Firearm injuries treated at trauma centers in the United... : Journal of Trauma and Acute Care Surgery (2024)

Firearm injuries and deaths continue to be a major public health problem, resulting in 48,830 deaths in the United States in 2021, of which 53.8% were suicides and 42.9% were homicides.¹ However, the number of nonfatal firearm injuries and the characteristics of patients and injuries are not well-known, as documented by a recent report from NORC at the University of Chicago.² Existing systems including the Centers for Disease Control and Prevention (CDC) Web-based Injury Statistics Query and Reporting System (WISQARS)³ and the Healthcare Cost and Utilization Project (HCUP) of the Agency for Healthcare Research and Quality⁴ are significantly limited in surveillance and in the collection of data including estimated incidence of nonfatal firearm injuries, clinical data, individual risk factors, circ*mstances surrounding injuries, and community-level social determinants of firearm injuries. Centers for Disease Control and Prevention WISQARS nonlethal injury data and HCUP use probability estimates from US hospitals from samples to generate estimates of nonlethal firearm injuries. Centers for Disease Control and Prevention WISQARS nonlethal firearm data are recognized as unreliable with wide ranges of estimates, and HCUP uses administrative and billing coding to identify cases, which poorly describes the intent, precise mechanism, and nature of injuries. The Expert Panel on Firearms Data Infrastructure called for the creation of “valid and reliable administrative data systems for tracking nonfatal gunshot injuries.”⁵

These databases do not collect or report on clinical information such as severity of injuries and their outcomes, nor do they provide data that better contextualize injuries including community characteristics, individual risk factors, comorbid illnesses, substance abuse or mental illness, life stressors, prior violent injuries or suicide attempts, how or why firearms are accessed or obtained for suicide attempts, circ*mstances preceding injury, and victim-perpetrator relationships. It is recognized that these data are critically important to provide insights into why such injuries occur, modifiable risk factors, and potential interventions. For this reason, mechanisms to capture these data have been developed through the CDC National Violent Death Reporting System⁶ but are limited to injuries that result in death. Given the large proportion of firearm assault and unintentional injuries that are nonlethal (approximately 89%),⁷ this is a significant limitation and has the potential to significantly bias our understanding of risk factors and the circ*mstances surrounding the firearm injury event and therefore limits our understanding of potential interventions to prevent reinjury or death. By contrast, approximately 10% of firearm suicide attempts are nonlethal.

Aggregated data generated from probability estimates such as those currently available with WISQARS and HCUP also preclude detailed analysis of nonlethal firearm injuries at the community or neighborhood level. This limits our understanding of risk factors in communities that may be associated with nonlethal firearm assaults, how they significantly differ between geographic areas, and what community level social determinants of violence might be modified by local interventions and policies. This is especially important in concentrated urban areas of firearm assaults where most victims in the US sustain nonlethal firearm injuries and where focused interventions could be used to address community risk factors that contribute to the circ*mstances impacting violence.

To address these needs, the American College of Surgeons (ACS) Committee on Trauma, with support from the National Collaborative on Gun Violence Research, leveraged an existing data system to capture nonlethal injuries, including patients treated and discharged from the emergency department (ED), and to collect additional data on patients who present with firearm injuries to trauma centers in the United States. Our goal was to capture additional information at the patient level pertaining to the context of the incident (e.g., setting, circ*mstances, perpetrator, and other pertinent data) that might direct prevention initiatives. This report describes the effort and provides overall results of this expanded data collection on firearm injured treated at a group of US trauma centers.

PATIENTS AND METHODS

The ACS Trauma Quality Improvement Program (TQIP) collects data for the purposes of performance benchmarking from more than 700 centers, representing more than 800 distinct trauma programs, across the United States, capturing an estimated 90% to 95% of all levels 1 and 2 (major trauma centers) and a less comprehensive sample of level 3 trauma centers. Prior studies indicate that verified and/or designated trauma centers care for approximately 70% of medically treated firearm injuries in the United States.⁸ Data collected are specified in the National Trauma Data Standard (https://www.facs.org/quality-programs/trauma/quality/national-trauma-data-bank/national-trauma-data-standard/) and include patient and injury characteristics, processes of care, and outcomes among all patients admitted, transferred to that center, or who died in hospital. Notably, before this initiative, the ACS TQIP only collected data on people with firearm injuries who met these criteria; patients assessed in the ED and discharged home would not routinely be captured.

Centers participating in TQIP were offered the opportunity to participate in this study. We provisionally enrolled 165 trauma centers to participate in this program; 128 ultimately contributed data (see list of people and centers who agreed to be listed in the acknowledgments). Centers had to participate in ACS TQIP over the duration of the study and agreed to collect data elements listed hereinafter on all individuals treated with firearm injuries (including those discharged alive from the ED). Centers were not provided any funding to support additional data collection. Centers were recruited through electronic mailings to the trauma directors in all ACS TQIP centers, holding a webinar for potential centers, ACS Committee on Trauma newsletters, and direct contact by study investigators with trauma directors.

This was a cross-sectional study that follows the STrengthening the Reporting of OBservational studies in Epidemiology guidelines, included in Supplemental Digital Content (Supplementary Data 1, https://links.lww.com/TA/D323).

Study Population

Patients eligible for the study were individuals of any age arriving alive at a participating trauma center between March 1, 2021, and February 28, 2022, who had sustained an injury due to a firearm. The study was approved by Advarr CIRBI.

Data Abstraction

Data were abstracted from the electronic health record (EHR) by trained personnel at each trauma center including registrars, clinicians, and research staff. In addition to the standard data collected for TQIP, the abstractors also extracted available additional data specific to this study. This new data included the following (Supplemental Digital Content, Supplementary Data 2, https://links.lww.com/TA/D324):

• Demographic characteristics: education, military status, and caregivers (pediatric patients);
• Risk factors: illicit substance use and intoxication, history of or newly identified/diagnosed mental illness, prior arrests/involvement in the criminal justice system, adverse child experiences;
• Circ*mstances: context/preceding events (assaults: altercation, commission of a crime, drug or gang-related, bystander, mass violence, intimate partner violence, child abuse; suicide attempts: life stressors, declining mental illness, terminal medical illness, suicide-homicides; unintentional: playing, cleaning, handling, hunting, accidental discharge when unaware of firearm presence), specific location of injury occurrence, perpetrator-victim relationships;
• Firearms (for self-inflicted and unintentional injuries): type implicated in the injury, ownership, access and storage at time of the incident (for self-inflicted and unintentional injuries);
• Functional outcomes and medical needs at time of discharge.

The direction provided to centers was to collect these data from the emergency medical services, ED, or inpatient medical record. There was no expectation for additional interview of patients to capture data that were not otherwise routinely collected during the course of care.

Together, this study required two modifications to existing data collection for trauma centers: (1) expanded inclusion criteria to capture patients discharged from the ED and (2) expanded data collection to provide additional information on the context of firearm injuries.

Data Analysis

Emergency department disposition was collapsed from 11 categories into 7: discharged alive/left against medical advice (home with services, home without services, left against medical advice), admitted to the operating room, admitted to the intensive care unit, admitted to the floor or observation unit (floor bed; observation unit, telemetry/step down unit), died in the ED, transferred to another facility, and other.

Injury setting was collapsed from 32 categories into 8: residence (house, apartment, rooming house; supervised residential facility; hotel/motel), school/childcare (elementary school, middle school; high school; college/university; unspecified school; childcare center, daycare, preschool), motor vehicle (motor vehicle; school bus), street (street/road, sidewalk, alley; highway, freeway; parking lot/public parking garage; bridge; railroad tracks), natural area (natural area; park, playground, public use area; cemetery, graveyard, or other burial ground; farm), public transit (public transportation or station), commercial area (bar, nightclub; service station; bank, credit union, ATM location; liquor store; other commercial establishment; office building; sports or athletic arena; synagogue, church, temple; hospital or medical facility), and other (abandoned house, building, or warehouse; jail, prison, detention facility; industrial or construction areas). Primary method of payment was collapsed from six categories into four: Medicaid/other government, self-pay/not billed/other, private/commercial insurance, and Medicare.

The relationship to shooter variable was also collapsed so that those who indicated being shot by a friend, family member, or coworker were grouped together. Race, firearm type, employment status, and injury intent variables were all variables in which more than one choice could be selected by the coders and were recoded to ease interpretation. Patients who were reported to have more than one racial category were grouped together, as were patients who were reported to have been injured by more than one firearm type. Any patient coded as both “unreported employment” and another employment status were coded as other employment status. Patients coded as “unemployed” and “student” were categorized as “student,” those coded with both “unemployed” and “retired” were categorized as “retired,” those coded with “disabled” and any other category were categorized as “disabled,” and those coded as “employed” and “retired” were categorized as “employed.” A new category, “working student,” was created for those who selected “employed” and “student.” Patients younger than 19 years did not have employment status information collected.

A binary variable was created for the prior suicide attempt/self-harm variable to indicate whether a patient had any suicidal ideation or previously self-harm incidents (any vs. none). However, those who were coded with more than one ideation were included in each category selected. The same approach was taken with the mental illness variable. Patients with at least one of the mental illnesses listed (major depression, anxiety, bipolar disorder, posttraumatic stress disorder, schizophrenia, obsessive-compulsive disorder, eating disorder, personality disorder, attention deficit disorder/attention deficit hyperactivity disorder, or other) were categorized as having at least one mental illness. Those who had missing values across all mental illness variables were marked as missing. Among those coded with at least one mental illness, the total number of illnesses selected was calculated (1, 2, or ≥3). Among those who had at least one mental illness, patients were coded in each category of mental illness as appropriate. To calculate average blood alcohol content, only patients who were marked as “yes” or “suspected” in the alcohol preinjury variable and had a blood alcohol content of greater than 0 were included.

Postdischarge service variables (rehabilitation/postdischarge needs, home health needs, and psychosocial ancillary services) were also “select all that apply” variables; within each postdischarge service variable, those with more than one service were counted in each category that was applicable (nonmutually exclusive categories).

To provide additional context around the patient and injury, we linked data from the Distressed Communities Index (DCI) to patient records meeting our inclusion criteria. The DCI is a validated index of prosperity developed by the Economic Innovation Group that includes variables related to education, housing, unemployment, poverty, and changes in business establishments. The scale ranges from 0 to 100 and is sorted into quintiles with the highest scores representing the most distressed communities. Distressed Communities Index data are publicly available and uses the US Census Bureau's American Community Survey 5-Year Estimates and the Census Bureau's Business Pattern's data set for 2016 and 2020.⁹

All data cleaning and tables were done in RStudio 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

There were 128 trauma centers that participated in this 12-month study, representing 17.25% of TQIP centers. Participating centers had a significantly higher volume of annual trauma admissions, were much more likely to be level I centers (73.3% vs. 25.5%), and were more likely to have pediatric capabilities compared with nonparticipating centers (Table 1). Participating centers were somewhat more likely to be located in the Midwest and less likely to be in the West census regions (see map in Supplemental Digital Content, Supplementary Data 3, https://links.lww.com/TA/D325).

There were a total of 17,395 patients included in the study population. They had a mean (SD) age of 30.2 (13.5) years, 82.5% were male, and the majority were Black and non-Hispanic (Table 2). Nearly half were insured by Medicaid, and over one quarter were uninsured. Only 24.0% were employed, and only 1.3% were noted to be veterans. A prior history of being shot or sustaining a nonfirearm assault injury was recorded in only a small proportion of patients, as was a history of prior suicidality or prior traumatic events. However, for those in whom it was known, 5.7% had been previously shot, and 47.1% had a prior suicide attempt. History of any mental illness was reported in 12.3% of patients overall, and 17.6% of those with the exclusion of missing/unknown, most commonly depression or anxiety. Of those with any mental illness recorded, 38.8% had more than one type reported.

Injuries were reported to have occurred most commonly in homes (31.2%) or on the street (26.6%), but 10.0% were reported to occur in motor vehicles and 9.0% in a commercial space (Table 3). Among those tested for alcohol, one quarter were positive, and alcohol use was suspected in 21.1%; in those in whom it was tested, the mean was 0.14 g/L. The majority (70.4%) of injuries were due to assaults, of which half were coded as being related to community violence, 18.3% as interpersonal violence, and 14.0% as random violence. Only 4.3% of firearm injuries were reported as intentionally self-inflicted in a suicide attempt, of whom 31.4% were reported to be intoxicated at the time and 15.6% were injured as part of a murder-suicide event. The majority of unintentional injuries were reported to be caused by handling the firearm. The relationship of victim to shooter was reported in only 56.1% of cases and was most commonly recorded as a stranger. The firearm type was nearly all handgun, but this was missing in more than half of cases.

Patients most commonly arrived by ground ambulance, although 19.0% did arrive by nonemergency means, primarily by private vehicle (Table 4). Nearly one third of patients were discharged from the ED, 25.9% were transferred directly to the operating room from the ED, and 10.9% were admitted to the intensive care unit; 5.9% died in the ED, and 10.3% died overall during their course of care. The mean Injury Severity Score (ISS) was 10.2, and nearly half had an ISS of 9 or greater. Initial ED evaluation indicated shock in 10.3%, and 11.5% had hemorrhage control surgery, most commonly with a laparotomy. Among those admitted, the mean length of stay was 7.9 days. Only 26.0% of patients discharged alive received any discharge services, most commonly social work or violence intervention services.

As shown in Table 5, 64.2% of patients lived in the two highest distressed quintiles of communities; only 7.5% lived in the least distressed quintile.

We also examined the association of missingness in key variables by whether patients were admitted to the hospital. As shown in Figure 1, the mean proportion of variables with missing data varied greatly among trauma centers, with a mean of 20.7% missing data. Patients not admitted had more missing data for prior arrest history, prior suicidality, prior traumatic events, toxicology and alcohol data, mental health history, ISS, and Abbreviated Injury Scale.

DISCUSSION

In this 12-month study involving 128 trauma centers, 17,395 patients were treated for firearm injuries, of whom one third of all patients were discharged alive from the ED, and overall 1 in 10 died. The majority of the injuries were due to assaults, and individuals were most commonly injured in their homes or on the street. The majority of patients lived in distressed communities and were Black or Hispanic. Only one in four patients received any discharge services. These findings reflect the known disproportionate burden of nonfatal firearm injuries notably due to assault among Black and Hispanic communities and contribute to the growing body of literature that demonstrates that firearm violence often concentrates in areas with higher social vulnerability and socioeconomic disparity.^10–13

This represents the largest study of patients treated for firearm injuries in trauma centers and differs from many prior studies by the inclusion of patients treated and released from the ED and those admitted for further care or who died in the ED. The fact that one third of all patients with firearm injuries treated at trauma centers were discharged from the ED indicates that prior studies relying just on hospitalization data are missing a large portion of overall firearm problem. It therefore provides a more complete picture of firearm injuries in the United States and complements the data available from the CDC on fatal firearm injuries.¹ These patients represent an injury and violence intervention opportunity for trauma centers that may not be presently addressed.

The initial intent of this study was to collect more detailed richer data on the individuals who were shot and treated at trauma centers, including the circ*mstances around these injuries. As shown in the tables, there was a large amount of missing data for many of those variables, indicating the amount of work and resources needed to comprehensively track and treat these patients. Common items such as sex, race, ethnicity, and insurance status were missing in 3.3% to 5.2% of cases despite this being usually collected in the EHR. Employment was unknown in over one quarter of cases, and unemployment is a strong risk factor for subsequent firearm injury mortality.¹⁴ Veteran status, one of the most important risk factors for firearm suicide,¹⁵ was missing in nearly half of cases. History of prior gunshot wounds, assault, or suicidality, all known risk factors for firearm injury and injury recidivism,¹⁶ were missing in the majority of patients. History of prior mental illness was not known in nearly one third of patients. The fact that 5.9% of patients died in the ED and a total of 10.3% of patients died or were transferred to hospice likely contributed to some of the missingness, as these patients are often not able to communicate their histories because of injury severity and the clinical teams are focusing efforts on preserving life. Missingness also varied by admission status for some but not all the variables with sizeable amount of missing data.

Having access to these data is central to providing quality of care to patients treated for gunshot wounds. While some of this information may have been present in the EHR, this information is likely to be distributed across several providers' notes and across several days from physicians, nurses, social workers, consultants, and other staff, thus making abstraction more difficult. That, however, may not likely be the case, given that dedicated trauma personnel searched the medical record in this study for this information. More likely, the missingness might reflect that much of these data are not routinely captured during the course of care by the health care team and so does not find its way into the medical record. Other possible reasons for the absence of this information are that the data are considered insufficiently important to document, as they may be perceived to not affect patient care or there may be patient and/or staff concern about documentation about the event that may have legal implications.

Surgeons and other health care professionals have been very involved in addressing the firearm epidemic and have acknowledged the need to provide more than surgical/medical care of the injuries and wounds.^17–24 To go beyond this aspirational goal, information should be collected on a routine basis as a part of clinical care and documented in a standardized way for teams treating firearm-injured patients to provide focused interventions and support and to direct and inform prevention initiatives. Standardization also removes potential biases that victims of violence and injury may face in their care. We suggest that teams caring for firearm-injured patients routinely collect information on all patients such as prior mental health and substance abuse, veteran status, prior injuries, and current and past suicidality. These facts in a patient's history are important in delivering trauma-informed care. Assessment of such information and documentation may require education of frontline clinicians and other team members such as violence intervention professionals and social workers on the utility of the information and methods of ascertaining it in trauma-informed ways.

It is noteworthy that only 12% of patients received subsequent violence prevention efforts, which may represent either a lack of these resources or selective offering to targeted patient populations. Hospital-based violence prevention programs require substantial resources that are not reimbursed by insurers and require an ongoing hospital-community partnership to be effective. These hospital-based and community violence prevention programs in which firearm victims are linked to longer-term services in the community hold important promise to reducing violence and injury recidivism and should be widely offered at trauma centers.¹⁷ Programs like the Health Alliance for Violence Intervention and firearm injury research centers around the country are actively fostering such efforts.

This study does have important limitations. First, many patients with firearm injuries die at the scene, especially those who used a firearm to attempt suicide, 90% of which result in death.²⁵ These individuals and characteristics unique to the patients who experience firearm suicide are thus largely missing from these data, which reflected that only 4.3% of the patients in this study had self-inflicted injuries. Prior studies have shown that intent as recorded by trauma registrars is highly accurate, unlike that coded in hospital discharge records.²⁶ Second, while the authors believe that the additional data collected on patients admitted to trauma center hospitals is important, and significant training of trauma center data registry personnel occurred, the data missingness may represent inadequate resources, training, and practices of the entire health care team, all of whom gather medical and social histories and document in the EHR. In addition, the extra time required of trauma registry personnel to locate and extract the additional data may have limited their ability to do so, notably during the data collection period when trauma centers reported an increase in trauma volume as a result of the COVID-19 pandemic. In addition, the total number of patients included in this study is an underrepresentation of all the patients treated at participating centers, as centers started participation at varying times during the study period and may not have contributed 12 months of data. The amount of time required to extract data was significant and may have been difficult for centers especially since it occurred when hospitals may have been very busy with patients during the pandemic and no additional funding was available to support this data collection at the center level. It is important to recognize which data points are hardest to obtain, for instance, prior assaultive injuries and suicidality and circ*mstances of the injury. Future studies on patients with firearm injuries treated in trauma centers will likely require dedicated funding to improve the quality of data collection and lessen missing data for those variables deemed most important for that study.

In summary, this study helps describe more than 17,000 patients treated for firearm injuries at ACS trauma centers, enhancing our knowledge of their injuries, clinical care, characteristics, and injury circ*mstances. While limitations were noted because of unknown and missing data, using trauma center data can be a valuable tool to improve our knowledge of firearm injuries if clinical practices of patient inquiry into risks and circ*mstances are standardized, as is documentation. More importantly, such practices could help reduce bias and promote trauma-informed care among the clinical team and guide potential interventions and support services for patients, including those who are treated and released from the ED. These may include hospital and community violence intervention programs, safe firearm storage counseling and storage devices, and mental health and substance use services. In addition, trauma centers and health care systems should play an active role in addressing “upstream” community level contributors of violence with communities and policy makers.

AUTHORSHIP

F.P.R., A.B.H., D.A.K., and A.N. contributed in the study design, data interpretation, writing, and critical revision of the manuscript. C.H. and B.P. contributed in the data collection, data analysis, data interpretation, and writing. A.W. contributed in the data analysis. S.B. contributed in the data analysis, data interpretation, writing, and critical revision. L.L.A. and S.K. contributed in the data interpretation and critical revision.

ACKNOWLEDGMENTS

We thank Holly Michaels, Melanie Neal, and Vanessa Aduro for their invaluable help with the study; the study Advisory Group and the ACS FAST group for their advice throughout the project; and Elieen Bulger, MD, and Ronald Stewart, MD, for their support throughout the project.

We also thank the Economic Innovation Group for development of the DCI. The findings expressed in this article are solely those of the listed authors and do not necessarily represent those of the Economic Innovation Group. The Economic Innovation Group does not guarantee the accuracy or reliability of or necessarily agree with the information provided herein.

This study was funded by the National Collaborative on Gun Violence Research by a grant to the American College of Surgeons.

DISCLOSURE

Conflict of Interest: Author Disclosure forms have been supplied and are provided as Supplemental Digital Content (https://links.lww.com/TA/D326).

The following participating investigators contributed to the data collection: Arrowhead Regional Medical Center, Jan Serrano, DNP, MHA, RN; Ascension Providence Hospital Southfield, Scott Barnes, DO; Ascension Providence Park Novi, Ehssan Zare, DO; Ascension St. Vincent Hospital/Peyton Manning Children's Hospital at Ascension St. Vincent, Lewis Jacobson, MB, ChB; Aultman Hospital, Sheree Nuske, BSN; Avera McKennan Hospital and University Health Center, Tami Schnetter, RN, BSN, TCRN; Barnes Jewish Hospital, Douglas Schuerer, MD; Baystate Medical Center, Reginald Alouidor, MD; Charleston Area Medical Center, Tiffany Lasky, MHS, DO; CHI Health Creighton University Medical Center Bergan Mercy, Eric Kuncir, MD, MS; Children's Healthcare of Atlanta at Scottish Rite, Alexis Smith, MD; Children's National Health System, Randall Burd, MD, PhD; Children's Wisconsin, Katherine Flynn-O'Brien, MD, MPH; CHRISTUS St. Michael Healthcare System, Lauren Jamison, MSN; Cincinnati Children's Hospital Medical Center, Meera Kotagal, MD, MPH; Cleveland Clinic Akron General, Jessica Krizo, PHN; Community Regional Medical Center, James Davis, MD; Connecticut Children's Medical Center, Amber Hunter; Dayton Children's Hospital, Lisa Schwing, RN; Dell Seton Medical Center at the University of Texas, Carlos Brown, MD; Detroit Receiving Hospital, Andrew Isaacson, MD; Dignity Health St. Joseph's Hospital and Medical Center, Jordan Weinberg, MD; East Carolina Health Medical Center, Joshua Aldridge, MD; Erie County Medical Center, William Flynn Jr., MD; Eskenazi Health, Erik Streib, MD; George Washington University Hospital, Babak Sarani, MD; Good Samaritan Medical Center Lafayette, Edward Pyun, MD; Grant Medical Center, Stephanie Doris, DO, MS; Gundersen Health System, Sarah Mathison, RHIT, CAISS; Harbor-UCLA Medical Center, Vincent Chong, MD, MS; Harborview Medical Center, Deepika Nehra, MD; Hartford Hospital, Jane Keating, MD; HCA Sunrise Hospital and Medical Center, Stefan Chock, MD; Henry Ford Hospital, Jeffrey Johnson, MD; Highland Hospital, Jessica Martinez; Jamaica Hospital Medical Center, Katherine McKenzie, DO; Jersey City Medical Center—RWJBarnabas Health, Bruno Molino, MD; John R. Oishei Children's Hospital, Tiffany Fabiano, MS; Johnson City Medical Center, Bracken Burns, DO; Kessler Trauma Center, Margaret Vercruysse, BS-HA, LPN; Kettering Health Main Campus, Melissa Moncrief, MD; Loyola University Medical Center, Richard Gonzalez, MD; Maimonides Medical Center, Julia Solby, LPN; Mary Bridge Children's Hospital, Mauricio A. Escobar Jr., MD; Mayo Clinic Rochester Trauma Centers, Brian Kim, MD; Medical Center of the Rockies, Jes Cofran, MSN, RN; MedStar Washington Hospital Center, Erin Hall, MD, MPH; MetroHealth Medical Center, Danielle Rossler, BSN, MBA; Mount Sinai Morningside, Yashani Singh, MS, MPH, RN; Northwell Health Cohen Children's Medical Center, Chethan Sathya, MD; NYC Health and Hospitals—Elmhurst, Praise Nesamony; Ohio State University Wexner Medical Center East Hospital, Jane Kilgore, MSN, RN, TCRN, CEN; OU Medical Center, Alisa Cross, MD; Parkland Memorial Hospital, Courtney Edwards, DNP, MPH, RN; Primary Children's Hospital, Katie W. Russell, MD; Prisma Health Richland, Jeremy Reeves, MD; Regional One Health, Peter Fischer, MD, MS; Regions Hospital, Uroghupatei Iyegha, MD; Renown Regional Medical Center, Myron Gomez, MD; Rhode Island Hospital/Hasbro Children's Hospital, Charles Adams, MD; Riley Hospital for Children at Indiana University Health, Matthew Landman, MD, MPH; Riverside Methodist Hospital, Jeff Hubartt, BSN, RN; Riverside University Health Systems, Raul Coimbra, MD, PhD; Sanford Medical Center, Lori Huber, BSN, RN, TCRN; Sanford Medical Center Fargo, Steven Briggs, MD; Sanford USD Medical Center, Paul Bjordahl, MD; Santa Clara Valley Medical Center, Tiffany E. Chao, MD, MPH; Sarasota Memorial Hospital, Jennifer Sweeney, DNP; Spartanburg Regional Healthcare System, Caleb Mentzer, DO; SSM Health Saint Louis University Hospital, Haley Bolyard, CSTR, CAISS; St. Louis Children's Hospital, Michele Herndon, MSN, RN; St. Mary's Medical Center, Jorge Vega, MD; Summa Akron City Hospital, Alexandra Carpenter, MHA, BSN; Sunnybrook Health Sciences Centre, Brandy Tanenbaum, MPH; Tacoma General Hospital, Betsy Harris, CSTR, CAISS; Tampa General Hospital/Tampa General Hospital Children's, Jose J. Diaz, MD; Texas Children's Hospital, Anthony Arredondo, DO; The Children's Hospital of Philadelphia, Michael Nance, MD; The Queen's Medical Center, Michael Hayashi, MD; The University of Vermont Medical Center, Andrew Erb, MD; ThedaCare Regional Medical Center—Neenah, Gretchen Reiland, BSN; UCHealth Memorial Hospital Central, Thomas Schroeppel, MD, MS; UCHealth University of Colorado Hospital, Michael Cripps, MD, MSCS; UF Health Shands Jacksonville Medical Center, Marie Crandall, MD, MPH; University Health System—San Antonio, Mark Muir, MD, MS; University Medical Center of Southern Nevada, Lisa Rogge, BSN; University of Louisville Hospital, Brian Harbrecht, MD; University of Missouri Health System, Christopher Nelson, MD; University of Wisconsin Hospital and Clinics Authority/American Family Children's Hospital, Thomas Ellison, RN; Upstate University Hospital/Golisano Children's Hospital, Roseanna Guzman-Curtis, MD, MPH; Virginia Commonwealth University Medical Center, Michael Aboutanos, MD, MPH; Wake Forest Baptist Medical Center, Martin Avery, MD; WellStar Atlanta Medical Center, Katherine Kohler, MD; West Virginia University Hospitals, James Bardes, MD; William W. Backus Hospital, Gary Kaml, MD; Wolfson Children's Hospital, Patsy Williamson, DNP; Yale-New Haven Hospital, Adrian Maung, MD, MBA.

REFERENCES

Supplemental Digital Content

• TA_00_00_2023_10_16_RIVARA_JT-D-23-00439_SDC1.docx; [Word] (31 KB)
• TA_00_00_2023_10_16_RIVARA_JT-D-23-00439_SDC2.docx; [Word] (35 KB)
• TA_00_00_2023_10_16_RIVARA_JT-D-23-00439_SDC3.docx; [Word] (796 KB)
• TA_00_00_2023_10_16_RIVARA_JT-D-23-00439_SDC4.pdf; [PDF] (5.94 MB)