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BackgroundAccurately assessing the regional activity of diseases such as COVID-19 is important in guiding public health interventions. Leveraging electronic health records (EHRs) to monitor outpatient clinical encounters may lead to the identification of emerging outbreaks. ObjectiveThe aim of this study is to investigate whether excess visits where the word “cough” was present in the EHR reason for visit, and hospitalizations with acute respiratory failure were more frequent from December 2019 to February 2020 compared with the preceding 5 years. MethodsA retrospective observational cohort was identified from a large US health system with 3 hospitals, over 180 clinics, and 2.5 million patient encounters annually. Data from patient encounters from July 1, 2014, to February 29, 2020, were included. Seasonal autoregressive integrated moving average (SARIMA) time-series models were used to evaluate if the observed winter 2019/2020 rates were higher than the forecast 95% prediction intervals. The estimated excess number of visits and hospitalizations in winter 2019/2020 were calculated compared to previous seasons. ResultsThe percentage of patients presenting with an EHR reason for visit containing the word “cough” to clinics exceeded the 95% prediction interval the week of December 22, 2019, and was consistently above the 95% prediction interval all 10 weeks through the end of February 2020. Similar trends were noted for emergency department visits and hospitalizations starting December 22, 2019, where observed data exceeded the 95% prediction interval in 6 and 7 of the 10 weeks, respectively. The estimated excess over the 3-month 2019/2020 winter season, obtained by either subtracting the maximum or subtracting the average of the five previous seasons from the current season, was 1.6 or 2.0 excess visits for cough per 1000 outpatient visits, 11.0 or 19.2 excess visits for cough per 1000 emergency department visits, and 21.4 or 39.1 excess visits per 1000 hospitalizations with acute respiratory failure, respectively. The total numbers of excess cases above the 95% predicted forecast interval were 168 cases in the outpatient clinics, 56 cases for the emergency department, and 18 hospitalized with acute respiratory failure. ConclusionsA significantly higher number of patients with respiratory complaints and diseases starting in late December 2019 and continuing through February 2020 suggests community spread of SARS-CoV-2 prior to established clinical awareness and testing capabilities. This provides a case example of how health system analytics combined with EHR data can provide powerful and agile tools for identifying when future trends in patient populations are outside of the expected ranges.

BackgroundPediatric patients with behavioral health emergencies (BHEs) are often transported to an emergency department (ED) by emergency medical services (EMS), despite having no physical medical complaints, to await psychiatric evaluation and treatment. This process leads to significant delays in their care. We examined the safety of directly transporting pediatric patients with BHEs from the field to an alternative destination of a psychiatric emergency service (PES) facility using an EMS protocol.MethodsA retrospective review from November 1, 2011, to November 1, 2016, was conducted for pediatric EMS encounters using EMS data from Alameda County, California. Our primary outcome was the safety of a prehospital alternative destination protocol. We identified the proportion of patients who required retransport to an ED within 24 h after arriving at PES (defined as a failed diversion). We also describe the mortality of all patients being transported for a BHE.ResultsThere were 38,241 total pediatric encounters, with 20.1% for BHEs. A total of 3122 (41%) BHE encounters met protocol criteria and were transported directly to the PES. Only 16 (0.5%) patients had a secondary transport (failed diversion) to an ED within 24 h of arrival. No patients with a BHE transported to the PES died within 30 days of the EMS encounter.ConclusionDeath and adverse clinical outcomes are extremely rare in pediatric patients using a prehospital alternative destination protocol. This information could significantly improve the care of children with BHEs.

Study objectiveOne in 4 deaths from COVID-19 has been attributed to hospital crowding. We simulated how many ambulances would be required to rebalance hospital load through systematic interhospital transfers. We assessed the potential feasibility of such a strategy and explored whether transfer requirement was a helpful measure and visualization of regional hospital crowding during COVID-19 surges.MethodsUsing data from the United States hospitals reporting occupancy to the Department of Health and Human Services from July 2020 to March 2022 and road network driving times, we estimated the number of ambulances required weekly to relieve overcapacity hospitals.ResultsDuring the peak week, which ended on January 8, 2021, approximately 1,563 ambulances would be needed for 15,389 simulated patient transports, of which 6,530 (42%) transports involved a 1-way driving time of more than 3 hours. Transfer demands were dramatically lower during most other weeks, with the median week requiring only 134 ambulances (interquartile range, 84 to 295) and involving only 116 transports with 1-way driving times above 3 hours (interquartile range, 4 to 548). On average, receiving hospitals were larger and located in more rural areas than sending hospitals.ConclusionThis simulation demonstrated that for most weeks during the pandemic, ambulance availability and bed capacity were unlikely to have been the main impediments to rebalancing hospital loads. Our metric provided an immediately available and much more complete measure of hospital system strain than counts of hospital admissions alone.

BackgroundShareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip.Methods and findingsRetrospective review of patients presenting to 180 clinics and 2 hospitals in greater Los Angeles between January 1, 2014 and May 14, 2020. Injuries were identified using a natural language processing (NLP) algorithm not previously used to identify injuries, tallied, and described along with required healthcare resources. We combine these tallies with municipal data on scooter use to report a monthly utilization-corrected rate of e-scooter injuries. We searched 36 million clinical notes. Our NLP algorithm correctly classified 92% of notes in the testing set compared with the gold standard of investigator review. In total, we identified 1,354 people injured by e-scooters; 30% were seen in more than one clinical setting (e.g., emergency department and a follow-up outpatient visit), 29% required advanced imaging, 6% required inpatient admission, and 2 died. We estimate 115 injuries per million e-scooter trips were treated in our health system.ConclusionsOur observed e-scooter injury rate is likely an underestimate, but is similar to that previously reported for motorcycles. However, the comparative severity of injuries is unknown. Our methodology may prove useful to study other clinical conditions not identifiable by existing diagnostic systems.

ImportanceMost drug epidemics in the United States have disproportionately affected nonwhite communities. Notably, the current opioid epidemic is heavily concentrated among low-income white communities, and the roots of this racial/ethnic phenomenon have not been adequately explained.ObjectiveTo examine the degree to which differential exposure to opioids via the health care system by race/ethnicity and income could be driving the observed social gradient of the current opioid epidemic, as well as to compare the trends in the prevalence of prescription opioids with those observed for stimulants and benzodiazepines.Design, setting, and participantsThis population-based study used 2011 through 2015 records from California's prescription drug monitoring program (Controlled Substance Utilization Review and Evaluation System), which longitudinally tracks all patients receiving controlled substance prescriptions in the state and contained unique records for 29.7 million individuals who received such a prescription from 2011 to 2015. Data were analyzed between January and May 2018.ExposuresA total of 1760 zip code tabulation areas (ZCTAs) in California, with associated racial/ethnic composition and per capita income.Main outcomes and measuresThe percentage of individuals receiving at least 1 prescription each year was calculated for opioids, benzodiazepines, and stimulants.ResultsA nearly 300% difference in opioid prescription prevalence across the race/ethnicity-income gradient was observed in California, with 44.2% of adults in the quintile of ZCTAs with the lowest-income/highest proportion-white population receiving at least 1 opioid prescription each year compared with 16.1% in the quintile with the highest-income/lowest proportion-white population and 23.6% of all individuals 15 years or older. Stimulant prescriptions were highly concentrated in mostly white high-income areas, with a prevalence of 3.8% among individuals in the quintile with the highest-income/highest proportion-white population and a prevalence of 0.6% in the quintile with the lowest-income/lowest proportion-white population. Benzodiazepine prescriptions did not have an income gradient but were concentrated in mostly white areas, with 15.7% of adults in the quintile of ZCTAs with the highest proportion-white population receiving at least 1 prescription each year compared with 7.0% among the quintile with the lowest proportion-white population.Conclusions and relevanceThe race/ethnicity and income pattern of opioid overdoses mirrored prescription rates, suggesting that differential exposure to opioids via the health care system may have induced the large, observed racial/ethnic gradient in the opioid epidemic. Across drug categories, controlled medications were much more likely to be prescribed to individuals living in majority-white areas. These discrepancies may have shielded nonwhite communities from the brunt of the prescription opioid epidemic but also represent disparities in treatment and access to all medications.

Study objectivePatients with acute psychiatric emergencies who receive an involuntary hold often spend hours in the emergency department (ED) because of a deficit in inpatient psychiatric beds. One solution to address the lack of prompt psychiatric evaluation in the ED has been to establish regional stand-alone psychiatric emergency services. However, patients receiving involuntary holds still need to be screened and evaluated to ensure that their behavior is not caused by an underlying and life-threatening nonpsychiatric illness. Although traditional regional emergency medical services (EMS) systems depend on the medical ED for this function, a field-screening protocol can allow EMS to directly transport a substantial portion of patients to a stand-alone psychiatric emergency service. The purpose of this investigation is to describe overall EMS use for patients receiving involuntary holds, compare patients receiving involuntary holds with all EMS patients, and evaluate the safety of field medical clearance of an established field-screening protocol in Alameda County, CA.MethodsWe obtained data for all EMS encounters between November 1, 2011, and November 1, 2016, using Alameda County's standardized data set. After unique patient identification, we describe the data at the patient level and at the encounter level. At the patient level, we compare "involuntary hold patients" (≥1 involuntary hold during the study period) with those who were "never held." Additionally, we assess the safety of out-of-hospital medical clearance by calculating the rate of failed diversion, defined as retransport of a patient to a medical ED within 12 hours of transport to the psychiatric emergency services by EMS.ResultsOf the 541,731 total EMS encounters in Alameda County during the study period, 10% (N=53,887) were identified as involuntary hold encounters. Of these involuntary hold patient encounters, 41% (N=22,074) resulted in direct transport of the patient to the stand-alone psychiatric emergency service for evaluation; 0.3% (N=60) failed diversion and required retransport within 12 hours. At the patient level, Alameda County EMS encountered 257,625 unique patients, and 10% (N=26,283) had at least one encounter for an involuntary hold during the study period. These "involuntary hold patients" were substantially younger, more likely to be men, and less likely to be insured. Additionally, they had higher overall EMS use: "involuntary hold patients" accounted for 24% of all encounters (N=128,003); 53,887 of these encounters were for involuntary holds, whereas an additional 74,116 were for other reasons. Similarly, 4% of "involuntary hold patients" had 20 or more encounters, whereas only 0.4% of "never held" patients were in this category. Last, the 7% of "involuntary hold patients" (N=1,907) who received greater than or equal to 5 involuntary holds during the study period accounted for 39% of all involuntary holds and 9% of all EMS encounters.ConclusionTen percent of all EMS encounters were for involuntary psychiatric holds. With an EMS-directed screening protocol, 41% of all such patient encounters resulted in direct transport of the patient to the psychiatric emergency service, bypassing medical clearance in the ED. Overall, only 0.3% of these patients required retransport to a medical ED within 12 hours of arrival to psychiatric emergency services. We found that 24% of all EMS encounters in Alameda County were attributable to "involuntary hold patients," reinforcing the importance of the effects of mental illness on EMS use.

Introduction: Each year residency programs expend considerable effort ranking applicants for the National Residency Matching Program (NRMP). We explored the relationship between residents’ NRMP rank list position as generated at our institution and their performance in residency and post-graduation to determine whether such efforts are justified.Methods: Faculty who were present for the 10 consecutive study years at an allopathic emergency medicine residency retrospectively evaluated residents on their overall performance, medical knowledge, and interpersonal skills. Residency graduates were surveyed regarding their current position, hours of clinical practice, academic, teaching and leadership roles, and publications. We compared match position to performance using graphical techniques as the primary form of analysis.Results: Ten faculty evaluated the 107 residents who graduated from the program during these 10 years by class year. Eighty-four residents responded to the survey. In general, we found little correlation between NRMP rank and faculty rank of resident performance. There was also little correlation between position in the NRMP rank list and the probability of having an academic career, publishing research, or having a teaching or leadership role.Conclusion: We found that the position on our NRMP rank list was of little value in predicting which residents would do best in residency or take on academic or leadership roles once graduated. Residencies should evaluate the processes they use to generate their rank list to determine whether the ranking process is sufficiently predictive to warrant the effort expended.

BACKGROUND: Randomized controlled trials (RCTs) often have more than one primary outcome and frequently have secondary and harm outcomes. Comparison of outcomes between study arms is the primary focus of RCTs, but there are times when the relation between outcomes is important, such as determining whether an intermediate outcome and a clinical outcome have a strong association. We sought to determine how often reports of RCTs depict the relations among outcomes at the individual patient level and, for those studies that use composite outcomes, how often the relations between component elements are depicted. METHODS: We selected 20 general, specialty and subspecialty medical journals with high impact factors that publish original clinical research. We identified every RCT in the 2011 and 2012 issues and randomly selected 10 articles per journal. For each article we recorded the number of outcomes, the number of composite outcomes and how often the relations between outcomes or elements of composite outcomes were portrayed. RESULTS: All but 16 of the 200 RCTs had more than one outcome. Thus, outcomes could have been related in 92% of studies, but such relations were only reported in 2 (1%). A total of 33 (17%) investigations measured a composite outcome, 32 of which showed data for each component. None, however, showed cross-tabulation of the components. CONCLUSIONS: Readers are rarely shown the relation between outcomes. Mandatory posting of datasets or requirements for detailed appendices would allow readers to see these cross-tabulations, helping future investigators know which outcomes are redundant, which provide unique information and which are most responsive to changes in the independent variables. While not every relationship between outcomes requires depiction, at present such information is seldom portrayed.

BACKGROUND: Randomized controlled trials (RCTs) often have more than one primary outcome and frequently have secondary and harm outcomes. Comparison of outcomes between study arms is the primary focus of RCTs, but there are times when the relation between outcomes is important, such as determining whether an intermediate outcome and a clinical outcome have a strong association. We sought to determine how often reports of RCTs depict the relations among outcomes at the individual patient level and, for those studies that use composite outcomes, how often the relations between component elements are depicted. METHODS: We selected 20 general, specialty and subspecialty medical journals with high impact factors that publish original clinical research. We identified every RCT in the 2011 and 2012 issues and randomly selected 10 articles per journal. For each article we recorded the number of outcomes, the number of composite outcomes and how often the relations between outcomes or elements of composite outcomes were portrayed. RESULTS: All but 16 of the 200 RCTs had more than one outcome. Thus, outcomes could have been related in 92% of studies, but such relations were only reported in 2 (1%). A total of 33 (17%) investigations measured a composite outcome, 32 of which showed data for each component. None, however, showed cross-tabulation of the components. CONCLUSIONS: Readers are rarely shown the relation between outcomes. Mandatory posting of datasets or requirements for detailed appendices would allow readers to see these cross-tabulations, helping future investigators know which outcomes are redundant, which provide unique information and which are most responsive to changes in the independent variables. While not every relationship between outcomes requires depiction, at present such information is seldom portrayed.

For patients suffering from diabetes and other chronic conditions, a large body of work demonstrates income-related disparities in access to coordinated preventive care. Much less is known about associations between poverty and consequential negative health outcomes. Few studies have assessed geographic patterns that link household incomes to major preventable complications of chronic diseases. Using statewide facility discharge data for California in 2009, we identified 7,973 lower-extremity amputations in 6,828 adults with diabetes. We mapped amputations based on residential ZIP codes and used data from the Census Bureau to produce corresponding maps of poverty rates. Comparisons of the maps show amputation "hot spots" in lower-income urban and rural regions of California. Prevalence-adjusted amputation rates varied tenfold between high-income and low-income regions. Our analysis does not support detailed causal inferences. However, our method for mapping complication hot spots using public data sources may help target interventions to the communities most in need.

The use of computed tomographic scanning in blunt head trauma has increased dramatically in recent years without an accompanying rise in the prevalence of injury or hospital admission for serious conditions. Because computed tomography is neither harmless nor inexpensive, researchers have attempted to optimize utilization, largely through research that describes which clinical variables predict intracranial injury, and use this information to develop clinical decision instruments. Although such techniques may be useful when the benefits and harms of each strategy (neuroimaging vs observation) are quantifiable and amenable to comparison, the exact magnitude of these benefits and harms remains unknown in this clinical scenario. We believe that most clinical decision instrument development efforts are misguided insofar as they ignore critical, nonclinical factors influencing the decision to image. In this article, we propose a conceptual model to illustrate how clinical and nonclinical factors influence emergency physicians making this decision. We posit that elements unrelated to standard clinical factors, such as personality of the physician, fear of litigation and of missed diagnoses, patient expectations, and compensation method, may have equal or greater impact on actual decision making than traditional clinical factors. We believe that 3 particular factors deserve special consideration for further research: fear of error/malpractice, financial incentives, and patient engagement. Acknowledgement and study of these factors will be essential if we are to understand how emergency physicians truly make these decisions and how test-ordering behavior can be modified.

BACKGROUND: We previously demonstrated that a computerized psychiatric screening interview (the PRIME-MD) can be used in the Emergency Department (ED) waiting room to identify patients with mental illness. In that trial, however, informing the ED physician of the PRIME-MD results did not increase the frequency of psychiatric diagnosis, consultation or referral. We conducted this study to determine whether telling the patient and physician the PRIME-MD result would result in the majority of PRIME-MD-diagnosed patients being directed toward treatment for their mental illness. METHODS: In this single-site RCT, consenting patients with non-specific somatic chief complaints (e.g., fatigue, back pain, etc.) completed the computerized PRIME-MD in the waiting room and were randomly assigned to one of three groups: patient and physician told PRIME-MD results, patient told PRIME-MD results, and neither told PRIME-MD results.The main outcome measure was the percentage of patients with a PRIME-MD diagnosis who received a psychiatric consultation or referral from the ED. RESULTS: 183 (5% of all ED patients) were approached. 123 eligible patients consented to participate, completed the PRIME-MD and were randomized. 95 patients had outcomes recorded. 51 (54%) had a PRIME-MD diagnosis and 8 (16%) of them were given a psychiatric consultation or referral in the ED. While the frequency of consultation or referral increased as the intervention's intensity increased (tell neither = 11% (1/9), tell patient 15% (3/20), tell patient and physician 18% (4/22)), no group came close to the 50% threshold we sought. For this reason, we stopped the trial after an interim analysis. CONCLUSION: Patients willingly completed the PRIME-MD and 54% had a PRIME-MD diagnosis. Unfortunately, at our institution, informing the patient (and physician) of the PRIME-MD results infrequently led to the patient being directed toward care for their psychiatric condition.