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Purpose We tested whether prospective use of electronic health record-based trigger algorithms to identify patients at risk of diagnostic delays could prevent delays in diagnostic evaluation for cancer. Methods We performed a cluster randomized controlled trial of primary care providers (PCPs) at two sites to test whether triggers that prospectively identify patients with potential delays in diagnostic evaluation for lung, colorectal, or prostate cancer can reduce time to follow-up diagnostic evaluation. Intervention steps included queries of the electronic health record repository for patients with abnormal findings and lack of associated follow-up actions, manual review of triggered records, and communication of this information to PCPs via secure e-mail and, if needed, phone calls to ensure message receipt. We compared times to diagnostic evaluation and proportions of patients followed up between intervention and control cohorts based on final review at 7 months. Results We recruited 72 PCPs (36 in the intervention group and 36 in the control group) and applied the trigger to all patients under their care from April 20, 2011, to July 19, 2012. Of 10,673 patients with abnormal findings, the trigger flagged 1,256 patients (11.8%) as high risk for delayed diagnostic evaluation. Times to diagnostic evaluation were significantly lower in intervention patients compared with control patients flagged by the colorectal trigger (median, 104 v 200 days, respectively; n = 557; P < .001) and prostate trigger (40% received evaluation at 144 v 192 days, respectively; n = 157; P < .001) but not the lung trigger (median, 65 v 93 days, respectively; n = 19; P = .59). More intervention patients than control patients received diagnostic evaluation by final review (73.4% v 52.2%, respectively; relative risk, 1.41; 95% CI, 1.25 to 1.58). Conclusion Electronic trigger-based interventions seem to be effective in reducing time to diagnostic evaluation of colorectal and prostate cancer as well as improving the proportion of patients who receive follow-up. Similar interventions could improve timeliness of diagnosis of other serious conditions.

With wider use of electronic health records (EHRs), physicians increasingly receive notifications via EHR-based inboxes (eg, Epic's In-Basket and General Electric Centricity's Documents). Examples of types of notifications include test results, responses to referrals, requests for medication refills, and messages from physicians and other health care professionals. 1,2 Previous work within the Department of Veterans Affairs found that health care professionals receive large quantities of EHR-based notifications, making it harder to discern important vs irrelevant information and increasing their risk of overlooking abnormal test results. 3-6 Information overload is of emerging concern because new types of notifications and "FYI" (for your information) messages can be easily created in the EHR (vs in a paper-based system). Furthermore, the additional workload to read and process these messages remains uncompensated in an environment of reduced reimbursements for office-based care. 1,2,4 Conversely, EHRs make it easier to measure the amount of information received. We quantified the notifications that physicians received via inboxes of commercial EHRs to estimate their burden.

ContextFailure to notify patients of test results is common even when electronic health records (EHRs) are used to report results to practitioners. We sought to understand the broad range of social and technical factors that affect test result management in an integrated EHR-based health system.MethodsBetween June and November 2010, we conducted a cross-sectional, web-based survey of all primary care practitioners (PCPs) within the Department of Veterans Affairs nationwide. Survey development was guided by a socio-technical model describing multiple inter-related dimensions of EHR use.FindingsOf 5001 PCPs invited, 2590 (51.8%) responded. 55.5% believed that the EHRs did not have convenient features for notifying patients of test results. Over a third (37.9%) reported having staff support needed for notifying patients of test results. Many relied on the patient's next visit to notify them for normal (46.1%) and abnormal results (20.1%). Only 45.7% reported receiving adequate training on using the EHR notification system and 35.1% reported having an assigned contact for technical assistance with the EHR; most received help from colleagues (60.4%). A majority (85.6%) stayed after hours or came in on weekends to address notifications; less than a third reported receiving protected time (30.1%). PCPs strongly endorsed several new features to improve test result management, including better tracking and visualization of result notifications.ConclusionsDespite an advanced EHR, both social and technical challenges exist in ensuring notification of test results to practitioners and patients. Current EHR technology requires significant improvement in order to avoid similar challenges elsewhere.

Objective: The United States Office of the National Coordinator for Health Information Technology sponsored the development of a “high-priority” list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive).Materials and methods: We conducted evaluations of electronic health records (EHRs) at a convenience sample of health care organizations across the United States using a standardized testing protocol with simulated orders.Results: Evaluations of 19 systems were conducted at 13 sites using 14 different EHRs. Across systems, 69% of the high-priority DDI pairs produced alerts. Implementation and display of the DDI alerts tested varied between systems, even when the same EHR vendor was used. Across the drug pairs evaluated, implementation and display of DDI alerts differed, ranging from 27% (4/15) to 93% (14/15) implementation.Discussion: Currently, there is no standard of care covering which DDI alerts to implement or how to display them to providers. Opportunities to improve DDI alerting include using differential displays based on DDI severity, establishing improved lists of clinically significant DDIs, and thoroughly reviewing organizational implementation decisions regarding DDIs.Conclusion: DDI alerting is clinically important but not standardized. There is significant room for improvement and standardization around evidence-based DDIs.

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.

OBJECTIVES: Electronic health records (EHR) enable transmission and tracking of referrals between primarycare practitioners (PCPs) and subspecialists. We used an EHR to examine follow-up actions on electronic referral communication in a large multispecialty VA facility. METHODS: We retrieved outpatient referrals to five subspecialties between October 2006 and December 2007, and queried the EHR to determine their status: completed, discontinued (returned to PCP), or unresolved (no action taken by subspecialist). All unresolved referrals, and random samples of discontinued and completed referrals were reviewed to determine whether subspecialists took follow-up actions (i.e., schedule appointments anytime in the future) within 30 days of referral-receipt. For referrals without timely follow-up, we determined whether inaction was supported by any predetermined justifiable reasons or associated with certain referral characteristics. We also reviewed if PCPs took the required action on returned information. RESULTS: Of 61,931 referrals, 22,535 were discontinued (36.4%), and 474 were unresolved (0.8%). We selected 412 discontinued referrals randomly for review. Of these, 52% lacked follow-up actions within 30 days. Appropriate justifications for inaction were documented in 69.8% (150/215) of those without action and included lack of prerequisite testing by the PCP and subspecialist opinion that no intervention was required despite referral. We estimated that at 30 days, 6.3% of all referrals were associated with an unexplained lack of follow-up actions by subspecialists. Conversely, 7.4% of discontinued referrals returned to PCPs were associated with an unexplained lack of follow-up. CONCLUSIONS: Although the EHR facilitates transmission of valuable information at the PCP-subspecialist interface, unexplained communication breakdowns in the referral process persist in a subset of cases.