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      ClinicalCodes: An Online Clinical Codes Repository to Improve the Validity and Reproducibility of Research Using Electronic Medical Records

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          Abstract

          Lists of clinical codes are the foundation for research undertaken using electronic medical records (EMRs). If clinical code lists are not available, reviewers are unable to determine the validity of research, full study replication is impossible, researchers are unable to make effective comparisons between studies, and the construction of new code lists is subject to much duplication of effort. Despite this, the publication of clinical codes is rarely if ever a requirement for obtaining grants, validating protocols, or publishing research. In a representative sample of 450 EMR primary research articles indexed on PubMed, we found that only 19 (5.1%) were accompanied by a full set of published clinical codes and 32 (8.6%) stated that code lists were available on request. To help address these problems, we have built an online repository where researchers using EMRs can upload and download lists of clinical codes. The repository will enable clinical researchers to better validate EMR studies, build on previous code lists and compare disease definitions across studies. It will also assist health informaticians in replicating database studies, tracking changes in disease definitions or clinical coding practice through time and sharing clinical code information across platforms and data sources as research objects.

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          Most cited references15

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          The inevitable application of big data to health care.

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            The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

            Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the websites of PLoS Medicine, Annals of Internal Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
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              Use of electronic health records in U.S. hospitals.

              Despite a consensus that the use of health information technology should lead to more efficient, safer, and higher-quality care, there are no reliable estimates of the prevalence of adoption of electronic health records in U.S. hospitals. We surveyed all acute care hospitals that are members of the American Hospital Association for the presence of specific electronic-record functionalities. Using a definition of electronic health records based on expert consensus, we determined the proportion of hospitals that had such systems in their clinical areas. We also examined the relationship of adoption of electronic health records to specific hospital characteristics and factors that were reported to be barriers to or facilitators of adoption. On the basis of responses from 63.1% of hospitals surveyed, only 1.5% of U.S. hospitals have a comprehensive electronic-records system (i.e., present in all clinical units), and an additional 7.6% have a basic system (i.e., present in at least one clinical unit). Computerized provider-order entry for medications has been implemented in only 17% of hospitals. Larger hospitals, those located in urban areas, and teaching hospitals were more likely to have electronic-records systems. Respondents cited capital requirements and high maintenance costs as the primary barriers to implementation, although hospitals with electronic-records systems were less likely to cite these barriers than hospitals without such systems. The very low levels of adoption of electronic health records in U.S. hospitals suggest that policymakers face substantial obstacles to the achievement of health care performance goals that depend on health information technology. A policy strategy focused on financial support, interoperability, and training of technical support staff may be necessary to spur adoption of electronic-records systems in U.S. hospitals. 2009 Massachusetts Medical Society
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                18 June 2014
                : 9
                : 6
                : e99825
                Affiliations
                [1 ]Centre for Primary Care, Institute for Population Health, University of Manchester, Manchester, United Kingdom
                [2 ]Centre for Biostatistics, Institute for Population Health, University of Manchester, Manchester, United Kingdom
                [3 ]Centre for Health Informatics, Institute for Population Health, University of Manchester, Manchester, United Kingdom
                [4 ]Centre for Pharmacoepidemiology and Drug Safety Research, Manchester Pharmacy School, University of Manchester, Manchester, United Kingdom
                [5 ]Manchester Institute for Biotechnology, University of Manchester, Manchester, United Kingdom
                UCL, United Kingdom
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DAS. Performed the experiments: DAS DR EK IO RP DA EC. Analyzed the data: DAS. Contributed to the writing of the manuscript: DAS DR EK IO RP DA EC.

                Article
                PONE-D-14-13144
                10.1371/journal.pone.0099825
                4062485
                24941260
                8ddf2dc6-53d9-4f8c-a369-25638c9fc622
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 March 2014
                : 19 May 2014
                Page count
                Pages: 6
                Funding
                The project “How valid are evaluations of effectiveness based on Primary Care Databases” was funded by the National Institute for Health Research (NIHR) School for Primary Care Research (SPCR, http://www.nihr.ac.uk/research/Pages/programmes_primary_care_research.aspx). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Epidemiology
                Disease Informatics
                Epidemiological Methods and Statistics
                Pharmacoepidemiology
                Research and Analysis Methods
                Database and Informatics Methods
                Health Informatics
                Research Assessment
                Publication Practices
                Open Access
                Peer Review
                Reproducibility
                Research Validity
                Research Design
                Observational Studies
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All data are held in the Github repository for the project at https://github.com/rOpenHealth/ClinicalCodes/tree/master/paper and on Figshare: http://figshare.com/account/projects/1286.

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