The purpose of this study was to explore and describe staff experiences in managing data and/or information when utilising the District Health Information System (DHIS) as a support mechanism for data quality improvement, including the strengths and weaknesses of current data management processes. It was also aimed to identify key barriers and to make recommendations on how data management can be strengthened. Key informants included in this study were those based at the district office (health programme managers and information officers) and at the primary health care (PHC) facilities (facility managers, clinical nurse practitioners and data capturers). An exploratory, descriptive and generic qualitative study was conducted. Consent was requested from each participant. Data were collected through semi-structured interviews. The study findings highlighted strengths, weaknesses and key barriers as experienced by the staff. Strengths, such as having data capturers and DHIS software at most if not all facilities, were highlighted. The weaknesses and key barriers highlighted were staff shortages of both clinical and health management information staff (HMIS), shortage of resources such as computers and Internet access, poor feedback, training needs and data quality issues. Most of the weaknesses and key barriers called for further and proper implementation of the District Health Management Information Systems (DHMIS) policy, the standard operating procedures (SOP), the eHealth strategy and training of the staff, due to the reported gaps between the policy and the reality and/or practice at the facility / Health Studies / M. A. (Public Health with specialisation in Medical Informatics)

Made available in DSpace on 2011-05-04T12:36:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2009 / Essa dissertação projeta um ambiente tecnológico para o compartilhamento de conhecimentos entre profissionais de tecnologia da informação em saúde do quadro efetivo do DATASUS. Tomando como ponto de partida a teoria da criação do conhecimento organizacional apresentada por Ikujiro Nonaka e Hirotaka Takeuchi, examina as contribuições teóricas e filosóficas de autores com trajetória no campo da filosofia, da gestão empresarial e/ou administração de negócios, e das tecnologias da informação e comunicação, elucidando as relações que se estabelecem entre organização, conhecimento e aprendizagem em rede no contexto complexo das atividades de gestão pública e privada - na contemporaneidade. O modelo proposto fundamenta-se em dois pressupostos principais: i) que a conversão do conhecimento tácito, existente nas organizações, em conhecimento explícito é uma dimensão da gestão do conhecimento fundamental para a qualidade das inovações; e, ii) que um ambiente tecnológico de apoio à interação intelectual entre os profissionais de uma organização potencializa a sua capacidade de inovação e a eficiência organizacional. Colocando em interação quem sabe, com quem quer saber ou com quem quer saber mais, o modelo permite a gestão do conhecimento relativo aos diversos assuntos de domínio do DATASUS, permitindo que os profissionais resolvam em conjunto os problemas de manutenção e desenvolvimento de sistemas de informação, debatendo e disponibilizando este conhecimento. Para a construção do ambiente tecnológico são utilizados conceitos e ferramentas relativos à introdução da web 2.0 de forma a proporcionar facilidade e agilidade à troca de conhecimento entre os membros componentes e a apoiar a gestão de conhecimento no DATASUS. / The present work designs a technological environment for knowledge sharing among professionals in technology of information in health in the effective DATASUS framework. Taking as its starting point the theory of organizational knowledge creation by Ikujiro Nonaka and Hirotaka Takeuchi, examines the theoretical contributions - and philosophical - from authors well known in the field of philosophy, business management and/or business administration and information and communication technology. This dissertation elucidates the relationships established among organization, knowledge and learning network in the context of a complex management activities - public and private - in the contemporary world. The proposed model is based on two key assumptions: i) the conversion of tacit knowledge, existing in organizations, in explicit knowledge is a dimension of knowledge management essential to the quality of innovations; and, ii) a technological environment to support intellectual interaction among professionals in an organization enhances its ability to innovate and the organizational effectiveness. Interacting “Who knows” with “Who wants to know” or “who wants to know more”, the model allows the management of knowledge regarding various matters of DATASUS domain, allowing professionals to solve together the problems of maintenance and development of information systems, discussing and providing this knowledge. For the construction of the technological environment it was use concepts and tools related to the introduction of the web 2.0 in order to provide easy and speed to the exchange of knowledge among the constituents members and support the management of knowledge in DATASUS.

Philosophiae Doctor - PhD / A review of the literature has shown that there is a lack of mental health information on which to base planning of mental health services and decisions concerning programme development for mental health services. Several studies have indicated that the use of an evidence-based health information system (HIS) reduces inappropriate clinical practices and promotes the quality of health care services. This study was aimed at developing a framework for a district-based mental health information management system, utilising the experiences of health care providers and caregivers about a district mental health information system (DMHIS). Activity Theory was used as the philosophical foundation of the information system for the study. A qualitative approach was employed using semi-structured individual interviews, Focus Group Discussions (FGDs), systematic review and document analysis. The intervention research design and development model of Rothman and Thomas (1994) was used to guide the study, which was conducted in the Cape Town Metropole area of the Western Cape. A purposive, convenient sampling method was employed to select study participants. Ethical clearance for the study was obtained from the University of the Western Cape, and permission to use the health facilities from the Department of Health. The data collection process involved 62 individual interview participants, from mental health nurses to district health managers, health information clerks, and patient caregivers/families and persons with stable mental conditions. Thirteen caregivers took part in the FGDs. Document review was conducted at three community mental health centres. The data were analysed manually using content analysis. Core findings of the interviews were lack of standardized information collection tools and contents for mental health, information infrastructure, capacity building, and resources. Information processing in terms of collection, compiling, analysing, feedback, access and sharing information were the major problems. Results from document analysis identified inconsistencies and inaccuracies of information recording and processing, which in turn affected the quality of information for decision making. Results from the systematic review identified five functional elements: organizational structure; information infrastructure; capacity building; inputs, process, output and feedback; and community and stakeholders’ participation in the design and implementation of a mental health information system (MHIS). The study has contributed a framework for a DMHIS based on the findings of the empirical and systematic review. It is recommended that there is a need to establish a HIS committee at district health facility level for effective implementation of the framework and quality information processing. There is a need to ensure that staffs have adequate knowledge and skills required for effective implementation of an information system. It is recommended that higher education institutions include a course on HISs in their curriculum. It is suggested that the South African Mental Health Policy be reviewed to include an MHIS and ensure involvement of the community and stakeholders in this system as well as adequate budget allocation.

This diploma thesis deals with the application of the information literacy concept in the healthcare, focusing on patients' information literacy development. Firstly, the Czech and U. S. model of health care system are briefly introduced with regard to their different impact on patiets' active participation in health care. Subsequently, preconditions for the emergence and development of the concept of health information literacy are described with emphasis on the terminology. The core of the thesis is focused on the description, analysis, and evaluation of selected activities of U. S. professional associations and organisations. The last part is aimed at selection of the appropriate activity for implementation in the Czech context and at the survey in the selected Czech professional libraries, which is oriented at the state of activities for information literacy development and implementation of selected activity.

<p>Chronic low back pain is the second most prevalent chronic condition in Canadian primary care settings. The treatment and diagnosis of chronic pain is challenging for primary care clinicians. Their main challenges are lack of knowledge and their approach toward assessing and treating pain. Evidence based guidelines have been developed for neuropathic pain and low back pain.</p> <p>CDSSs for chronic diseases are becoming popular in primary care settings as a mean to implement CPGs. A CDSS prototype for diagnosis and treatment of chronic, non-cancer pain in primary care was developed at McMaster University. It is evident that poor usability can hinder the uptake of health information technologies.</p> <p>The objective of this study was to test the usability of Pain Assistant using think aloud protocols with SUS scores in 2 iterations. In this study 13 primary care providers including family physicians, nurse practitioners and residents used Pain Assistant to complete 3 different patient case scenarios. Participants were asked to comment on both barriers and facilitators of usability of Pain Assistant. Additionally time to complete patient case scenarios was calculated for each participant. A comparison questionnaire gathered user preference between introducing CPGs in paper format and computerized decision support system.</p> <p>This study showed that iterative usability testing of the Pain Assistant with participation of real-end users has the potential to uncover usability issues of the Pain Assistant. Problems of user interface were the main usability barrier in first testing iteration following by problems of content. Changes were made to system design for second round based on the issues came up in the first iteration. However, because of time constrains not all the changes were implemented for second round of testing. Most of the refinements were to resolve user interface issues. In the second iteration, the problems with the content of Pain Assistant were the major barrier. The changes to the system design were successful in resolving user interface problems since the changed issues did not come up again in second round. Pain Assistant had an above the average usability score however no significant changes seen in SUS score. The time needed to complete tasks remained identical in both iterations. In addition, participants preferred to have CPGs in electronic formats than paper. Further study after implementing all the system changes needed to determine the effectiveness of system refinements.</p> / Master of Science (MSc)

In a landmark report, the Secretary of Health and Human Services once characterized the legacy of disparities in healthcare and health outcomes in the United States as “an affront to our ideals and the ongoing genius of American medicine.” Since then, a vast amount of scientific evidence regarding health equity has been generated and important interventions developed. Yet despite substantial concerted efforts, health inequity remains a persistent and pervasive public health concern. A significant challenge is the lack of scalable resources to organize, synthesize, and integrate knowledge gleaned from available scientific evidence and real-world observational data in a comprehensive, systematic fashion. Recognizing this, the National Institute on Minority Health and Health Disparities recently embarked on a science visioning process and enumerated a set of strategic goals to foster a new generation of research capable of making major strides. Among the strategies proposed, the institute promotes development of new methods and measurements that enable 1) evaluation of health equity research and ensuring its relevance to a diversity of populations, 2) better leveraging and fostering linkage between existing and emerging data sources to enhance analytic capacity, and 3) analysis of health determinants contributing to health disparities among subpopulations and small groups. In alignment with this vision, the studies presented in this thesis seek to advance health equity science by developing, applying, and evaluating informatics-based approaches to support evidence synthesis, monitoring, and precision. In particular, systematic, scalable, and sustainable (i.e., reproducible) approaches are emphasized. This dissertation employs robust methods for big data collection, integration, and analysis while drawing from a rich set of existing and emerging data sources including a large corpus of biomedical literature, electronic health records from the largest public health information exchange in the United States, open datasets provided by public agencies, proprietary national insurance claims datasets, and public health reporting data. The dissertation first aims to facilitate large-scale evidence synthesis to identify major areas of focus in health equity research and elucidate potentially less well studied populations, conditions, and topics. In order to accomplish these tasks, it draws from the informatics toolbox by leveraging machine learning, natural language processing, and symbolic reasoning to assess a vast portfolio of research and compare it to real-world data on condition prevalence. In doing so, it spotlights potential paths for additional scientific inquiry and attention in public health practice. Ultimately, we find that there are indeed potential disparities in disparities research and elucidate less well studied areas of interest. Building on these insights, this thesis then leverages underutilized real-world data sources (e.g., health information exchanges) and a common data model to buttress the highly fragmented and outdated public health data infrastructure currently used to monitor conditions of interest and elucidate potential disparities among populations. By intention, the illustrative example presented operates at a scale commensurate with current regional public health reporting, increases the number and types of data elements available for analysis, and improves turnaround time for surveillance report generation. We found a substantial lack of alignment between testing practices and population- and neighborhood-level trends in cases of sexually transmitted infections, signaling potential disparities and inefficient resource allocation. Thus, our work meets several hallmarks of infectious disease surveillance in the era of big data including volume, variety, velocity, and value, respectively. Importantly, these findings were not otherwise or less likely detectable given existing public health reporting practices. Finally, as existing health equity literature and public health surveillance practices do not often incorporate intersectionality as an integral lens for drawing comparisons, in large part due to the technical intractability of examining all possible demographic intersections, we demonstrate a novel subgroup discovery approach tailored to elucidating intersectional disparities in health outcomes. In doing so, it aims to better inform efforts to recognize and engage subgroups who might benefit from greater attention and more closely tailored interventions. To our knowledge, this new approach is the first to leverage supervised clustering to operationalize intersectionality for health disparities research. To ground this work, clinical examples focus especially on demonstrating application of each new approach to generalizable use cases involving HIV and other sexually transmitted infections – highly stigmatized conditions for which there is a long history of inequity.

Master of Science / Department of Journalism and Mass Communications / Joye C. Gordon / This experimental research adopts a typology of frames by Levin, Gaeth, and Schneider (1998) and seeks to a) determine what combination of attribute and goal frames produces the strongest effect on vaccination behavior; b) ascertain to what extent personal relevance of vaccination moderates this framing effect; and c) explore how individual pre-existing characteristics, such as recent vaccination history, vaccine risk perception, vaccine dread, and general attitude toward vaccination influence the persuasive power of framed messages. The study, designed as field experiment 2 (+/- attribute frame) x 2 (+/- goal frame) x 2(involvement), recruited 476 adult female participants that were exposed online to four experimental framing manipulations and a control condition. The main effect is consistent with the typology of frames — the combination of the positive attribute and the negative goal frame was the only condition that was significantly more persuasive than the control condition. Participants who had children or were pregnant, for whom vaccination was more relevant and meaningful, have not reacted to message framing differently. However, general pre-existing attitudes towards vaccines, perception of vaccine safety, perception of vaccine efficacy, vaccine dread, and vicarious experience with vaccine side effects, appear to be associated with antecedents of vaccination behavior. Overall, this study has focused on ecological validity,aiming at the applicability of framing theory in the context of health communication.

The purpose of this study was to show how information from the District Health Information System can be used to empower managers to make evidence-based decisions that will strengthen the health care system to reduce the under-five mortality rate. A quantitative, contextual, exploratory evaluative and descriptive approach was followed and a data extraction framework, based on systems theory, was developed to guide the process of extracting existing routine data. A results-based approach was used to measure under-five mortality related health care in terms of impact, outcomes, outputs, processes and inputs. The study has highlighted that proxy indicators obtained this way places health care managers in the position to monitor progress towards achieving the Millennium Development Goal for child mortality in the interim periods between large population surveys. The findings displayed in the diagnostic performance profile revealed that drastic interventions are required to reduce the under-five mortality rate. / Health Studies / M.A. (Health Studies)

The current dissertation provides an examination of health information technology (HIT) by analyzing big datasets. It contains two separate essays focused on: (1) the evolving intellectual structure of the healthcare informatics (HI) and healthcare IT (HIT) scholarly communities, and (2) the impact of social support exchange embedded in social interactions on health promotion outcomes associated with online health community use. Overall, this dissertation extends current theories by applying a unique combination of methods (natural language processing, machine learning, social network analysis, and structural equation modeling etc.) to the analyses of primary datasets. The goal of the first study is to obtain a full understanding of the underlying dynamics of the intellectual structures of HI and its sub-discipline HIT. Using multiple statistical methods including citation and co-citation analysis, social network analysis (SNA), and latent semantic analysis (LSA), this essay shows how HIT research has emerged in IS journals and distinguished itself from the larger HI context. The research themes, intellectual leadership, cohesion of these themes and networks of researchers, and journal presence revealed in our longitudinal intellectual structure analyses foretell how, in particular, these HI and HIT fields have evolved to date and also how they could evolve in the future. Our findings identify which research streams are central (versus peripheral) and which are cohesive (as opposed to disparate). Suggestions for vibrant areas of future research emerge from our analysis. The second part of the dissertation focuses on comprehensively understanding the effect of social support exchange in online health communities on individual members’ health promotion outcomes. This study examines the effectiveness of online consumer-to-consumer social support exchange on health promotion outcomes via analyses of big health data. Based on previous research, we propose a conceptual framework which integrates social capital theory and social support theory in the context of online health communities and test it through a quantitative field study and multiple analyses of a big online health community dataset. Specifically, natural language processing and machine learning techniques are utilized to automate content analysis of digital trace data. This research not only extends current theories of social support exchange in online health communities, but also sheds light on the design and management of such communities.

Radio frequency identification (RFID) technology is a useful technology that has myriad applications in technology, retail, manufacturing, and healthcare settings. Not dependent upon line-of-sight, RFID can scan devices in their proximity and report the information to connected (wired or other wireless) information systems. Once touted as the panacea for home healthcare, RFID devices can add benefit to patients in remote settings. RFID devices have been used to optimize systems in areas such as manufacturing and healthcare to expose inefficiencies in a system or process. Unlike manufacturing, however, RFID in healthcare settings presents security and privacy concerns to the people being tracked by the devices – particularly healthcare workers including nurses and doctors. This research presented a theoretical model that assessed the effect of five independent variables, namely, cognitive factors, of privacy concerns regarding surveillance and RFID devices and trust in the electronic medium, subjective norm, existence of security policy, and persistence of data on a dependent variable - intention to use RFID. The theoretical model presented in this research is based on the technology acceptance model and the extended theory of planned behavior. The research showed significant relationships between the cognitive factors of privacy concerns regarding surveillance and RFID devices, and trust and the electronic medium and perception of external control on intention to use. The theoretical model used in this research can be refined to better understand intention to use RFID in hospital environments.