Emergency Department Use Among Combat and Non-Combat Post-9/11 Military Veterans.

INTRODUCTION: Most post-9/11 Veterans have completed at least 1 combat deployment-a known factor associated with adverse health outcomes. Such Veterans are known to have unmet health care needs, and the emergency department (ED) may serve as a safety net, yet little is known about whether combat status is associated with more frequent ED use. We sought to evaluate the relationship between combat status and frequency of ED use among post-9/11 Veterans and assess the most common reasons for ED visits. MATERIALS AND METHODS: This retrospective cohort study consisted of post-9/11 Veterans who enrolled in U.S. Department of Veterans Affairs (VA) care between fiscal years (FYs) 2005 and 2015. Data were obtained from the VA Corporate Data Warehouse. Incidence rates for ED visits for combat and non-combat Veterans were compared from FY 2010 to 2019 using zero-inflated negative binomial regression. The most frequent reasons for ED visits were determined using International Classification of Diseases codes. This study was approved by the Stanford Institutional Review Board. RESULTS: Among 1.3 million Veterans included in analyses, 70.4% had deployed to a combat zone. The mean (SD) age of our cohort was 32.6 (5.0) years and 83.5% of Veterans were male. After controlling for other factors, combat Veterans had 1.84 times the rate of ED visits compared to non-combat Veterans (95% CI, 1.83-1.85). Only combat Veterans had a mental health-related ED visit (suicidal ideations) among the top 3 reasons for ED presentation. CONCLUSIONS: Those who deployed to a combat zone had a significantly higher rate of ED use compared to those who did not. Further, mental health-related ED diagnoses appeared to be more prevalent in combat Veterans. These findings highlight the unique health care needs faced by combat Veterans and emphasize the importance of tailored interventions and support services for this specific population.

A Review of COVID-19-Related Publications and Lag Times During the First Six Months of the Year 2020.

INTRODUCTION: Considering the need for information regarding approaches to prevention and treatment of coronavirus disease 2019 (COVID-19), we sought to determine publication lag times of COVID-19-related original research articles published in top general medicine and emergency medicine (EM) journals. We further sought to characterize the types of COVID-19 publications within these journals. METHODS: We reviewed 125 top-ranked general medicine journals and 20 top-ranked EM-specific journals for COVID-19-related publications. We abstracted article titles and manuscript details for each COVID-19-related article published between January 1-June 30, 2020, and categorized articles as one of the following: original research; case report; review; or commentary. We abstracted data for preprint publications over the same time period and determined whether articles from the general medicine and EM journals had been previously published as preprint articles. Our primary outcomes were the following: 1) lag time (days) between global cumulative World Health Organization (WHO)-confirmed cases of COVID-19 and publications; 2) lag times between preprint article publication and peer-reviewed journal publication; and 3) lag times between submission and publication in peer-reviewed journals. Our secondary outcome was to characterize COVID-19-related publications. RESULTS: The first original research publications appeared in a general medicine journal 20 days and in an EM journal 58 days after the first WHO-confirmed case of COVID-19. We found median and mean lag times between preprint publications and journal publications of 32 days (19, 49) and 36 days (22) for general medicine journals, and 26 days (16, 36) and 25 days (13) for EM journals. Median and mean lag times between submission and publication were 30 days (19, 45) and 35 days (13) for general medicine journals, and 23 days (11, 39) and 27 days (19) for EM journals. Of 2530 general medicine journal articles and 351 EM journal articles, 28% and 23.6% were original research. We noted substantial closing of the preprint to peer-reviewed publication (160 days pre-pandemic) and peer-reviewed journal submission to publication (194 days pre-pandemic) lag times for COVID-19 manuscripts. CONCLUSION: We found a rapid and robust response with shortened publication lag times to meet the need for the publication of original research and other vital medical information related to COVID-19 during the first six months of 2020.

Ensuring the safety of health information systems: using heuristics for patient safety.

Health information systems (HISs) are typically seen as a mechanism for reducing medical errors. However, there is evidence to suggest that technology can facilitate or induce medical errors. Therefore, it is crucial that we fully test systems prior to their implementation in real-world settings. Presently, evidence-based evaluation heuristics that are specific to HISs do not exist for assessing aspects of interface design that may facilitate errors. A three-phase study was conducted to determine the utility of evidence-based heuristics in evaluating a human-technology interface (i.e., the Veterans Affairs Computerized Patient Record System [VA CPRS]). Phase one consisted of a systematic review of the health informatics literature involving technology-facilitated or technology-induced error. Phase two involved reviewing the literature and generating a comprehensive list of 38 heuristics that could be used to evaluate an HIS for technology-induced errors. Lastly, phase three involved conducting a heuristic evaluation of the VA CPRS system using evidence-based heuristics. Results from this work are discussed.

Using heuristic evaluations to assess the safety of health information systems.

Health information systems (HISs) are typically seen as a mechanism for reducing medical errors. There is, however, evidence to prove that technology may actually be the cause of errors. As a result, it is crucial to fully test any system prior to its implementation. At present, evidence-based evaluation heuristics do not exist for assessing aspects of interface design that lead to medical errors. A three phase study was conducted to develop evidence-based heuristics for evaluating interfaces. Phase 1 consisted of a systematic review of the literature. In Phase 2 a comprehensive list of 33 evaluation heuristics was developed based on the review that could be used to test for potential technology induced errors. Phase 3 involved applying these healthcare specific heuristics to evaluate a HIS.