An Evaluation of Pediatric Secondary Overtriage in the Pennsylvania Trauma System.

BACKGROUND: We sought to determine the secondary overtriage rate of pediatric trauma patients admitted to pediatric trauma centers. We hypothesized that pediatric secondary overtriage (POT) would constitute a large percentage of admissions to PTC. MATERIALS AND METHODS: The Pennsylvania Trauma Outcome Study database was retrospectively queried from 2003 to 2017 for pediatric (age ≤ 18 y) trauma patients transferred to accredited pediatric trauma centers in Pennsylvania (n = 6). Patients were stratified based on discharge within (early) and beyond (late) 24 h following admission. POT was defined as patients transferred to a PTC with an early discharge. Multilevel mixed-effects logistic regression model controlling for demographic and injury severity covariates were utilized to determine the adjusted impact of injury patterns on early discharge. RESULTS: A total of 37,653 patients met inclusion criteria. For transfers, POT compromised 18,752 (49.8%) patients. Compared to POT, non-POT were more severely injured (ISS: 10 versus 6;P < 0.001) and spent less time in the ED (Min: 181 versus 207;P < 0.001). In adjusted analysis, concussion, closed skull vault fractures, supracondylar humerus fractures, and consults to neurosurgery were associated with increased odds of POT. Overall, femur fracture, child abuse evaluation, and consults to plastic surgery, orthopedics, and ophthalmology were all associated with a decreased risk of being POT. CONCLUSIONS: POT comprises 49.8% of PTC transfer admissions in Pennsylvania's trauma system. Improving community resources for management of pediatric concussion and mild TBI could result in decreased rates of POT to PTCs. Developing better inter-facility transfer guidelines and increased education of adult TC and nontrauma center hospitals is needed to decrease POT. LEVEL OF EVIDENCE: Epidemiologic study, level III.

Predictors of Trauma High Resource Consumers in a Mature Trauma System.

BACKGROUND: Extended hospital length of stay (LOS) is widely associated with significant healthcare costs. Since LOS is a known surrogate for cost, we sought to evaluate outliers. We hypothesized that particular characteristics are likely predictive of trauma high resource consumers (THRC) and can be used to more effectively manage care of this population. METHODS: The Pennsylvania Trauma Outcome Study database was retrospectively queried from 2003-2017 for all adult (age ≥15) trauma patients admitted to accredited trauma centers in Pennsylvania. THRC were defined as patients with hospital LOS two standard deviations above the population mean or ≥22 days (p<0.05). Patient demographics, comorbid conditions and clinical variables were compared between THRC and non-THRC to identify potential predictor variables. A multilevel mixed-effects logistic regression model controlling for age, gender, injury severity, admission Glasgow coma score, systolic blood pressure, and injury year assessed the adjusted impact of clinical factors in predicting THRC status. The National Trauma Data Bank (NTDB) was retrospectively queried from 2014-2016 for all adult (age ≥15) trauma patients admitted to state-accredited trauma centers and likewise were assessed for factors associated with THRC. RESULTS: A total of 465,601 patients met inclusion criteria [THRC: 16,818 (3.6%); non-THRC 448,783 (96.4%)]. Compared to non-THRC counterparts, THRC patients were significantly more severely injured (median ISS: 9 vs. 22, p<0.001). In adjusted analysis, gunshot wound (GSW) to the abdomen, undergoing major surgery and reintubation along with injury to the spine, upper or lower extremities were significantly associated with THRC. From the NTDB, 2 323 945 patients met inclusion criteria. In adjusted analysis, GSW to the abdomen was significantly associated with THRC. Penetrating injury overall was associated with decreased risk of being a THRC in the NTDB dataset. Those who had either GSW to abdomen, surgery, or reintubation required significantly longer LOS (p<0.001). CONCLUSIONS: Reintubation, major surgery, gunshot wound to abdomen, along with injury to the spine, upper or lower extremities are all strongly predictive of THRC. Understanding the profile of the THRC will allow clinicians and case management to proactively put processes in place to streamline care and potentially reduce costs and LOS.

The Effects of Fasting Status on the Relative Risk of Pulmonary Aspiration in Acute Care Surgery Patients.

BACKGROUND: Acute care surgery patients are often unfasted at the time of surgery, presenting a unique opportunity to study the effects of fasting on the risk of pulmonary aspiration. We aimed to determine the relative risk of aspiration in patients who were fasted at the time of surgery according to guidelines versus those in an unfasted state. METHODS: A retrospective chart review of 100 patients who underwent appendectomy (n = 76) or exploratory laparotomy (n = 24) was conducted at a single institution in 2016-2017. Using the American Society of Anesthesiologists (ASA) Practice Guidelines for Preoperative Fasting, patients were stratified into study and control groups according to whether they were unfasted (nothing by mouth for <8 hours prior to surgery) or fasted (nothing by mouth for >8 hours prior to surgery). Data controlled for patients' age, sex, body mass index (BMI), most recent hemoglobin A1c, presence of gastroesophageal reflux disease (GERD), and presence of hiatal hernia. RESULTS: Of the 76 patients who underwent appendectomy, 15% were unfasted with a total of 0 aspiration events (P < .001). Of the 24 patients who underwent exploratory laparotomy, 42% were unfasted with a total of 0 aspiration events (P < .001). This yields a relative risk of pulmonary aspiration of 1.0 (absolute risk of 0) in both the study and control groups. DISCUSSION: In an acute care surgery population including patients who were not fasted according to guidelines, there was no increase in the risk of pulmonary aspiration. LEVEL OF EVIDENCE: Epidemiological study; Level III.

An analysis of pediatric social vulnerability in the Pennsylvania trauma system.

BACKGROUND: The social vulnerability index (SVI) is used to assess resilience to external influences that may affect human health. Social vulnerability has been noted to be a barrier to healthcare access for pediatric patients. We hypothesized that Pennsylvania (PA) pediatric trauma patients high on the social vulnerability index would have significantly lower rates of rehab admission following admission to a hospital for traumatic injury. METHODS: The SVI was determined for each PA zip code area utilizing the census tract based 2014 SVI provided by the CDC along with a weighted crosswalk between census tracts and zip code areas using the Housing and Urban Development zip code crosswalk files. The rate of the uninsured population was extracted from the CDC SVI files in addition to other US Census variables based upon estimates from the 2014 American Community Survey (ACS). We also included the individual primary payer status of each subject. Pediatric (age <15 years) trauma admissions with in-hospital mortality excluded, were extracted from the PA Healthcare Cost Containment Council (PHC4) for all hospital admissions for the period of 2003-2015 (n = 63,545). Complete case analysis was conducted based upon the final model providing a sample of 52,794. Cases were coded as rehab patients based upon discharge status (n = 603; 1.1%). A multi-level logistic model was used to determine if subjects had a higher odds of being discharged to rehab based on SVI, undertriage rates of their zip code area of residence and their own primary payer status; this was adjusted for age, multi-system injury and a head, chest or abdomen injury with abbreviate injury scale (AIS) severity > = 3. RESULTS: SVI and undertriage rates of the zip code areas of residence were not significantly associated with admission to rehab. The individual primary payer status of the subject was significantly associated with admission to rehab (OR 95%CI vs. self/uninsured; Medicaid 3.65 1.84-7.24; Commercial = 3.09 1.56-6.11; other/unknown = 2.85 1.02-7.93). Admission to rehab was also significantly associated with age, injury severity (ISS), head or chest injury with AIS scores > = 3, year of admission and hospital type. CONCLUSION: Individual patient level factors (primary payer of patient) may be associated with the odds of rehab admission rather than neighborhood factors. LEVEL OF EVIDENCE: Epidemiologic: Level III.

An analysis of overtriage and undertriage by advanced life support transport in a mature trauma system.

BACKGROUND: While issues regarding triage of severely injured trauma patients are well publicized, little information exists concerning the difference between triage rates for patients transported by advanced life support (ALS) and basic life support (BLS). We sought to analyze statewide trends in undertriage (UT) and overtriage (OT) to address this question, hypothesizing that there would be a difference between the UT and OT rates for ALS compared with BLS over a 13-year period. METHODS: All patients submitted to Pennsylvania Trauma Outcomes Study database from 2003 to 2015 were analyzed. Undertriage was defined as not calling a trauma alert for patients with an Injury Severity Score (ISS) of 16 or greater. Overtriage was defined as calling a trauma alert for patients with an ISS of 9 or less. A logistic regression was used to assess mortality between triage groups in ALS and BLS. A multinomial logistic regression assessed the adjusted impact of ALS versus BLS transport on UT and OT versus normal triage while controlling for age, sex, Glasgow Coma Scale, systolic blood pressure (SBP), pulse, Shock Index and injury year. RESULTS: A total of 462,830 patients met inclusion criteria, of which 115,825 had an ISS of 16 or greater and 257,855 had an ISS of 9 or less. Both ALS and BLS had significantly increased mortality when patients were undertriaged compared with the reference group. Multivariate analysis in the form of a multinomial logistic regression revealed that patients transported by ALS had a decreased adjusted rate of undertriage (relative risk ratio, 0.92; 95% confidence interval, 0.87-0.97; p = 0.003) and an increased adjusted rate of OT (relative risk ratio, 1.59; 95% confidence interval, 1.54-1.64; p < 0.001) compared with patients transported by BLS. CONCLUSION: Compared with their BLS counterparts, while UT is significantly lower, OT is substantially higher in ALS-further increasing the high levels of resource (over)utilization in trauma patients. Undertriage in both ALS and BLS are associated with increased mortality rates. Additional education, especially in the BLS provider, on identifying the major trauma victim may be warranted based on the results of this study. LEVEL OF EVIDENCE: Epidemiological, Level III.

The geriatric trauma patient: A neglected individual in a mature trauma system.

BACKGROUND: Those older than 65 years represent the fastest growing demographic in the United States. As such, their care has been emphasized by trauma entities such as the American College of Surgeons Committee on Trauma. Unfortunately, much of that focus has been of their care once they reach the hospital with little attention on the access of geriatric trauma patients to trauma centers (TCs). We sought to determine the rate of geriatric undertriage (UT) to TCs within a mature trauma system and hypothesized that there would be variation and clustering of the geriatric undertriage rate (UTR) within a mature trauma system because of the admission of geriatric trauma patient to nontrauma centers (NTCs). METHODS: From 2003 to 2015, all geriatric (age >65 years) admissions with an Injury Severity Score of greater than 9 from the Pennsylvania Trauma Systems Foundation (PTSF) registry and those meeting trauma criteria (International Classification of Diseases, Ninth Revision: 800-959) from the Pennsylvania Health Care Cost Containment Council (PHC4) database were included. Undertriage rate was defined as patients not admitted to TCs (n = 27) divided by the total number of patients as from the PHC4 database. The PHC4 contains all inpatient admissions within Pennsylvania (PA), while PTSF reports admissions to PA TCs. The zip code of residence was used to aggregate calculations of UTR as well as other aggregate patient and census demographics, and UTR was categorized into lower, middle box, and upper quartiles. ArcGIS Desktop: Version 10.7, ESRI, Redlands, CA and GeoDa: Version 1.14.0, Open source license were used for geospatial mapping of UT with a spatial empirical Bayesian smoothed UTR, and Stata: Version 16.1, Stata Corp., College Station TX was used for statistical analyses. RESULTS: Pennsylvania Trauma Systems Foundation had 58,336 cases, while PHC4 had 111,626 that met the inclusion criteria, resulting in a median (Q1-Q3) smoothed UTR of 50.5% (38.2-60.1%) across PA zip code tabulation areas. Geospatial mapping reveals significant clusters of UT regions with high UTR in some of the rural regions with limited access to a TC. The lowest quartile UTR regions tended to have higher population density relative to the middle or upper quartile UTR regions. At the patient level, the lowest UTR regions had more racial and ethnic diversity, a higher injury severity, and higher rates of treatment at a TC. Undertriage rate regions that were closer to NTCs had a higher odds of being in the upper UTR quartile; 4.48 (2.52-7.99) for NTC with less than 200 beds and 8.53 (4.70-15.47) for NTC with 200 beds or greater compared with zip code tabulation areas with a TC as the closest hospital. CONCLUSION: There are significant clusters of geriatric UT within a mature trauma system. Increased emphasis needs to focus prehospital on identifying the severely injured geriatric patient including specific geriatric triage protocols. LEVEL OF EVIDENCE: Epidemiological, Level III.

An analysis of outcomes and predictors of intensive care unit bouncebacks in a mature trauma system.

BACKGROUND: With the recent birth of the Pennsylvania TQIP Collaborative, statewide data identified unplanned admissions to the intensive care unit (ICU) as an overarching issue plaguing the state trauma community. To better understand the impact of this unique population, we sought to determine the effect of unplanned ICU admission/readmission on mortality to identify potential predictors of this population. We hypothesized that ICU bounceback (ICUBB) patients would experience increased mortality compared with non-ICUBB controls and would likely be associated with specific patterns of complications. METHODS: The Pennsylvania Trauma Outcome Study database was retrospectively queried from 2012 to 2015 for all ICU admissions. Unadjusted mortality rates were compared between ICUBB and non-ICUBB counterparts. Multilevel mixed-effects logistic regression models assessed the adjusted impact of ICUBB on mortality and the adjusted predictive impact of 8 complications on ICUBB. RESULTS: A total of 58,013 ICU admissions were identified from 2012 to 2015. From these, 53,715 survived their ICU index admission. The ICUBB rate was determined to be 3.82% (2,054/53,715). Compared with the non-ICUBB population, ICUBB patients had a significantly higher mortality rate (12% vs. 8%; p < 0.001). In adjusted analysis, ICUBB was associated with a 70% increased odds ratio for mortality (adjusted odds ratio, 1.70; 95% confidence interval, 1.44-2.00; p < 0.001). Adjusted analysis of predictive variables revealed unplanned intubation, sepsis, and pulmonary embolism as the strongest predictors of ICUBB. CONCLUSION: Intensive care unit bouncebacks are associated with worse outcomes and are disproportionately burdened by respiratory complications. These findings emphasize the importance of the TQIP Collaborative in identifying statewide issues in need of performance improvement within mature trauma systems. LEVEL OF EVIDENCE: Epidemiological study, level III.

A comparison of adolescent penetrating trauma patients managed at pediatric versus adult trauma centers in a mature trauma system.

BACKGROUND: While there is little debate that pediatric trauma centers (PTC) are uniquely equipped to manage pediatric trauma patients, the extent to which adolescents benefit from treatment there remains controversial. We sought to elucidate differences in management approach and outcome between PTC and adult trauma centers (ATC) for the adolescent penetrating trauma population. We hypothesized that improved mortality would be observed at ATC for this subset of patients. METHODS: Adolescent patients (age, 15-18 years), presenting to Pennsylvania-accredited trauma centers between 2003 and 2017 with penetrating injury, were queried from the Pennsylvania Trauma Outcome Study database. Dead on arrival, transfer patients, and those admitted to a Level III or Level IV trauma center were excluded from analysis. Patient length of stay, number of complications, surgical intervention, and mortality were compared between ATC and PTC. Multilevel mixed effects logistic regression models with trauma center as the clustering variable were used to assess the impact of center type (ATC/PTC) on management approach and mortality adjusted for appropriate covariates. RESULTS: A total of 2,630 adolescent patients met inclusion criteria (PTC: n = 428 [16.3%]; ATC: n = 2,202 [83.7%]). Pediatric trauma centers had a lower adjusted odds of mortality (adjusted odds ratio [AOR], 0.35; 95% confidence interval [CI], 0.17-0.74; p = 0.006) and a lower adjusted odds of surgery (AOR, 0.67; 95% CI, 0.0.48-0.93; p = 0.016) than their ATC counterparts. There were no differences in complication rates (AOR, 0.94; 95% CI, 0.57-1.55; p = 0.793) or length of stay longer than 4 days (AOR, 0.95; 95% CI, 0.61-1.48; p = 0.812) between the PTCs and ATCs. There were also differences in penetrating injury type between PTC and ATC. CONCLUSION: The adolescent penetrating trauma patient population treated at PTC had less surgery performed with improved mortality compared with ATC. LEVEL OF EVIDENCE: Therapeutic, Level IV.

A preliminary analysis of Level IV trauma centers within an organized trauma system.

BACKGROUND: The effect of Level IV trauma center (TC) accreditation within an existing trauma network remains understudied. This study compared preaccreditation to postaccreditation data from Level IV TCs within a mature trauma system in Pennsylvania to determine whether TC designation affected time to and/or rate of transfer to definitive care. Level IV TCs were hypothesized to have a decreased time to transfer following accreditation and improved mortality. METHODS: The Pennsylvania Trauma Systems Foundation collects predesignation and postdesignation data from hospitals pursuing accreditation. Data from Pennsylvania Trauma Systems Foundation between 2012 and 2017 were analyzed. Variables of interest included patient demographics, injury severity, mortality, and incidence of surgical interventions precredentialingto postcredentialing. A multilevel mixed-effects logistic regression model assessed the adjusted impact of Level IV TC accreditation on transfer rate. ArcGIS Desktop was used for geospatial mapping of lives and geographic area covered by the addition of Level IV TCs in Pennsylvania. RESULTS: Five hospitals underwent Level IV credentialing from 2012 to 2017, providing data on 5,076 cases (pre, 2,395 [47.2%]; post, 2,681 [52.8%]). No significant difference in age, admission Glasgow Coma Scale score, or shock index was observed preaccreditation to postaccreditation. A difference in transfer rate was observed after credentialing in unadjusted (62.7% vs. 63.3%; p < 0.014) and adjusted analyses (adjusted odds ratios, 1.13, p = 0.389). There was a trend toward reduced odds of mortality postcredentialing (adjusted odds ratios, 0.59, p = 0.261). Major surgical intervention decreased (Pre, 0.42%; Post, 0.04%; p = 0.004). CONCLUSION: Level IV TC accreditation has beneficial effects on increased transfer rates and may improve mortality. It is important to continue to observe the impact of Level IV TCs on patient outcomes within a mature trauma system. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III.

An analysis of pediatric trauma center undertriage in a mature trauma system.

BACKGROUND: Improved mortality as a result of appropriate triage has been well established in adult trauma and may be generalizable to the pediatric trauma population as well. We sought to determine the overall undertriage rate (UTR) in the pediatric trauma population within Pennsylvania (PA). We hypothesized that a significant portion of pediatric trauma population would be undertriaged. METHODS: All pediatric (age younger than 15) admissions meeting trauma criteria (International Classification of Diseases, Ninth Revision: 800-959) from 2003 to 2015 were extracted from the Pennsylvania Health Care Cost Containment Council (PHC4) database and the Pennsylvania Trauma Systems Foundation (PTSF) registry. Undertriage was defined as patients not admitted to PTSF-verified pediatric trauma centers (n = 6). The PHC4 contains inpatient admissions within PA, while PTSF only reports admissions to PA trauma centers. ArcGIS Desktop was used for geospatial mapping of undertriage. RESULTS: A total of 37,607 cases in PTSF and 63,954 cases in PHC4 met criteria, suggesting UTR of 45.8% across PA. Geospatial mapping reveals significant clusters of undertriage regions with high UTR in the eastern half of the state compared to low UTR in the western half. High UTR seems to be centered around nonpediatric facilities. The UTR for patients with a probability of death 1% or less was 39.2%. CONCLUSION: Undertriage is clustered in eastern PA, with most areas of high undertriage located around existing trauma centers in high-density population areas. This pattern may suggest pediatric undertriage is related to a system issue as opposed to inadequate access. LEVEL OF EVIDENCE: Retrospective study, without negative criteria, Level III.

The magic number: Are improved outcomes observed at trauma centers with undertriage rates below 5%?

BACKGROUND: The American College of Surgeons Committee on Trauma (ACSCOT) advises trauma centers maintain <5% undertriage rate (UTR), but provides limited rationale for this figure. We sought to determine whether patients managed at Level I/II trauma centers with a UTR less than 5% had improved outcomes compared with centers with greater than 5% UTR. We hypothesized that similar overall adjusted outcomes would be observed at trauma centers in Pennsylvania regardless of their compliance with ACSCOT undertriage recommendation. METHODS: The Pennsylvania Trauma Outcome Study database was retrospectively queried for all trauma patients managed at accredited adult Level I/II trauma centers (n = 27) from 2003 to 2015. Patients with missing data on Injury Severity Score and/or Trauma Activation Status were excluded from the analysis. Institutional UTR were calculated for all trauma centers based on ACSCOT criteria (Injury Severity Score >15; no trauma activation) and were categorized into less than 5% or greater than 5% subgroups. A multilevel mixed-effects logistic regression model assessed the adjusted impact of management at centers with less than 5% undertriage. Statistical significance was set at p less than 0.05. RESULTS: A total of 404,315 patients from 27 trauma centers met inclusion criteria. Institutional UTRs ranged from 0% to 20.5%, with 15 centers exhibiting UTR less than 5% and 12 centers with UTR greater than 5%. No clinically meaningful difference in unadjusted mortality rate was observed between subgroups (<5% UTR: 5.19%; >5% UTR: 5.20%; p < 0.001). In adjusted analysis, no difference in mortality was found for patients managed at centers with less than 5% UTR compared to those with greater than 5% UTR (adjusted odds ratio, 1.06; 95% confidence interval, 0.85-1.33; p = 0.608). CONCLUSION: Achieving ACSCOT less than 5% undertriage standards appears to have limited impact on institutional mortality. Further research should seek to identify new triage criteria that can be uniformly applied to all trauma centers. LEVEL OF EVIDENCE: Epidemiological study, level III.

Improved outcomes in elderly trauma patients with the implementation of two innovative geriatric-specific protocols-Final report.

BACKGROUND: Elderly trauma care is challenging owing to the unique physiology and comorbidities prevalent in this population. To improve the care of these patients, two practice management guidelines (PMGs) were implemented: high-risk geriatric protocol (HRGP), which triages patients based on injury patterns and comorbid conditions for occult hypotension, and the anticoagulation and trauma (ACT) alert, which is designed to streamline the care of geriatric trauma patients on anticoagulants. We hypothesized that both HRGP and ACT would decrease mortality and complications in geriatric trauma patients. METHODS: Geriatric blunt trauma patients (aged ≥65) presenting to our Level II center from January 2000 to July 2016 were extracted from the trauma registry. Do-not-resuscitate patients were excluded. The study period was divided into three phases: Phase 1, no PMGs in place (2000 to January 2006); Phase 2, HRGP only (February 2006 to February 2012); and Phase 3, HRGP + ACT (March 2012 to July 2016). Multivariate logistic regression models assessed adjusted mortality and complications during these phases to quantify the impact of these protocols. Statistical significance was set at p < 0.05. RESULTS: A total of 8,471 geriatric trauma patients met inclusion criteria. Overall mortality rate was 5.6% (Phase 1, 7.2%; Phase 2, 6.1%; Phase 3, 4.0%). No significant change in mortality was observed during Phase 2 with the HRGP only (adjusted odds ratio (OR), 0.98; 95% confidence interval, 0.73-1.34; p = 0.957); however, a significantly reduced OR of mortality was found during Phase 3 with the combination of both the HRGP and ACT (adjusted OR, 0.67; 95% confidence interval, 0.47-0.94; p = 0.021). No significant changes in incidence of complications was observed over the study duration. CONCLUSIONS: Geriatric trauma patients are not simply older adults. Improved outcomes can be realized with specific PMGs tailored to the geriatric trauma patients' needs. LEVEL OF EVIDENCE: Epidemiologic study, level III.

Preliminary results of a novel hay-hole fall prevention initiative.

BACKGROUND: Hay-hole falls are a prevalent source of trauma among Anabaptists-particularly Anabaptist youth. We sought to decrease hay-hole falls in South Central Pennsylvania through the development and distribution of all-weather hay-hole covers to members of the at-risk Anabaptist community. METHODS: Following the creation of a rural trauma prevention syndicate, hay-hole cover prototypes co-designed and endorsed by the Pennsylvania Amish Safety Committee were developed and distributed throughout South Central Pennsylvania. Preintervention and postintervention surveys were distributed to recipients to gain an understanding of the hay-hole fall problem in this population, to provide insight into the acceptance of the cover within the community, and to determine the efficacy of the cover in preventing falls. RESULTS: A total of 231 hay-hole covers were distributed throughout eight rural trauma-prone counties in Pennsylvania. According to preintervention survey data, 52% of cover recipients reported at least one hay-hole fall on their property, with 46% reporting multiple falls (median fall rate, 1.00 [1.00-2.00] hay-hole falls per respondent). The median self-reported distance from hay-hole to ground floor was 10.0 (8.00-12.0) feet, and the median number of hay-holes present on-property was 3.00 (2.00-4.00) per respondent. Postintervention survey data found 98% compliance with hay-hole cover installation and no subsequent reported hay-hole falls. CONCLUSION: With the support of the Pennsylvania Amish Safety Committee, we developed a well-received hay-hole cover which could effectively reduce fall trauma across other rural communities in the United States. LEVEL OF EVIDENCE: Epidemiological study, Level III.

Undertriage in trauma: Does an organized trauma network capture the major trauma victim? A statewide analysis.

BACKGROUND: Proper triage of critically injured trauma patients to accredited trauma centers (TCs) is essential for survival and patient outcomes. We sought to determine the percentage of patients meeting trauma criteria who received care at non-TCs (NTCs) within the statewide trauma system that exists in the state of Pennsylvania. We hypothesized that a substantial proportion of the trauma population would be undertriaged to NTCs with undertriage rates (UTR) decreasing with increasing severity of injury. METHODS: All adult (age ≥15) hospital admissions meeting trauma criteria (ICD-9, 800-959; Injury Severity Score [ISS], > 9 or > 15) from 2003 to 2015 were extracted from the Pennsylvania Health Care Cost Containment Council (PHC4) database, and compared with the corresponding trauma population within the Pennsylvania Trauma Systems Foundation (PTSF) registry. PHC4 contains all hospital admissions within PA while PTSF collects data on all trauma cases managed at designated TCs (Level I-IV). The percentage of patients meeting trauma criteria who are undertriaged to NTCs was determined and Network Analyst Location-Allocation function in ArcGIS Desktop was used to generate geospatial representations of undertriage based on ISSs throughout the state. RESULTS: For ISS > 9, 173,022 cases were identified from 2003 to 2015 in PTSF, while 255,263 cases meeting trauma criteria were found in the PHC4 database over the same timeframe suggesting UTR of 32.2%. For ISS > 15, UTR was determined to be 33.6%. Visual geospatial analysis suggests regions with limited access to TCs comprise the highest proportion of undertriaged trauma patients. CONCLUSION: Despite the existence of a statewide trauma framework for over 30 years, approximately, a third of severely injured trauma patients are managed at hospitals outside of the trauma system in PA. Intelligent trauma system design should include an objective process like geospatial mapping rather than the current system which is driven by competitive models of financial and health care system imperatives. LEVEL OF EVIDENCE: Epidemiological study, level III; Therapeutic, level IV.

Development of a trauma system and optimal placement of trauma centers using geospatial mapping.

BACKGROUND: The care of patients at individual trauma centers (TCs) has been carefully optimized, but not the placement of TCs within the trauma systems. We sought to objectively determine the optimal placement of trauma centers in Pennsylvania using geospatial mapping. METHODS: We used the Pennsylvania Trauma Systems Foundation (PTSF) and Pennsylvania Health Care Cost Containment Council (PHC4) registries for adult (age ≥15) trauma between 2003 and 2015 (n = 377,540 and n = 255,263). TCs and zip codes outside of PA were included to account for edge effects with trauma cases aggregated to the Zip Code Tabulation Area centroid of residence. Model assumptions included no previous TCs (clean slate); travel time intervals of 45, 60, 90, and 120 minutes; TC capacity based on trauma cases per bed size; and candidate hospitals ≥200 beds. We used Network Analyst Location-Allocation function in ArcGIS Desktop to generate models optimally placing 1 to 27 TCs (27 current PA TCs) and assessed model outcomes. RESULTS: At a travel time of 60 minutes and 27 sites, optimally placed models for PTSF and PHC4 covered 95.6% and 96.8% of trauma cases in comparison with the existing network reaching 92.3% or 90.6% of trauma cases based on PTSF or PHC4 inclusion. When controlled for existing coverage, the optimal numbers of TCs for PTSF and PHC4 were determined to be 22 and 16, respectively. CONCLUSIONS: The clean slate model clearly demonstrates that the optimal trauma system for the state of Pennsylvania differs significantly from the existing system. Geospatial mapping should be considered as a tool for informed decision-making when organizing a statewide trauma system. LEVEL OF EVIDENCE: Epidemiological study/Care management, level III.

Parathyroid hormone as a marker for hypoperfusion in trauma: A prospective observational study.

BACKGROUND: Hyperparathyroidism is common in critical illness. Intact parathyroid hormone has a half-life of 3 minutes to 5 minutes due to rapid clearance by the liver, kidneys, and bone. In hemorrhagic shock, decreased clearance may occur, thus making parathyroid hormone a potential early marker for hypoperfusion. We hypothesized that early hyperparathyroidism predicts mortality and transfusion in trauma patients. METHODS: A prospective observational study was performed at a Level I trauma center in consecutive adult patients receiving the highest level of trauma team activation. Parathyroid hormone and lactic acid were added to the standard laboratory panel drawn in the trauma bay on arrival, before the administration of any blood products. The primary outcomes assessed were transfusion in 24 hours and mortality. RESULTS: Forty-six patients were included. Median age was 47 years, 82.6% were men, 15.2% suffered penetrating trauma, and 21.7% died. Patients who were transfused in the first 24 hours (n = 17) had higher parathyroid hormone (182.0 pg/mL vs. 73.5 pg/mL, p < 0.001) and lactic acid (4.6 pg/mL vs. 2.3 pg/mL, p = 0.001). Patients who did not survive to discharge (n = 10) also had higher parathyroid hormone (180.3 pg/mL vs. 79.3 pg/mL, p < 0.001) and lactic acid (5.5 mmol/L vs. 2.5 mmol/L, p = 0.001). For predicting transfusion in the first 24 hours, parathyroid hormone has an area under the receiver operating characteristic curve of 0.876 compared with 0.793 for lactic acid and 0.734 for systolic blood pressure. Parathyroid hormone has an area under the receiver operating characteristic curve of 0.875 for predicting mortality compared with 0.835 for lactic acid and 0.732 for systolic blood pressure. CONCLUSION: Hyperparathyroidism on hospital arrival in trauma patients predicts mortality and transfusion in the first 24 hours. Further research should investigate the value of parathyroid hormone as an endpoint for resuscitation. LEVEL OF EVIDENCE: Prognostic, level II.

Outcome differences in adolescent blunt severe polytrauma patients managed at pediatric versus adult trauma centers.

BACKGROUND: Previous research suggests adolescent trauma patients can be managed equally effectively at pediatric and adult trauma centers. We sought to determine whether this association would be upheld for adolescent severe polytrauma patients. We hypothesized that no difference in adjusted outcomes would be observed between pediatric trauma centers (PTCs) and adult trauma centers (ATCs) for this population. METHODS: All severely injured adolescent (aged 12-17 years) polytrauma patients were extracted from the Pennsylvania Trauma Outcomes Study database from 2003 to 2015. Polytrauma was defined as an Abbreviated Injury Scale (AIS) score ≥3 for two or more AIS-defined body regions. Dead on arrival, transfer, and penetrating trauma patients were excluded from analysis. ATC were defined as adult-only centers, whereas standalone pediatric hospitals and adult centers with pediatric affiliation were considered PTC. Multilevel mixed-effects logistic regression models assessed the adjusted impact of center type on mortality and total complications while controlling for age, shock index, Injury Severity Score, Glasgow Coma Scale motor score, trauma center level, case volume, and injury year. A generalized linear mixed model characterized functional status at discharge (FSD) while controlling for the same variables. RESULTS: A total of 1,606 patients met inclusion criteria (PTC: 868 [54.1%]; ATC: 738 [45.9%]), 139 (8.66%) of which died in-hospital. No significant difference in mortality (adjusted odds ratio [AOR]: 1.10, 95% CI 0.54-2.24; p = 0.794; area under the receiver operating characteristic: 0.89) was observed between designations in adjusted analysis; however, FSD (AOR: 0.38, 95% CI 0.15-0.97; p = 0.043) was found to be lower and total complication trends higher (AOR: 1.78, 95% CI 0.98-3.32; p = 0.058) at PTC for adolescent polytrauma patients. CONCLUSION: Contrary to existing literature on adolescent trauma patients, our results suggest patients aged 12-17 presenting with polytrauma may experience improved overall outcomes when managed at adult compared to pediatric trauma centers. LEVEL OF EVIDENCE: Epidemiologic study, level III.

A novel approach to optimal placement of new trauma centers within an existing trauma system using geospatial mapping.

BACKGROUND: Trauma system expansion is a complex process often governed by financial and health care system imperatives. We sought to propose a new, informed approach to trauma system expansion through the use of geospatial mapping. We hypothesized that geospatial mapping set to specific parameters could effectively identify optimal placement of new trauma centers (TC) within an existing trauma system. METHODS: We used Pennsylvania Trauma Systems Foundation registry data of adult (age, ≥ 15 years) trauma for calendar years 2003 to 2015 (n = 408,432), hospital demographics, road networks, and US Census data files. We included TCs and zip codes outside of Pennsylvania to account for edge effects with trauma cases aggregated to the zip code centroid of residence. Our model assumptions included existing Pennsylvania Trauma Systems Foundation Level I and II TCs, a maximum travel time of 60 minutes to the TC, capacity based on mean statewide ratios of trauma cases per hospital bed size, Injury Severity Score, candidate hospitals with 200 or more licensed beds and 30 minutes or longer or 15 minutes or longer from an existing TC in nonurban/urban areas, respectively. We used the Network Analyst Location-Allocation function in ArcGIS Desktop to generate spatial models. RESULTS: Of the 130 candidate sites, only 14 met the bed size and travel time criteria from an existing TC. Approximately 70% of zip codes and 91% of cases were within 60 minutes of an existing TC. Adding one to six new optimally paced TCs increased to a maximum of 82% of zip codes and 96% of cases within 60 minutes of an existing TC. Changes to model assumptions had an impact on which candidate sites were selected. CONCLUSION: Intelligent trauma system design should include an objective process like geospatial to determine the optimum locations for new TCs within existing trauma networks. LEVEL OF EVIDENCE: Epidemiological study, level III.

Vena Cava Filter Use in Trauma and Rates of Pulmonary Embolism, 2003-2015.

IMPORTANCE: Vena cava filter (VCF) placement for pulmonary embolism (PE) prophylaxis in trauma is controversial. Limited research exists detailing trends in VCF use and occurrence of PE over time. OBJECTIVE: To analyze state and nationwide temporal trends in VCF placement and PE occurrence from 2003 to 2015 using available data sets. DESIGN, SETTING, AND PARTICIPANTS: A retrospective trauma cohort study was conducted using data from the Pennsylvania Trauma Outcome Study (PTOS) (461 974 patients from 2003 to 2015), the National Trauma Data Bank (NTDB) (5 755 095 patients from 2003 to 2014), and the National (Nationwide) Inpatient Sample (NIS) (24 449 476 patients from 2003 to 2013) databases. MAIN OUTCOMES AND MEASURES: Temporal trends in VCF placement and PE rates, filter type (prophylactic or therapeutic), and established predictors of PE (obesity, pregnancy, cancer, deep vein thrombosis, major procedure, spinal cord paralysis, venous injury, lower extremity fracture, pelvic fracture, central line, intracranial hemorrhage, and blood transfusion). Prophylactic filters were defined as VCFs placed before or without an existing PE, while therapeutic filters were defined as VCFs placed after a PE. RESULTS: Of the 461 974 patients in PTOS, the mean (SD) age was 47.2 (26.4) and 61.6% (284 621) were men; of the 5 755 095 patients in NTDB, the mean age (SD) was 42.0 (24.3) and 63.7% (3 666 504) were men; and of the 24 449 476 patients in NIS, the mean (SD) age was 58.0 (25.2) and 49.7% (12 160 231) were men. Of patients receiving a filter (11 405 in the PTOS, 71 029 in the NTDB, and 189 957 in the NIS), most were prophylactic VCFs (93.6% in the PTOS, 93.5% in the NTDB, and 93.3% in the NIS). Unadjusted and adjusted temporal trends for the PTOS and NTDB showed initial increases in filter placement followed by significant declines (unadjusted reductions in VCF placement rates, 76.8% in the PTOS and 53.3% in the NTDB). The NIS demonstrated a similar unadjusted trend, with a slight increase and modest decline (22.2%) in VCF placement rates over time; however, adjusted trends showed a slight but significant increase in filter rates. Adjusted PE rates for the PTOS and NTDB showed significant initial increases followed by slight decreases, with limited variation during the declining filter use periods. The NIS showed an initial increase in PE rates followed by a period of stagnation. CONCLUSIONS AND RELEVANCE: Despite a precipitous decline of VCF use in trauma, PE rates remained unchanged during this period. Taking this association into consideration, VCFs may have limited utility in influencing rates of PE. More judicious identification of at-risk patients is warranted to determine individuals who would most benefit from a VCF.

Big children or little adults? A statewide analysis of adolescent isolated severe traumatic brain injury outcomes at pediatric versus adult trauma centers.

BACKGROUND: The appropriate managing center for adolescent trauma patients is debated. We sought to determine whether outcome differences existed for adolescent severe traumatic brain injury (sTBI) patients treated at pediatric versus adult trauma centers. We hypothesized that no difference in mortality, functional status at discharge (FSD), or overall complication rate would be observed between center types. METHODS: All adolescent trauma patients (aged 15-17 years) presenting with isolated sTBI (head Abbreviated Injury Scale [AIS] score ≥3; all other AIS body region scores ≤2) to accredited Levels I to II trauma centers in Pennsylvania from 2003 to 2015 were extracted from the Pennsylvania Trauma Outcome Study database. Dead on arrival, transfer, and penetrating trauma patients were excluded from analysis. Adult trauma centers were defined as non-pediatirc (PED) (n = 24), whereas standalone pediatric hospitals and adult centers with pediatric affiliation were considered Pediatric (n = 9). Multilevel mixed effects logistic regression models and a generalized linear mixed models assessed the adjusted impact of center type on mortality, overall complications, and FSD. Significance was defined as a p value less than 0.05. RESULTS: A total of 1,109 isolated sTBI patients aged 15 to 17 years presented over the 13-year study period (non-PED, 685; PED, 424). In adjusted analysis controlling for age, shock index, head AIS, Glasgow Coma Scale motor, trauma center level of managing facility, case volume of managing facility, and injury year, no significant difference in mortality (adjusted odds ratio, 0.82; 95% confidence interval [CI], 0.23-2.86; p = 0.754), FSD (coefficient, -0.85; 95% CI, -2.03 to 0.28; p = 0.136), or total complication rate (adjusted odds ratio, 1.21; 95% CI, 0.43-3.39; p = 0.714) was observed between center types. CONCLUSION: Although the optimal treatment facility for adolescent patients is frequently debated, patients aged 15 to 17 years presenting with isolated sTBI may experience similar outcomes when managed at pediatric and adult trauma centers. LEVEL OF EVIDENCE: Epidemiologic study, level III; therapeutic study, level IV.