Disposition Outcomes Following Prehospital Use of Naloxone in a Large Metropolitan City in the United States.

OBJECTIVES: During a drug overdose, research suggests individuals may not call 9-1-1 out of fear of criminal justice concerns. Of those that call, research is inconclusive about the disposition of the emergency transport. We evaluated transport outcomes for adults with opioid-related overdose in the Emergency Medical Services (EMS) of a large metropolitan city in the United States. METHODS: We reviewed the EMS incident report database from the patient care record system for years 2018 to 2022. We queried all records, searching for relevant terms, and two reviewers cross-checked the database to identify cases that did not result in death at the scene. Study outcome was defined as hospital transportation or no transportation. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for hospital transport with patient age, sex, race and ethnicity as the independent variables. RESULTS: We identified 5,482 cases of nonfatal opioid-related overdose. Of these, 4,984 (90.9%) were transported to the hospital; 37 (0.7%) were placed in police custody; 304 (5.5%) were not transferred; and 157 (2.9%) had unknown outcomes. Among 5,288 with data on the transport outcome, the majority were male (65%), and the highest proportion were White (39%). Compared to those who were not transported, each 1-year increase in age was related to a 2% increase in the odds of transportation (OR: 1.02, 95% CI: 1.01-1.02). Compared to White patients, Black and Hispanic patients were 43% OR: 1.43, 95% CI: 1.07-1.90) and 44% (OR: 1.44, 95% CI: 1.03-2.00) more likely to be transported. CONCLUSIONS: Individuals with suspected opioid-related overdose who call 9-1-1 are most often transported to the hospital. Current EMS procedures are successful at on-scene treatment and transportation; however, data on the long-term impact of opioid-related overdoses are still needed.

County-level factors underlying opioid mortality in the United States.

BACKGROUND: Mortality from overdoses involving opioids in the United States (U.S.) has reached epidemic proportions. More research is needed to examine the underlying factors contributing to opioid-related mortality regionally. This study's objective was to identify and examine the county-level factors most closely associated with opioid-related overdose deaths across all counties in the U.S.Methods: Using a national cross-sectional ecological study design, we analyzed the relationships between 17 county-level characteristics in four categories (i.e. socio-economic, availability of medical care, health-related concerns, and demographics) with opioid mortality. Data were extracted from the Robert Wood Johnson County Health Rankings aggregate database and Centers for Disease Control and Prevention (CDC)'s Wide-ranging Online Data for Epidemiological Research (WONDER) system.Results: There were 1058 counties (33.67% of 3142 nationally) with reported opioid-related fatalities. Median opioid-related mortality was 15.61 per 100,000 persons. Multivariate regression results indicate that counties with the highest opioid-related mortality had increased rates of tobacco use, HIV, Non-Hispanic Caucasians, and females and were rural areas, but lower rates of food insecurity and uninsured adults. The rates of tobacco use and HIV had the strongest association with mortality. Availability of either mental health or primary care providers were not significantly associated with mortality. Severe housing problems, high school graduation rate, obesity, violent crime, and median household income also did not contribute to county-level differences in overdose mortality.Conclusions: Future health policies should fund further investigations and ultimately address the most influential and significant underlying county-level factors associated with opioid-related mortality.

A Framework for EMS Outreach for Drug Overdose Survivors: A Case Report of the Houston Emergency Opioid Engagement System.

OBJECTIVE: Fatalities from drug-induced overdoses in the United States have taken greater than 292,000 lives in the last five years, and nearly two-thirds of these are opioid-related. The burden on prehospital emergency medical services (EMS) to respond to these incidents is growing. The standard of care typically involves overdose reversal and rapid transport, although a few agencies have begun to use community paramedicine to more proactively follow-up, initiate treatment, and refer patients to addiction medicine providers. Methods: In this manuscript we share the details of an outreach case study to serve as a blueprint for other agencies and municipalities to adopt and refine. The University of Texas Health Science Center, in partnership with the Houston Fire Department and other local first responder agencies, developed a program in Houston, Texas based on rapid response to post-overdose survivors using available incident data from the primary municipal agencies. Results: The Houston Emergency Opioid Engagement System (HEROES) was created to more comprehensively address the opioid epidemic. By utilizing data extracted from the patient care record system, a team comprised of a peer recovery coach and a paramedic is dispatched to the home location of a recent overdose (OD) incident to provide outreach. Conclusions: Outreach dialog and motivational interviewing techniques are used to provide awareness of treatment options and to engage individuals into a treatment program. A case report of this program and recommendations for broader adoption are presented.

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the United States (US). Better cardiovascular health (CVH) is associated with CVD prevention. Predicting future CVH levels may help providers better manage patients' CVH. We hypothesized that CVH measures can be predicted based on previous measurements from longitudinal electronic health record (EHR) data. METHODS: The Guideline Advantage (TGA) dataset was used and contained EHR data from 70 outpatient clinics across the United States (US). We studied predictions of 5 CVH submetrics: smoking status (SMK), body mass index (BMI), blood pressure (BP), hemoglobin A1c (A1C), and low-density lipoprotein (LDL). We applied embedding techniques and long short-term memory (LSTM) networks - to predict future CVH category levels from all the previous CVH measurements of 216,445 unique patients for each CVH submetric. RESULTS: The LSTM model performance was evaluated by the area under the receiver operator curve (AUROC): the micro-average AUROC was 0.99 for SMK prediction; 0.97 for BMI; 0.84 for BP; 0.91 for A1C; and 0.93 for LDL prediction. Model performance was not improved by using all 5 submetric measures compared with using single submetric measures. CONCLUSIONS: We suggest that future CVH levels can be predicted using previous CVH measurements for each submetric, which has implications for population cardiovascular health management. Predicting patients' future CVH levels might directly increase patient CVH health and thus quality of life, while also indirectly decreasing the burden and cost for clinical health system caused by CVD and cancers.

Women and ethnoracial minorities with poor cardiovascular health measures associated with a higher risk of developing mood disorder.

BACKGROUND: Mood disorders (MDS) are a type of mental health illness that effects millions of people in the United States. Early prediction of MDS can give providers greater opportunity to treat these disorders. We hypothesized that longitudinal cardiovascular health (CVH) measurements would be informative for MDS prediction. METHODS: To test this hypothesis, the American Heart Association's Guideline Advantage (TGA) dataset was used, which contained longitudinal EHR from 70 outpatient clinics. The statistical analysis and machine learning models were employed to identify the associations of the MDS and the longitudinal CVH metrics and other confounding factors. RESULTS: Patients diagnosed with MDS consistently had a higher proportion of poor CVH compared to patients without MDS, with the largest difference between groups for Body mass index (BMI) and Smoking. Race and gender were associated with status of CVH metrics. Approximate 46% female patients with MDS had a poor hemoglobin A1C compared to 44% of those without MDS; 62% of those with MDS had poor BMI compared to 47% of those without MDS; 59% of those with MDS had poor blood pressure (BP) compared to 43% of those without MDS; and 43% of those with MDS were current smokers compared to 17% of those without MDS. CONCLUSIONS: Women and ethnoracial minorities with poor cardiovascular health measures were associated with a higher risk of development of MDS, which indicated the high utility for using routine medical records data collected in care to improve detection and treatment for MDS among patients with poor CVH.

Opioid prescribing patterns and overdose deaths in Texas.

BACKGROUND: Opioid use disorder has recently been declared a public health emergency, yet it is unknown whether opioid prescribing patterns have changed over time. Our objective is to examine opioid prescribing behavior and overdose fatalities in one large state prior to state-mandated usage of a prescription drug monitoring program (PDMP). Methods: We relied on de-identified longitudinal data from state and national databases for opioid prescriptions and overdose deaths in Texas between 2013 and 2017. Descriptive statistics and trend analyses were used to assess proportional differences and changes over time. Results: Prescriptions for opioids represented over 45% of the total controlled medications dispensed across the entire period. This equates to roughly 17.7 million opioid prescriptions dispensed per year, or 63.7 opioid prescriptions per 100 persons, slightly less than the reported national average. Hydrocodone was the most widely prescribed opioid (32.9%), followed by tramadol (26.9%) and codeine (21.5%). The overall controlled substance prescribing rate appears to be decreasing in the latest year, and the composition of opioids has shifted. We found a reduction in schedule II medications (such as hydrocodone and fentanyl) and increase in schedule IV medications such as tramadol. At the same time, total overdose fatalities increased 42% during this time, and population-adjusted rates increased 34% to 5.87 deaths per 100,000 persons. Conclusions: While prescribing rates have decreased in Texas, overdose deaths from both legal and illicit opioids are rising, suggesting that changing physician prescribing behavior alone may not be sufficient to curb the epidemic. Policies and community interventions should be considered to address increases in both prescription and illicit opioid deaths.

Telehealth Impact on Primary Care Related Ambulance Transports.

Introduction: Telehealth has been used nominally for trauma, neurological, and cardiovascular incidents in prehospital emergency medical services (EMS). Yet, much less is known about the use of telehealth for low-acuity primary care. We examine the development of one telehealth program and its impact on unnecessary ambulance transports. Objective: The objective of this study is to describe the development and impact of a large-scale telehealth program on ambulance transports. Methods: We describe the patient characteristics and results from a cohort of patients in Houston, Texas who received a prehospital telehealth consultation from an emergency medicine physician. Inclusion criteria were adults and pediatric patients with complaints considered to be non-urgent, primary care related. Data were analyzed for 36 months, from January 2015 through December 2017. Our primary dependent variable was the percentage of patients transported by ambulance. We used descriptive statistics to describe patient demographics, chi-square to examine differences between groups, and logistic regression to explore the effects with multivariate controls including age, gender, race, and chief complaint. Results: A total of 15,067 patients were enrolled (53% female; average age 44 years ± 19 years) over the three-year period. The 3 primary chief complaints were based on abdominal pains (13% of cases), nausea/vomiting/diarrhea (NVD) (9.4%), and back pain (9.3%). Ambulance transports represented 11.2% of all transports in the program, while alternative taxi transportation was used in 75.6%, and the remainder were self- or no-transports. Taxi transportation to an alternate, affiliated clinic (versus ED) was utilized in 5% of incidents. After multivariate controls, older age patients presenting with low-risk, non-acute chest pain, shortness of breath, and dizziness were much more likely to use ambulance transport. Race and gender were not significant predictors of ambulance transport. Conclusions: We found telehealth offers a technology strategy to address potentially unnecessary ambulance transports. Based on prior cost-effectiveness analyses, the reduction of unnecessary ambulance transports translates to an overall reduction in EMS agency costs. Telehealth programs offer a viable solution to support alternate destination and alternate transport programs.

Gender-based outcome differences for emergency department presentation ofnon-STEMI acute coronary syndrome.

BACKGROUND: It is known that women generally have worse mortality outcomes than men with regards to ST-segment elevation myocardial infarction. However, less is known about contemporary gender differences in non-STEMI acute coronary syndrome, particularly those presenting to emergency departments within a regionalized system of care with standardized protocols. METHODS: Retrospective registry data from 2010 to 2016 were examined from the North Texas Mission: Lifeline system of care, representing 33 hospitals around the Dallas Texas metropolitan area. We explored gender-based differences using multivariate logistic regression model, controlling for patient's age, baseline condition, and hospital factors. RESULTS: There were 16,861 patients who presented directly to emergency departments with NSTEMI, and 6513 (38.6%) were women. At baseline, women were older (68.04 vs. 63.7 years, p < 0.001) and presented with history of prior cardiovascular disease more often than men. Women had higher unadjusted in-hospital mortality rates than men (4.8% vs. 3.9%, p < 0.001), which persisted after controlling for patient age, comorbidities, and hospital factors. Women also had 23 min longer ED lengths of stay (p < 0.001) and were much less likely to receive an early invasive strategy (diagnostic coronary angiography within 24 h of arrival) than men (47.0% vs 54.4%, p < 0.001). CONCLUSION: Emergency department NSTEMI protocols should consider potential gender disparities that exist for women. Overall, women had worse outcomes, which persist even in an urban system of care with standardized protocols.

Exploring Business Strategy in Health Information Exchange Organizations.

Unlike consumer goods industries, healthcare has been slow to implement technolo gies that support exchange of data in patients' health records. This results in avoid able medication errors, avoidable hospital readmissions, unnecessary duplicate testing, and other inefficient or wasteful practices. Community-based regional health information exchange (HIE) organizations have evolved in response to federal aims to encourage interoperability, yet little is known about their strategic approach. We use the lens of institutional and strategic management theories to empirically explore the differences in business strategies deployed in HIEs that are, to date, financially sustainable versus those that are not. We developed a 20-question survey targeted to CEOs to assess HIE business strategies. Our sample consisted of 60 community-based exchanges distributed throughout the United States, and we achieved a 58% response rate. Questions centered on competitive strategy and financial sustainability. We relied on logistic regression methods to explore relationships between variables. Our regression identified characteristics common to sustainable organizations. We defined sustainability as revenues exceeding operational costs. Seventeen of the 35 organizations (49%) defined themselves as currently sustainable. Focus and cost leadership strategies were significantly associated with sustainability. Growth strate gies, which were much more common than other strategies, were not associated with sustainability. We saw little evidence of a differentiation strategy (i.e., the basis of competition whereby the attributes of a product or service are unmatched by rivals). Most CEOs had a relatively optimistic outlook, with 60% stating they were confident of surviving over the next 5 years; however, nearly 9% of the organizations were in some phase of divestiture or exit from the market. HIEs are evolving differently based on local leadership decisions, yet their strategic approach is isomorphic (or similar). Further insight into successful business strategies could help ensure the long-term survival of HIEs.

The effect of interhospital transfers, emergency medical services, and distance on ischemic time in a rural ST-elevation myocardial infarction system of care.

BACKGROUND: Regional myocardial infarction systems of care have been shown to improve timely access to primary percutaneous coronary intervention (PCI). However, there is a relatively sparse research on rural "frontier" regions. Arrival mode, high rates of interhospital transfers, long transport times, low population density, and mostly volunteer emergency medical services (EMS) distinguish this region from metropolitan systems of care. We sought to assess the effect of interhospital transfers, distance, and arrival mode on total ischemic times for patients with ST-elevation myocardial infarctions undergoing primary PCI. METHODS: We assessed patient data from our observational cohort of 395 patients with ST-elevation myocardial infarction with PCI as their primary treatment strategy. Data came from the 10 PCI hospitals participating in the Wyoming Mission: Lifeline program from January 2013 to September 2014. We performed both regression and tests of differences. RESULTS: Median total ischemic time was nearly 2.7 times greater in transferred patients than those presenting directly (379 vs 140 minutes). Distance in miles traveled between patient's home and PCI facility was 2.5 times larger in transfer patients (51 vs 20 miles). Emergency medical services arrival was associated with 23% shorter total ischemic times than self-arrival. CONCLUSIONS: Transfer patients from referral hospitals had significantly greater total ischemic time, and use of EMS was associated with significantly lower times. Transport distance was mixed in its effect. These findings suggest a continued focus on improving transitions between referral and receiving centers and enhancing coordination in rural systems of care to reduce the multiplier effect of transfers on total ischemic time.

Emergency medical services as a strategy for improving ST-elevation myocardial infarction system treatment times.

BACKGROUND: Reducing delays in time to treatment is a key goal of ST-elevation myocardial infarction (STEMI) emergency care. Emergency medical services (EMS) are a critical component of the STEMI chain of survival. STUDY OBJECTIVE: We sought to assess the impact of the careful integration of EMS as a strategy for improving systemic treatment times for STEMI. METHODS: We conducted a study of all 747 nontransfer STEMI patients who underwent primary percutaneous coronary intervention (PCI) in Dallas County, Texas from October 1, 2010 through December 31, 2011. EMS leaders from 24 agencies and 15 major PCI receiving hospitals collected and shared common, de-identified patient data. We used 15 months of data to develop a generalized linear regression to assess the impact of EMS on two treatment metrics-hospital door to balloon (D2B) time, and symptom onset to arterial reperfusion (SOAR) time, a new metric we developed to assess total treatment times. RESULTS: We found statistically significant reductions in median D2B (11.1-min reduction) and SOAR (63.5-min reduction) treatment times when EMS transported patients to the receiving facility, compared to self-transport. In addition, when trained EMS paramedics field-activated the cardiac catheterization laboratory using predefined specified protocols, D2B times were reduced by 38% (43 min) after controlling for confounding variables, and field activation was associated with a 21.9% reduction (73 min) in the mean SOAR time (both with p < 0.001). CONCLUSION: Active EMS engagement in STEMI treatment was associated with significantly lower D2B and total coronary reperfusion times.

How Financial Beliefs and Behaviors Influence the Financial Health of Individuals Struggling with Opioid Use Disorder.

The surge in opioid use disorder (OUD) over the past decade escalated opioid overdoses to a leading cause of death in the United States. With adverse effects on cognition, risk-taking, and decision-making, OUD may negatively influence financial well-being. This study examined the financial health of individuals diagnosed with OUD by reviewing financial beliefs and financial behaviors. We evaluated quality of life, perceptions of financial condition during active use and recovery, and total debt. We distributed a 20-item survey to 150 individuals in an outpatient treatment program for OUD in a large metropolitan area, yielding a 56% response rate. The results revealed low overall financial health, with a median debt of USD 12,961 and a quality-of-life score of 72.80, 9.4% lower than the U.S. average (82.10). Most participants (65.75%) reported improved financial health during recovery, while a higher majority (79.45%) worsened during active use. Unemployment affected 42% of respondents, and 9.52% were employed only part-time. Regression analysis highlighted a strong association between lack of full-time employment and a lack of financial advising with total debt. High financial anxiety and active use were associated with lower quality of life. Individuals with OUD may benefit from financial interventions, resources, and counseling to improve their financial health.

The Impact of COVID-19 on the Financial Performance of Largest Teaching Hospitals.

The COVID-19 pandemic disrupted hospital operations. Anecdotal evidence suggests financial performance likewise suffered, yet little empirical research supports this claim. This study aimed to explore the impact of the pandemic on the financial performance of the most prominent academic hospitals in the United States. Data from the 115 largest major teaching hospitals in the United States were extracted from the American Hospital Directory for three years (2019-2021). We hypothesized that the year and region would moderate the relationship between a hospital's return on assets (financial performance) and specific operational variables. We found evidence through descriptive statistics and multivariate moderated regressions that financial positions rebounded in 2021, mainly through reductions in adjusted full-time employees and liabilities and an increase in non-operating income. Our results also found that the Midwest region significantly outperformed the other three regions, particularly in terms of lower salaries and operational expenses. These findings suggest potential for future initiatives encouraging efficiency and finding alternate sources of income beyond patient income. Hospitals should focus on improving financial reserves, building out non-operational revenue streams, and implementing operational efficiencies to foster better financial resiliency. These suggestions may enable healthcare administrators and facilities to adapt to future pandemics and environmental turbulence.

Longitudinal changes in the operating efficiency of public safety-net hospitals.

Government-operated trauma facilities fill an important role as safety nets in our health system, providing care to millions of individuals who lack health insurance. Because these hospitals are often the most financially constrained, continuous improvement in operating efficiency seems to be a necessary component of their organizational strategy. In this study, we analyze the longitudinal changes in efficiency of a large sample of government-operated safety-net hospitals from 2004 to 2008. Employing an analytical tool called data envelopment analysis, our findings suggest that as a group these hospitals have become more efficient over time, improving by 2.1 percent over the five-year study period.

The impact of chief executive officer optimism on hospital strategic decision making.

BACKGROUND: Previous strategic decision making research has focused mostly on the analytical positioning approach, which broadly emphasizes an alignment between rationality and the external environment. In this study, we propose that hospital chief executive optimism (or the general tendency to expect positive future outcomes) will moderate the relationship between comprehensively rational decision-making process and organizational performance. PURPOSE: The purpose of this study was to explore the impact that dispositional optimism has on the well-established relationship between rational decision-making processes and organizational performance. Specifically, we hypothesized that optimism will moderate the relationship between the level of rationality and the organization's performance. We further suggest that this relationship will be more negative for those with high, as opposed to low, optimism. METHODS: We surveyed 168 hospital CEOs and used moderated hierarchical regression methods to statically test our hypothesis. FINDINGS: On the basis of a survey study of 168 hospital CEOs, we found evidence of a complex interplay of optimism in the rationality-organizational performance relationship. More specifically, we found that the two-way interactions between optimism and rational decision making were negatively associated with performance and that where optimism was the highest, the rationality-performance relationship was the most negative. Executive optimism was positively associated with organizational performance. We also found that greater perceived environmental turbulence, when interacting with optimism, did not have a significant interaction effect on the rationality-performance relationship. PRACTICE IMPLICATIONS: These findings suggest potential for broader participation in strategic processes and the use of organizational development techniques that assess executive disposition and traits for recruitment processes, because CEO optimism influences hospital-level processes. Research implications include incorporating greater use of behavior and cognition constructs to better depict decision-making processes in complex organizations like hospitals.

Sociodemographic and Clinical Characteristics Associated with Improvements in Quality of Life for Participants with Opioid Use Disorder.

BACKGROUND: The Houston Emergency Opioid Engagement System was established to create an access pathway into long-term recovery for individuals with opioid use disorder. The program determines effectiveness across multiple dimensions, one of which is by measuring the participant's reported quality of life (QoL) at the beginning of the program and at successive intervals. METHODS: A visual analog scale was used to measure the change in QoL among participants after joining the program. We then identified sociodemographic and clinical characteristics associated with changes in QoL. RESULTS: 71% of the participants (n = 494) experienced an increase in their QoL scores, with an average improvement of 15.8 ± 29 points out of a hundred. We identified 10 factors associated with a significant change in QoL. Participants who relapsed during treatment experienced minor increases in QoL, and participants who attended professional counseling experienced the largest increases in QoL compared with those who did not. CONCLUSIONS: Insight into significant factors associated with increases in QoL may inform programs on areas of focus. The inclusion of counseling and other services that address factors such as psychological distress were found to increase participants' QoL and success in recovery.

Machine Learning for Predicting Risk of Early Dropout in a Recovery Program for Opioid Use Disorder.

BACKGROUND: An increase in opioid use has led to an opioid crisis during the last decade, leading to declarations of a public health emergency. In response to this call, the Houston Emergency Opioid Engagement System (HEROES) was established and created an emergency access pathway into long-term recovery for individuals with an opioid use disorder. A major contributor to the success of the program is retention of the enrolled individuals in the program. METHODS: We have identified an increase in dropout from the program after 90 and 120 days. Based on more than 700 program participants, we developed a machine learning approach to predict the individualized risk for dropping out of the program. RESULTS: Our model achieved sensitivity of 0.81 and specificity of 0.65 for dropout at 90 days and improved the performance to sensitivity of 0.86 and specificity of 0.66 for 120 days. Additionally, we identified individual risk factors for dropout, including previous overdose and relapse and improvement in reported quality of life. CONCLUSIONS: Our informatics approach provides insight into an area where programs may allocate additional resources in order to retain high-risk individuals and increase the chances of success in recovery.

The Impact of Pediatric Opioid-Related Visits on U.S. Emergency Departments.

BACKGROUND: While there is significant research exploring adults' use of opioids, there has been minimal focus on the opioid impact within emergency departments for the pediatric population. METHODS: We examined data from the Agency for Healthcare Research, the National Emergency Department Sample (NEDS), and death data from the Centers for Disease Control and Prevention. Sociodemographic and financial variables were analyzed for encounters during 2014-2017 for patients under age 18, matching diagnoses codes for opioid-related overdose or opioid use disorder. RESULTS: During this period, 59,658 children presented to an ED for any diagnoses involving opioids. The majority (68.5%) of visits were related to overdoses (poisoning), with a mean age of 11.3 years and a majority female (53%). There was a curvilinear relationship between age and encounters, with teens representing the majority of visits, followed by infants. The highest volume was seen in the Southern U.S., with over 58% more opioid visits than the next highest region (Midwest). Charges exceeded USD 157 million, representing 2% of total ED costs, with Medicaid responsible for 54% of the total. CONCLUSIONS: With increases in substance use among children, there is a growing need for pediatric emergency physicians to recognize, refer, and initiate treatments.

Eligibility of out-of-hospital cardiac arrest patients for extracorporeal cardiopulmonary resuscitation in the United States: A geographic information system model.

BACKGROUND: Recent evidence suggest that extracorporeal cardiopulmonary resuscitation (ECPR) may improve survival rates for nontraumatic out-of-hospital cardiac arrest (OHCA). Eligibility criteria for ECPR are often based on patient age, clinical variables, and facility capabilities. Expanding access to ECPR across the U.S. requires a better understanding of how these factors interact with transport time to ECPR centers. METHODS: We constructed a Geographic Information System (GIS) model to estimate the number of ECPR candidates in the U.S. We utilized a Resuscitation Outcome Consortium (ROC) database to model time-dependent rates of ECPR eligibility and the Cardiac Arrest Registry to Enhance Survival (CARES) registry to determine the total number of OHCA patients who meet pre-specified ECPR criteria within designated transportation times. The combined model was used to estimate the total number of ECPR candidates. RESULTS: There were 588,203 OHCA patients in the CARES registry from 2013 to 2020. After applying clinical eligibility criteria, 22,104 (3.76%) OHCA patients were deemed eligible for ECPR. The rate of ROSC increased with longer resuscitation time, which resulted in fewer ECPR candidates. The proportion of OHCA patients eligible for ECPR increased with older age cutoffs. Only 1.68% (9,889/588,203) of OHCA patients in the U.S. were eligible for ECPR based on a 45-minute transportation time to an ECMO-ready center model. CONCLUSIONS: Less than 2% of OHCA patients are eligible for ECPR in the U.S. GIS models can identify the impact of clinical criteria, transportation time, and hospital capabilities on ECPR eligibility to inform future implementation strategies.