13 research outputs found

    Quality of Data Entry Using Single Entry, Double Entry and Automated Forms Processing–An Example Based on a Study of Patient-Reported Outcomes

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    Background: The clinical and scientific usage of patient-reported outcome measures is increasing in the health services. Often paper forms are used. Manual double entry of data is defined as the definitive gold standard for transferring data to an electronic format, but the process is laborious. Automated forms processing may be an alternative, but further validation is warranted. Methods: 200 patients were randomly selected from a cohort of 5777 patients who had previously answered two different questionnaires. The questionnaires were scanned using an automated forms processing technique, as well as processed by single and double manual data entry, using the EpiData Entry data entry program. The main outcome measure was the proportion of correctly entered numbers at question, form and study level. Results: Manual double-key data entry (error proportion per 1000 fields = 0.046 (95 % CI: 0.001–0.258)) performed better than single-key data entry (error proportion per 1000 fields = 0.370 (95 % CI: 0.160–0.729), (p = 0.020)). There was no statistical difference between Optical Mark Recognition (error proportion per 1000 fields = 0.046 (95 % CI: 0.001–0.258)) and double-key data entry (p = 1.000). With the Intelligent Character Recognition method, there was no statistical difference compared to single-key data entry (error proportion per 1000 fields = 6.734 (95 % CI: 0.817–24.113), (p = 0.656)), as well as double-key data entry (error proportion per 1000 fields = 3.367 (95 % CI: 0.085–18.616)), (p = 0.319))

    Reviewing the integration of patient data: how systems are evolving in practice to meet patient needs

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    <p>Abstract</p> <p>Background</p> <p>The integration of Information Systems (IS) is essential to support shared care and to provide consistent care to individuals – patient-centred care. This paper identifies, appraises and summarises studies examining different approaches to integrate patient data from heterogeneous IS.</p> <p>Methods</p> <p>The literature was systematically reviewed between 1995–2005 to identify articles mentioning patient records, computers and data integration or sharing.</p> <p>Results</p> <p>Of 3124 articles, 84 were included describing 56 distinct projects. Most of the projects were on a regional scale. Integration was most commonly accomplished by messaging with pre-defined templates and middleware solutions. HL7 was the most widely used messaging standard. Direct database access and web services were the most common communication methods. The user interface for most systems was a Web browser. Regarding the type of medical data shared, 77% of projects integrated diagnosis and problems, 67% medical images and 65% lab results. More recently significantly more IS are extending to primary care and integrating referral letters.</p> <p>Conclusion</p> <p>It is clear that Information Systems are evolving to meet people's needs by implementing regional networks, allowing patient access and integration of ever more items of patient data. Many distinct technological solutions coexist to integrate patient data, using differing standards and data architectures which may difficult further interoperability.</p

    The Influence of Information Technology on Patient-Physician Relationships

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    Interpersonal relationships and information are intertwined as essential cornerstones of health care. Although information technology (IT) has done much to advance medicine, we are not even close to realizing its full potential. Indeed, issues related to mismanaging health information often undermine relationship-centered care. Information technology must be implemented in ways that preserve and uplift relationships in care, while accommodating major deficiencies in managing information and making medical decisions. Increased collaboration between experts in IT and relationship-centered care is needed, along with inclusion of relationship-based measures in informatics research
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