with the users’ experience (EHR and clinical), patient case complexity, and a lack of cognitive support provided by the system to help the user find and synthesize information. The methodology is used to assess how health IT can be improved to better support clinicians’ information management and coordination processes (e.g., context-sensitive design), and to inform how resources can best be allocated for clinician observation and training. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2017

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-07-17T18:21:26Z No. of bitstreams: 1 Arquivototal.pdf: 16322215 bytes, checksum: c172a5636f12cf8195f2382f1c23de59 (MD5) / Made available in DSpace on 2018-07-17T18:21:26Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 16322215 bytes, checksum: c172a5636f12cf8195f2382f1c23de59 (MD5) Previous issue date: 2013-02-27 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Various researches in molecular epidemiology, molecular diagnosis and evolutionary genetics related to pathogens are compared to managing large amounts of data derived from institutions such as, hospitals or laboratories. Although there already are some proposals to connect molecular information to the diagnosis of pathogens, none of them uses high performance bioinformatics tools which are embedded in a system and linked to a patient’s electronic record. The MolEpi tool has been developed as a system of data and information management addressed to public health, incorporating clinical and epidemiological information about patients, as well as molecular data of 16S rRNA sequences of pathogenic bacteria. In order to confirm which species of these bacteria were identified, biological samples (urine, secretions and purulent wounds, tracheal aspirate and blood) and subsequently incubation and growth of colonies in culture, and PCR was used followed by sequencing and analysis of the conserved coding region for 16S ribosomal RNA (rDNA). Such strategy enabled fast bacterial identification, regardless of prior knowledge of the species of microorganism under study. Moreover MolEpi is a system interconnected to repositories of specific sequences as Genbank (NCBI), RDP-II (Ribosomal Database Project - MSU) and GreenGene (LBL). In this way, once the sequences of clinical isolates are confirmed and validated, they can be used as reference in the identification of other unknown microorganisms. Thus, a local database was established, representing the profile of pathogens found in the hospital unity of study and which should be object of public health surveillance. In order to develop MolEpi, we used the Java programming language and the PostgreSQL8.3 object-relational database. It was also developed BACSearch, which has the following programs to handle the analysis of 16S rDNA sequences, we used the framework BioJava; to multiple alignment, ClustalW2, MAFFT and MUSCLE, and for editing of multiple alignment and phylogenetic analysis, the JalView2.4.0 was used. The system was validated with 200 clinical specimens isolated and identified from sites of nosocomial infection. The DNA sequences produced from these samples were subjected to BLAST by using the developed tool, which identified Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Morganella morganii as the main pathogens involved. Data on resistance patterns of the species were obtained in microbiology laboratory, and incorporated into the database. The application of MolEpi tool to the Health System can provide prompt and accurate diagnosis, connected to relevant network information which can be intended for health professionals. / A maioria das pesquisas em epidemiologia molecular, diagnóstico molecular e genética evolutiva são confrontadas com o gerenciamento de grandes volumes de dados. Além disso, os dados utilizados em estudos de doenças patogênicas são complexos e geralmente derivam de instituições tais como hospitais ou laboratórios. Embora já existam propostas que conecte informações moleculares ao diagnóstico de patogenias, nenhuma delas utilizam ferramentas de bioinformática de alto desempenho incorporadas a um sistema e vinculada a um prontuário eletrônico do paciente. MolEpi foi desenvolvido como um sistema de gerenciamento de dados e informações dimensionado a saúde pública, incorporando informações clínicas e epidemiológicas sobre pacientes e dados moleculares de sequências do gene rRNA 16S de bactérias patogênicas. Para identificação destas bactérias foram utilizadas amostras biológicas (urina, secreções e purulentas de feridas, aspirado traqueal e sangue) e PCR seguida de sequenciamento e análise da região conservada codificadora de RNA ribossômico (rDNA) 16S. Este estratégia permite uma identificação bacteriana rápida, independente de conhecimento prévio da espécie de microrganismo em estudo. O MolEpi é um sistema facilmente atualizável com as sequências específicas de bancos como Genbank(NCBI), RDP-II (Ribosomal Database Project - MSU) e GreenGene (LBL). A partir da confirmação e validação das sequências dos isolados clínicos, estas podem ser utilizadas como referência na identificação de outros microrganismos desconhecidos. Neste sentido, foi estabelecido um banco de dados local, representativo do perfil de patógenos encontrados na unidade hospitalar de estudo e objeto de vigilância epidemiológica. Para o desenvolvimento do MolEpi, utilizamos a linguagem Java e banco de dados PostgreSQL8.3. Foi desenvolvido também o BACSearch, que possui os seguintes programas: para o processamento de sequências de rDNA 16S utilizamos os frameworks BioJava; para alinhamento múltiplo foi implementado o ClustalW2, MAFFT e o MUSCLE e para edição do alinhamento múltiplo e análise filogenética foi utilizado JalView R⃝2.4.0b2. O sistema foi validado com 200 espécimes clínicos identificadas e isoladas de sítios de infecção hospitalar. As sequências de DNA produzidas a partir destas amostras foram submetidas ao BLAST, utilizando a ferramenta desenvolvida, identificando Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiela pneumonie e Staphylococcus aureus como os principais patógenos correspondentes. Os dados sobre o padrão de resistência das espécies foram obtidos em laboratório de microbiologia e incorporados ao banco de dados. A aplicação do MolEpi ao Sistema Único de Saúde poderá fornecer diagnósticos mais rápidos, precisos, e interligados a uma rede de informações relevantes para o profissional de saúde.