O processamento automático de dados hospitalares tem uma grande importância nas tomadas de decisão em ambientes de saúde. Gestores e profissionais dessa área podem utilizar ferramentas e sistemas de informação que facilitem a visualização e análise destes dados. Neste sentido, o objetivo deste trabalho foi propor uma metodologia de análise que auxiliasse estes profissionais da saúde na gerência de dados hospitalares. Particularmente, esta nova abordagem foi o estudo e a inserção de uma estatística de segunda ordem, que é o caso da competição entre hospitais, no Portal Web do Observatório Regional de Atenção Hospitalar, que tem como objetivo divulgar informações estatísticas de assistência hospitalar. Para isso, foi desenvolvida uma ferramenta para expressar a competitividade entre dois hospitais a partir da medida de Aproximação Relacional proposta por Min-Woong Sohn. Os resultados mostraram que a ferramenta desenvolvida não só permitiu que fosse realizada uma classificação dos hospitais do DRS-XIII com relação à força competitiva exercida por cada um deles no mercado hospitalar, como ainda possibilitou uma maior exploração da medida proposta por Sohn. Isso se deve ao fato da ferramenta disponibilizar aos usuários um conjunto de filtros que permitem a realização de diversas consultas em tempo real. Essa característica contribuiu para a identificação de importantes fenômenos que não seriam reconhecidos no método tradicional. / The automatic processing in hospital data has great significance in making decisions at healthcare environments. Managers and professionals in this area can use tools and information systems to facilitate the view and analyze of these data. In this context, the intent of this study was to propose a methodology of analysis to support healthcare professionals in the management of hospital data. Particularly, this new approach was the study and the inclusion of a second order statistic, which is the case of competition among hospitals, in the Web Portal of the Regional Observatory of Hospital Care (Observatório Regional de Atenção Hospitalar - ORAH), which aims to disseminate statistical information of hospital care. For this, we developed a tool to express the competition among two hospitals using the measurement Relational Approach proposed by Min-Woong Sohn. The results showed that the developed tool not only allowed a classification of DRS-XIII hospitals about competitive force exerted by each of them in the hospital market, but also allowed greater exploitation of the measure proposed by Sohn. This is because the tool provide users a list of filters that allow you to perform several queries in real time. This characteristic has contributed to the identification of important phenomena that would not be recognized in the traditional method.

abstract: Blockchain technology enables a distributed and decentralized environment without any central authority. Healthcare is one industry in which blockchain is expected to have significant impacts. In recent years, the Healthcare Information Exchange(HIE) has been shown to benefit the healthcare industry remarkably. It has been shown that blockchain could help to improve multiple aspects of the HIE system. When Blockchain technology meets HIE, there are only a few proposed systems and they all suffer from the following two problems. First, the existing systems are not patient-centric in terms of data governance. Patients do not own their data and have no direct control over it. Second, there is no defined protocol among different systems on how to share sensitive data. To address the issues mentioned above, this paper proposes MedFabric4Me, a blockchain-based platform for HIE. MedFabric4Me is a patient-centric system where patients own their healthcare data and share on a need-to-know basis. First, analyzed the requirements for a patient-centric system which ensures tamper-proof sharing of data among participants. Based on the analysis, a Merkle root based mechanism is created to ensure that data has not tampered. Second, a distributed Proxy re-encryption system is used for secure encryption of data during storage and sharing of records. Third, combining off-chain storage and on-chain access management for both authenticability and privacy. MedFabric4Me is a two-pronged solution platform, composed of on-chain and off-chain components. The on-chain solution is implemented on the secure network of Hyperledger Fabric(HLF) while the off-chain solution uses Interplanetary File System(IPFS) to store data securely. Ethereum based Nucypher, a proxy re-encryption network provides cryptographic access controls to actors for encrypted data sharing. To demonstrate the practicality and scalability, a prototype solution of MedFabric4Me is implemented and evaluated the performance measure of the system against an already implemented HIE. Results show that decentralization technology like blockchain could help to mitigate some issues that HIE faces today, like transparency for patients, slow emergency response, and better access control. Finally, this research concluded with the benefits and shortcomings of MedFabric4Me with some directions and work that could benefit MedFabric4Me in terms of operation and performance. / Dissertation/Thesis / Masters Thesis Computer Engineering 2020

Magister Commercii (Information Management) - MCom(IM) / In South Africa, public health facilities provide free antiretroviral treatment (ART) mainly via primary healthcare (PHC) nurses. To streamline data collection an electronic HIV information system (TIER.Net), was introduced in 2010. Data originates in paper-based records completed by clinicians with the data from these paper systems then being captured into TIER.Net by clerical data capturers. TIER.Net is designed to effectively monitor outcomes of the ART programme and generate information for planning, management and decision making. For Enock Mgijima subdistrict to attain these functions, it is imperative that data collected at the 21 PHC facilities in the sub-district be of good quality. There has been uncertainty around the quality levels of the data collected through the paper records and TIER.Net, and it was unclear which factors promote or inhibit improved data quality.

The Live Well Springfield (LWS) movement is a collaborative effort of partner organizations in Springfield, Massachusetts. The project promotes healthy living by increasing knowledge and awareness of food and physical activity. A key LWS strategy was the creation of a website to function as an information hub. In addition to local event and health information, the website features 16 narratives depicting residents practicing healthy lifestyle choices, designed to encourage community engagement. To date, there has been no evaluation of the website’s reach and effect. A mixed methods approach, surveys and focus group discussions, was designed to collect data from people who live, work, or attend school in Springfield. Focus group participants were recruited in person at Springfield Community College, via recruitment posters (distributed at STCC), and through email requests from a previously compiled list of residents willing to be contacted. A website evaluation survey was developed using eHealth research constructs and the Expectation-Confirmation Model (ECM). This survey measured users’ perceived quality and satisfaction with the website. The survey was accessible via the livewellspringfield.org homepage, the LWS Facebook page, and emailed directly to potential respondents. The validated eHealth Literacy Scale (eHEALS) was incorporated into the survey and focus group sessions to assess self-reported skills for using eHealth resources. Each hour-long focus group (n=5 and n=6, respectively) was video/audio recorded and fully transcribed. Focus group transcripts were analyzed to thematically organize responses to narratives and fact-based health messages and assess the appeal, relevance, effectiveness, perceived purpose, and appropriateness. Survey data was analyzed to produce frequencies, descriptive statistics, and correlations. A mean eHEALS score of 4.22 of 5.00 (SD=0.83) was calculated from 36 responses, suggesting this sample felt very knowledgeable and confident using eHealth resources. Health Literacy Advisor (HLA) software was used to analyze an aggregate of all narratives, resulting in a Fry-based reading grade level of 8.4. On a five-point Likert scale, mean satisfaction with the website was 4.71 (SD=0.53), and mean likelihood to return was 4.76 (SD=0.51). Content analysis of focus group transcripts resulted in 184 responses coded for one or more themes. The largest proportion of responses (40.2%) related to effectiveness. One third of these effectiveness-related responses were negative toward the fact-based examples. Although the narratives were greatly preferred in both groups, all respondents made comments or agreed with suggestions to have both affective narratives and strictly fact-based health messages accessible, regardless of initial preferences. Results and interpretations will be reported to LWS partners to inform potential revisions of the website revisions and contribute to ongoing activities of the LWS initiative.

Health information networks continue to expand under the Affordable Care Act yet little research has been done to query and analyze multiple patient populations in parallel. Differences between hospitals relating to patient demographics, treatment approaches, disease prevalences, and medical coding practices all pose significant challenges for multi-site analysis and interpretation. Furthermore, numerous methodological issues arise when attempting to analyze disease association in heterogeneous health care settings. These issues will only continue to increase as greater numbers of hospitals are linked. To address these challenges, I developed the Shared Health Research Informatics Network (SHRINE), a distributed query and analysis system used by more than 60 health institutions for a wide range of disease studies. SHRINE was used to conduct one of the largest comorbidity studies in Autism Spectrum Disorders. SHRINE has enabled population scale studies in diabetes, rheumatology, public health, and pathology. Using Natural Language Processing, we de-identify physician notes and query pathology reports to locate human tissues for high-throughput biological validation. Samples and evidence obtained using these methods supported novel discoveries in human metabolism and paripartum cardiomyopathy, respectively. Each hospital in the SHRINE network hosts a local peer database that cannot be overridden by any federal agency. SHRINE can search both coded clinical concepts and de-identified physician notes to obtain very large cohort sizes for analysis. SHRINE intelligently clusters phenotypic concepts to minimize differences in health care settings. I then analyzed a statewide sample of all Massachusetts acute care hospitals and found diagnoses codes useful for predicting Acute Myocardial Infarction (AMI). The AMI association methods selected 96 clinical concepts. Manual review of PubMed citations supported the automated associations. AMI associations were most often discovered in the circulatory system and were most strongly linked to background diabetic retinopathy, diabetes with renal manifestations, and hypertension with complications. AMI risks were strongly associated with chronic kidney failure, liver diseases, chronic airway obstruction, hemodialysis procedures, and medical device complications. Learning the AMI associated risk factors improved disease predictions for patients in Massachusetts acute care hospitals.

The goal of this study was to determine relationships between health information behaviors and population health as well as their relationships with particular facets of urban ecology.

Includes bibliographical references / Problem Statement: The use of mobile technology in health (mHealth) has been ascribed as transformative power in the health systems of the developing countries, especially for improving healthcare delivery in rural areas. However, the full potential of mHealth has not been realised and there is a dearth of evidence on effectiveness and impact. This has limited informed policy-making, affecting the buy-in from investors and policy makers, and limiting adoption and scaling up of mHealth interventions that could benefit rural communities. Purpose of the research: The main objective of this study was to examine how mHealth interventions contribute to maternal health outcomes in a developing country context, at a micro level. The specific aims were to examine how mHealth outcomes for maternal health consumers in rural communities are produced and how variations in outcomes can be explained. Design/methodology/approach: The study adopted a critical realism approach, and drew on Capability Approach as a theoretical lens, with the aim to explain how and why mHealth interventions work in maternal health, for whom, and in what circumstances; by analysing patterns between context, mechanisms and outcomes. Data for this research was obtained through semi-structured interviews with users of mHealth in maternal healthcare in Malawi, and various project stakeholders. Project documents were also used as secondary data. Findings: mHealth interventions may affect maternal health outcomes and service delivery through multiple mechanisms. Three different types of mechanisms were found to produce mHealth outcomes for women in maternal health. These were: Technology adoption mechanisms that led to the uptake and adoption of mHealth services in maternal health; agential mechanisms that facilitated agency of consumers in achieving health goals; and health system mechanisms for realisation of desired health outcomes. A myriad of personal, sociocultural, and environmental factors either activated or inhibited the mechanisms, resulting invaried outcomes for the women. Originality/contribution: mHealth as a complement to existing maternal health services can lead to improvement in consumer behaviour and experiences, and even clinical outcomes. This research has highlighted a pathway through which mHealth outcomes are produced for consumers in maternal health. This process starts from mHealth acceptance and adoption as a technology by the consumers; to women acting as agents of their own health by utilising the opportunities generated by mHealth; and finally health system efficiencies for provision of adequate care to the women. This understanding of how mHealth works in maternal health can improve design and operations of such interventions for effectiveness that may lead to the realisation of its full potential.

Magister Commercii (Information Management) - MCom(IM) / In the past, the Western Cape Department of Health had no formal or technologically enabled system for patient administration. This resulted in an administrative burden, increased waiting times for patients and doctors who needed results back from other sections, and missing patient files within the community health institutions such as clinics and hospitals. The Primary Healthcare Information System (PHCIS) was developed to solve this problem. However, it was later discovered that even though the PHCIS had been installed across the Western Cape clinics, there was a limited adoption and use of the PHCIS. Hence, the aim of this study was to investigate the factors that hinder the adoption and use of PHCIS by healthcare workers in the public healthcare clinics in the Khayelitsha sub-district in the Western Cape Province

This paper aims to describe health information seeking behaviour and identify its associated factors among undergraduate university students in developing countries. An online survey is used to collect data from 138 students. The data is analysed using the multivariate logistic regression analysis method. Results reveal that a substantial number of students have sought health information mostly from the Internet. Health literacy, perceived susceptibility to health problems and alcohol consumption are found to be the significant factors influencing health information seeking behaviour. Results provide an understanding of health information seeking behaviour in developing countries.

Background: Health information system (HIS) performance has been defined as “data quality and the continuous use of information †. The quality of data, as well as the culture of data use in an organisation has been shown to shape the way data is used. In order to fully understand data use practices with the aim of strengthening the HIS, one needs to first understand whether the context and “culture†in the organisation is conducive to data use. Are the policies, structures, processes and people within the organisation aiding data use? In what ways do managers view and use data? Aim: In this study, we sought to explore the culture of health information use on a district and sub district management level. The aim was to contribute to the wider knowledge on information use by exploring the data use practices and factors that shape its use among these managers. What is the culture of data use in the district management structures? When, why and in what way does data get brought into the management discussion? Do managers feel that the information produced are useful in aiding their decision making, and what do they recommend be changed? What are the key factors that affect data use practices? Methods: This thesis comprises a literature review of published articles, conducted in order to provide context for the study of the culture of data use, whilst defining the problem to be investigated. The full thesis comprises the literature review, the original study protocol, a full manuscript in the format of a publishable article and a set of appendices. The study was granted ethical approval and permission from the provincial department of health. Given the exploratory purpose of the study, we conducted a mini ethnographic case study using qualitative research methods in a rural health district of the Western Cape Province of South Africa. The researcher employed ethnographic methods that included participant observation, in depth key informant interviews, document reviews as well as informal conversations to collect data. We used the PRISM framework as a guide for analysing our findings. Findings: Our findings suggest that there is a strong focus in this district on reporting requirements and technical aspects of producing good quality data. The drive to achieve excellence in production of quality data may be in tension with another important organisational value, which is the need of managers, for ease of access to relevant data, to facilitate decision-making and improvement of health service delivery. Managers’ overall experience is of not receiving the health information support they require. Instead, they experienced an organisational culture of using health information to narrowly measure targets and performance, which left them feeling unsupported and frustrated. Managers were resilient in managing these challenges and created alternative ways of accessing the data they needed for decision-making. Conclusion: We conclude that in our setting where the technical component of producing good data was well performed, this was not sufficient to guarantee effective use of data for quality improvements. Behavioural and organisational factors were found to play an important role as both obstacles and facilitators in shaping the culture of data use, information that is useful to inform design of interventions for health information strengthening.