International journal of medical informatics
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The aim of this study is to evaluate the effectiveness and efficiency of privacy-preserving data cubes of electronic medical records (EMRs). An EMR data cube is a complex of EMR statistics that are summarized or aggregated by all possible combinations of attributes. Data cubes are widely utilized for efficient big data analysis and also have great potential for EMR analysis. For safe data analysis without privacy breaches, we must consider the privacy preservation characteristics of the EMR data cube. In this paper, we introduce a design for a privacy-preserving EMR data cube and the anonymization methods needed to achieve data privacy. We further focus on changes in efficiency and effectiveness that are caused by the anonymization process for privacy preservation. Thus, we experimentally evaluate various types of privacy-preserving EMR data cubes using several practical metrics and discuss the applicability of each anonymization method with consideration for the EMR analysis environment. ⋯ The utility of anonymized EMR data cubes varies widely according to the anonymization method, and the applicability of the anonymization method depends on the features of the EMR analysis environment. The findings help to adopt the optimal anonymization method considering the EMR analysis environment and goal of the EMR analysis.
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Self-management can optimize health outcomes for individuals with chronic pain (CP), an increasing fiscal and social burden in Canada. However, self-management is rarely integrated into the regular care (team activities and medical treatment) patients receive. Health information technology offers an opportunity to provide regular monitoring and exchange of information between patient and care team. ⋯ Internet-based programs contain automated, communication and decision support features that can address information and care gaps reported by patients and clinicians. However, focus groups identified functionalities not reported in the literature, non-medical and condition- and context-specific information, integration of personal health records, and the role of the different health professionals in chronic pain management were not identified. These gaps need to be considered in the future development of Internet-based programs. While the association between the mechanisms of Internet-based programs' features and outcomes is not clearly established, the results of this study indicate that interactivity, personalization and tailored messages, combined with therapist contact will maximize the effectiveness of an Internet-based chronic pain program in enhancing self-management.
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To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. ⋯ Our proposed framework demonstrates a more accurate and efficient approach for identifying subjects with and without T2DM from EHR.
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Survey studies of health information systems use tend to focus on availability of functionalities, adoption and intensity of use. Usability surveys have not been systematically conducted by any healthcare professional groups on a national scale on a repeated basis. This paper presents results from two cross-sectional surveys of physicians' experiences with the usability of currently used EHR systems in Finland. The research questions were: To what extent has the overall situation improved between 2010 and 2014? What differences are there between healthcare sectors? ⋯ Surveys about the usability of EHR systems are needed to monitor their development at regional and national levels. To our knowledge, this study is the first national eHealth observatory questionnaire that focuses on usability and is used to monitor the long-term development of EHRs. The results do not show notable improvements in physician's ratings for their EHRs between the years 2010 and 2014 in Finland. Instead, the results indicate the existence of serious problems and deficiencies which considerably hinder the efficiency of EHR use and physician's routine work. The survey results call for considerable amount of development work in order to achieve the expected benefits of EHR systems and to avoid technology-induced errors which may endanger patient safety. The findings of repeated surveys can be used to inform healthcare providers, decision makers and politicians about the current state of EHR usability and differences between brands as well as for improvements of EHR usability. This survey will be repeated in 2017 and there is a plan to include other healthcare professional groups in future surveys.