Introdução: Araraquara (SP) possui um programa de vacinação bem sucedido desde a década de 80, com o mais antigo Registro Informatizado de Imunização (RII) do país. Objetivos: Estimar a cobertura vacinal (CV) aos 12 e 24 meses de vida, em crianças nascidas em 2012, no município de Araraquara, investigar fatores associados à vacinação incompleta e analisar os eventos adversos pós-vacinação (EAPV). Métodos: Estudo observacional com componentes descritivo e analítico, abrangendo a coorte de crianças nascidas em 2012, residentes no município e registradas no Sistema de Informação de Nascidos Vivos (SINASC). Foram excluídas as crianças que faleceram no primeiro ano de vida e aquelas que se mudaram de Araraquara. As variáveis do estudo incluíram dados de vacinação e características maternas, de pré- natal/nascimento, do(s) serviço(s) de saúde e da área de residência. Estimou-se as CV e respectivos intervalos de confiança de 95 por cento (IC 95 por cento ) para cada vacina e esquema completo, conforme as normas vigentes no Estado de São Paulo em 2012/2013. A associação entre o esquema vacinal incompleto e as variáveis independentes foi investigada por meio da estimativa da odds ratio (OR) bruta e ajustada, por regressão logística múltipla não condicional hierarquizada, com os respectivos IC 95 por cento . Resultados: 2740 crianças estavam registradas no SINASC como residentes e 99,6 por cento dessas constavam no RII. Após excluir 30 óbitos (1,1 por cento ) e 98 crianças que se mudaram (3,6 por cento ), foram estudadas 2612 crianças. A CV para o esquema completo por doses recebidas aos 12 meses foi 67,9 por cento e aos 24 meses 79,7 por cento ; por doses oportunas foi 46,2 por cento e 32,8 por cento , respectivamente. A vacina sarampo, caxumba e rubéola apresentou a menor CV aos 12 meses por dose recebida (74,8 por cento ) e aos 24 meses por dose oportuna (53,5 por cento ). As vacinas com componente pertussis foram responsáveis por 58,8 por cento (10/17) dos casos de EAPV e febre foi a manifestação mais comum. A distribuição espacial da CV do esquema completo por área de residência não apresentou diferença estatística. No modelo final, mostraram-se independentemente associadas à vacinação incompleta: mães com idade entre 14 e 19 anos [aos 12 meses (OR:2,0); aos 24 meses (OR:2,5)]; com 12 anos ou mais de estudo [aos 12 meses (OR:1,9), aos 24 meses (OR:2,3)]; com três ou mais filhos [aos 12 meses (OR:3,2), aos 24 meses (OR:2,1)]; com menos de sete consultas de pré-natal [aos 12 meses (OR:1,7), aos 24 meses (OR:2,3)]; a criança ter frequentado unidade de saúde (US) pública e privada [aos 12 meses (OR:6,0), aos 24 meses (OR:8,0)], sem Estratégia Saúde da Família [aos 24 meses (OR:1,5)]; e ter vínculo fraco com a US [aos 24 meses (OR:1,4)]. Conclusão: Em Araraquara, a CV por vacina não é homogênea e há atraso vacinal. O uso do RII para o seu monitoramento pode constituir uma estratégia efetiva. A ausência de disparidades nas CV entre as distintas áreas de residência sugere a efetividade do programa de imunização na promoção da equidade em saúde. Recomenda-se priorizar ações de incentivo à vacinação de crianças filhas de mulheres com alta escolaridade e que apresentam vínculo mais frágil com os serviços públicos de saúde / Introduction: Araraquara (SP) has a successful vaccination program since the 80\'s, with the oldest Electronic Immunization Registry (EIR) in the country. Objectives: To estimate vaccination coverage (VC) at 12 and 24 months of life in children born in 2012 in the city of Araraquara, to investigate factors associated with incomplete vaccination and to analyze the adverse events following immunization (AEFI). Methods: An observational descriptive and analytical study comprising the cohort of children born in 2012, living in the city of Araraquara and recorded in the Live Births Information System (SINASC). Children who died in the first year of life or who moved from Araraquara were excluded. Study variables included vaccination data and characteristics of the mother, the antenatal/birth, the health unit (HU) and the area of residence. VC and the respective 95 per cent confidence intervals (95 per cent CI) were estimated for each vaccine and complete schedule, following the São Paulo\'s State recommendations in the years 2012/2013. The association between the incomplete vaccination schedule and the independent variables was investigated by estimating the crude and adjusted odds ratio (OR) by hierarchical non-conditional multiple logistic regression with the respective 95 per cent CI. Results: 2740 children were enrolled in the SINASC as residents and 99.6 per cent of them were in the EIR. After excluding 30 deaths (1.1 per cent ) and 98 children who moved (3.6 per cent ), 2612 children were studied. VC by received doses for the complete schedule at 12 months was 67.9 per cent and at 24 months was 79.7 per cent ; by timely doses was 46.2 per cent and 32.8 per cent , respectively. The measles, mumps and rubella vaccine had the lowest VC at 12 months per received dose (74.8 per cent ) and at 24 months per timely dose (53.5 per cent ). Vaccines with pertussis componente were responsible for 58.8 per cent (10/17) of AEFI cases and fever was the most common manifestation. The spatial distribution of VC of the complete schedule by area of residence did not present statistical difference. In the final model, incomplete vaccination was associated with mother between 14 and 19 years old [at 12 months (OR: 2.0); at 24 months (OR: 2.5)]; with 12 years or more of study [at 12 months (OR: 1.9), at 24 months (OR: 2.3) ]; with three or more children [at 12 months (OR: 3.2), at 24 months (OR: 2.1)]; with less than seven antenatal visits [at 12 months (OR: 1.7), at 24 months (OR: 2.3)]; the child has attended both public and private HU [at 12 months (OR: 6.0), at 24 months (OR: 8.0)], a HU without Family Health Strategy [at 24 months (OR: 1.5)]; and who had a weak link with the HU [at 24 months (OR: 1.4)]. Conclusion: VC per vaccine is not homogeneous in Araraquara and there is a vaccine delay. The use of RII for its monitoring can be an effective strategy. The lack of disparities in VC among the different areas of residence suggests the effectiveness of the immunization program in promoting health equity. It is recommended to prioritize actions to encourage children vaccination of mothers with high schooling and who have a more fragile link with public HU

"Our modern society is increasingly relying on the collection, processing, and sharing of digital information. There are two fundamental trends: (1) Enabled by the rapid developments in sensor, wireless, and networking technologies, communication and networking are becoming more and more pervasive and ad hoc. (2) Driven by the explosive growth of hardware and software capabilities, computation power is becoming a public utility and information is often stored in centralized servers which facilitate ubiquitous access and sharing. Many emerging platforms and systems hinge on both dimensions, such as E-healthcare and Smart Grid. However, the majority information handled by these critical systems is usually sensitive and of high value, while various security breaches could compromise the social welfare of these systems. Thus there is an urgent need to develop security and privacy mechanisms to protect the authenticity, integrity and confidentiality of the collected data, and to control the disclosure of private information. In achieving that, two unique challenges arise: (1) There lacks centralized trusted parties in pervasive networking; (2) The remote data servers tend not to be trusted by system users in handling their data. They make existing security solutions developed for traditional networked information systems unsuitable. To this end, in this dissertation we propose a series of user-centric security and privacy mechanisms that resolve these challenging issues in untrusted network and computing environments, spanning wireless body area networks (WBAN), mobile social networks (MSN), and cloud computing. The main contributions of this dissertation are fourfold. First, we propose a secure ad hoc trust initialization protocol for WBAN, without relying on any pre-established security context among nodes, while defending against a powerful wireless attacker that may or may not compromise sensor nodes. The protocol is highly usable for a human user. Second, we present novel schemes for sharing sensitive information among distributed mobile hosts in MSN which preserves user privacy, where the users neither need to fully trust each other nor rely on any central trusted party. Third, to realize owner-controlled sharing of sensitive data stored on untrusted servers, we put forward a data access control framework using Multi-Authority Attribute-Based Encryption (ABE), that supports scalable fine-grained access and on-demand user revocation, and is free of key-escrow. Finally, we propose mechanisms for authorized keyword search over encrypted data on untrusted servers, with efficient multi-dimensional range, subset and equality query capabilities, and with enhanced search privacy. The common characteristic of our contributions is they minimize the extent of trust that users must place in the corresponding network or computing environments, in a way that is user-centric, i.e., favoring individual owners/users."

Semantic interoperability within the health care sector requires that patient data be fully available and shared without ambiguity across participating health facilities. The need for the current research was based on federal stipulations that required health facilities provide complete and optimal care to patients by allowing full access to their health records. The ongoing discussions to achieve interoperability within the health care industry continue to emphasize the need for healthcare facilities to successfully adopt and implement Electronic Health Record (EHR) systems. Reluctance by the healthcare industry to implement these EHRs for the purpose of achieving interoperability has led to the current research problem where it was determined that there is no existing single data standardization structure that can effectively share and interpret patient data within heterogeneous systems. The current research used the design science research methodology (DSRM) to design and develop a master data standardization and translation (MDST) model that allowed seamless exchange of healthcare data among multiple facilities. To achieve interoperability through a common data standardization structure, where multiple independent data models can coexist, the translation mechanism incorporated the use of the Resource Description Framework (RDF). Using RDF, a universal exchange language, allowed for multiple data models and vocabularies to be easily combined and interrelated within a single environment thereby reducing data definition ambiguity. Based on the results from the research, key functional capabilities to effectively map and translate health data were documented. The research solution addressed two primary issues that impact semantic interoperability – the need for a centralized standards repository and a framework that effectively maps and translates data between various EHRs and vocabularies. Thus, health professionals have a single interpretation of health data across multiple facilities which ensures the integrity and validity of patient care. The research contributed to the field of design science development through the advancements of the underlying theories, phases, and frameworks used in the design and development of data translation models. While the current research focused on the development of a single, common information model, further research opportunities and recommendations could include investigations into the implementation of these types of artifacts within a single environment at a multi-facility hospital entity.

Medication errors increased 64.4% from 2015 to 2018 in the United States due to the use of computerized physician order entry (CPOE) systems and the inability to exchange information among health care facilities. Healthcare information exchange (HIE) and subsequent discrepancies resulted in significant medical errors due to the lack of exchangeable health care information using technology software. The purpose of this qualitative multiple case study was to explore the strategies health care business managers used to manage computerized physician order entry systems within health care facilities to reduce medication errors and increase profitability. The population of the study was 8 clinical business managers in 2 successful small health care clinics located in the mid-Atlantic region of the United States. Data were collected from semistructured interviews with health care leaders and documents from the health care organization as a resource. Inductive analysis was guided by the Donabedian theory and sociotechnical system theory, and trustworthiness of interpretations was confirmed through member checking. Three themes emerged: standardizing data formats reduced medication errors and increased profits, adopting user-friendly HIE reduced medication errors and increase profits, and efficient communication reduced medication errors and increased profits. The findings of this study contribute to positive change through improved health care delivery to patients resulting in healthier communities.

Health care leaders lack the strategies to implement cloud security for electronic medical records to prevent a breach of patient data. The purpose of this qualitative case study was to explore strategies senior information technology leaders in the healthcare industry use to implement cloud security to minimize electronic health record cyberattacks. The theory supporting this study was routine activities theory. Routine activities theory is a theory of criminal events that can be applied to technology. The study's population consisted of senior information technology leaders from a medical facility in a large northeastern city. Data collection included semistructured interviews, phone interviews, and analysis of organizational documents. The use of member checking and methodological triangulation increased the validity of this study's findings among all participants. There were 5 major themes that emerged from the study (a) requirement of coordination with the electronic health record vendor and the private cloud vendor, (b) protection of the organization, (c) requirements based on government and organizational regulations, (d) access management, (e) a focus on continuous improvement. The results of this study may create awareness of the necessity to secure electronic health records in the cloud to minimize cyberattacks. Cloud security is essential because of its social impact on the ability to protect confidential data and information. The results of this study will further serve as a foundation for positive social change by increasing awareness in support of the implementation of electronic health record cloud security.

In November 2012 Uppsala County Council (UCC) introduced an eHealth service, ‘My Health Record’, that gives all inhabitants over age 18 in Uppsala County access to their health records online. However, this service has not been evaluated before this study. We conducted an interview study, based on User Experience (UX) and Patient empowerment, with users of ‘My Health Record’ to get their opinions, and to see if and how the service can be improved. Our findings shows that the users are positive to the service and the aspects that can be improved mostly concern information and communication. Based on these results, we propose design principles as well as concrete design proposals which can be useful for re-designing the service as well as inspiration for similar projects. Additionally, an interesting finding is that the interviewees had very few opinions and complains on the actual interface, which could mean that the content (the health record) is so interesting that the interface becomes almost “invisible”. A conclusion we make is that UX and Patient empowerment is a good fit for each other, and that UX has advantages over traditional usability in services like this.

Distributional semantics allows models of linguistic meaning to be derived from observations of language use in large amounts of text. By modeling the meaning of words in semantic (vector) space on the basis of co-occurrence information, distributional semantics permits a quantitative interpretation of (relative) word meaning in an unsupervised setting, i.e., human annotations are not required. The ability to obtain inexpensive word representations in this manner helps to alleviate the bottleneck of fully supervised approaches to natural language processing, especially since models of distributional semantics are data-driven and hence agnostic to both language and domain. All that is required to obtain distributed word representations is a sizeable corpus; however, the composition of the semantic space is not only affected by the underlying data but also by certain model hyperparameters. While these can be optimized for a specific downstream task, there are currently limitations to the extent the many aspects of semantics can be captured in a single model. This dissertation investigates the possibility of capturing multiple aspects of lexical semantics by adopting the ensemble methodology within a distributional semantic framework to create ensembles of semantic spaces. To that end, various strategies for creating the constituent semantic spaces, as well as for combining them, are explored in a number of studies. The notion of semantic space ensembles is generalizable across languages and domains; however, the use of unsupervised methods is particularly valuable in low-resource settings, in particular when annotated corpora are scarce, as in the domain of Swedish healthcare. The semantic space ensembles are here empirically evaluated for tasks that have promising applications in healthcare. It is shown that semantic space ensembles – created by exploiting various corpora and data types, as well as by adjusting model hyperparameters such as the size of the context window and the strategy for handling word order within the context window – are able to outperform the use of any single constituent model on a range of tasks. The semantic space ensembles are used both directly for k-nearest neighbors retrieval and for semi-supervised machine learning. Applying semantic space ensembles to important medical problems facilitates the secondary use of healthcare data, which, despite its abundance and transformative potential, is grossly underutilized. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4 and 5: Unpublished conference papers.</p> / High-Performance Data Mining for Drug Effect Detection

Racial/ethnic disparities in cancer care are well documented in the research literature; however, less is known about the extent and potential source of cancer care disparities in the Veterans Health Administration (VA). In my first paper, I use logistic regression and hospital fixed effects models to examine racial disparities in 20 cancer-related quality measures and the extent to which racial differences in site of care explain VA cancer care disparities. I found evidence of racial disparities in 7 out of 20 cancer-related quality measures. In general, these disparities were primarily driven by racial differences in care for black and white patients within the same VA hospital, rather than racial differences in site of care.

Despite rapid advances in technology, there is currently a complex, and somewhat disjointed approach to the way health information is collected, stored, and organized for both healthcare consumers and professionals. Incompatible electronic medical records from various healthcare providers add to the complexity of a system tasked with delivering a patient’s relevant medical information in a timely manner to the appropriate point of care. Personal health records (PHR) grew out of the efforts to produce an integrated electronic record to manage the multifaceted aspects of healthcare required by both healthcare consumers and professionals. PHRs are a transformative technology with the potential to alter patient-provider relationships in a way that produces a more efficient and cost effective healthcare system as a result of better patient outcomes. PHRs can potentially include a wide variety of users ranging from the lay public to clinical professionals. As such, it is important to identify potential user groups and their corresponding health information needs in order to design PHRs that maximize accessibility, usability, and clinical relevance. This study focused on laypeople who represented a wide age-range of individuals, evenly split in gender, with an above average level of computer literacy. Most of the participants had not used an electronic PHR prior to this study. However, after a hands-on session with PHR software, most participants found it to be easy to use, accompanied with the functionality they expected from such a system. Most participants were satisfied that an electronic PHR would meet their health information needs and would recommend the use of PHRs to family and friends. Anyone in the general public is a potential PHR user. However, this study found that individuals with chronic conditions and those with complex health needs had the most to gain from using a PHR as an integral part of their healthcare routine. This study also demonstrated that an individual’s health condition has a stronger influence on their perceptions about the usefulness of PHRs than does their demographic background (age, education, computer literacy). Finally, this study established that PHRs are considered by participants of the study to be useful tools in meeting their health information needs. / Graduate / 0723 / 0769 / 0984 / dguarin@uvic.ca

Background: UK primary care accounts for 90% of patient contacts in the NHS, and over 300 million consultations every year. Consequently, when primary is suboptimal it has important impacts on population health. At the same time, virtually all general practices use electronic health records (EHR) to capture patient data. Clinical Decision Support (CDS) systems use it to highlight when individual patients do not receive care consistent with clinical guidelines, though ignore the wider population. Electronic Audit and Feedback (e-A&F) systems address the wider population, but their results are difficult to interpret. EHR data has the richness to suggest ways in which care quality could be improved, though this is currently not exploited. The aim of this thesis was to make progress towards better use of primary care EHR data for the purposes of quality improvement (QI) by focusing on e-A&F as a vehicle. Research Objectives were: 1) Develop a model and recommendations to guide EHR data analysis and its communication to health professionals; 2) Use these models and recommendations to develop a system for UK primary care; 3) Implement and evaluate the system to test the models and recommendations, and derive generalisable knowledge. Methods: The overall approach of this thesis was informed by guidance from the Medical Research Council on the development of complex interventions, and Boyrcki et al.’s evidence-based framework for the development of health information technologies (Chapter 2). Theory was first identified through a critical examination of the empirical and theoretical literature regarding CDS and e-A&F systems (Chapter 3), then built upon in a systematic literature search and metasynthesis of qualitative studies of A&F (and e-A&F) interventions (Chapter 4). This resulted in the development a new theory of A&F (Clinical Performance Feedback Intervention Theory; CP-FIT), which was used to inform the development of an e-A&F system for UK primary care – the Performance Improvement plaN GeneratoR (PINGR; version 1). PINGR was then iteratively optimised through a series of three empirical studies. First, its usability was evaluated by software experts using Heuristic Evaluation and Cognitive Walkthrough methodologies (Chapter 5). GPs then performed structured tasks using the system in a laboratory whilst their on-screen interactions and eye movements were recorded (Chapter 6). Finally, PINGR was implemented in 15 GP practices, and CP-FIT used to guide the mixed methods evaluation including examinations of usage records, and interviews with 38 health professionals. Results: There are both empirical and theoretical arguments for combining features from CDS and e-A&F systems to increase their effectiveness; a key recommendation is that e-A&F systems should suggest clinical actions to health professionals (Chapter 3). This is supported by CP-FIT, which has three core propositions: 1) A&F interventions exert their effects through health professionals taking action; 2) Health care organisations have limited capacity to engage with A&F; and 3) Health care professionals and organisations have a strong set of beliefs and behaviours regarding how they provide patient care (Chapter 4). Based on these findings, the unique feature of PINGR is that it suggests improvement actions to users based on EHR data analysis (‘decision-supported feedback’). Key findings from PINGR’s usability evaluation with software experts translated into a set of design guidelines for e-A&F interfaces regarding: summarising clinical performance, patient lists, patient-level information, and suggested actions (Chapter 5). When tested with GPs, these guidelines were found to impact: user engagement; actionability; and information prioritisation (Chapter 6). Following its implementation in practice, PINGR was used on 227 occasions to facilitate the care of 725 patients. These patients were 1.8 (95% CI 1.6-1.9) times more likely to receive improved care according to at least one clinical guideline. Barriers and facilitators to its success included: the resources available to use it; its perceived relative advantages; how compatible it was with pre-existing beliefs and ways of working; the credibility of its data; the complexity of the clinical problems it highlighted; and the ability to act on its recommendations (Chapter 7). Conclusion: It is both feasible and acceptable to health professionals to make better use of EHR data for QI by enabling e-A&F systems to suggest actions for them to take. When designing e-A&F interfaces, attention should be paid to how they summarise clinical performance, and present patient lists and detailed patient-level information. Implementation of e-A&F interventions is influenced by availability of resources, compatibility with existing workflows, and ability to take action based on their feedback results. Unresolved tensions exist regarding how they may deal with patient complexity. Policymakers should consider the relevance of these findings for National Clinical Audits and pay-for-performance initiatives.