Trauma center performance indicators for nonfatal outcomes: a scoping review of the literature

Defining and measuring quality in acute paediatric trauma stabilisation: a phenomenographic study

Objectives

Trauma is the leading cause of death in children. The lack of an accepted definition of what constitutes a high-quality stabilisation of a traumatically injured child has limited the evaluation of direct interventions in simulation-based education and service-delivery models to improve trauma care. The aim of this study was to create a framework that delineates quality by exploring the perceptions of the multi-disciplinary team providing and improving this initial care.

Methods

Interviews were conducted with 36 experienced UK trauma team members and governance administrators (clinical directors to executive board level), from three standard UK trauma units. This study used a phenomenographic approach to explore the relationships and hierarchy between the contrasting perceptions of quality and evaluation of quality in this acute context.

Results

The findings show that defining quality is a more complex concept than simple proxy measurements, such as time to CT scanning. They also show that the concept of quality requires the consideration of a spectrum of perspectives that range from the simple to the more sophisticated.

This study highlights the importance of teamwork, individualised perspectives and the culture of care provision, when describing quality. A novel framework to delineate quality is presented, comprising System, Team, Process, Individual, Data and Culture.

Conclusions

This study has created a framework of understanding of acute paediatric trauma care quality and its measurement from the perspectives of team members and administrators. A framework and future tools to capture and disseminate the System, Team, Process, Individual, Data and Culture perspectives of the quality of trauma stabilisations could be a key advance in the care of severely injured children.

Electronic supplementary material

The online version of this article (10.1186/s41077-019-0091-z) contains supplementary material, which is available to authorized users.

A traumatic tale of two cities: does EMS level of care and transportation model affect survival in patients with trauma at level 1 trauma centres in two neighbouring Canadian provinces?

BACKGROUND

Two distinct Emergency Medical Services (EMS) systems exist in Atlantic Canada. Nova Scotia operates an Advanced Emergency Medical System (AEMS) and New Brunswick operates a Basic Emergency Medical System (BEMS). We sought to determine if survival rates differed between the two systems.

METHODS

This study examined patients with trauma who were transported directly to a level 1 trauma centre in New Brunswick or Nova Scotia between 1 April 2011 and 31 March 2013. Data were extracted from the respective provincial trauma registries; the lowest common Injury Severity Score (ISS) collected by both registries was ISS≥13. Survival to hospital and survival to discharge or 30 days were the primary endpoints. A separate analysis was performed on severely injured patients. Hypothesis testing was conducted using Fisher's exact test and the Student's t-test.

RESULTS

101 cases met inclusion criteria in New Brunswick and were compared with 251 cases in Nova Scotia. Overall mortality was low with 93% of patients surviving to hospital and 80% of patients surviving to discharge or 30 days. There was no difference in survival to hospital between the AEMS (232/251, 92%) and BEMS (97/101, 96%; OR 1.98, 95% CI 0.66 to 5.99; p=0.34) groups. Furthermore, when comparing patients with more severe injuries (ISS>24) there was no significant difference in survival (71/80, 89% vs 31/33, 94%; OR 1.96, 95% CI 0.40 to 9.63; p=0.50).

CONCLUSION

Overall survival to hospital was the same between advanced and basic Canadian EMS systems. As numbers included are low, individual case benefit cannot be excluded.

The association of patient and trauma characteristics with the health-related quality of life in a Dutch trauma population

Background

It is suggested in literature to use the Health Related Quality of Life (HRQoL) as an outcome indicator for evaluating trauma centre performances. In order to predict HRQoL, characteristics that could be of influence on a predictive model should be identified. This study identifies patient and injury characteristics associated with the HRQoL in a general trauma population.

Methods

Retrospective study of trauma patients admitted from 1st January 2007 through 31th December 2012. Patients were aged ≥18 years and discharged alive from the level I trauma centre. A combined health survey (SF-36 and EQ-5D) was sent to all traceable patients. The subdomain outcomes and EQ-5D index value (EQ-5Di) were compared with the reference population. A linear regression analysis was performed to identify parameters associated parameters with the HRQoL outcome.

Results

A total of 1870 patients were included for analyses. Compared to the eligible population, included patients were significantly older, more severely injured, more often admitted in the ICU and had a longer admission duration.

The SF-36 and EQ-5Di were significantly lower compared to the Dutch reference population.

The variables age, Injury Severity Score, hospital length of stay, ICU length of stay, Revised Trauma Score, probability of survival, and severe injury to the head and extremities were associated with the HRQoL in the majority of the subdomains.

Discussion

In order to use HRQoL as an indicator for trauma centre performances, there should be a consensus of the ideal timing for the measurement of HRQoL post-injury and the appropriate HRQoL instrument. Furthermore, standardised HRQoL outcomes must be developed.

Conclusion

This study revealed eight factors (described above) which could be used to predict the HRQoL in trauma patients.

The truth about trauma readmissions

BACKGROUND

There is a paucity of data on the causes and associated patient factors for unplanned readmissions among trauma patients.

METHODS

We examined patients admitted for traumatic injuries between 2007 and 2011 in the California State Inpatient Database. Using chi-square tests and multivariate logistic regression models, we determined rates, reasons, locations, and patient factors associated with 30-day readmissions.

RESULTS

Among 252,752 trauma discharges, the overall readmission rate was 7.56%, with 36% of readmissions occurring at a hospital different from the hospital of initial admission. Predictors of readmissions included being discharged against medical advice (odds ratio [OR]: 2.56 [2.35 to 2.76]); Charlson scores ≥2 (OR: 2.00 [1.91 to 2.10]); and age ≥45 years (OR: 1.29 [1.25 to 1.33]). Major reasons for readmissions were musculoskeletal complaints (22.29%), psychiatric conditions (9.40%), and surgical infections (6.69%).

CONCLUSIONS

Health and social vulnerabilities influence readmission among trauma patients, with many readmitted at other hospitals. Targeted interventions among high-risk patients may reduce readmissions after traumatic injuries.