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Introduction: Patients who doctor shop for opioids are a vulnerable population that present a difficult dilemma for their health care providers regarding best methods of immediate treatment and how to manage their risk of harm from opioids. We aim to describe and compare opioid prescription patterns among high quantity prescription patients who doctor shopped, high quantity prescription patients who did not (doctor shopping eligible patients), and the remaining patients who received opioid prescriptions to guide population health policies for high risk opioid use patients. Methods: We performed a cross-sectional descriptive analysis of opioid prescriptions during an 8-year period using California's de-identified Controlled Substance Utilization Review and Evaluation System (CURES) database from years 2008–2015. We identified the prevalence of patients who doctor shopped and depicted their opioid prescription patterns including prescriber characteristics, in comparison to the aforementioned groups. Doctor shopping was defined by patients who received greater than 6 or more prescriptions from at least 6 different prescribers within 6 months of time. Results: Among the 3 million individuals who received an opioid prescription during the 8-year period, 1.3% met the doctor shopper definition. These patients received high levels of chronic opioids with 82% and 33% averaging greater than 20 and 100 morphine milligram equivalents (MME) daily, respectively, in comparison to 72% and 18% in the doctor shopping eligible group. Patients who doctor shopped received a significant proportion of their MME from 1 main prescriber (54%) and only received 2–5% of their total MME from episodic care providers, despite 88% receiving a prescription from these providers. Conclusions: Patients who doctor shop are at high risk of opioid use disorder but represent a small fraction of those with dangerous opioid use. Furthermore, these individuals do not receive substantial opioids from episodic providers, which challenges the utility of prescription reduction programs in curbing use among this population. These results suggest we re-evaluate physician roles in the care of these patients and focus on referral to treatment and harm reduction strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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Background: Accurately 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.Objective: The 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.Methods: A 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.Results: The 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.Conclusions: A 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. [ABSTRACT FROM AUTHOR]

Importance: Knowledge of medical care in US Immigration and Customs Enforcement (ICE) detention centers is limited. Reviews show high rates of preventable deaths while in detention due to substandard medical care within detention centers., Objective: To describe characteristics of medical emergencies at ICE detention centers in California., Design, Setting, and Participants: This cross-sectional study analyzed emergency medical services (EMS)-reported medical emergencies activated through 911 from January 1, 2018, to December 31, 2022, at 3 of the 5 ICE detention centers in California: Adelanto ICE Processing Center, Imperial Regional Detention Facility, and Otay Mesa Detention Center., Exposure: Medical services requiring 911 activation., Main Outcomes and Measures: Data included the number of EMS-reported medical emergencies; ICE-reported medical emergencies; patient age and sex; and medical data in the EMS report, including primary symptom, EMS provider (emergency medical technician or paramedic) impression, vital signs, and interventions performed, using descriptive statistics., Results: In this analysis of 3 detention centers with a mean daily census of 775 (range, 504-1001) individuals per center, there was a median of 68 (IQR, 10-88) EMS-reported emergencies per center per year for a total of 1224 emergencies. The EMS-reported emergencies involved 881 males (72%) and 338 females (28%) with a median age of 39.0 (IQR 30.0-49.0) years. The ratios of female-to-male EMS-reported emergencies were 0.51 (95% CI, 0.31-0.87) at Adelanto, 0.86 (95% CI, 0.31-2.43) at Imperial, and 1.60 (95% CI, 1.40-1.83) at Otay Mesa. Pregnancy-related emergencies accounted for 12.4% (42 of 338) of emergencies in females. A total of 357 individuals (29.2%) had at least 1 abnormal vital sign during their EMS encounter. Psychiatric emergencies comprised 48 EMS responses (3.9%), despite higher rates of ICE-reported psychiatric-related complaints. The median number of monthly EMS-reported emergencies across all 3 centers was 3 (IQR, 0-9) vs 4 ICE-reported emergencies (IQR, 1-15)., Conclusions and Relevance: In this study of medical emergencies at 3 of 5 ICE detention facilities in California, there were discrepancies in EMS vs ICE reported emergencies. The data suggested that vulnerable populations, such as pregnant women, had an increased number of medical emergencies, while individuals with psychiatric emergencies accounted for fewer reported emergencies. Based on these findings, emergency medical care provision in ICE detention centers requires increased transparency to ensure appropriate delivery of care.

Importance: Most 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., Objective: To 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 Participants: This 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., Exposures: A total of 1760 zip code tabulation areas (ZCTAs) in California, with associated racial/ethnic composition and per capita income., Main Outcomes and Measures: The percentage of individuals receiving at least 1 prescription each year was calculated for opioids, benzodiazepines, and stimulants., Results: A 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 Relevance: The 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.

Importance: Since September 2017, standing electric scooters have proliferated rapidly as an inexpensive, easy mode of transportation. Although there are regulations for safe riding established by both electric scooter companies and local governments, public common use practices and the incidence and types of injuries associated with these standing electric scooters are unknown., Objective: To characterize injuries associated with standing electric scooter use, the clinical outcomes of injured patients, and common use practices in the first US metropolitan area to experience adoption of this technology., Design, Setting, and Participants: This study of a case series used retrospective cohort medical record review of all patients presenting with injuries associated with standing electric scooter use between September 1, 2017, and August 31, 2018, at 2 urban emergency departments associated with an academic medical center in Southern California. All electric scooter riders at selected public intersections in the community surrounding the 2 hospitals were also observed during a 7-hour observation period in September 2018., Main Outcomes and Measures: Incidence and characteristics of injuries and observation of riders' common use practices., Results: Two hundred forty-nine patients (145 [58.2%] male; mean [SD] age, 33.7 [15.3] years) presented to the emergency department with injuries associated with standing electric scooter use during the study period. Two hundred twenty-eight (91.6%) were injured as riders and 21 (8.4%) as nonriders. Twenty-seven patients were younger than 18 years (10.8%). Ten riders (4.4%) were documented as having worn a helmet, and 12 patients (4.8%) had either a blood alcohol level greater than 0.05% or were perceived to be intoxicated by a physician. Frequent injuries included fractures (79 [31.7%]), head injury (100 [40.2%]), and contusions, sprains, and lacerations without fracture or head injury (69 [27.7%]). The majority of patients (234 [94.0%]) were discharged home from the emergency department; of the 15 admitted patients, 2 had severe injuries and were admitted to the intensive care unit. Among 193 observed electric scooter riders in the local community in September 2018, 182 (94.3%) were not wearing a helmet., Conclusions and Relevance: Injuries associated with standing electric scooter use are a new phenomenon and vary in severity. In this study, helmet use was low and a significant subset of injuries occurred in patients younger than 18 years, the minimum age permitted by private scooter company regulations. These findings may inform public policy regarding standing electric scooter use.

Study Objective: We determine episodic and high-quantity prescribers' contribution to opioid prescriptions and total morphine milligram equivalents in California, especially among individuals prescribed large amounts of opioids., Methods: This was a cross-sectional descriptive analysis of opioid prescribing patterns during an 8-year period using the de-identified Controlled Substance Utilization Review and Evaluation System (CURES) database, the California subsection of the prescription drug monitoring program. We took a 10% random sample of all patients and stratified them by the amount of prescription opioids obtained during their maximal 90-day period. We identified "episodic prescribers" as those whose prescribing pattern included short-acting opioids on greater than 95% of all prescriptions, fewer than or equal to 31 pills on 95% of all prescriptions, only 1 prescription in the database for greater than 90% of all patients to whom they gave opioids, fewer than 6 prescriptions in the database to greater than 99% of patients given opioids, and fewer than 540 prescriptions per year. We identified top 5% prescribers by their morphine milligram equivalents per day in the database. We examined the relationship between patient opioid prescriptions and provider type, with the primary analysis performed on the patient cohort who received only short-acting opioids in an attempt to avoid guideline-concordant palliative, oncologic, and addiction care, and a secondary analysis performed on all patients., Results: Among patients with short-acting opioid only, episodic prescribers (14.6% of 173,000 prescribers) wrote at least one prescription to 25% of 2.7 million individuals but were responsible for less than 9% of the 10.5 million opioid prescriptions and less than 3% of the 3.9 billion morphine milligram equivalents in our sample. Among individuals with high morphine milligram equivalents use, episodic prescribers were responsible for 2.8% of prescriptions and 0.6% of total morphine milligram equivalents. Conversely, the top 5% of prescribers prescribed at least 29.8% of prescriptions and 48.8% of total morphine milligram equivalents, with a greater contribution in patients with high morphine milligram equivalents., Conclusion: Episodic prescribers contribute minimally to total opioid prescriptions, especially among individuals categorized as using high morphine milligram equivalents. Interventions focused on reducing opioid prescriptions in the episodic care setting are unlikely to yield important reductions in the prescription opioid supply; conversely, targeting high-quantity prescribers has the potential to create substantial reductions., (Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

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., (Project HOPE—The People-to-People Health Foundation, Inc.)