Undertriage Rates Research Articles

The development and validation of an obstetric triage acuity index: a mixed-method study

Background There is uncertainty about the applicability of developed country triage scales in the developing population. Objective To develop and validate an obstetric triage scale in Iran. Methods This exploratory sequential mixed-method study was conducted on experienced gynecologists, emergency medicine, midwives, and nurses as evaluators, and pregnant or parturient women as sample. Development of obstetric triage acuity index was done using qualitative study and literature review. Thirty-two evaluators in two rounds evaluated the clinical impact score, content validity ratio, and content validity index. The tool performance was compared with a standard reference in 415 women. The association of urgency levels with hospitalization, resource utilization, and emergency department length of stay were assessed in 599 women. Five midwives independently double-triaged 234 convenience women to estimate inter-rater reliability. Results Out of 191 items in the initial draft, 9 (4.7%) items in the face validity, 33 (18.1%) in the first, and 5 (3.2%) in the second content validity round were removed because not meeting the expected thresholds. Nine items added based on evaluators’ suggestions. Finally, total items had a kappa above 0.74, and S-CVI/Ave, S-CVI/UA were 0.99 and 0.86, respectively. There was a significant correlation between the two tools (r = 0.661, p < 0). Level 1 mothers had a higher chance of using ≥ 2 resources (OR = 16.4, 95% CI = 2.06–129.98) and hospitalization (OR = 18.0, 95% CI = 3.96–81.51) compared to the level 5, after adjusting for gestational age/postpartum, and referral method. Sensitivity, specificity, and accuracy of the scale in predicting hospitalization were 74.8% (95% CI = 69.73–79.49), 80.8% (95% CI = 73.60–86.74), and 76.7% (72.67–80.48), respectively. The over and under-triage rates were 6.1% and 17.1%, respectively. The absolute agreement inter-raters was 86.8%, and the linear weighted kappa was 0.86 (95% CI = 0.81–0.91). Conclusion The designed OB triage scale showed good validity and reliability in the tertiary teaching hospital. Studying this tool at lower levels, non-educational, and public hospitals are recommended for external validity testing.

An analysis of pediatric social vulnerability in the Pennsylvania trauma system

BackgroundThe 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. MethodsThe 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. ResultsSVI 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. ConclusionIndividual patient level factors (primary payer of patient) may be associated with the odds of rehab admission rather than neighborhood factors. Level of EvidenceEpidemiologic: Level III.

Effect of New 9-1-1 System on Efficiency of Initial Resource Assignment

Objective: To determine the impact of a new dispatch system on the efficiency of first resource assignment for critical EMS patients. Methods: In December 2014, the Los Angeles Fire Department (LAFD) implemented a new, internally-developed dispatch system. An interrupted time series study compared 9-1-1 incidents processed by LAFD-telecommunicators using either the Medical Priority Dispatch System® (MPDS, January 1 - September 30, 2014), or Los Angeles Tiered Dispatch System (LA-TDS, January 1 - September 30, 2015). All incidents were assigned a Dispatch Level of Service (DLOS), based on whether a basic life support (BLS) or advanced life support (ALS) resource was dispatched, and a Field-Recommended Level of Service (RLOS), a metric based on medical necessity, required scope of practice, number and intensity of interventions, and patient severity. DLOS options included BLS or ALS, whereas RLOS options included BLS, ALS1 and ALS2, with ALS2 cases having the greatest medical need. The primary outcome was critical under-triage rate, and secondary outcomes included rates of over-triage, total resource utilization and test characteristics of each dispatch system. Results: 563,188 incidents met inclusion criteria, including 271,604 using MPDS and 291,584 using LA-TDS. During the MPDS period, 96,561 (35.6%) incidents were initially dispatched with BLS resources (including 194 (0.071% ultimately found in the field to be high-acuity RLOS ALS2), and 175,043 were dispatched with ALS resources. During the LA-TDS period, 127,827 (43.8%) were dispatched as BLS (including 154 RLOS ALS2) and 163,798 were dispatched as ALS. For the primary outcome, the critical under-triage rate was 0.20% using MPDS and 0.12% using LA-TDS (Z 4.7, p < 0.0001, RR 0.61 CI 95% 0.50-0.76), and this improvement was primarily driven by improved triage of cardiac arrest. The over-triage rate using MPDS was 44%, which decreased to 33% using LA-TDS. LA-TDS was associated with significant improvements in specificity, positive predictive value and accuracy of initial resource assignment, and is projected to have saved over 23,000 EMS resource dispatches over the 9-month study period. Conclusion: The new Los Angeles Tiered Dispatch System significantly improved the efficiency of initial 9-1-1 resource assignments by decreasing both over-triage and critical under-triage, thus sending more appropriate resources to each 9-1-1 call.

Efforts to Improve Appropriate Trauma Activation for Patients Transferred to a Level 1 Trauma Center From Outside Hospitals.

Trauma centers monitor under- and overtriage rates to comply with American College of Surgeons Committee on Trauma verification requirements. Efforts to maintain acceptable rates are often undertaken as part of quality assurance. The purpose of this project was to improve the institutional undertriage rate by focusing on appropriately triaging patients transferred from outside hospitals (OSHs). Trauma physicians received education and pocket cards outlining injury severity score (ISS) calculation to aid in prospectively estimating ISS for patients transferred from OSHs, and activate the trauma response expected for that score. Under- and overtriage rates before and after the intervention were compared. The postintervention period saw a significant decrease in overall overtriage rate, with simultaneous trend toward lower overall undertriage rate, attributable to the significant reduction in undertriage rate of patients transferred from OSHs. Prospectively estimating ISS to assist in determining trauma activation level shows promise in managing appropriate patient triage. However, questions arose regarding the necessity for full trauma activation for transferred patients, regardless of ISS. It may be necessary to reconsider how patients transferred from OSHs are evaluated. Full trauma activation can be a financial and resource burden, and should not be taken lightly.

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

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. 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. 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. 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. Epidemiological, Level III.

Undertriage as quality of care parameter in an emergency department

Undertriage or the underestimation of the urgency of the condition of a person arriving in an emergency department (ED) represents a measure of quality care. To estimate the prevalence of undertriage in a high complexity hospital of Argentina; to describe characteristics and mortality of these patients. All consultations admitted to the ED during 2014 were analyzed. Those assigned to a lower level of admission risk (classified as Emergency Severity Index -ESI- 3 to 5) but required hospitalization in intensive care units (ICU) as the first hospitalization place were considered as an undertriage. A random sample of correctly categorized admissions (ESI 1 or 2), who were subsequently hospitalized in the ICU, was selected as a comparison group. The global undertriage prevalence was 0.30% (316/104,832). Among patients admitted to the ICU, the prevalence was 21% (316/1,461; 95% confidence intervals (CI) 19-24). The 316 patients whose severity was underestimated had a median age of 73 years, and admitted between 7 a.m. and 9 p.m. in a greater proportion. Overall hospital mortality was 8.9% (95% CI 6.78-11.38), and all deaths occurred after the patient was transferred from the emergency room. There were no differences in mortality between patients with correct triage or undertriage (11 and 7% respectively, p = 0.09). No differences were observed either in the total number of critical interventions during care in the first 24 hours. Significant differences were observed in requirements for mechanical ventilation (11 and 4% respectively, p = 0.01), orotracheal intubation (10 and 5% respectively p = 0.01) and non-invasive ventilation (8 and 4% respectively, p = 0.05). Undertriage rate in this series was low, but it can be improved.

Comparative analysis of MGAP, GAP, and RISC2 as predictors of patient outcome and emergency interventional need in emergency room treatment of the injured.

Little is known about the capabilities of triage and risk scores to predict the outcomes of injured patients, other than mortality, or to determine the need for trauma center resources. Retrospective analysis of prospectively gathered monocenter data on consecutively admitted adult emergency room trauma patients. For each patient, the GAP (Glasgow Coma Scale, Age and Pressure), MGAP (mechanism + GAP) scores and the revised injury severity classification 2 (RISC2) were calculated. The predictive performance of these scores was compared for the assessment of trauma severity, hospital resource need and early patient outcomes (area under the receiver operator characteristics, AUROC). 2112 patients were evaluated [mean age 49.1years; Injury Severity Score (ISS) 9.5]. GAP, MGAP, and RISC2 worked best at predicting mortality (AUROC 93.2, 93.5 and 96.1%, respectively). Other endpoints such as ISS > 15, emergency interventions, disability status, and return-not-home were predicted less precisely by these three scores, better by RISC2 (AUROC range 66.2-88.8%) than by (M)GAP-scores (55.2-84.1%), except for preclinical interventions. Over- and undertriage rates for the (M)GAP scores varied between 27.5-53.4% and 10.4-30%, respectively. The almost comparable precision of the three risk scores in the prediction of outcome or interventional need following trauma, and the fact, that the RISC2 can only be calculated following extensive diagnostics, favor earlier applicable (M)GAP scoring in the emergency setting. Overall, due to its easier use, the GAP appears to be the most preferable for the early assessment and triage of the injured in a trauma setting based on this European trauma center experience (NCT02165137).

The Suitability of the CdC field Triage for Korean Trauma Care

Purpose: Accurate and appropriate prehospital field triage is essential for a trauma system. The Korean trauma system (established in 2014) uses the trauma field triage algorithm of the United States Centers for Disease Control and Prevention (CDC). This study evaluated the suitability of the CDC field triage criteria for major trauma cases (injury severity score >15) in Korea. Methods: This retrospective cohort study evaluated trauma patients who presented at the authors’ regional trauma center from January 1 to May 7, 2017. The undertriage and overtriage rates of each CDC field triage step were calculated. Receiver operating characteristic curves were constructed, and the area under the curve (AUC) was evaluated for each step. Results: Among the 1,009 enrolled patients, 168 (16.7%) had major trauma. The undertriage/overtriage rates of each step (steps I, II, III, and IV) of CDC field triage were 9.2%/47.4%, 6.3%/50.8%, 4.5%/59.4%, and 5.3%/78.9%, respectively. The AUC values of each CDC triage step were 0.722, 0.783, 0.791, and 0.615, respectively. The AUC values of the separate components of each step (physiologic criteria, anatomic criteria, mechanism- of-injury criteria, and special considerations) were 0.722, 0.648, 0.647, and 0.456, respectively. Conclusions: The CDC field triage system is acceptable, but not ideal, for Korean trauma care. If we follow the protocol, it would be preferable to omit step IV. The Korean Triage and Acuity Scale may be a good indicator for in-hospital triage. However, a new triage protocol that is simple to estimate on-scene while having good performance should be developed.

Does Mechanism of Injury Predict Trauma Center Need for Children?

Objective To determine if the Mechanism of Injury Criteria of the Field Triage Decision Scheme (FTDS) are accurate for identifying children who need the resources of a trauma center. Methods EMS providers transporting any injured child ≤15 years, regardless of severity, to a pediatric trauma center in 3 midsized communities over 3 years were interviewed. Data collected through the interview included EMS observed physiologic condition, suspected anatomic injuries, and mechanism. Patients were then followed to determine if they needed the resources of a trauma center by reviewing their medical record after hospital discharge. Patients were considered to need a trauma center if they received an intervention included in a previously published consensus definition. Data were analyzed with descriptive statistics including positive likelihood ratios (+LR) and 95% confidence intervals (95%CI). Results 9,483 provider interviews were conducted and linked to hospital outcome data. Of those, 230 (2.4%) met the consensus definition for needing a trauma center. 1,572 enrolled patients were excluded from further analysis because they met the Physiologic or Anatomic Criteria of the FTDS. Of the remaining 7,911 cases, 62 met the consensus definition for needing a trauma center (TC). Taken as a whole, the Mechanism of Injury Criteria of the FTDS identified 14 of the remaining 62 children who needed the resources of a trauma center for a 77% under-triage rate. The mechanisms sustained were 36% fall (16 needed TC), 28% motor vehicle crash (MVC) (20 needed TC), 7% struck by a vehicle (10 needed TC), <1% motorcycle crash (none needed TC), and 29% had a mechanism not included in the FTDS (16 needed TC). Of those who sustained a mechanisms not listed in the FTDS, the most common mechanisms were sport related injuries not including falls (24% of 2,283 cases with a mechanism not included) and assault (13%). Among those who fell from a height greater than 10 feet, 4 needed a TC (+LR 5.9; 95%CI 2.8-12.6). Among those in a MVC, 41 were reported to have been ejected and none needed a TC, while 31 had reported meeting the intrusion criteria and 0 needed a TC. There were 32 reported as having a death in the same vehicle, and 2 needed a TC (+LR 7.42; 95%CI: 1.90-29.0). Conclusion Over a quarter of the children who needed the resources of a trauma center were not identified using the Physiologic or Anatomic Criteria of the Field Triage Decision Scheme. The Mechanism of Injury Criteria did not apply to over a quarter of the mechanisms experienced by children transported by EMS for injury. Use of the Mechanism Criteria did not greatly enhance identification of children who need a trauma center. More work is needed to improve the tool used to assist EMS providers in the identification of children who need the resources of a trauma center.

Centralization of Prehospital Triage Improves Triage of Pediatric Trauma Patients.

This study describes the experience at a level 1 pediatric trauma center before and after the centralization of prehospital trauma triage, focusing on the rate of undertriage of trauma patients. Before centralization, emergency physicians were responsible for triaging these patients with mainly physiology-based criteria; after centralization, paramedics in a communication center performed this function using the same criteria. This retrospective study includes 10 years of pediatric trauma registry patients at our institution, 5 years before and after centralization of prehospital triage. Rates of undertriage were calculated by both the Cribari Method and by disposition from the emergency department. Logistic regression was used to assess the effect of centralization on the incidence of undertriage while adjusting for differences in case-mix. Over the 10-year study period, 1862 trauma activations meeting inclusion and exclusion criteria were recorded in the trauma registry: 893 patients in the precentralization and 969 in the postcentralization groups. After centralization of the triage process, there were statistically significant decreases in the rates of undertriage from 8.7% to 4.2% (adjusted odds ratio, 0.49; 95% confidence interval, 0.33-0.73) when analyzed by the Cribari Method and from 37.7% to 27.7% when analyzed by disposition from the emergency department (adjusted odds ratio, 0.66; 95% confidence interval, 0.64-0.81). This represents a reduction in undertriage by 51.7% and 26.5%, respectively. Centralization of prehospital trauma triage at a level 1 pediatric trauma facility significantly reduced undertriage rates. Trauma centers should consider similar processes to improve prehospital triage.

Redefining the Trauma Triage Matrix: The Role of Emergent Interventions

BackgroundA tiered trauma team activation (TTA) system aims to allocate resources proportional to the patient's need based upon injury burden. The current metrics used to evaluate appropriateness of TTA are the trauma triage matrix (TTM), need for trauma intervention (NFTI), and secondary triage assessment tool (STAT). Materials and methodsIn this retrospective study, we compared the effectiveness of the need for an emergent intervention within 6 h (NEI-6) with existing definitions. Data from the Michigan Trauma Quality Improvement Program was utilized. The dataset contains information from 31 level 1 and 2 trauma centers from 2011 to 2017. Inclusion criteria were: adult patients (≥16 y) and ISS ≥5. Results73,818 patients were included in the study. Thirty percentage of trauma patients met criteria for STAT, 21% for NFTI, 20% for TTM, and 13% for NEI-6. NEI-6 was associated with the lowest rate of undertriage at 6.5% (STAT 22.3%, NFTI 14.0%, TTM 14.3%). NEI-6 best predicted undertriage mortality, early mortality, in-hospital mortality, and late (>60 h) mortality. Most patients who met criteria for TTM (58%), NFTI (51%), and STAT (62%) did not require emergent intervention. All four methods had similar rates of early mortality for patients who did not meet criteria (0.3%-0.5%). ConclusionsNEI-6 performs better than TTM, NFTI, and STAT in terms of undertriage, mortality and need for resource utilization. Other methods resulted in significantly more full TTAs than NEI-6 without identifying patients at risk for early mortality. NEI-6 represents a novel tool to determine trauma activation appropriateness.

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

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). 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. 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. 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. Epidemiological, Level III.

Prehospital triage of acute aortic syndrome using a machine learning algorithm.

Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS. Details of consecutive patients enrolled in a regional specialist aortic network were collected prospectively. Two prediction algorithms for AAS based on logistic regression and an ensemble machine learning method called SuperLearner (SL) were developed. Undertriage was defined as the proportion of patients with AAS not transported to the specialist aortic centre, and overtriage as the proportion of patients with alternative diagnoses but transported to the specialist aortic centre. Data for 976 hospital admissions between February 2010 and June 2017 were included; 609 (62·4 per cent) had AAS. Overtriage and undertriage rates were 52·3 and 16·1 per cent respectively. The population was divided into a training cohort (743 patients) and a validation cohort (233). The area under the receiver operating characteristic (ROC) curve values for the logistic regression score and the SL were 0·68 (95 per cent c.i. 0·64 to 0·72) and 0·87 (0·84 to 0·89) respectively (P < 0·001) in the training cohort, and 0·67 (0·60 to 0·74) and 0·73 (0·66 to 0·79) in the validation cohort (P = 0·038). The logistic regression score was associated with undertriage and overtriage rates of 33·7 (bootstrapped 95 per cent c.i. 29·3 to 38·3) and 7·2 (4·8 to 9·8) per cent respectively, whereas the SL yielded undertriage and overtriage rates of 1·0 (0·3 to 2·0) and 30·2 (25·8 to 34·8) per cent respectively. A machine learning prediction model performed well in discriminating AAS and could be clinically useful in prehospital triage of patients with suspected AAS.

Accuracy of pre-hospital trauma triage and field triage decision rules in children (P2-T2 study): an observational study

Adequate pre-hospital trauma triage is crucial to enable optimal care in inclusive trauma systems. Transport of children in need of specialised trauma care to lower-level trauma centres is associated with adverse patient outcomes. We aimed to evaluate the diagnostic accuracy of paediatric field triage based on patient destination and triage tools. We did a multisite observational study (P2-T2) of all children (aged <16 years) transported with high priority by ambulance from the scene of injury to any emergency department in seven of 11 inclusive trauma regions in the Netherlands. Diagnostic accuracy based on the initial transport destination was evaluated in terms of undertriage rate (ie, the proportion of patients in need of specialised trauma care who were initially transported to a lower-level paediatric or adult trauma centre) and overtriage rate (ie, the proportion of patients not requiring specialised trauma care who were transported to a level-I [highest level] paediatric trauma centre). The Dutch National Protocol of Ambulance Services and Field Triage Decision Scheme triage protocols were externally validated using data from this cohort against an anatomical (Injury Severity Score [ISS] ≥16) and a resource-based reference standard. Between Jan 1, 2015, and Dec 31, 2017, 12 915 children (median age 10·3 years, IQR 4·2-13·6) were transported to the emergency department with injuries. 4091 (31·7%) patients were admitted to hospital, of whom 129 (3·2%) patients had an ISS of 16 or greater and 227 (5·5%) patients used critical resources within a limited timeframe. Ten patients died within 24 h of arrival at the emergency department. Based on the primary reference standard (ISS ≥16), the undertriage rate was 16·3% (95% CI 10·8-23·7) and the overtriage rate was 21·2% (20·5-22·0). The National Protocol of Ambulance Services had a sensitivity of 53·5% (95% CI 43·9-62·9) and a specificity of 94·0% (93·4-94·6), and the Field Triage Decision Scheme had a sensitivity of 64·5% (54·1-74·1) and a specificity of 84·3% (83·1-85·5). Too many children in need of specialised care were transported to lower-level paediatric or adult trauma centres, which is associated with increased mortality and morbidity. Current protocols cannot accurately discriminate between patients at low and high risk, and highly sensitive and child-specific triage tools need to be developed to ensure the right patient is transported to the right hospital. The Netherlands Organisation for Health Research and Development, Innovation Fund Health Insurers.

Over-Under Triage in Trauma Team Activation: A retrospective analysis in Asst Monza

Meeting the literature standards during the triage process of trauma victims, allows to make optimal use of the resources available in Trauma Centers and defines their level of quality and efficiency. Otherwise, it may occur over or under-triage. Up to now, in the reality under study and in the national literature, there wasn't any available data about efficiency and effectiveness in the triage of traumatic patients, therefore the primary objective of this study is to evaluate the over and under-triage rate in activating Trauma Team (TT) in the ASST of Monza San Gerardo Hospital. The study design is retrospective monocentric observational. During the analysis, the TT-activation in ASST of Monza-San Gerardo Hospital produced an over-triage of 62,9% and an under-triage of 1,7% for the same year. The use of TT-activation algorithm is the first step of the entire care process ofthe trauma victim. This tool should guarantee the right balance between high sensitivity and high specificity (minimum over-triage rate with the possibility of higher under-triage). However, there is no sharing of these algorithms as they are inhomogeneous in the different realities; for example, the definition of major trauma, of TT and of its composition is still uneven. This study measured the over and under-triage rate related to the TT activation in the ASST of Monza. It is therefore advisable to monitor those rates periodically, as possible indicators of quality of assistance and to pursue the mission of increasing efficiency as well as effectiveness.

Validity and Reliability of Emergency Severity Index and Conventional Three-Tier Triage System in the Emergency Department, Hospital Universiti Sains Malaysia.

BackgroundThe study aimed to examine the reliability and validity of the existing three-tier triaging system and a new five-level emergency triaging system, emergency severity index (ESI), in the Emergency Department (ED) of Hospital Universiti Sains Malaysia (HUSM).MethodsThis study was conducted in HUSM’s ED over two study periods. In the first three months, 300 patients were triaged under the three-tier triaging system, and, in the subsequent three months, 280 patients were triaged under the ESI. The patients were triaged by junior paramedics and the triage records were retained and later re-triaged by senior paramedics. The inter-rater reliability was evaluated using Cohen's Kappa statistics. The acuity ratings of the junior paramedics were compared with those of the expert panel to determine the sensitivity and specificity of each acuity level for both the ESI and the three-tier triaging system. The over-triage rate, under-triage rate, amount of resources used, admission rate and discharge rate were also determined.ResultsThe inter-rater agreement for the three-tier triaging system was 0.81 while that of the ESI was 0.75. The ESI had a higher average sensitivity of 74.3% and a specificity of 94.4% while the three-tier system’s average sensitivity was 68.5% and its specificity 87.0%. The average under-triage and over-triage rates for the ESI were 10.7% and 6.2%, respectively, which were lower than the three-tier system’s average under-triage rate of 13.1% and over-triage rate of 17.1%. The urgency levels of both the ESI and the three-tier system were associated with increased admission rates and resources used in the ED.ConclusionThe ESI’s inter-rater reliability was comparable to the three-tier triaging system and it demonstrated better validity than the existing three-tier system.

Two-Tiered Ambulance Dispatch and Redeployment considering Patient Severity Classification Errors.

A two-tiered ambulance system, consisting of advanced and basic life support for emergency and nonemergency patient care, respectively, can provide a cost-efficient emergency medical service. However, such a system requires accurate classification of patient severity to avoid complications. Thus, this study considers a two-tiered ambulance dispatch and redeployment problem in which the average patient severity classification errors are known. This study builds on previous research into the ambulance dispatch and redeployment problem by additionally considering multiple types of patients and ambulances, and patient classification errors. We formulate this dynamic decision-making problem as a semi-Markov decision process and propose a mini-batch monotone-approximate dynamic programming (ADP) algorithm to solve the problem within a reasonable computation time. Computational experiments using realistic system dynamics based on historical data from Seoul reveal that the proposed approach and algorithm reduce the risk level index (RLI) for all patients by an average of 11.2% compared to the greedy policy. In this numerical study, we identify the influence of certain system parameters such as the percentage of advanced-life support units among all ambulances and patient classification errors. A key finding is that an increase in undertriage rates has a greater negative effect on patient RLI than an increase in overtriage rates. The proposed algorithm delivers an efficient two-tiered ambulance management strategy. Furthermore, our findings could provide useful guidelines for practitioners, enabling them to classify patient severity in order to minimize undertriage rates.

Hospital resources do not predict accuracy of secondary trauma triage: A population-based analysis.

The identification of patients who require transfer from non-trauma centers to trauma centers (secondary triage) is complicated by high rates of undertriage and overtriage. The objective of this study was to evaluate variations in secondary triage accuracy across non-trauma centers and identify factors associated with highly accurate secondary triage. We performed a population-based study of injured patients who presented to non-trauma centers in a large regional trauma system. Patients were categorized as undertriaged, overtriaged, or appropriately triaged based on transfer status and presence of a severe injury (Injury Severity Score >15, death within 24 hours, or critical injury as defined by the American College of Surgeons). Mixed-effect models, adjusted for case mix and hospital resource, were used to compare triage accuracy across hospitals and identify factors associated with high-performing centers. Among 118,973 patients identified at 182 non-trauma centers, 37,528 (31.5%) had severe injuries. The majority (76.9%) of severely injured patients were not transferred to a trauma center (undertriaged), while 9.6% of nonseverely injured patients were transferred to a trauma center (overtriaged). Mixed-effect models demonstrated that at the average hospital severely injured patients were 3.76 times more likely to be transferred than nonseverely injured patients (diagnostic odds ratio, 3.76; 95% confidence interval, 3.20-4.31). Despite significant variation in triage accuracy across hospitals, adjusted analyses suggested that local resources bore no relationship to triage accuracy. Triage accuracy varies significantly across non-trauma centers, after adjusting for hospital resources. These findings suggest that other potentially modifiable factors play a key role in transfer decisions. Therapeutic/care management, level IV.

Accuracy of algorithms to predict injury severity in older adults for trauma triage

Objective: Older adults make up a rapidly increasing proportion of motor vehicle occupants and previous studies have demonstrated that this population is more susceptible to traumatic injuries. The CDC recommends that patients anticipated to have severe injuries (Injury Severity Score [ISS] ≥ 16) be transported to a trauma center. The recommended target rate for undertriage is ≤ 5% and for overtriage is ≤ 50%. Several regression-based algorithms for injury prediction have been developed in order to predict severe injury in occupants involved in a motor vehicle collision (MVC). The objective of this study to was to determine if the accuracy of regression-based injury severity prediction algorithms decreases for older adults.Methods: Data were obtained from the National Automotive Sampling System – Crashworthiness Data System (NASS-CDS) from the years 2000–2015. Adult occupants involved in non-rollover MVCs were included. Regression-based injury risk models to predict severe injury (ISS ≥ 16) were developed using random split-samples with the following variables: age, delta-V, direction of impact, belt status, and number of impacts. Separate models were trained using data from the following age groups: (1) all adults, (2) 15–54 years, (3) ≥45 years, (4) ≥55 years, and (5) ≥65 years. The models were compared using the mean receiver operating characteristic area under curve (ROC-AUC) after 1,000 iterations of training and testing. The predicted rates of overtriage were then determined for each group in order to achieve an undertriage rate of 5%.Results: There were 24,577 occupants (6,863,306 weighted) included in this analysis. The injury prediction model trained using data from all adults did not perform as well when tested on older adults (ROC-AUC: 15–54 years: 0.874 [95% CI: [0.851–0.895]; 45+ years: 0.837 [95% CI: 0.802–869]; 55+ years: 0.821 [95% CI: 0.775–0.864]; and 65+ years: 0.813 [95% CI: 0.754–0.866]). The accuracy of this model decreased in each decade of life. The performance did not change significantly when age-specific data were used to train the prediction models (ROC-AUC: 18–54 years: 0.874 [95% CI: 0.851–0.896]; 45+ years: 0.836 [95% CI: 0.798–0.871]; 55+ years: 0.822 [95% CI: 0.779–0.864]; and 65+ years: 0.808 [95% CI: 0.748–0.868]). In order to achieve an undertriage rate of 5%, the predicted overtriage rate by these models were 50% for occupants 15–54 years, 61% for occupants ≥ 55 years, 70% for occupants ≥ 55 years, and 71% for occupants ≥ 65 years.Conclusion: The results of this study indicate that it is more difficult to accurately predict severe injury in older adults involved in MVCs, which has the potential to result in significant overtriage. This decreased accuracy is likely due to variations in fragility in older adults. These findings indicate that special care should be taken when using regression-based prediction models to determine the appropriate hospital destination for older occupants.

Association of Practitioner Interfacility Triage Performance With Outcomes for Severely Injured Patients With Fee-for-Service Medicare Insurance

Despite evidence that treatment of severely injured patients at trauma centers is associated with reduced mortality, nearly half of all such patients are treated at nontrauma centers (undertriaged). Little is known about whether interfacility undertriage occurs because of practitioner decision-making or institutional and regional factors. To assess the associations between variation in triage practitioners at nontrauma centers and between practitioner-level variation and patient outcomes after injury. This retrospective cohort study used Medicare claims data from severely injured patients presenting to nontrauma centers and the practitioners who evaluated them in the emergency department from January 1, 2010, to October 15, 2015. Data analysis was performed from January 15, 2018, to March 21, 2019. Proportion of variation in undertriage associated with practitioners, practitioner rates of undertriage, practitioner characteristics associated with undertriage, and 30-day case-fatality rate. A total of 124 008 severely injured patients (mean [SD] age, 81 [8.4] years; 67 253 [54.2%] female) and the 25 376 practitioners (5564 [21.9%] female) who evaluated the patients in the emergency department of nontrauma centers were included in the study. Undertriage occurred among 85 403 patients (68.9%), with 40.6% of total variation associated with practitioners, 37.8% with hospitals, and 6.7% with regions. Compared with physicians with National Provider Identification (NPI) enumeration before 2007, those with an NPI enumerated between 2007 and 2010 had an undertriage risk ratio (RR) of 0.98 (95% CI, 0.97-0.99), and those with an NPI enumerated after 2010 had an undertriage RR of 0.96 (95% CI, 0.94-0.99). Hospitals with neurosurgeons had an undertriage RR of 1.51 (95% CI, 1.45-1.57) compared with those that did not; hospitals with spine surgeons had an undertriage RR of 1.10 (95% CI, 1.06-1.13); hospitals with general surgeons had an undertriage RR of 1.13 (95% CI, 1.09-1.17). Compared with practitioners who undertriaged 25% or less of patients, a statistically significant increase was found in the odds of death for patients treated by practitioners with a triage rate of less than 25% to 50% (odds ratio [OR], 1.08; 95% CI, 1.05-1.20) and less than 50% to 75% undertriage (OR, 1.12; 95% CI, 1.09-1.26) but not undertriage at greater than 75% (OR, 1.03, 95% CI, 1.00-1.18). In sensitivity analyses to adjust for unmeasured confounding, the association between triage practices and the case fatality rate became monotonic; compared with patients treated by practitioners with an undertriage rate of 25% or less, the odds of case fatality were 1.13 (95% CI, 1.05-1.21; P = .001) among patients treated by practitioners with undertriage rates less than 25% to 50%, 1.22 (95% CI, 1.13-1.32; P < .001) for patients treated by practitioners with undertriage rates less than 50% to 75%, and 1.20 (95% CI, 1.10-1.30; P < .001) for patients treated by practitioners with undertriage rates greater than 75%. The findings suggest that individual practitioner practices are an important source of variation in triage and represent a potential locus of intervention to reduce preventable deaths after injury.