Os Sistemas de Registro Eletrônico em Saúde (S-RES) permitem manipular e analisar um grande volume de dados e informações de saúde. O desenvolvimento, disponibilização e uso de funcionalidades para S-RES pode beneficiar tanto os profissionais de saúde como os pacientes. Estes sistemas devem ser próprios para o contexto onde serão utilizados, podendo estar voltados a diferentes áreas da saúde, assim como para diferentes níveis de atenção à saúde. Para o usuário final, a adequação do S-RES é avaliada pela qualidade em uso que resulta, principalmente, da funcionalidade, confiabilidade, usabilidade e eficiência do sistema. O termo funcionalidade designa o aspecto do sistema computacional que retrata as funções necessárias para a resolução de problemas dentro de um determinado contexto de uso. A funcionalidade se refere àquilo que um programa faz e, no caso de software interativo, o que ele deve oferecer para seus usuários. Frente a este contexto, a presente dissertação se propõe a identificar, através da literatura e de documentos de referência sobre o tema, as funcionalidades para os S-RES com potencial de apoiar os profissionais de saúde na prestação do cuidado ao paciente na Atenção Primária à Saúde (APS). Nenhuma das listas de funcionalidades existentes na literatura é específica para S-RES para APS. Foi realizada uma revisão da literatura nas principais bases de dados da área da saúde. Para a extração das funcionalidades, foram selecionados os documentos mais relevantes e que eram referência para os demais materiais consultados. As funcionalidades apresentadas pelos documentos foram compiladas e formatadas em uma planilha eletrônica de maneira que pudessem ser utilizadas para seleção de funcionalidades para um S-RES para APS. As funcionalidades identificadas foram categorizadas e agrupadas por similaridade de aplicação em sete categorias relacionadas ao contexto de trabalho na APS. Três documentos foram utilizados para a seleção das funcionalidades. A análise das funcionalidades identificadas evidenciou a predominância de funcionalidades relacionadas a aspectos clínicos da prestação do cuidado dos pacientes. De um total de 145 funcionalidades, 91 (62,8%) foram classificadas como de “manejo clínico do paciente”, grande parte dessas voltadas para o diagnóstico e tratamento clínico, como também para o apoio à decisão clínica. O conjunto de funcionalidades relacionadas à “prevenção” e às classificadas como de “educação em saúde e comunicação com o paciente” representaram juntas apenas 20% do total, com respectivamente 11,7% e 8,3% do total de funcionalidades identificadas. Importantes funcionalidades para S-RES de APS que consideram as perspectivas e preferências do paciente e de sua família em relação à saúde, e ainda, o relacionamentos entre os sujeitos, foram classificadas como “aspectos subjetivos e familiares” e representaram 4,8% do total de funcionalidades de APS. Por fim, é possível reconhecer que a maioria das funcionalidades para S-RES adequadas ao contexto da APS está direcionada ao manejo clínico dos pacientes. São poucas as funcionalidades que contemplam as demais dimensões do trabalho em APS e que favorecem uma compreensão da pessoa de modo integral. / Electronic Health Records (EHR) systems allow to manipulate and analyze large volumes of data and health information. The development , availability and use of features for EHR systems can benefit both health professionals and patients. These systems shall be suitable to the context where they will be used, or can be directed to different areas of health, as well as different levels of health care. For the end user, the adequacy of the EHR systems is evaluated for quality in use which results mainly from the: functionality, reliability, usability and system efficiency. Functionality refers to the aspect of the computer system that represents the functions required to solve problems within a specified context of use. Functionality refers to what a program does and, in the case of interactive software, what it must offer to its users. Facing this context, this thesis aims to identify, through literature and reference documents on the subject, the functionality for the EHR systems with the potential to support health professionals in the provision of patient care in Primary health Care (PHC). None of functionalities lists existing in the literature is specific to EHR systems for PHC. A literature review was conducted in the main bases of health care data. For the extraction of functionalities, the most relevant documents were selected and they were reference for other found materials. The functionalities presented by the documents were compiled and formatted in a electronic spreadsheet. So it could be used for selection of functionalities for an EHR systems for PHC. The identified functionalities were categorized and grouped by similarity application in seven categories related to the work context in PHC. Three documents were used for selection of functionalities. The analysis of the identified functionalities showed the predominance of functionalities related to clinical aspects of the provision of patient care. The total of 145 functionalities, 91 (62.8%) were classified as "clinical management of patients", most of these focused on the diagnosis and treatment, but also to clinical decision support. The group of functionalities related to "prevention" and classified as "health education and communication with the patient" together accounted for only 20% of the total, respectively 11.7% and 8.3% of the identified functionalities. Important functionalities to EHR systems for Primary Healh Care which regard the perspectives and preferences of patients and their families in relation to health, and also the relationships between the subjects were classified as "subjective and family aspects" and represented 4.8% of total PHC functionalities. Finally, it is possible to recognize that most of the appropriate EHR systems functionalities to the context of Primary Health Care is directed to the clinical management of patients. There are few functionalities that contemplate other dimensions of Primary Health Care work and support a comprehension of the person as a whole.

Os Sistemas de Registro Eletrônico em Saúde (S-RES) permitem manipular e analisar um grande volume de dados e informações de saúde. O desenvolvimento, disponibilização e uso de funcionalidades para S-RES pode beneficiar tanto os profissionais de saúde como os pacientes. Estes sistemas devem ser próprios para o contexto onde serão utilizados, podendo estar voltados a diferentes áreas da saúde, assim como para diferentes níveis de atenção à saúde. Para o usuário final, a adequação do S-RES é avaliada pela qualidade em uso que resulta, principalmente, da funcionalidade, confiabilidade, usabilidade e eficiência do sistema. O termo funcionalidade designa o aspecto do sistema computacional que retrata as funções necessárias para a resolução de problemas dentro de um determinado contexto de uso. A funcionalidade se refere àquilo que um programa faz e, no caso de software interativo, o que ele deve oferecer para seus usuários. Frente a este contexto, a presente dissertação se propõe a identificar, através da literatura e de documentos de referência sobre o tema, as funcionalidades para os S-RES com potencial de apoiar os profissionais de saúde na prestação do cuidado ao paciente na Atenção Primária à Saúde (APS). Nenhuma das listas de funcionalidades existentes na literatura é específica para S-RES para APS. Foi realizada uma revisão da literatura nas principais bases de dados da área da saúde. Para a extração das funcionalidades, foram selecionados os documentos mais relevantes e que eram referência para os demais materiais consultados. As funcionalidades apresentadas pelos documentos foram compiladas e formatadas em uma planilha eletrônica de maneira que pudessem ser utilizadas para seleção de funcionalidades para um S-RES para APS. As funcionalidades identificadas foram categorizadas e agrupadas por similaridade de aplicação em sete categorias relacionadas ao contexto de trabalho na APS. Três documentos foram utilizados para a seleção das funcionalidades. A análise das funcionalidades identificadas evidenciou a predominância de funcionalidades relacionadas a aspectos clínicos da prestação do cuidado dos pacientes. De um total de 145 funcionalidades, 91 (62,8%) foram classificadas como de “manejo clínico do paciente”, grande parte dessas voltadas para o diagnóstico e tratamento clínico, como também para o apoio à decisão clínica. O conjunto de funcionalidades relacionadas à “prevenção” e às classificadas como de “educação em saúde e comunicação com o paciente” representaram juntas apenas 20% do total, com respectivamente 11,7% e 8,3% do total de funcionalidades identificadas. Importantes funcionalidades para S-RES de APS que consideram as perspectivas e preferências do paciente e de sua família em relação à saúde, e ainda, o relacionamentos entre os sujeitos, foram classificadas como “aspectos subjetivos e familiares” e representaram 4,8% do total de funcionalidades de APS. Por fim, é possível reconhecer que a maioria das funcionalidades para S-RES adequadas ao contexto da APS está direcionada ao manejo clínico dos pacientes. São poucas as funcionalidades que contemplam as demais dimensões do trabalho em APS e que favorecem uma compreensão da pessoa de modo integral. / Electronic Health Records (EHR) systems allow to manipulate and analyze large volumes of data and health information. The development , availability and use of features for EHR systems can benefit both health professionals and patients. These systems shall be suitable to the context where they will be used, or can be directed to different areas of health, as well as different levels of health care. For the end user, the adequacy of the EHR systems is evaluated for quality in use which results mainly from the: functionality, reliability, usability and system efficiency. Functionality refers to the aspect of the computer system that represents the functions required to solve problems within a specified context of use. Functionality refers to what a program does and, in the case of interactive software, what it must offer to its users. Facing this context, this thesis aims to identify, through literature and reference documents on the subject, the functionality for the EHR systems with the potential to support health professionals in the provision of patient care in Primary health Care (PHC). None of functionalities lists existing in the literature is specific to EHR systems for PHC. A literature review was conducted in the main bases of health care data. For the extraction of functionalities, the most relevant documents were selected and they were reference for other found materials. The functionalities presented by the documents were compiled and formatted in a electronic spreadsheet. So it could be used for selection of functionalities for an EHR systems for PHC. The identified functionalities were categorized and grouped by similarity application in seven categories related to the work context in PHC. Three documents were used for selection of functionalities. The analysis of the identified functionalities showed the predominance of functionalities related to clinical aspects of the provision of patient care. The total of 145 functionalities, 91 (62.8%) were classified as "clinical management of patients", most of these focused on the diagnosis and treatment, but also to clinical decision support. The group of functionalities related to "prevention" and classified as "health education and communication with the patient" together accounted for only 20% of the total, respectively 11.7% and 8.3% of the identified functionalities. Important functionalities to EHR systems for Primary Healh Care which regard the perspectives and preferences of patients and their families in relation to health, and also the relationships between the subjects were classified as "subjective and family aspects" and represented 4.8% of total PHC functionalities. Finally, it is possible to recognize that most of the appropriate EHR systems functionalities to the context of Primary Health Care is directed to the clinical management of patients. There are few functionalities that contemplate other dimensions of Primary Health Care work and support a comprehension of the person as a whole.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2015-01-13T11:26:26Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Renata Dutra Braga - 2014.pdf: 3194957 bytes, checksum: 9b4e4b86421eb376d6e430fc3b6e2a6b (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-01-13T11:26:47Z (GMT) No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Renata Dutra Braga - 2014.pdf: 3194957 bytes, checksum: 9b4e4b86421eb376d6e430fc3b6e2a6b (MD5) / Made available in DSpace on 2015-01-13T11:26:47Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Renata Dutra Braga - 2014.pdf: 3194957 bytes, checksum: 9b4e4b86421eb376d6e430fc3b6e2a6b (MD5) Previous issue date: 2014-03-14 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / There are various health information systems in use in the country, which serve different purposes, but are not interoperable. To ensure interoperability in the development of a model that serves different health professions was held this research, which aimed to define a conceptual model for the registration of health information in primary care. Methods: This action research with analytical approach was held in conjunction with a panel of experts to represent the health professions recognized by the National Health Council (CNS), which through discussion meetings identified and systematized essential information needed to evaluate the overall health of individual, in the context of multidisciplinary primary care demands generating a preliminary model. This model was validated by Delphi method and a consensus model was proposed. Results: The conceptual model to health information registration obtained goes beyond the demands of administration, since its focus is the individual - source of all the information that generates health demands. The central structure of the information registry model comprised four groups of information, which were called pillars: Data Gathering, Diagnosis, Care Plan and Evaluation. Each of these pillars presented subgroups important to the different professions, whose complexity limit of detail of information stood on the complexity of primary health care. Conclusion: This study represents a joint effort to establish an architecture of essential information for creating an electronic record in interoperable and necessary to meet the individual's health in primary care. / Há vários sistemas de informação em saúde em uso no país, que servem a propósitos distintos, contudo não são interoperáveis. Para assegurar a interoperabilidade na elaboração de um modelo que atende diferentes profissões de saúde realizou-se esta pesquisa, cujo objetivo foi definir um modelo conceitual para o registro da informação em saúde na atenção primária. Métodos: Esta pesquisa-ação, com abordagem analítica, foi realizada em conjunto com um painel de profissionais que, por meio de reuniões de discussão identificou e sistematizou informações essenciais para a avaliação da saúde geral do indivíduo, no contexto das demandas multiprofissionais da atenção primária, gerando um modelo preliminar. Esse modelo foi validado pelo método Delphi e um modelo consensual foi proposto. Resultados: O modelo conceitual de registro da informação em saúde obtido extrapola as demandas da gestão administrativa, visto que o seu foco foi o indivíduo – fonte de todas as informações que geram as demandas em saúde. A estrutura central do modelo compreendeu quatro grupos de informações, denominados de pilares: Coleta de Dados, Diagnóstico, Plano de Cuidados e Avaliação. Cada um desses pilares apresentaram subgrupos importantes para as diferentes profissões, cujo limite de complexidade e detalhamento da informação situou-se na atenção primária em saúde. Conclusão: Este estudo representa um esforço conjunto para o estabelecimento de uma arquitetura de informações essenciais para a criação de um registro eletrônico em saúde interoperável e necessárias para o atendimento do indivíduo na atenção primária.

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.”

Yes / Background: Electronic personal health records (ePHRs) are secure Web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ ePHR use is important to increase adoption rates and improve the implementation success of ePHRs. Objective: This study aimed to examine factors associated with patients’ use of ePHRs in England. Methods: The unified theory of acceptance and use of technology was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in 4 general practices in West Yorkshire, England. Factors associated with the use of ePHRs were explored using structural equation modeling. Results: Of 800 eligible patients invited to take part in the survey, 624 (78.0%) returned a valid questionnaire. Behavioral intention (BI) was significantly influenced by performance expectancy (PE; beta=.57, P<.001), effort expectancy (EE; beta=.16, P<.001), and perceived privacy and security (PPS; beta=.24, P<.001). The path from social influence to BI was not significant (beta=.03, P=.18). Facilitating conditions (FC) and BI significantly influenced use behavior (UB; beta=.25, P<.001 and beta=.53, P<.001, respectively). PE significantly mediated the effect of EE and PPS on BI (beta=.19, P<.001 and beta=.28, P=.001, respectively). Age significantly moderated 3 paths: PE→BI, EE→BI, and FC→UB. Sex significantly moderated only the relationship between PE and BI. A total of 2 paths were significantly moderated by education and internet access: EE→BI and FC→UB. Income moderated the relationship between FC and UB. The adapted model accounted for 51% of the variance in PE, 76% of the variance in BI, and 48% of the variance in UB. Conclusions: This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills to ensure systems are useful and easy to use. The proposed model accounted for 48% of the variance in UB, indicating the existence of other, as yet unidentified, factors that influence the adoption of ePHRs. Future studies should confirm the effect of the factors included in this model and identify additional factors.

eHealth Strategies in countries have shown a trend that countries are moving to Electronic Health Records(EHR). EHR implementation is expected to produce benefits for patients, professionals, organisations, and the population as a whole. The use of some format of an Electronic Health Record is used by many countries and others are in the implementation or planning phases. South Africa has kicked of the project to implement a national EHR as part of the national eHealth Strategy. This study aims to analyse the key success factors from other EHR implementation projects and evaluate if South Africa is ready to implement an EHR.

The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified a set of cultural and sub-cultural dimensions in SA health information security and services.

eHealth Strategies in countries have shown a trend that countries are moving to Electronic Health Records(EHR). EHR implementation is expected to produce benefits for patients, professionals, organisations, and the population as a whole. The use of some format of an Electronic Health Record is used by many countries and others are in the implementation or planning phases. South Africa has kicked of the project to implement a national EHR as part of the national eHealth Strategy. This study aims to analyse the key success factors from other EHR implementation projects and evaluate if South Africa is ready to implement an EHR.

A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine. / BACKGROUND: In order to improve the quality and efficacy of healthcare while reducing the overall cost to deliver that healthcare, it has become increasingly important to manage utilization of services for populations of patients. Healthcare systems are aggressively working to identify patients at risk for hospital readmissions. Although readmission rates have been studied before, parameters for identifying patients at risk for readmission appear to vary depending the patient population. We will examine existing Electronic Health Record (EHR) data at Banner Health to establish what parameters are clinical indicators for readmission risk. Three conditions were identified by the CMS to have high and costly readmissions rates; heart failure (HF), acute myocardial infarction (AMI), and pneumonia. This study will focus on attempting to determine the primary predictive variables for these three conditions in order to have maximum impact on cost savings. METHODS: A literature review was done and 68 possible risk variables were identified. Of these, 30 of the variables were identifiable within the EHR system. Inclusion criteria for individual patient records are that they had an index admission secondary to AMI, heart failure, or pneumonia and that they had a subsequent readmission within 30 days of the index admission. Pediatric populations were not studied since they have unique factors for readmission that are not generalizable. Logistics regression was applied to all data including data with missing data rows. This allowed all coefficients to be interpreted for significance. This model was termed the full model. Variables that were determined to be insignificant were subsequently removed to create a new reduced model. Chi square testing was then done to compare the reduced model to the full model to determine if any significant differences existed between the two. RESULTS: Several variables were determined to be the significant predictors of readmission. The final reduced model had 19 predictors. When analyzed using ROC analysis, the area under the curve (AUC) was 0.64. CONCLUSION: Several variables were identified that could be significant contributors to readmission risk. The final model had an AUC on it ROC of 0.64 suggesting that it would only have poor to moderate clinical value for predicting readmission.

The ongoing digitization of healthcare, which has been much accelerated by the widespread adoption of electronic health records, generates unprecedented amounts of clinical data in a readily computable form. This, in turn, affords great opportunities for making meaningful secondary use of clinical data in the endeavor to improve healthcare, as well as to support epidemiology and medical research. To that end, there is a need for techniques capable of effectively and efficiently analyzing large amounts of clinical data. While machine learning provides the necessary tools, learning effective predictive models from electronic health records comes with many challenges due to the complexity of the data. Electronic health records contain heterogeneous and longitudinal data that jointly provides a rich perspective of patient trajectories in the healthcare process. The diverse characteristics of the data need to be properly accounted for when learning predictive models from clinical data. However, how best to represent healthcare data for predictive modeling has been insufficiently studied. This thesis addresses several of the technical challenges involved in learning effective predictive models from electronic health records. Methods are developed to address the challenges of (i) representing heterogeneous types of data, (ii) leveraging the concept hierarchy of clinical codes, and (iii) modeling the temporality of clinical events. The proposed methods are evaluated empirically in the context of detecting adverse drug events in electronic health records. Various representations of each type of data that account for its unique characteristics are investigated and it is shown that combining multiple representations yields improved predictive performance. It is also demonstrated how the information embedded in the concept hierarchy of clinical codes can be exploited, both for creating enriched feature spaces and for decomposing the predictive task. Moreover, incorporating temporal information leads to more effective predictive models by distinguishing between event occurrences in the patient history. Both single-point representations, using pre-assigned or learned temporal weights, and multivariate time series representations are shown to be more informative than representations in which temporality is ignored. Effective methods for representing heterogeneous and longitudinal data are key for enhancing and truly enabling meaningful secondary use of electronic health records through large-scale analysis of clinical data.