Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Detecting Variation in Clinical Practice Patterns for Geriatric Trauma Care Using Social Network Analysis.

OBJECTIVE: To characterize hospital-level professional networks of physicians caring for older trauma patients as a function of trauma patient age distribution. BACKGROUND: The causal factors associated with between-hospital variation in geriatric trauma outcomes are poorly understood. Variation in physician practice patterns reflected by differences in professional networks might contribute to hospital-level differences in outcomes for older trauma patients. METHODS: This is a population-based, cross-sectional study of injured older adults (age 65 or above) and their physicians from January 1, 2014, to December 31, 2015, using Health Care Cost and Utilization Project inpatient data and Medicare claims from 158 hospitals in Florida. We used social network analyses to characterize the hospitals in terms of network density, cohesion, small-worldness, and heterogeneity, then used bivariate statistics to assess the relationship between network characteristics and hospital-level proportion of trauma patients who were aged 65 or above. RESULTS: We identified 107,713 older trauma patients and 169,282 patient-physician dyads. The hospital-level proportion of trauma patients who were aged 65 or above ranged from 21.5% to 89.1%. Network density, cohesion, and small-worldness in physician networks were positively correlated with hospital geriatric trauma proportions ( R =0.29, P <0.001; R =0.16, P =0.048; and R =0.19, P <0.001, respectively). Network heterogeneity was negatively correlated with geriatric trauma proportion ( R =0.40, P <0.001). CONCLUSIONS: Characteristics of professional networks among physicians caring for injured older adults are associated with the hospital-level proportion of trauma patients who are older, indicating differences in practice patterns at hospitals with older trauma populations. Associations between interspecialty collaboration and patient outcomes should be explored as an opportunity to improve the treatment of injured older adults.

Linking Trauma Registry Patients With Insurance Claims: Creating a Longitudinal Patient Record.

INTRODUCTION: Trauma registries and their quality improvement programs only collect data from the acute hospital admission, and no additional information is captured once the patient is discharged. This lack of long-term data limits these programs' ability to affect change. The goal of this study was to create a longitudinal patient record by linking trauma registry data with third party payer claims data to allow the tracking of these patients after discharge. METHODS: Trauma quality collaborative data (2018-2019) was utilized. Inclusion criteria were patients age ≥18, ISS ≥5 and a length of stay ≥1 d. In-hospital deaths were excluded. A deterministic match was performed with insurance claims records based on the hospital name, date of birth, sex, and dates of service (±1 d). The effect of payer type, ZIP code, International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis specificity and exact dates of service on the match rate was analyzed. RESULTS: The overall match rate between these two patient record sources was 27.5%. There was a significantly higher match rate (42.8% versus 6.1%, P < 0.001) for patients with a payer that was contained in the insurance collaborative. In a subanalysis, exact dates of service did not substantially affect this match rate; however, specific International Classification of Diseases, Tenth Revision, Clinical Modification codes (i.e., all 7 characters) reduced this rate by almost half. CONCLUSIONS: We demonstrated the successful linkage of patient records in a trauma registry with their insurance claims. This will allow us to the collect longitudinal information so that we can follow these patients' long-term outcomes and subsequently improve their care.

The Impact of Redlining on Modern-Day Firearm Injuries: A Nationwide Study of Federal Policy.

OBJECTIVES: To evaluate whether exposure to the United States discriminatory housing practice of redlining, which occurred in over 200 cities in the 1930s, is associated with modern-day, community-level incidence of firearm injury. BACKGROUND: Firearm violence is a public health epidemic within the United States. Federal policies are crucial in both shaping and reducing the risk of firearm violence; identifying policies that might have contributed to risks also offers potential solutions. We analyzed whether 1930s exposure to the discriminatory housing practices that occurred in over 200 US cities was associated with the modern-day, community-level incidence of firearm injury. METHODS: We performed a nationwide retrospective cohort study between 2014 and 2018. Urban Zip Code Tabulation Areas (ZCTAs) historically exposed to detrimental redlining (grades C and D) were matched to unexposed ZCTAs based on modern-day population-level demographic characteristics (ie, age, Gini index, median income, percentage Black population, and education level). Incidence of firearm injury was derived from the Gun Violence Archive and aggregated to ZCTA level counts. Our primary outcome was the incidence of firearm injury, modeled using zero-inflated negative binomial regression. RESULTS: When controlling for urban firearm risk factors, neighborhoods with detrimental redlining were associated with 2.6 additional firearm incidents annually compared with nonredlined areas with similar modern-day risk factors. Over our study period, this accounts for an additional 23,000 firearm injuries. CONCLUSIONS: Historic, discriminatory Federal policies continue to impact modern-day firearm violence. Policies aimed at reversing detrimental redlining may offer an economic means to reduce firearm violence.

Long-term Mental Health Trajectories of Injured Military Servicemembers: Comparing Combat to Noncombat Related Injuries.

OBJECTIVE: We sought to quantify the impact of injury characteristics and setting on the development of mental health conditions, comparing combat to noncombat injury mechanisms. BACKGROUND: Due to advances in combat casualty care, military service-members are surviving traumatic injuries at substantial rates. The nature and setting of traumatic injury may influence the development of subsequent mental health disorders more than clinical injury characteristics. METHODS: TRICARE claims data was used to identify servicemembers injured in combat between 2007 and 2011. Controls were servicemembers injured in a noncombat setting matched by age, sex, and injury severity. The rate of development, and time to diagnosis [in days (d)], of 3 common mental health conditions (post-traumatic stress disorder, depression, and anxiety) among combat-injured servicemembers were compared to controls. Risk factors for developing a new mental health condition after traumatic injury were evaluated using multivariable logistic regression that controlled for confounders. RESULTS: There were 3979 combat-injured servicemember and 3979 matched controls. The majority of combat injured servicemembers (n = 2524, 63%) were diagnosed with a new mental health condition during the course of follow-up, compared to 36% (n = 1415) of controls ( P < 0.001). In the adjusted model, those with combat-related injury were significantly more likely to be diagnosed with a new mental health condition [odds ratio (OR): 3.18, [95% confidence interval (CI): 2.88-3.50]]. Junior (OR: 3.33, 95%CI: 2.66-4.17) and senior enlisted (OR: 2.56, 95%CI: 2.07-3.17) servicemem-bers were also at significantly greater risk. CONCLUSIONS: We found significantly higher rates of new mental health conditions among servicemembers injured in combat compared to service-members sustaining injuries in noncombat settings. This indicates that injury mechanism and environment are important drivers of mental health sequelae after trauma.

The Hidden Costs of War: Healthcare Utilization Among Individuals Sustaining Combat-related Trauma (2007-2018).

OBJECTIVE: We sought to evaluate long-term healthcare requirements of American military servicemembers with combat-related injuries. SUMMARY OF BACKGROUND DATA: US military conflicts since 2001 have produced the most combat casualties since Vietnam. Long-term consequences on healthcare utilization and associated costs remain unknown. METHODS: We identified servicemembers who were treated for combat-related injuries between 2007 and 2011. Controls consisted of active-duty servicemembers injured in the civilian sector, without any history of combat-related trauma, matched (1:1) on year of injury, biologic sex injury severity, and age at time of injury. Surveillance was performed through 2018. Total annual healthcare expenditures were evaluated overall and then as expenditures in the first year after injury and for subsequent years. Negative binomial regression was used to identify the adjusted influence of combat injury on healthcare costs. RESULTS: The combat-injured cohort consisted of 3981 individuals and we identified 3979 controls. Total healthcare utilization during the follow-up period resulted in median costs of $142,214 (IQR $61,428, $323,060) per combat-injured servicemember as compared to $50,741 (IQR $26,669, $104,134) among controls. Median expenditures, adjusted for duration of follow-up, for the combat-injured were $45,211 (IQR $18,698, $105,437). In adjusted analysis, overall costs were 30% higher (1.30; 95% confidence interval: 1.23, 1.37) for combat-injured personnel. CONCLUSION: This investigation represents the longest continuous observation of healthcare utilization among individuals after combat injury and the first to assess costs. Expenditures were 30% higher for individuals injured as a result of combat-related trauma when compared to those injured in the civilian sector.

The Trauma Dyad: The Role of Informal Caregivers for Older Adults After Traumatic Injury.

OBJECTIVE: To investigate the association between higher injury severity and increased informal caregiving received by injured older adults. SUMMARY OF BACKGROUND DATA: Injured older adults experience high rates of functional decline and disability after hospitalization. Little is known about the scope of caregiving received post-discharge, particularly from informal caregivers such as family. METHODS: We used the National Health and Aging Trends Study 2011 to 2018 linked to Medicare claims to identify adults ≥65 with hospital admission for traumatic injury and a National Health and Aging Trends Study interview within 12 months pre- and post-trauma. Injury severity was assessed using the injury severity score (ISS, low 0-9; moderate 10-15; severe 16-75). Patients reported the types and hours of formal and informal help received and any unmet care needs. Multi variable logistic regression models examined the association between ISS and increase in informal caregiving hours after discharge. RESULTS: We identified 430 trauma patients. Most were female (67.7%), non-Hispanic White (83.4%) and half were frail. The most common mechanism of injury was fall (80.8%) and median injury severity was low (ISS = 9). Those reporting receiving help with any activity increased post-trauma (49.0% to 72.4%, P < 0.01), and unmet needs nearly doubled (22.8% to 43.0%, P < 0.01). Patients had a median of 2 caregivers and most (75.6%) were informal, often family members. Median weekly hours of care received pre- versus post-injury increased from 8 to 14 (P < 0.01). ISS did not independently predict increase in caregiving hours; pre-trauma frailty predicted an increase in hours ≥8 per week. CONCLUSIONS: Injured older adults reported high baseline care needs which increased significantly after hospital discharge and were mostly met by informal caregivers. Injury was associated with increased need for assistance and unmet needs regardless of injury severity. These results can help set expectations for caregivers and facilitate post-acute care transitions.

Association between Surgery, Anesthesia, and Obstetric Workforce and Emergent Surgical and Obstetric Mortality among United States Hospital Referral Regions.

OBJECTIVE: To determine the association between SAO workforce and mortality from emergent surgical and obstetric conditions within US HR Rs. BACKGROUND: SAO workforce per capita has been identified as a core metric of surgical capacity by the Lancet Commission on Global Surgery, but its utility has not been assessed at the subnational level for a high-income country. METHODS: The number of practicing surgeons, anesthesiologists, and obstetricians per capita was estimated for all HRRs using the US Health Resources & Services Administration Area Health Resource File Database. Deaths due to emergent general surgical and obstetric conditions were determined from the Center for Disease Control and Prevention WONDER database. We utilized B-spline quantile regression to model the relationship between SAO workforce and emergent surgical mortality at different quantiles of mortality and calculated the expected change in mortality associated with increases in SAO workforce. RESULTS: The median SAO workforce across all HRRs was 74.2 per 100,000 population (interquartile range 33.3-241.0). All HRRs met the Lancet Commission on Global Surgery lower target of 20 SAO per 100,000, and 97.7% met the upper target of 40 per 100,000. Nearly 2.8 million Americans lived in HRRs with fewer than 40 SAO per 100,000. Increases in SAO workforce were associated with decreases in surgical mortality in HRRs with high mortality, with minimal additional decreases in mortality above 60 to 80 SAO per 100,000. CONCLUSIONS: Increasing SAO workforce capacity may reduce emergent surgical and obstetric mortality in regions with high surgical mortality but diminishing returns may be seen above 60 to 80 SAO per 100,000. Trial Registration: N/A.

Value of Ambulatory Modified Radical Mastectomy.

BACKGROUND: Modified radical mastectomy (MRM) still is largely performed in inpatient settings. This study sought to determine the value (expenditures and complications) of ambulatory MRM. METHODS: Health Care Utilization Project (HCUP) state databases from 2016 were queried for patients who underwent MRM. The study examined rates of 30-day readmission for surgical-site infection (SSI) or hematoma, charges by index care setting, and predictors of 30-day readmission. RESULTS: Overall, 8090 patients underwent MRM: 5113 (63 %) inpatient and 2977 (37 %) ambulatory patients. Compared with the patients who underwent inpatient MRM, those who underwent ambulatory MRM were older (61 vs. 59 years), more often white (66 % vs. 57 %), in the lowest income quartile (28 % vs. 21 %), insured by Medicare (43 % vs. 33 %) and residents in a small metro area (6 % vs. 4 %) (all p < 0.01). Of the 5113 patients treated as inpatients, 126 (2.5 %) were readmitted, whereas 50 (1.7 %) of the ambulatory patients were readmitted (p = 0.02). The adjusted charge for inpatient MRM without readmission was $113,878 (range, $107,355-120,402) compared with $94,463 (range, $86,021-102,907) for ambulatory MRM, and the charge for inpatient MRM requiring readmission was $159,355 (range, $147,142-171,568) compared with $139,940 (range, $125,808-154,073) for ambulatory MRM (all p < 0.01). This difference remained significant after adjustment for hospital length of stay. Adjusted logistic regression showed that the ambulatory setting was protective for readmission (odds ratio, 0.49; 95 % confidence interval, 0.35-0.70; p < 0.01). CONCLUSIONS: The analyses suggest that ambulatory MRM is both safe and less expensive. The findings advocate that MRM, a last holdout of inpatient care within breast surgical oncology, can be transitioned to the ambulatory setting for appropriate patients.

Geospatial Assessment to Improve Time to Treatment (GAITT).

INTRODUCTION: Geographic information systems (GIS) can optimize trauma systems by identifying ways to reduce time to treatment. Using GIS, this study analyzed a system in Maryland served by Johns Hopkins Suburban Hospital and the University of Maryland Capital Region Medical Center. It was hypothesized that including Walter Reed National Military Medical Center (WRNMMC) in the Maryland trauma system in an access simulation would provide increased timely access for a portion of the local population. MATERIALS AND METHODS: Using ArcGIS Online, catchment areas with and without WRNMMC were built. Catchment areas captured Johns Hopkins Suburban Hospital, University of Maryland Capital Region Medical Center, and WRNMMC at 5-, 10-, 15-, 20-, 25-, 30-, 45-, and 60-min. Various time conditions were simulated (12 am, 8 am, 12 pm, and 5 pm) on a weekday and weekend day. Data was enriched with 19 variables addressing population size, socioeconomic status, and diversity. RESULTS: All catchment areas benefited on at least one time-day simulation, but the largest increases in mean population coverage were in the 0-5 (10.5%), 5-10 (12.3%), and 10-15 min (5.7%) catchment areas. These areas benefited regardless of time-day simulation. The lowest increase in mean population coverage was seen in the 20-25-min catchment area (0.1%). Subgroup analysis revealed that all socioeconomic status and diversity groups gained coverage. CONCLUSIONS: This study suggests that incorporating WRNMMC into the Maryland trauma system might yield increased population coverage for timely trauma access. If incorporated, WRNMMC may provide nonstop or flexible coverage, possibly in different traffic scenarios or while civilian centers are on diversion status.

Impact of hospital characteristics on best-practice adherence for gallstone pancreatitis: a nationwide analysis.

BACKGROUND: Current guidelines recommend cholecystectomy during the index admission for gallstone pancreatitis, and a growing body of evidence indicates that patients benefit from cholecystectomy within the first 48 h of admission. We examined the impact of hospital characteristics on adherence to these data-driven practices. METHODS: We queried the National Inpatient Sample for patients admitted for gallstone pancreatitis between October 2015 and December 2018. Patients who underwent same-admission cholecystectomy were identified by procedure codes. Cholecystectomies within the first two days were classified as early cholecystectomies. Multivariable logistic regression was used to determine the association between hospital characteristics and adherence to these practices. RESULTS: Of 163,390 admissions for gallstone pancreatitis, only 90,790 (55.6%) underwent cholecystectomy before discharge. Mean time from admission to cholecystectomy was 2.9 days; 27.0% of patients (44,005) underwent early cholecystectomy. Odds of same-admission cholecystectomy were highest in large hospitals (OR 1.21, 95% CI 1.13-1.28), urban teaching centers (OR 1.33, 95% CI 1.21-1.46), and the South (OR 1.70, 95% CI 1.57-1.83). Odds of early cholecystectomy did not vary with hospital size, urban-rural status, or teaching status but were highest in the West (OR 1.98, 95% CI 1.80-2.18). CONCLUSION: Best-practice adherence for cholecystectomy in gallstone pancreatitis remains low despite an abundance of evidence and clinical practice guidelines. Active interventions are needed to improve delivery of surgical care for this patient population. Implementation efforts should focus on small hospitals, rural areas, and health systems in the Northeast region.

A National Assessment of Trauma Systems Using the American College of Surgeons NBATS Tool: Geographic Distribution of Trauma Center Need.

OBJECTIVE: To compare the needs based assessment of trauma systems (NBATS) tool estimates of trauma center need to the existing trauma infrastructure using observed national trauma volume. SUMMARY OF BACKGROUND DATA: Robust trauma systems have improved outcomes for severely injured patients. The NBATS tool was created by the American College of Surgeons to align trauma resource allocation with regional needs. METHODS: Data from the Agency for Healthcare Research and Quality Healthcare Costs and Utilization Project State Inpatient Databases, the Trauma Information Exchange Program, and US Census was used to calculate an NBATS score for each trauma service area (TSA) as defined by the Pittsburgh Atlas. This score was used to estimate the number of trauma centers allocated to each TSA and compared to the number of existing trauma centers. RESULTS: NBATS predicts the need for 117 additional trauma centers across the United States to provide adequate access to trauma care nationwide. At least 1 additional trauma center is needed in 49% of TSAs. CONCLUSIONS: Application of the NBATS tool nationally shows the need for additional trauma infrastructure across a large segment of the United States. We identified some limitations of the NBATS tool, including preferential weighting based on current infrastructure. The NBATS tool provides a good framework to begin the national discussion around investing in the expansion of trauma systems nationally, however, in many instances lacks the granularity to drive change at the local level.

The Social Vulnerability Index and Long-term Outcomes After Traumatic Injury.

OBJECTIVE: The aim of this study was to evaluate the Social Vulnerability Index (SVI) as a predictor of long-term outcomes after injury. BACKGROUND: The SVI is a measure used in emergency preparedness to identify need for resources in the event of a disaster or hazardous event, ranking each census tract on 15 demographic/social factors. METHODS: Moderate-severely injured adult patients treated at 1 of 3 level-1 trauma centers were prospectively followed 6 to 14 months post-injury. These data were matched at the census tract level with overall SVI percentile rankings. Patients were stratified based on SVI quartiles, with the lowest quartile designated as low SVI, the middle 2 quartiles as average SVI, and the highest quartile as high SVI. Multivariable adjusted regression models were used to assess whether SVI was associated with long-term outcomes after injury. RESULTS: A total of 3153 patients were included [54% male, mean age 61.6 (SD = 21.6)]. The median overall SVI percentile rank was 35th (IQR: 16th-65th). compared to low SVI patients, high SVI patients were more likely to have new functional limitations [odds ratio (OR), 1.51; 95% confidence interval (CI), 1.19-1.92), to not have returned to work (OR, 2.01; 95% CI, 1.40-2.89), and to screen positive for post-traumatic stress disorder (OR, 1.56; 95% CI, 1.12-2.17). Similar results were obtained when comparing average with low SVI patients, with average SVI patients having significantly worse outcomes. CONCLUSIONS: The SVI has potential utility in predicting individuals at higher risk for adverse long-term outcomes after injury. This measure may be a useful needs assessment tool for clinicians and researchers in identifying communities that may benefit most from targeted prevention and intervention efforts.

Which Geriatric Variables Most Strongly Inform Discharge Disposition After Emergency Surgery?

INTRODUCTION: Older adults account for an increasing proportion of emergency surgical procedures and have longer hospital lengths of stay than their elective counterparts. Identifying those at greatest risk of discharge to a postacute care facility would improve postoperative planning. We aimed to examine the role of preoperative cognitive and functional status on discharge disposition after emergency surgery in older adults. METHODS: We used American College of Surgeons National Surgical Quality Improvement Program Geriatric Pilot Project data from 2014 to 2018 to identify patients ≥65 y who underwent inpatient emergency surgery. The primary outcome was nonhome discharge, defined as discharge to an acute rehabilitation facility, a skilled nursing facility, or a nonhome unskilled facility. Logistic regression controlling for patient characteristics was used to determine the association of preoperative geriatric-specific variables with nonhome discharge. RESULTS: Of 3494 patients, 53.9% were not discharged home. In multivariable analysis, a fall within the past year (odds ratio [OR] = 5.3, 95% confidence interval [CI] = 4.4-6.5) was most strongly associated with nonhome discharge. The outcome was also independently associated with preoperative use of a mobility aid (OR = 2.0, 95% CI = 1.7-2.4), partially dependent functional status (OR = 1.8, 95% CI = 1.4-2.5), and surrogate consent (OR = 1.4, 95% CI = 1.1-1.8), but not cognitive impairment (OR = 1.0, 95% CI = 0.7-1.3). CONCLUSIONS: Assessing for a history of falls and impaired mobility at the initial surgical evaluation can rapidly identify patients most likely to need postacute care. Further work is needed to assess the association between pre-existing cognitive impairment and discharge disposition after emergency surgery.

Defining Referral Regions for Inpatient Trauma Care: The Utility of a Novel Geographic Definition.

INTRODUCTION: Geographic variation is an inherent feature of the US health system. Despite efforts to account for geographic variation in trauma system strengthening, it remains unclear how trauma "regions" should be defined. The objective of this study is to evaluate the utility of a novel definition of Trauma Referral Regions (TRR) for assessing geographic variation in inpatient trauma across the age span of hospitalized trauma patients. METHODS: Using 2016-2017 State Inpatient Databases, we assessed the extent of geographic variability in three common metrics of hospital use (localization index, market share index, net patient flow) among TRRs and, as a comparison, trauma regions alternatively defined based on Hospital Referral Regions, Hospital Service Areas, and counties. RESULTS: A total of 860,593 admissions from 102 TRRs, 127 Hospital Referral Regions, 884 Hospital Service Areas, and 583 counties were included. Consistent with expectations for distinct trauma regions, TRR presented with high average localization indices (mean [standard deviation]: 83.4 [11.7%]), low market share indices (mean [standard deviation]: 11.9 [7.0%]), and net patient flows close to 1.00. Similar results were found among stratified pediatric, adult, and older adult patients. Associations between TRRs and variations in important demographic features (e.g., travel time by road to the nearest Level I or II Trauma Center) suggest that while indicative of standalone trauma regions, TRRs are also able to simultaneously capture critical variations in regional trauma care. CONCLUSIONS: TRRs offer a standalone set of geographic regions with minimal variation in common metrics of hospital use, minimal geographic clustering, and preserved associations with important demographic factors. They provide a needed, valid means of assessing geographic variation among trauma systems.

The Utility of a Novel Definition of Health Care Regions in the United States in the Era of COVID-19: A Validation of the Pittsburgh Atlas Using Pneumonia Admissions.

STUDY OBJECTIVE: The COVID-19 pandemic in the United States has underscored the need to understand health care in a regional context. However, there are multiple definitions of health care regions available for conducting geospatial analyses. In this study, we compare the novel Pittsburgh Atlas, which defined regions for emergency care, with the existing definitions of regions, counties, and the Dartmouth Atlas, with respect to nonemergent acute medical conditions using pneumonia admissions. METHODS: We identified patients hospitalized with a primary diagnosis of pneumonia or a primary admitting diagnosis of sepsis with a secondary diagnosis of pneumonia in the Agency for Healthcare Research and Quality's State Inpatient Databases. We calculated the percentage of region concordant care, the localization index, and market share for 3 definitions of health care regions (the Pittsburgh Atlas, Dartmouth Atlas, and counties). We used logistic regression identified predictors of region concordant care. RESULTS: We identified 1,582,287 patients who met the inclusion criteria. We found that the Pittsburgh Atlas and Dartmouth Atlas definitions of regions performed similarly with respect to both localization index (92.0 [interquartile range 87.9 to 95.7] versus 90.3 [interquartile range 81.4 to 94.5]) and market share (8.5 [interquartile range 5.1 to 13.6] versus 9.4 [interquartile range 6.7 to 14.1]). Both atlases outperformed the localization index (67.5 [interquartile range 49.9 to 83.9]) and market share (20.0% [interquartile range 11.4 to 31.4]) of the counties. Within a given referral region, the demographic factors, including age, sex, race/ethnicity, insurance status, and the level of severity, affected concordance rates between residential and hospital regions. CONCLUSION: Because the Pittsburgh Atlas also has the benefit of respecting state and county boundaries, the use of this definition may have improved policy applicability without sacrificing accuracy in defining health care regions for acute medical conditions.

Geographic Distribution of Orthopaedic Trauma Resources and Service Use in the United States: A Cross Sectional Analysis.

BACKGROUND: Management of orthopaedic injury is an essential component of comprehensive trauma care, and availability of orthopaedic surgeons impacts trauma system capacity and accessibility of care. We sought to estimate the geographic distribution of orthopaedic injury in the United States and identify regions needing additional orthopaedic trauma resources. METHODS: In this retrospective cross-sectional study using 2014 Agency for Healthcare Research and Quality State Inpatient Datasets from 26 states and the District of Columbia, administrative data were used to determine hospital referral region (HRR)-level incidence of orthopaedic trauma and surgical care. Factors associated with HRR-level orthopaedic trauma volume were identified using negative binomial regression, and model parameters were used to estimate injury incidence and operative volume in unobserved HRRs. The primary outcomes of interest were HRR-level incidence of orthopaedic injury, polytrauma, and emergency orthopaedic surgery, as well and the number of emergency orthopaedic surgery patients per orthopaedic surgeon. RESULTS: Orthopaedic injury incidence and operative patients per orthopaedic surgeon were associated with HRR-level volume of medical service use, population characteristics, geographic characteristics, and existing trauma care resources. Orthopaedic injury incidence ranged from 20 patients/HRR to 33,260 patients/HRR. Polytrauma incidence ranged from < 10 patients/HRR to 12,140 patients/HRR. Emergency orthopaedic surgery incidence ranged from < 10 patients/HRR to 18,759 patients/HRR. The volume of operative orthopaedic trauma patients per orthopaedic surgeon ranged from < 10 patients/surgeon to 224 patients and/or surgeon. DISCUSSION: The incidence of orthopaedic injury and volume of injury patients per orthopaedic surgeon varies substantially across HRRs in the United States. Regions with high patient volume and moderate patient-to-provider ratios may be ideal settings for orthopaedic trauma training programs or post-fellowship professional opportunities. Future research should examine the impact of high volume orthopaedic trauma volume and high patient-to-provider ratios on health outcomes.

A Multistate Study of Race and Ethnic Disparities in Access to Trauma Care.

BACKGROUND: There are well-documented disparities in outcomes for injured Black and Hispanic patients in the United States. However, patient level characteristics cannot fully explain the differences in outcomes and system-level factors, including the trauma center designation of the hospital to which a patient presents, may contribute to their worse outcomes. We aim to determine if Black and Hispanic patients are more likely to be undertriaged, compared with white patients. METHODS: This is a retrospective, cross-sectional, population-based study that uses data from the 2014 Agency for Healthcare Research and Quality Healthcare Costs and Utilization Project State Inpatient Databases. We included data from all states with available State Inpatient Databases data that included both race and hospital characteristics needed for analysis (n = 18). Logistic regression was used to identify predictors of severely injured (Injury Severity Score ≥16) patients being brought to a trauma center. RESULTS: We identified 70,970 severely injured trauma patients with complete data. Non-Hispanic White represented 74.1% of the study population, 9.8% were non-Hispanic Black, and 9.7% were Hispanic. After adjustment for other demographic and injury characteristics, Non-Hispanic Black and Hispanic patients were more likely to be undertriaged, compared with white patients (odds ratio, 1.20; 95% confidence interval, 1.12-1.29 and odds ratio, 1.39; 95% confidence interval, 1.29-1.48, respectively). Male sex and older age were associated with higher odds of undertriage, whereas urban residence, high injury severity, and penetrating injury were associated with lower odds of undertriage. CONCLUSIONS: Severely injured Black and Hispanic trauma patients are more likely to be undertriaged than otherwise similar white patients. The factors that contribute to racial and ethnic disparities in receiving trauma center care need to be identified and addressed to provide equitable trauma care.

Risk Prediction Accuracy Differs for Transferred and Nontransferred Emergency General Surgery Cases in the ACS-NSQIP.

BACKGROUND: Risk prediction accuracy of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Surgical Risk Calculator has been shown to differ between emergency and elective surgery. Benchmarking methods of clinical performance require accurate risk estimation, and current methods rarely account for admission source; therefore, our goal was to assess whether the ACS-NSQIP predicts mortality comparably between transferred and nontransferred emergency general surgery (EGS) cases. MATERIALS AND METHODS: This is a retrospective study using the ACS-NSQIP database from 2005 to 2014including all inpatients who underwent one of seven previously described EGS procedures. The admission source was classified as directly admitted versus transferred from an outside emergency room or an acute care facility. We compared the accuracy of ACS-NSQIP-predicted mortality probabilities using the observed-to-expected (O:E) ratio and Brier score. A subgroup analysis was performed to compare accuracy of high-risk and low-risk procedures. RESULTS: A total of 206,103 EGS admissions were identified, of which 6.97% were transfers. Overall mortality was 3.26% for the entire cohort and 10.24% within the transfer group. The O:E ratios generated by ACS-NSQIP models differed between transferred patients (O:E = 1.0, 95% confidence interval = 0.97-1.02) and nontransferred patients (O:E = 1.12, 95% confidence interval = 1.09-1.14). The Brier score for transferred patients was greater than that for nontransferred patients (0.063 versus 0.018, respectively) showing higher accuracy for nontransferred patients. CONCLUSIONS: The ACS-NSQIP risk estimates used for benchmarking differ between transferred and nontransferred EGS cases. Analyses of the Brier score by the ACS-NSQIP risk calculator demonstrated inferior prediction for transferred patients. This increased burden on accepting institutions will have an impact on quality metrics and should be considered for benchmarking of clinical performance.

The National Burden of Orthopedic Injury: Cross-Sectional Estimates for Trauma System Planning and Optimization.

BACKGROUND: Management of orthopedic injuries is a critical component of comprehensive trauma care. As patterns of injury incidence and recovery change in the face of emerging injury prevention efforts and technologies and an aging US population, assessment of the burden of orthopedic injury is essential to optimize trauma system planning. We sought to estimate the incidence of orthopedic injury requiring emergency orthopedic surgery in the United States. METHODS: Using nationally representative samples from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project, we estimated the incidence of orthopedic injury, polytrauma with orthopedic injury, and emergency operative orthopedic procedures performed for the management of traumatic injury. We used multivariable logistic regression to identify patient, injury, and hospital characteristics associated with odds of emergency orthopedic surgery. RESULTS: A total of 7,214,915 patients were diagnosed with orthopedic injury in 2013-2014, resulting in 1,167,656 emergency orthopedic surgical procedures. Fall-related injuries accounted for 51% of health care encounters and 61% of emergency orthopedic surgical procedures. Odds of emergency orthopedic surgery were 2.04 times greater for patients with polytrauma, compared with isolated orthopedic injury (P < 0.001). CONCLUSIONS: The total burden or orthopedic injury in the United States is substantial, and there is considerable heterogeneity in demand for care and practice patterns in the orthopedic trauma community. Population-based trauma system planning and tailored care delivery models would likely optimize initial treatment, recovery, and health outcomes for orthopedic trauma patients.