142 research outputs found

    Access to electronic health records by care setting and provider type: perceptions of cancer care providers in Ontario, Canada

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    <p>Abstract</p> <p>Background</p> <p>The use of electronic health records (EHRs) to support the organization and delivery of healthcare is evolving rapidly. However, little is known regarding potential variation in access to EHRs by provider type or care setting. This paper reports on observed variation in the perceptions of access to EHRs by a wide range of cancer care providers covering diverse cancer care settings in Ontario, Canada.</p> <p>Methods</p> <p>Perspectives were sought regarding EHR access and health record completeness for cancer patients as part of an internet survey of 5663 cancer care providers and administrators in Ontario. Data were analyzed using a multilevel logistic regression model. Provider type, location of work, and access to computer or internet were included as covariates in the model.</p> <p>Results</p> <p>A total of 1997 of 5663 (35%) valid responses were collected. Focusing on data from cancer care providers (N = 1247), significant variation in EHR access and health record completeness was observed between provider types, location of work, and level of computer access. Providers who worked in community hospitals were half as likely as those who worked in teaching hospitals to have access to their patients' EHRs (OR 0.45 95% CI: 0.24–0.85, p < 0.05) and were six times less likely to have access to other organizations' EHRs (OR 0.15 95% CI: 0.02–1.00, p < 0.05). Compared to surgeons, nurses (OR 3.47 95% CI: 1.80–6.68, p < 0.05), radiation therapists/physicists (OR 7.86 95% CI: 2.54–25.34, p < 0.05), and other clinicians (OR 4.92 95% CI: 2.15–11.27, p < 0.05) were more likely to report good access to their organization's EHRs.</p> <p>Conclusion</p> <p>Variability in access across different provider groups, organization types, and geographic locations illustrates the fragmented nature of EHR adoption in the cancer system. Along with focusing on technological aspects of EHR adoption within organizations, it is essential that there is cross-organizational and cross-provider access to EHRs to ensure patient continuity of care, system efficiency, and high quality care.</p

    Meta-analysis of operative experiences of general surgery trainees during training

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    BACKGROUND: General surgical training curricula around the world set defined operative numbers to be achieved before completion of training. However, there are few studies reporting total operative experience in training. This systematic review aimed to quantify the published global operative experience at completion of training in general surgery. METHODS: Electronic databases were searched systematically for articles in any language relating to operative experience in trainees completing postgraduate general surgical training. Two reviewers independently assessed citations for inclusion using agreed criteria. Studies were assessed for quantitative data in addition to study design and purpose. A meta-analysis was performed using a random-effects model of studies with appropriate data. RESULTS: The search resulted in 1979 titles for review. Of these, 24 studies were eligible for inclusion in the review and data from five studies were used in the meta-analysis. Studies with published data of operative experience at completion of surgical training originated from the USA (19), UK (2), the Netherlands (1), Spain (1) and Thailand (1). Mean total operative experience in training varied from 783 procedures in Thailand to 1915 in the UK. Meta-analysis produced a mean pooled estimate of 1366 (95 per cent c.i. 1026 to 1707) procedures per trainee at completion of training. There was marked heterogeneity between studies (I2 = 99.6 per cent). CONCLUSION: There is a lack of robust data describing the operative experiences of general surgical trainees outside the USA. The number of surgical procedures performed by general surgeons in training varies considerably across the world

    Accuracy of syndrome definitions based on diagnoses in physician claims

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    <p>Abstract</p> <p>Background</p> <p>Community clinics offer potential for timelier outbreak detection and monitoring than emergency departments. However, the accuracy of syndrome definitions used in surveillance has never been evaluated in community settings. This study's objective was to assess the accuracy of syndrome definitions based on diagnostic codes in physician claims for identifying 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory including influenza-like illness) in community clinics.</p> <p>Methods</p> <p>We selected a random sample of 3,600 community-based primary care physicians who practiced in the fee-for-service system in the province of Quebec, Canada in 2005-2007. We randomly selected 10 visits per physician from their claims, stratifying on syndrome type and presence, diagnosis, and month. Double-blinded chart reviews were conducted by telephone with consenting physicians to obtain information on patient diagnoses for each sampled visit. The sensitivity, specificity, and positive predictive value (PPV) of physician claims were estimated by comparison to chart review.</p> <p>Results</p> <p>1,098 (30.5%) physicians completed the chart review. A chart entry on the date of the corresponding claim was found for 10,529 (95.9%) visits. The sensitivity of syndrome definitions based on diagnostic codes in physician claims was low, ranging from 0.11 (fever) to 0.44 (respiratory), the specificity was high, and the PPV was moderate to high, ranging from 0.59 (fever) to 0.85 (respiratory). We found that rarely used diagnostic codes had a higher probability of being false-positives, and that more commonly used diagnostic codes had a higher PPV.</p> <p>Conclusions</p> <p>Future research should identify physician, patient, and encounter characteristics associated with the accuracy of diagnostic codes in physician claims. This would enable public health to improve syndromic surveillance, either by focusing on physician claims whose diagnostic code is more likely to be accurate, or by using all physician claims and weighing each according to the likelihood that its diagnostic code is accurate.</p
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