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Background Infants born prematurely or with complex medical problems are surviving to discharge in growing numbers and often require significant monitoring and coordination of care in the ambulatory setting. Using Healthcare Failure Modes and Effects Analysis (HFMEA), we identified a large number of potentially serious error points in this transition of care. Purpose To test whether a multifaceted intervention that included a health coach to assist families and an enhanced personal health record to improve the quality of information available to parents and community professionals would decrease adverse events and improve family assessment of the transition. Methods Using a concurrent cohort design, infants in one geographic area (pod) of the intensive care nursery received the intervention; infants in two other pods received routine discharge care. Primary outcomes included deaths, sick visits, unplanned readmissions and missed appointments within 1 month of discharge. The family assessed the transition using a modified version of the Care Transitions Measure. Results 125 intervention infants (54% boys) and 104 control infants (48% boys) were enrolled over 18 months. The groups were similar in maternal education, insurance status, language spoken and number of adults in the home, birth weight and length of stay. At least one adverse outcome occurred in 63 (50.4%) intervention infants and 56 (53.8%) control infants (p=0.55). At 24-48 h post discharge, caregivers in the intervention group had significantly higher scores on the adapted care transitions measure (3.51 vs 3.27, p<0.0001); however, at 30 days, the difference was no longer significant (3.45 vs 3.40, p=0.27). Conclusions A multicomponent discharge intervention designed to address specific problems identified using HFMEA did not reduce certain adverse outcomes in the post-discharge period. [ABSTRACT FROM AUTHOR]

Background Delayed diagnosis of cancer can lead to patient harm, and strategies are needed to proactively and efficiently detect such delays in care. We aimed to develop and evaluate 'trigger' algorithms to electronically flag medical records of patients with potential delays in prostate and colorectal cancer (CRC) diagnosis. Methods We mined retrospective data from two large integrated health systems with comprehensive electronic health records (EHR) to iteratively develop triggers. Data mining algorithms identified all patient records with specific demographics and a lack of appropriate and timely follow-up actions on four diagnostic clues that were newly documented in the EHR: abnormal prostate-specific antigen (PSA), positive faecal occult blood test (FOBT), iron-deficiency anaemia (IDA), and haematochezia. Triggers subsequently excluded patients not needing follow-up (eg, terminal illness) or who had already received appropriate and timely care. Each of the four final triggers was applied to a test cohort, and chart reviews of randomly selected records identified by the triggers were used to calculate positive predictive values (PPV). Results The PSA trigger was applied to records of 292 587 patients seen between 1 January 2009 and 31 December 2009, and the CRC triggers were applied to 291 773 patients seen between 1 March 2009 and 28 February 2010. Overall, 1564 trigger positive patients were identified (426 PSA, 355 FOBT, 610 IDA and 173 haematochezia). Record reviews revealed PPVs of 70.2%, 66.7%, 67.5%, and 58.3% for the PSA, FOBT, IDA and haematochezia triggers, respectively. Use of all four triggers at the study sites could detect an estimated 1048 instances of delayed or missed follow-up of abnormal findings annually and 47 high-grade cancers. Conclusions EHR-based triggers can be used successfully to flag patient records lacking follow-up of abnormal clinical findings suspicious for cancer. [ABSTRACT FROM AUTHOR]

Background Delayed diagnosis of cancer can lead to patient harm, and strategies are needed to proactively and efficiently detect such delays in care. We aimed to develop and evaluate 'trigger' algorithms to electronically flag medical records of patients with potential delays in prostate and colorectal cancer (CRC) diagnosis. Methods We mined retrospective data from two large integrated health systems with comprehensive electronic health records (EHR) to iteratively develop triggers. Data mining algorithms identified all patient records with specific demographics and a lack of appropriate and timely follow-up actions on four diagnostic clues that were newly documented in the EHR: abnormal prostate-specific antigen (PSA), positive faecal occult blood test (FOBT), iron-deficiency anaemia (IDA), and haematochezia. Triggers subsequently excluded patients not needing follow-up (eg, terminal illness) or who had already received appropriate and timely care. Each of the four final triggers was applied to a test cohort, and chart reviews of randomly selected records identified by the triggers were used to calculate positive predictive values (PPV). Results The PSA trigger was applied to records of 292 587 patients seen between 1 January 2009 and 31 December 2009, and the CRC triggers were applied to 291 773 patients seen between 1 March 2009 and 28 February 2010. Overall, 1564 trigger positive patients were identified (426 PSA, 355 FOBT, 610 IDA and 173 haematochezia). Record reviews revealed PPVs of 70.2%, 66.7%, 67.5%, and 58.3% for the PSA, FOBT, IDA and haematochezia triggers, respectively. Use of all four triggers at the study sites could detect an estimated 1048 instances of delayed or missed follow-up of abnormal findings annually and 47 high-grade cancers. Conclusions EHR-based triggers can be used successfully to flag patient records lacking follow-up of abnormal clinical findings suspicious for cancer. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the trends in patterns of disease-modifying antirheumatic drugs (DMARDs) and biological agents use from 1999 to 2009 and to identify patient characteristics associated with different patterns of their use in a national sample of Veterans with rheumatoid arthritis (RA). Design: A retrospective cohort study. Settings: Administrative databases of the USA Department of Veterans Affairs. Participants: An incident cohort of 13 254 patients with newly diagnosed RA was identified. Primary outcome measures: Trends and choice of DMARDs and biological agents' usage, and time intervals between RA diagnosis and treatment Results: Methotrexate use as first-line agent increased from 39.9% to 57.2% over the study period (p<0.001). Although biological dispensations increased over other DMARDs and biological agents, from 3.4% to 25% from 1999 to 2009, the percentage of RA patients diagnosed between 1999 and 2007 who had biologics dispensations remained steady at 23.3-26.7%. Compared with Caucasian, African Americans were less likely to receive biologics (HR 0.71, 95% CI 0.63 to 0.81). Patients aged 75 and older were less likely to receive biologics than those younger than 45 (HR 0.29, 95% CI 0.23 to 0.36). The time interval between RA diagnosis and treatment with DMARDs and biological agents decreased significantly over time (median: 51 days in 1999-2001 to 28 days in 2006-2007). Conclusions: Methotrexate use increased as it became the preferred first-line agent, while other traditional agents declined. Dispensation of biologics increased significantly, but the proportion of RA patients eventually given biologics stabilised below 30%. A significant shorter time between RA diagnosis and DMARD or biological agent initiation in recent years suggests improvements in quality of care. There were disproportionately lower use of biologics in certain age and ethnic groups, and further studies will be needed to elucidate these observations. [ABSTRACT FROM AUTHOR]

Background: Diagnostic errors in primary care are harmful but difficult to detect. The authors tested an electronic health record (EHR)-based method to detect diagnostic errors in routine primary care practice. Methods: The authors conducted a retrospective study of primary care visit records 'triggered' through electronic queries for possible evidence of diagnostic errors: Trigger 1: A primary care index visit followed by unplanned hospitalisation within 14 days and Trigger 2: A primary care index visit followed by ⩾1 unscheduled visit(s) within 14 days. Control visits met neither criterion. Electronic trigger queries were applied to EHR repositories at two large healthcare systems between 1 October 2006 and 30 September 2007. Blinded physician-reviewers independently determined presence or absence of diagnostic errors in selected triggered and control visits. An error was defined as a missed opportunity to make or pursue the correct diagnosis when adequate data were available at the index visit. Disagreements were resolved by an independent third reviewer. Results: Queries were applied to 212 165 visits. On record review, the authors found diagnostic errors in 141 of 674 Trigger 1-positive records (positive predictive value (PPV)=20.9%, 95% CI 17.9% to 24.0%) and 36 of 669 Trigger 2-positive records (PPV=5.4%, 95% CI 3.7% to 7.1%). The control PPV of 2.1% (95% CI 0.1% to 3.3%) was significantly lower than that of both triggers (p⩽0.002). Inter-reviewer reliability was modest, though higher than in comparable previous studies (κ=0.37 (95% CI 0.31 to 0.44)). Conclusions: While physician agreement on diagnostic error remains low, an EHR-facilitated surveillance methodology could be useful for gaining insight into the origin of these errors. [ABSTRACT FROM AUTHOR]