OBJECTIVES: We report on findings from a meeting convened by the American College of Medical Informatics (ACMI) to characterize aspects of the patient experience that could be improved using informatics. MATERIALS AND METHODS: The American College of Medical Informatics fellows were invited to share their experiences as patients and suggest informatics approaches that may improve the patient experience. RESULTS: We identified 4 themes: (1) getting the right care, (2) data sharing and data interoperability, (3) guiding low-cost evaluations, and (4) predictive analytics. DISCUSSION: Despite widespread adoption of health IT, patient experiences remain far from optimal. CONCLUSION: The American College of Medical Informatics fellows identified informatics approaches, applications, and research areas that have the potential to improve patient experiences with health care systems.

The Safety Assurance Factors for Electronic Health Record (EHR) Resilience (SAFER) Guides provide recommendations to healthcare organizations for conducting proactive self-assessments of the safety and effectiveness of their EHR implementation and use. Originally released in 2014, they were last updated in 2016. In 2022, the Centers for Medicare and Medicaid Services required their annual attestation by US hospitals. OBJECTIVES: This case study describes how SAFER Guide recommendations were updated to align with current evidence and clinical practice. MATERIALS AND METHODS: Over nine months, a multidisciplinary team updated SAFER Guides through literature reviews, iterative feedback, and online meetings. RESULTS: We reduced the number of recommended practices across all Guides by 40% and consolidated 9 Guides into 8 to maximize ease of use, feasibility, and utility. We provide a 4-level evidence grading hierarchy for each recommendation and a new 5-point rating scale to self-assess implementation status of the recommendation. We included 429 citations of which 289 (67%) were published since the 2016 revision. DISCUSSION: SAFER Guides were revised to offer EHR best practices, adaptable to unique organizational needs, with interactive content available at: https://www.healthit.gov/topic/safety/safer-guides. CONCLUSION: Revisions ensure that the 2025 SAFER Guides represent the best available current evidence for EHR developers and healthcare organizations.

OBJECTIVES: Missed and delayed cancer diagnoses are common, harmful, and often preventable. We previously validated a digital quality measure (dQM) of emergency presentation (EP) of lung cancer in 2 US health systems. This study aimed to apply the dQM to a new national electronic health record (EHR) database and examine demographic associations. MATERIALS AND METHODS: We applied the dQM (emergency encounter followed by new lung cancer diagnosis within 30 days) to Epic Cosmos, a deidentified database covering 184 million US patients. We examined dQM associations with sociodemographic factors. RESULTS: The overall EP rate was 19.6%. EP rate was higher in Black vs White patients (24% vs 19%, P < .001) and patients with younger age, higher social vulnerability, lower-income ZIP code, and self-reported transport difficulties. DISCUSSION: We successfully applied a dQM based on cancer EP to the largest US EHR database. CONCLUSION: This dQM could be a marker for sociodemographic vulnerabilities in cancer diagnosis.

OBJECTIVE: Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance. MATERIALS AND METHODS: We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of appropriate follow-up, and exclusions that signified follow-up was unnecessary. Clinicians reviewed 100 positive and 20 negative randomly selected records for each eCQM at each site to validate accuracy and categorized missed opportunities related to system, provider, or patient factors. RESULTS: We implemented the CRC eCQM at both sites, while the lung cancer eCQM was only implemented at the VA due to lack of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. For the CRC eCQM, the rate of appropriate follow-up was 36.0% (26 746/74 314 patients) in the VA after removing clinical exclusions and 41.1% at Geisinger (1009/2461 patients; P < .001). Similarly, the rate of appropriate evaluation for lung cancer in the VA was 61.5% (25 166/40 924 patients). Reviewers most frequently attributed missed opportunities at both sites to provider factors (84 of 157). CONCLUSIONS: We implemented 2 eCQMs to evaluate the diagnostic process in cancer at 2 large health systems. Health care organizations can use these eCQMs to monitor diagnostic performance related to cancer.

BACKGROUND: The 21st Century Cures Act mandates patients' access to their electronic health record (EHR) notes. To our knowledge, no previous work has systematically invited patients to proactively report diagnostic concerns while documenting and tracking their diagnostic experiences through EHR-based clinician note review. OBJECTIVE: To test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes. METHODS: In a large integrated health system, patients aged 18-85 years actively using the patient portal and seen between October 2019 and February 2020 were invited to respond to an online questionnaire if an EHR algorithm detected any recent unexpected return visit following an initial primary care consultation ("at-risk" visit). We developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to several dimensions of the diagnostic process based on notes review and recall of recent "at-risk" visits. Additional questions assessed patients' trust in their providers and their general feelings about the visit. The primary outcome was a self-reported diagnostic concern. Multivariate logistic regression tested whether the primary outcome was predicted by instrument variables. RESULTS: Of 293 566 visits, the algorithm identified 1282 eligible patients, of whom 486 responded. After applying exclusion criteria, 418 patients were included in the analysis. Fifty-one patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements "the care plan the provider developed for me addressed all my medical concerns" [odds ratio (OR), 2.65; 95% confidence interval [CI], 1.45-4.87) and "I trust the provider that I saw during my visit" (OR, 2.10; 95% CI, 1.19-3.71) and agreed with the statement "I did not have a good feeling about my visit" (OR, 1.48; 95% CI, 1.09-2.01). CONCLUSION: Patients can identify diagnostic concerns based on a proactive online structured evaluation of visit notes. This surveillance strategy could potentially improve transparency in the diagnostic process.

Over the next decade, many health care organizations (HCOs) will transition from one electronic health record (EHR) to another; some forced by hospital acquisition and others by choice in search of better EHRs. Herein, we apply principles of Requisite Imagination, or the ability to imagine key aspects of the future one is planning, to offer 6 recommendations on how to proactively safeguard these transitions. First, HCOs should implement a proactive leadership structure that values communication. Second, HCOs should implement proactive risk assessment and testing processes. Third, HCOs should anticipate and reduce unwarranted variation in their EHR and clinical processes. Fourth, HCOs should establish a culture of conscious inquiry with routine system monitoring. Fifth, HCOs should foresee and reduce information access problems. Sixth, HCOs should support their workforce through difficult EHR transitions. Proactive approaches using Requisite Imagination principles outlined here can help ensure safe, effective, and economically sound EHR transitions.

Addressing environmental pollution and climate change is one of the biggest sociotechnical challenges of our time. While information technology has led to improvements in healthcare, it has also contributed to increased energy usage, destructive natural resource extraction, piles of e-waste, and increased greenhouse gases. We introduce a framework "Information technology-enabled Clinical cLimate InforMAtics acTions for the Environment" (i-CLIMATE) to illustrate how clinical informatics can help reduce healthcare's environmental pollution and climate-related impacts using 5 actionable components: (1) create a circular economy for health IT, (2) reduce energy consumption through smarter use of health IT, (3) support more environmentally friendly decision-making by clinicians and health administrators, (4) mobilize healthcare workforce environmental stewardship through informatics, and (5) Inform policies and regulations for change. We define Clinical Climate Informatics as a field that applies data, information, and knowledge management principles to operationalize components of the i-CLIMATE Framework.

Clinicians face competing pressures of being clinically productive while using imperfect electronic health record (EHR) systems and maximizing face-to-face time with patients. EHR use is increasingly associated with clinician burnout and underscores the need for interventions to improve clinicians' experiences. With an aim of addressing this need, we share evidence-based informatics approaches, pragmatic next steps, and future research directions to improve 3 of the highest contributors to EHR burden: (1) documentation, (2) chart review, and (3) inbox tasks. These approaches leverage speech recognition technologies, natural language processing, artificial intelligence, and redesign of EHR workflow and user interfaces. We also offer a perspective on how EHR vendors, healthcare system leaders, and policymakers all play an integral role while sharing responsibility in helping make evidence-based sociotechnical solutions available and easy to use.

OBJECTIVE: Diagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs). METHODS: Using two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit. RESULTS: We applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for "missed" = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen's kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%). CONCLUSION: In a large national EHR repository, a symptom-disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.

Objective: Online portals provide patients with access to their test results, but it is unknown how patients use these tools to manage results and what information is available to promote understanding. We conducted a mixed-methods study to explore patients' experiences and preferences when accessing their test results via portals. Materials and Methods: We conducted 95 interviews (13 semistructured and 82 structured) with adults who viewed a test result in their portal between April 2015 and September 2016 at 4 large outpatient clinics in Houston, Texas. Semistructured interviews were coded using content analysis and transformed into quantitative data and integrated with the structured interview data. Descriptive statistics were used to summarize the structured data. Results: Nearly two-thirds (63%) did not receive any explanatory information or test result interpretation at the time they received the result, and 46% conducted online searches for further information about their result. Patients who received an abnormal result were more likely to experience negative emotions (56% vs 21%; P = .003) and more likely to call their physician (44% vs 15%; P = .002) compared with those who received normal results. Discussion: Study findings suggest that online portals are not currently designed to present test results to patients in a meaningful way. Patients experienced negative emotions often with abnormal results, but sometimes even with normal results. Simply providing access via portals is insufficient; additional strategies are needed to help patients interpret and manage their online test results. Conclusion: Given the absence of national guidance, our findings could help strengthen policy and practice in this area and inform innovations that promote patient understanding of test results.

Objective: Mobile applications for improving diagnostic decision making often lack clinical evaluation. We evaluated if a mobile application improves generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning. Methods: In an experimental, vignette study, physicians diagnosed 8 patient vignettes with normal prothrombin times (PT) and abnormal partial thromboplastin times (PTT). Physicians made test ordering and diagnosis decisions for 4 vignettes using each resource: a mobile app, PTT Advisor, developed by the Centers for Disease Control and Prevention (CDC)'s Clinical Laboratory Integration into Healthcare Collaborative (CLIHC); and usual clinical decision support. Then, physicians answered questions regarding their perceptions of the app's usefulness for diagnostic decision making and learning using a modified Kirkpatrick Training Evaluation Framework. Results: Data from 368 vignettes solved by 46 physicians at 7 US health care institutions show advantages for using PTT Advisor over usual clinical decision support on test ordering and diagnostic decision accuracy (82.6 vs 70.2% correct; P < .001), confidence in decisions (7.5 vs 6.3 out of 10; P < .001), and vignette completion time (3:02 vs 3:53 min.; P = .06). Physicians reported positive perceptions of the app's potential for improved clinical decision making, and recommended it be used to address broader diagnostic challenges. Conclusions: A mobile app, PTT Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes. Similar methods could be useful for evaluating apps aimed at improving testing and diagnosis for other conditions.

Objective: The Safety Assurance Factors for EHR Resilience (SAFER) guides were released in 2014 to help health systems conduct proactive risk assessment of electronic health record (EHR)- safety related policies, processes, procedures, and configurations. The extent to which SAFER recommendations are followed is unknown. Methods: We conducted risk assessments of 8 organizations of varying size, complexity, EHR, and EHR adoption maturity. Each organization self-assessed adherence to all 140 unique SAFER recommendations contained within 9 guides (range 10-29 recommendations per guide). In each guide, recommendations were organized into 3 broad domains: "safe health IT" (total 45 recommendations); "using health IT safely" (total 80 recommendations); and "monitoring health IT" (total 15 recommendations). Results: The 8 sites fully implemented 25 of 140 (18%) SAFER recommendations. Mean number of "fully implemented" recommendations per guide ranged from 94% (System Interfaces-18 recommendations) to 63% (Clinical Communication-12 recommendations). Adherence was higher for "safe health IT" domain (82.1%) vs "using health IT safely" (72.5%) and "monitoring health IT" (67.3%). Conclusions: Despite availability of recommendations on how to improve use of EHRs, most recommendations were not fully implemented. New national policy initiatives are needed to stimulate implementation of these best practices.

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.

OBJECTIVE: Methods to identify and study safety risks of electronic health records (EHRs) are underdeveloped and largely depend on limited end-user reports. "Safety huddles" have been found useful in creating a sense of collective situational awareness that increases an organization's capacity to respond to safety concerns. We explored the use of safety huddles for identifying and learning about EHR-related safety concerns. DESIGN: Data were obtained from daily safety huddle briefing notes recorded at a single midsized tertiary-care hospital in the United States over 1 year. Huddles were attended by key administrative, clinical, and information technology staff. We conducted a content analysis of huddle notes to identify what EHR-related safety concerns were discussed. We expanded a previously developed EHR-related error taxonomy to categorize types of EHR-related safety concerns recorded in the notes. RESULTS: On review of daily huddle notes spanning 249 days, we identified 245 EHR-related safety concerns. For our analysis, we defined EHR technology to include a specific EHR functionality, an entire clinical software application, or the hardware system. Most concerns (41.6%) involved " EHR technology working incorrectly, " followed by 25.7% involving " EHR technology not working at all. " Concerns related to "EHR technology missing or absent" accounted for 16.7%, whereas 15.9% were linked to " user errors ." CONCLUSIONS: Safety huddles promoted discussion of several technology-related issues at the organization level and can serve as a promising technique to identify and address EHR-related safety concerns. Based on our findings, we recommend that health care organizations consider huddles as a strategy to promote understanding and improvement of EHR safety.

The Office of the National Coordinator for Health Information Technology is expected to oversee creation of a Health Information Technology (HIT) Safety Center. While its functions are still being defined, the center is envisioned as a public-private entity focusing on promotion of HIT related patient safety. We propose that the HIT Safety Center leverages its unique position to work with key administrative and policy stakeholders, healthcare organizations (HCOs), and HIT vendors to achieve four goals: (1) facilitate creation of a nationwide 'post-marketing' surveillance system to monitor HIT related safety events; (2) develop methods and governance structures to support investigation of major HIT related safety events; (3) create the infrastructure and methods needed to carry out random assessments of HIT related safety in complex HCOs; and (4) advocate for HIT safety with government and private entities. The convening ability of a federally supported HIT Safety Center could be critically important to our transformation to a safe and effective HIT enabled healthcare system.

Accurate display and interpretation of clinical laboratory test results is essential for safe and effective diagnosis and treatment. In an attempt to ascertain how well current electronic health records (EHRs) facilitated these processes, we evaluated the graphical displays of laboratory test results in eight EHRs using objective criteria for optimal graphs based on literature and expert opinion. None of the EHRs met all 11 criteria; the magnitude of deficiency ranged from one EHR meeting 10 of 11 criteria to three EHRs meeting only 5 of 11 criteria. One criterion (i.e., the EHR has a graph with y-axis labels that display both the name of the measured variable and the units of measure) was absent from all EHRs. One EHR system graphed results in reverse chronological order. One EHR system plotted data collected at unequally-spaced points in time using equally-spaced data points, which had the effect of erroneously depicting the visual slope perception between data points. This deficiency could have a significant, negative impact on patient safety. Only two EHR systems allowed users to see, hover-over, or click on a data point to see the precise values of the x-y coordinates. Our study suggests that many current EHR-generated graphs do not meet evidence-based criteria aimed at improving laboratory data comprehension.

OBJECTIVES: We conducted a systematic review to determine the effect of providing patients access to their medical records (electronic or paper-based) on healthcare quality, as defined by measures of safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity. METHODS: Articles indexed in PubMed from January 1970 to January 2012 were reviewed. Twenty-seven English-language controlled studies were included. Outcomes were categorized as measures of effectiveness (n=19), patient-centeredness (n=16), and efficiency (n=2); no study addressed safety, timeliness, or equity. RESULTS: Outcomes were equivocal with respect to several aspects of effectiveness and patient-centeredness. Efficiency outcomes in terms of frequency of in-person and telephone encounters were mixed. Access to health records appeared to enhance patients' perceptions of control and reduced or had no effect on patient anxiety. CONCLUSION: Although few positive findings generally favored patient access, the literature is unclear on whether providing patients access to their medical records improves quality.

OBJECTIVE: A recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system. METHODS: The Informatics Patient Safety Office of the Veterans Health Administration (VA) maintains a non-punitive, voluntary reporting system to collect and investigate EHR-related safety concerns (ie, adverse events, potential events, and near misses). We analyzed completed investigations using an eight-dimension sociotechnical conceptual model that accounted for both technical and non-technical dimensions of safety. Using the framework analysis approach to qualitative data, we identified emergent and recurring safety concerns common to multiple reports. RESULTS: We extracted 100 consecutive, unique, closed investigations between August 2009 and May 2013 from 344 reported incidents. Seventy-four involved unsafe technology and 25 involved unsafe use of technology. A majority (70%) involved two or more model dimensions. Most often, non-technical dimensions such as workflow, policies, and personnel interacted in a complex fashion with technical dimensions such as software/hardware, content, and user interface to produce safety concerns. Most (94%) safety concerns related to either unmet data-display needs in the EHR (ie, displayed information available to the end user failed to reduce uncertainty or led to increased potential for patient harm), software upgrades or modifications, data transmission between components of the EHR, or 'hidden dependencies' within the EHR. DISCUSSION: EHR-related safety concerns involving both unsafe technology and unsafe use of technology persist long after 'go-live' and despite the sophisticated EHR infrastructure represented in our data source. Currently, few healthcare institutions have reporting and analysis capabilities similar to the VA. CONCLUSIONS: Because EHR-related safety concerns have complex sociotechnical origins, institutions with long-standing as well as recent EHR implementations should build a robust infrastructure to monitor and learn from them.

CONTEXT: Failure 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. METHODS: Between 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. FINDINGS: Of 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. CONCLUSIONS: Despite 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: Electronic medical records (EMRs) facilitate abnormal test result communication through "alert" notifications. The aim was to evaluate how primary care providers (PCPs) manage alerts related to critical diagnostic test results on their EMR screens, and compare alert-management strategies of providers with high versus low rates of timely follow-up of results. DESIGN: 28 PCPs from a large, tertiary care Veterans Affairs Medical Center (VAMC) were purposively sampled according to their rates of timely follow-up of alerts, determined in a previous study. Using techniques from cognitive task analysis, participants were interviewed about how and when they manage alerts, focusing on four alert-management features to filter, sort and reduce unnecessary alerts on their EMR screens. RESULTS: Provider knowledge of alert-management features ranged between 4% and 75%. Almost half (46%) of providers did not use any of these features, and none used more than two. Providers with higher versus lower rates of timely follow-up used the four features similarly, except one (customizing alert notifications). Providers with low rates of timely follow-up tended to manually scan the alert list and process alerts heuristically using their clinical judgment. Additionally, 46% of providers used at least one workaround strategy to manage alerts. CONCLUSION: Considerable heterogeneity exists in provider use of alert-management strategies; specific strategies may be associated with lower rates of timely follow-up. Standardization of alert-management strategies including improving provider knowledge of appropriate tools in the EMR to manage alerts could reduce the lack of timely follow-up of abnormal diagnostic test results.

OBJECTIVE: Communication of abnormal test results in the outpatient setting is prone to error. Using information technology can improve communication and improve patient safety. We standardized processes and procedures in a computerized test result notification system and examined their effectiveness to reduce errors in communication of abnormal imaging results. DESIGN: We prospectively analyzed outcomes of computerized notification of abnormal test results (alerts) that providers did not explicitly acknowledge receiving in the electronic medical record of an ambulatory multispecialty clinic. MEASUREMENTS: In the study period, 190,799 outpatient visits occurred and 20,680 outpatient imaging tests were performed. We tracked 1,017 transmitted alerts electronically. Using a taxonomy of communication errors, we focused on alerts in which errors in acknowledgment and reception occurred. Unacknowledged alerts were identified through electronic tracking. Among these, we performed chart reviews to determine any evidence of documented response, such as ordering a follow-up test or consultation. If no response was documented, we contacted providers by telephone to determine their awareness of the test results and any follow-up action they had taken. These processes confirmed the presence or absence of alert reception. RESULTS: Providers failed to acknowledge receipt of over one-third (368 of 1,017) of transmitted alerts. In 45 of these cases (4% of abnormal results), the imaging study was completely lost to follow-up 4 weeks after the date of study. Overall, 0.2% of outpatient imaging was lost to follow-up. The rate of lost to follow-up imaging was 0.02% per outpatient visit. CONCLUSION: Imaging results continue to be lost to follow-up in a computerized test result notification system that alerted physicians through the electronic medical record. Although comparison data from previous studies are limited, the rate of results lost to follow-up appears to be lower than that reported in systems that do not use information technology comparable to what we evaluated.