Academic literature on the topic 'Health informatics'

Patient data in health care have traditionally been used to support direct patient care. Although there is great potential in combining such data with genetic information from patients to improve diagnosis and therapy decisions (i.e. personalized medicine) and in secondary uses such as data mining, this is complex to realize due to technical, commercial and legal issues related with combining and refining patient data. Clinical decision support systems (CDSS) are great catalysts for enabling evidence-based medicine in clinical practice. Although patient data can be the base for CDSS logic, it is often scattered among heterogenous data sources (even in different health care centers). Data integration and subsequent data mining must consider codification of patient data with terminology systems in addition to legal and ethical aspects of using such data. Although computerization of the patient record systems has been underway for a long time, some data is still unstructured. Investigation regarding the feasibility of using electronic patient records (EPR) as data sources for data mining is therefore important. Association rules can be used as a base for CDSS development. Logic representation affect the usability of the systems and the possibility of providing explanations of the generated advice. Several properties of these rules are relatively easy to explain (such as support and confidence), which in itself can improve end-user confidence in advice from CDSS. Information from information sources other than the EPR can also be important for diagnosis and/or treatment decisions. Drug prescription is a process that is particularly dependent on reliable information regarding, among other things, drug-drug interactions which can have serious effects. CDSS and other information systems are not useful unless they are available at the time and location of patient care. This motivates using mobile devices for CDSS. Information structures of interactions affect representation in informatics systems. These structures can be represented using a category theory based implementation of rough sets (rough monads). Development of guidelines and CDSS can be based on existing guidelines with connections to external information systems that validate advice given the particular patient situation (for example, previously prescribed drugs may interact with recommended drugs by CDSS). Rules for CDSS can also be generated directly from patient data but this assumes that such data is structured and representative. Although there is great potential in CDSS to improve the quality and efficiency of health care, these systems must be properly integrated with existing processes in health care (workflows) and with other information systems. Health care workflows manage physical resources such as patients and doctors and can help to standardize care processes and support management decisions through workflow simulation. Such simulations allow information bottle-necks or insufficient resources (equipment, personnel) to be identified. As personalized medicine using genetic information of patients become economically feasible, computational requirements increase. In this sense, distributing computations through web services and system-oriented workflows can complement human-oriented workflows. Issues related to dynamic service discovery, semantic annotations of data, service inputs/outputs affect the feasibility of system-oriented workflow construction and sharing. Additionally, sharing of system-oriented workflows increase the possibilities of peer-review and workflow re-usage.

This thesis developed new search engine models that elicit the meaning behind the words found in documents and queries, rather than simply matching keywords. These new models were applied to searching medical records: an area where search is particularly challenging yet can have significant benefits to our society.

There is a marked trend of using information technologies to improve healthcare. Among all the health IT, electronic health record (EHR) systems hold great promises as they modernize the paradigm and practice of care provision. However, empirical studies in the literature found mixed evidence on whether EHRs improve quality of care. I posit two explanations for the mixed evidence. First, most prior studies failed to account for system use and only focused on EHR purchase or adoption. Second, most existing EHR systems provide inadequate clinical decision support and hence, fail to reveal the full potential of digital health. In this dissertation I address two broad research questions: a) Does meaningful use of EHRs improve quality of care? and b) How do we advance clinical decision making through innovative computational techniques of healthcare analytics? To these ends, the dissertation comprises four essays. The first essay examines whether meaningful use of EHRs improve quality of care through a natural experiment. I found that meaningful use significantly improve quality of care, and this effect is greater in historically disadvantaged hospitals such as small, non-teaching, or rural hospitals. These empirical findings present salient practical and policy implications about the role of health IT. On the other hand, in the other three essays I work with real-world EHR data sets and propose healthcare analytics frameworks and methods to better utilize clinical text (Essay II), integrate clinical guidelines and EHR data for risk prediction (Essay III), and develop a principled approach for multifaceted risk profiling (Essay IV). Models, frameworks, and design principles proposed in these essays advance not only health IT research, but also more broadly contribute to business analytics, design science, and predictive modeling research.

In the light of an ageing society with shrinking economic resources, deinstitutionalization of elderly care is a general trend. As a result, homecare is increasing, and increasingly shared between different health and social care organizations. To provide a holistic overview about the patient care process, i.e. to be patient-centred, shared homecare needs to be integrated. This requires improved support for information sharing and cooperation between different actors, such as care professionals, patients and their relatives. The research objectives of this thesis are therefore to study information and communication needs for patient-centered shared homecare, to explore how integrated information and communication technology (ICT) can support information sharing, and to analyze how current standards for continuity of care and semantic interoperability meet requirements of patient-centered shared homecare. An action research approach, characterized by an iterative cycle, an emphasis on change and close collaboration with practitioners, patients and their relatives, was used. Studying one specific homecare setting closely, intersection points between involved actors and specific needs for information sharing were identified and described as shared information objects. An integration architecture making shared information objects available through integration of existing systems was designed and implemented. Mobile virtual health record (VHR) applications thereby enable a seamless flow of information between involved actors. These applications were tested and validated in the OLD@HOME-project. Moreover, the underlying information model for a shared care plan was mapped against current standards. Some important discrepancies were identified between these results and current standards for continuity of care, stressing the importance of evaluating standardized models against requirements of evolving healthcare contexts. In conclusion, this thesis gives important insights into the needs and requirements of shared homecare, enabling a shift towards patient-centered homecare through mobile access to aggregated information from current feeder systems and documentation at the point of need.

This research investigated the question of whether automatic or system-generated information classification methods can help humans better manage information. A series of four experiments were conducted; they investigated the usability (i.e., usefulness) of two automatic approaches to information classification, the concept space approach and a Kohonen-based SOM approach in the context of information retrieval. The concept space approach was evaluated in three different domains: Electronic Brainstorming (EBS) sessions, the Internet, and medical literature (the CancerLit collection). The Kohonen-based SOM approach was evaluated in the Internet and medical literature (CancerLit) domains only. In each case, the approach under investigation was compared with existing systems in order to demonstrate performance viability. The basic premise that information management, in particular information retrieval, can be successfully supported by system-based information classification techniques and that humans would find such techniques viable and useful was supported by the experiments. The concept space approach was more successful than the Kohonen-based SOM approach. After modifications to the algorithms based on user feedback from the EBS experiments had been made, users found the concept space approach results to be comparable (in the Internet study) or superior (in the CancerLit study) to existing information classification systems. The key future enhancement will be incorporation of better ways to identify document descriptors through syntactic and semantic front-end processing. The Kohonen-based SOM approach was considered difficult to use in all but one specialized case (the dynamic SOM created as part of the CancerLit prototype). This can probably be attributed to the fact that its associative organization does not match with the standard mental models (hierarchical and alphabetic) for information classification.

Personal informatics are important tools in health self-management as they support individuals to quantify and self-reflect on their lifestyle. Human-computer interaction researchers have devoted resources on studying how to design such tools. Various motivational strategies have been explored for their capabilities in improving user engagement. However, such strategies are developed with an assumption that the targeted consumer of information is the one directly manipulating user interfaces of the system that has information. This may not always be the case for users in developing regions. As a result, such systems may not scale well in contexts where a targeted consumer (beneficiary) may use technology through the facilitation of another person (intermediary) whom is responsible for manipulating user interfaces, because such facilitators are not recognized as part of the system, hence motivational strategies don't cater for them. In order to uncover design implications for intermediated technology use in the context of personal health informatics (PHI), the researcher started with the theoretical framing of the work followed by a contextual enquiry which led to development of mobile applications' prototypes for tracking nutrition and physical activity. Evaluation of the prototypes revealed that a familial relationship is a prerequisite for such an intervention. The most promising combination involves family members, possibly a child and a parent working together. The study used self-determination theory to understand how a collaborative gamified system can increase engagement. The result revealed that gamification as the source of a significant increase in perceived competence in intermediary users whom also tended to consider themselves as co-owners of the interaction experience. Therefore, gamification was found to be a catalyst for increasing collaboration between an intermediary and beneficiary user of technology, provided that the two users that formed a pair had a prior social relationship. In the absence of gamification, intermediary users tended to be less engaged in the intervention. The study highlights both the positive and negative aspects of gamification in promoting collaboration in intermediated use and its general implications in health settings. Design considerations required in order to improve the overall user experience of both users involved are proposed. In general, this work contributes to both theory and empirical validation of factors for, supporting proximate-enabled intermediated use of personal health informatics.