Association between health system navigation factors and preventable trauma mortality in Western Cape, South Africa

Abstract

Background

Timely access to trauma care is critical to reducing injury mortality. In the Western Cape of South Africa, trauma care is delivered in a tiered system. Resource limitations at lower facility levels—such as limited imaging, surgical access, or after-hours support—necessitate transfers to higher levels for on-going care of serious injury. Delays—including delays from transfers—can impact mortality. This study quantitatively reexamines a cohort of trauma decedents to further elucidate system navigation factors associated with preventable trauma mortality.

Methods

In the Western Cape, an ongoing, observational cohort study, Epidemiology and Outcomes of Prolonged Trauma Care (EpiC), enrolls adult patients who experience major trauma. In 2024, a multi-disciplinary expert panel determined preventability of EpiC trauma deaths. Injury details and process indicators (e.g., time of arrival, length of stay, interfacility transfers (IFT)) for each case were captured by the EpiC study. Characteristics of preventable versus non-preventable cases were compared using Chi-square, Wilcoxon signed rank tests, and logistic regression analysis to assess associations between health system navigation factors and preventable trauma mortality.

Results

A total of 160 cases were included: 63 were preventable (39.4%) and 97 were non-preventable (60.6%). Though the median total health facility length of stay was found to be significantly higher in the preventable death cohort (39.7 h; IQR 5.7, 184.8) versus non-preventable (10.3 h; IQR 1.5, 59.1); p-value = 0.0024), the majority of deaths occurred in the emergency centre (EC) in both groups (54% preventable cohort, 68% non-preventable cohort, p-value = 0.2232). There was no statistically significant increased odds of preventable death when examining EC length of stay or arrival to an EC during a less resourced time. However, independent of injury severity and first EC length of stay, there was a significant association between patients receiving IFT and increased odds of dying from a preventable death (OR 2.94, 95%CI 1.09–7.87).

Conclusion

These findings likely demonstrate IFT as a marker of increased trauma system complexity and extended exposure to system vulnerabilities across multiple phases of care. Tiered trauma systems in resource-constrained settings should account for this association in system design and operations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12245-026-01221-1.

Introduction

Injuries remain a leading global cause of death, responsible for approximately 4.4 million deaths annually, with the vast majority occurring in low- and middle-income countries (LMICs) [1]. Timely access to trauma care is critical to reducing injury mortality, as life-saving interventions, such as transfusion and hemorrhage control, are most effective when delivered early [2]. However, in sub-Saharan Africa, deficiencies across the trauma care continuum, including limited prehospital providers and ambulances, minimal team-based trauma care, and restricted operative capability, contribute to a higher burden of potentially preventable trauma deaths [3]. Delays — whether in seeking, reaching, or receiving care — have been shown to influence care outcomes. In one South African study, 41% of examined trauma deaths were potentially preventable, with 59% of these due to in-hospital delays, such as delayed diagnosis, inadequate resuscitation, and limited access to surgical or critical care [3]. Previously reported contributors to potentially avoidable or preventable deaths include poor healthcare literacy, transport barriers, and poorly coordinated referral processes [4, 5]. Intentional trauma preventable death rate examination, through both statistical analysis and expert panel reviews, have been increasingly utilized worldwide to identify opportunities to reduce injury mortality in developing trauma systems [6, 7]. Effective trauma systems are known to reduce such mortality through organised EMS systems, structured triage protocols, dedicated emergency care training, and referral pathways [8, 9].

Similar to many other nations, South Africa’s public healthcare system follows a tiered structure, comprising of primary health care (PHC) clinics, district hospitals (level 1), regional hospitals (level 2), and tertiary hospitals (level 3) [10]. Each tier offers progressively more comprehensive services. In the Western Cape of South Africa, resource deficits at lower levels—such as limited laboratory testing, imaging or surgical care often necessitate interfacility transfers to higher-level centres for ongoing management of serious injury [11]. Though existing studies have demonstrated increased odds of mortality among patients with traumatic injuries who undergo inter-facility transfer to tertiary facilities in LMICs, assessments of death preventability and injury survivability for patients receiving care at non-tertiary facilities remain underreported [12].

Strengthening the trauma care continuum to reduce unnecessary morbidity and mortality from injury requires a multifaceted examination of existing deficits in prehospital, intra-facility, and inter-facility care provision. This study quantitatively reexamines a cohort of trauma decedents to further elucidate system navigation factors associated with preventable trauma mortality.

Methods

Study design

This is a secondary analysis of data collected during an expert panel review of 210 deaths occurring in 2023, identified by an ongoing observational cohort study in the Western Cape of South Africa called, “Epidemiology and Outcomes of Prolonged Trauma Care (EpiC).” The primary analysis of the expert panel review reported approximately 1/3 of trauma deaths to be preventable or potentially preventable, largely from haemorrhage or multiorgan failure/sepsis [13]. The present study was motivated by discussions with experts during the review and aims to assess health system navigation factors associated with preventable death. The present study utilizes two sources of data from the parent EpiC study, namely trauma clinical care data and preventable trauma death data,

Setting and population

The Western Cape carries a high trauma burden, driven largely by interpersonal violence and road traffic accidents. EpiC enrolls adult patients who experience moderate to severe trauma and receive care within 24 h of injury at one of six government facilities [14]. EpiC facilities represent the entire spectrum of care, including two PHCs (Khayelitsha Site B and Delft), two level 1 District Hospitals (Khayelitsha and Ceres Hospitals), one level 2 Secondary Hospital (Worcester Hospital), and one tertiary (Tygerberg Hospital) care facility. Suresh et al. offers a comprehensive description of each EpiC site, provider roles and hospital capabilities [14]. These facilities further represent both rural (Worcester and Ceres) and urban facilities in the Western Cape, with the longest interfacility transport time of approximately two hours from Ceres to Tygerberg.

Expert panel review process

In 2024, a multi-disciplinary expert panel was convened to review the clinical records of EpiC trauma decedents from the prior year. Composed of 30 clinical providers from the Western Cape, the expert panel was divided into three groups, with each group having representation from all six EpiC facilities and relevant medical specialties (prehospital care, family medicine, emergency medicine, intensive care, trauma surgery, orthopaedic surgery, neurosurgery, and forensic pathology). Following best practice recommendations from the WHO guidelines for preventable death reviews, the expert panel systematically assessed preventability through consensus discussion and conducted a rapid qualitative analysis of factors impacting each case over a two-day period [13].

Case inclusion/exclusion

All trauma deaths captured by the EpiC study from January 1st through December 31st, 2023 were included in the expert panel review, including patients who died during EMS transport from the scene. Cases excluded from the EpiC study, and therefore excluded from this review, were individuals who were prisoners or who presented to the hospital with envenomation, toxicologic injuries, and drownings. Patients were also excluded if the patient was seen at a non-study site or transported from scene by a private EMS agency. Helicopter or other air EMS is not routinely used in this context. For the purposes of this analysis, deaths that were pronounced on-scene and did not receive clinical care by the health system were excluded.

Data collection

The following variables were routinely abstracted from health records by trained EpiC data collectors: demographics; injury details; date and times for location of death; arrival and departure from facilities and facility units; and EMS transport times. Additional information on the EpiC study’s data collection procedures is further outlined by Suresh et al. [14] EpiC data collectors present at the expert panel review documented the panel’s consensus determination of preventability, as well as recommendations for care or system improvements. Preventability was determined using a categorization scheme devised from peer-reviewed publications and explicit existing WHO guidelines on preventable death panel reviews that includes assessment of survivability of anatomic injuries, as well as deviations from standard of care evaluation and treatment, further detailed by Dixon et al. in 2024 [15]. Of note, the expert panel did not have access to the Abbreviate Injury Scores or New Injury Severity Score (NISS) as part of their clinical review and relied on injuries as documented in the clinical notes, radiology reports and postmortem reports. Prior meta-analysis supports use of multidisciplinary panel review in determining preventable death rates [6].

In alignment with prior studies, subcategories of “preventable” mortality, indicating minimal anatomic injuries with a high likelihood of survival (> 50%) and “potentially preventable” mortality, referring to anatomic injuries and sequelae that were severe but medically survivable (25–50% probability of survival) were combined for comparative analysis [6, 15]. Similarly, “non-preventable with opportunity for improved care”, “non-preventable without opportunity for improved care”, and “indeterminate preventability” categories with probability of survival estimated to be less than 25% or unable to be determined were also combined [6, 15]. Investigators of this study defined relevant health system navigation indicator variables as informed by the discussions with the local expert mortality panel reviewers. (Table 1)

Table 1.

Selected health system navigation indicators

Process Indicator	Definition	Data Type
Time from injury to primary EMS arrival	Time from injury to arrival of EMS on scene.	Continuous (hours)
Time from injury to first health facility arrival	Time from injury to time of arrival at first health facility.	Continuous (hours)
First EC Arrival Time of Day	Time of arrival to first EC during day (8am-6pm) or night (6pm-8am).	Binary (Day/Night)
First EC Arrival During Less Resourced Period - Personnel	Time of arrival to first EC during a period of decreased staffing of EC providers (6pm-8am all facilities).	Binary (Yes/No)
First EC Arrival During Less Resourced Period – Facility Resources	Time of arrival to first EC during a period of decreased facility resources, such as access to CT imaging or surgical services: PHCs and Level 1 (CRS) – All times Level 1 (KHA) and Level 2 (WOC) – 6pm-8am everyday and 8a-6p Saturday/Sunday Level 3 (TBH) – Not applicable.	Binary (Yes/No)
First EC Arrival During Less Resourced Period - Combined	Time of arrival to first EC during the combined periods of less resourced personnel and facility resources as defined above.	Binary (Yes/No)
EC Length of Stay	Duration of time between EC arrival at health facility and departure from EC or death.	Continuous (hours)
Interfacility transfer	Transfer from one health facility to another for further care of injury.	Binary (Yes/No)
Time to second facility	Time from injury to arrival at second health facility for patients who underwent an inter-facility transfer.	Continuous (hours)
Total Health Facility Length of Stay	Time from first EC arrival to discharge from final health facility or death.	Continuous (hours)

Legend: EC = emergency centre; EMS = emergency medical services, PHC-Primary Health Center; CRS-Ceres District Hospital; WOC-Worcester Regional Hospital; KHA-Khayelitsha District Hospital; TBH-Tygerberg Tertiary Hospital

Data analysis

Patient demographic and injury characteristics were described using frequencies and percentages for categorical variables and medians with interquartile ranges for continuous variables.

Wilcoxon rank sum was reported for non-parametric continuous variables and Chi-square was reported for categorical variables where a p-value of ≤ 0.05 determined significance. Simple logistic regression was used to examine the association between independent variables of interest and the odds of having the primary outcome (i.e., a preventable death). Multivariable logistic regression was used to control for injury severity using the NISS and health system navigation variables of interest (Table 1). All analyses were done using SAS software (Version 9.4, SAS Institute Inc).

Ethics

This study received ethical approval with a waiver of informed consent from the Human Research Ethics Committee of Stellenbosch University (Ethics Reference No. N20/03/036), a reliance agreement from the Colorado Multiple Institute Review Board (COMIRB #20–2176), and a subject protection requirements concurrence memo from the Defense Health Agency Office of Human Research Oversight (OHRO Log # E01863.1x).

Results

Of the 160 deaths that met the study inclusion criteria, 63 (39%) were determined to be preventable by the panel. The study population had a median age of 32 years, and the majority were male (n = 137, 85.6%). Blunt force injuries were sustained by 75 patients (46.9%), while 62 patients (38.8%) sustained penetrating injuries. The median NISS was 37.0 (IQR: 26.0, 50.0), indicating very severe injury. The majority of patients (n = 92, 57.5%) utilized primary EMS transport to reach a healthcare facility, but only 25 patients (15.6%) required an inter-facility transfer. Geographically, 75% (n = 120) of all injuries occurred within the City of Cape Town with the remaining 25% (n = 40) occurring in the rural Cape Winelands region.

When comparing cohorts of deaths found to be preventable versus non-preventable, there were no statistically significant differences in age, sex distribution, or injury force type.(Table 2) The preventable death cohort did include a higher number of deaths with injury mechanisms of struck/stabbed (n = 26, 41.3%) and vehicular injury (n = 20, 31.7%) compared to the non-preventable group, in which the top injury mechanisms reported were struck/stabbed (n = 31, 32%) and firearm (n = 31, 32%). Importantly, and understandably given the mortality panel definitions, the non-preventable deaths cohort had a significantly higher median NISS of 41.0 (IQR 34.0, 57.0) compared to the median NISS score of 27.0 in the preventable deaths cohort (IQR 22.0, 41.0; p-value < 0.0001).

Table 2.

Decedent characteristics by death preventability category

Characteristic	All Deaths (N = 160)	Preventable/ Potentially Preventable (N = 63)	Non-Preventable/ Indeterminate (N = 97)	p-value
Age, median (IQR)	32.1 (27.0, 42.3)	33.3 (28.2, 47.0)	31.3 (26.1, 40.2)	0.0978c
Sex, n (%)				0.9793d
Male	137 (85.6%)	54 (85.7%)	83 (85.6%)
Female	23 (14.4%)	9 (14.3%)	14 (14.4%)
Injury Location, n (%)				0.5131d
Cape Winelands	40 (25.0%)	14 (22.2%)	26 (26.8%)
City of Cape Town	120 (75.0%)	49 (77.8%)	71 (73.2%)
Injury Force Type, n (%)				0.0877d
Blunt	75 (46.9%)	34 (54.0%)	41 (42.3%)
Penetrating	62 (38.8%)	19 (30.2%)	43 (44.3%)
Blunt+Penetrating	7 (4.4%)	5 (7.9%)	2 (2.1%)
Othera	16 (10.0%)	5 (7.9%)	11 (11.3%)
Injury Mechanism, n (%)				0.0373d
Struck/Stabbed	57 (35.6%)	26 (41.3%)	31 (32.0%)
Firearm	42 (26.3%)	11 (17.5%)	31 (32.0%)
Vehicular Injury	37 (23.1%)	20 (31.7%)	17 (17.5%)
Thermal	16 (10.0%)	5 (7.9%)	11 (11.3%)
Otherb	8 (5.0%)	1 (1.6%)	7 (7.2%)
New Injury Severity Score (NISS)
Median (IQR)	37.0 (26.0, 50.0)	27.0 (22.0, 41.0)	41.0 (34.0, 57.0)	< .0001c

^aOther includes burn and multiple injury force type; ^bOther includes fall, choking/hanging, and iatrogenic injuries; ^cWilcoxon rank sum p-value; ^dChi-Square p-value

The majority of decedents arrived to the EC at night (n = 115, 72%), with no significant difference between preventable (n = 40, 63.5%) and non-preventable (n = 75, 77.3%) cohorts. (Table 3) Additionally, there was no statistically significant difference in the proportion of patients who arrived to an EC during a less resourced time between the preventable and non-preventable cohorts: 84.1% (n = 53) of the preventable death cohort compared to 83.5% (n = 81) of the non-preventable death cohort (p-value = 0.9170), even when further examined during periods of less personnel or facility resources. (Table 3)

Table 3.

Timing of system navigation by death preventability category

Characteristic	All Deaths (N = 160)	Preventable/ Potentially Preventable (N = 63)	Non-Preventable/ Indeterminate (N = 97)	p-value
Initial EC Arrival Time of Day, n (%)
Day	45 (28.1%)	23 (36.5%)	22 (22.7%)	0.0784b
Night	115 (71.9%)	40 (63.5%)	75 (77.3%)
First EC Arrival During Less Resourced Time-Personnel, yes n (%)	126 (78.8%)	47 (74.6%)	79 (81.4%)	0.3014a
First EC Arrival During Less Resourced Time-Resources, yes n (%)	97 (60.6%)	43 (68.3%)	54 (55.7%)	0.1114a
First EC Arrival During Less Resourced Time-Combined (Personnel and Resources), yes n (%)	134 (83.8%)	53 (84.1%)	81 (83.5%)	0.9170a
Facility Location of Death, n (%)				0.2961b
First EC	86 (53.8%)	28 (44.4%)	58 (59.8%)
Second EC	14 (8.8%)	6 (9.5%)	8 (8.2%)
ICU	29 (18.1%)	14 (22.2%)	15 (15.5%)
OT	1 (0.6%)	1 (1.6%)	0 (0.0%)
Ward	30 (18.8%)	14 (22.2%)	16 (16.5%)

^aWilcoxon rank sum p-value; ^bChi-Square p-value

There were no significant differences in median time from injury to EMS arrival (preventable 0.7 h (IQR 0.5,1.3) vs. non-preventable 0.6 h (IQR 0.4,1.3)) or from injury to first health facility arrival (preventable 1.6 (IQR 0.5,2.2) vs. non-preventable 1.4 (IQR 0.8,2.0)). (Table 4). Though the median total health facility length of stay was found to be significantly higher in the preventable death cohort (preventable cohort 39.7 h (IQR 5.7, 184.8) vs. non-preventable cohort 10.3 h (IQR 1.5, 59.1); p-value = 0.0024), the majority of deaths occurred in an EC in both groups (54% preventable cohort vs. 68% non-preventable cohort, p = 0.2961).

Table 4.

Durations of system navigation phases by death preventability category

Characteristic, number of deaths (N = 160)	All Deaths, median time in hours (IQR)	Preventable/ Potentially Preventable, median time in hours (IQR)	Non-Preventable/ Indeterminate, median time in hours (IQR)	p-value
Time from injury to EMS arrival, n = 92	0.6 (0.4, 1.3)	0.7 (0.5, 1.3)	0.6 (0.4, 1.3)	0.7770b
Time from injury to first health facility arrival, n = 160	1.6 (0.7, 2.0)	1.6 (0.5, 2.2)	1.4 (0.8, 2.0)	0.8995b
First EC Lenth of Stay, n = 160	5.0 (2.0, 13.0)	6.0 (3.0, 12.0)	5.0 (1.0, 14.0)	0.1268b
Second EC Length of Stay, n = 22	15.5 (10.0, 36.0)	13.0 (6.0, 60.5)a	18.0 (14.0, 30.0)	0.5748b
Time to Second Facility
Non-tertiary, n = 4	5.4 (3.4, 7.3)	3.4 (3.0, 3.8)	7.3 (7.0, 7.7)	0.2453b
Tertiary, n = 18	9.0 (6.5, 14.4)	8.5 (6.3, 12.1)	11.6 (7.3, 23.0)	0.3069b
Total Health Facility Length of Stay, n = 160	16.4 (2.2, 101.2)	39.7 (5.7, 184.8)	10.3 (1.5, 59.1)	0.0024b

^aOne patient had a second EC length of stay of 401.5 h (16 days)

^bWilcoxon rank sum p-value

Of the 160 total deaths reviewed, 25 patients underwent interfacility transfer (22 of which were transferred from one EC to another EC; 3 were transferred from an EC to an inpatient care unit). NISS was similar between groups (median NISS among patients undergoing IFT 34.0 (IQR 22.0, 43.0); median NISS among patients without IFT 38.0 (IQR 27.0, 50.0). Demographic and injury details for patients undergoing an IFT are available in Additional file 1.

Due to small sample size, total EC length of stay (first and second facility combined) was categorized into 0–6, > 6–12 and > 12 h. When compared to a shorter EC length of stay (0–6 h), a longer EC length of stay was not associated with an increased odds of preventable death: 6–12 h to 0–6 h (OR 1.73 95%CI 0.74–3.96) and > 12 h to 0–6 h (OR1.24, 95%CI 0.59–2.59). (Table 5) Examining time of arrival to an EC during less resourced periods similarly demonstrated no significant association with a preventable death, with arrival during a combined less-resourced period odds of preventable death being 0.96 (95%CI 0.40–2.26).

Table 5.

Univariate models analyzing health system navigation variables and preventable death

Characteristic	Odds Ratio & 95% Confidence Interval (odds of dying from a preventable cause)	p-value
Total EC Length of Stay
6–12 h vs. 0–6 h	1.73 (0.74–3.96)	0.2075a
≥ 12 h vs. 0-6 h	1.24 (0.59–2.59)	0.5675 a
Interfacility Transfer
IFT vs. no IFT	2.72 (1.13–6.52)	0.0250 a
EC arrival during low-resource period (combined)
Low-resource period vs. non low-resource period	0.96 (0.40–2.26)	0.9170 a
EC arrival during low-resource period, personnel
Low-resource personnel vs. not low-resource personnel	0.67 (0.31–1.44)	0.3014 a
EC arrival during low resource period, facility resources
Low-resource facility vs. not low-resource facility	1.71 (0.88–3.32)	0.1114 a

^aChi-square p-values

In univariate analysis, patients requiring an interfacility transfer during their care had 2.72 times higher odds of dying from a preventable death compared to those without an interfacility transfer (CI 1.13–6.52, p-value = 0.0250). (Table 5)

To account for potential confounders, a multivariable analysis, controlling for NISS and first EC length of stay, was conducted and found that an interfacility transfer was still associated with significantly higher odds of a preventable death (2.94, 95% CI 1.09–7.87). Due to the small sample size and non-significant difference between cohorts in age, sex, and mechanism these were not included in the multivariable model. Absence of multicollinearity among variables used for the multivariable analysis was confirmed using variance inflation factors.

Discussion

To our knowledge, this study represents the first appraisal of its kind of the association between health system navigation factors, including IFTs, and preventable mortality from traumatic injury. We analyzed a cohort of injury decedents in the Western Cape previously evaluated in a multidisciplinary preventable mortality review panel. Our analysis of health system navigation variables, defined by investigators of this study and informed by the expert panel that reviewed this cohort of decedents, found no significant association with preventable deaths and EC length of stay or arrival to the EC during a less resourced time. However, we did find an association of nearly 3-fold increased odds of dying from a preventable death and having undergone an IFT, even after controlling for injury severity and initial EC length of stay.

Our analysis did not appreciate any statistically significant associations between preventable trauma mortality and arrival to an EC during periods of limited resources, defined as periods at each health facility in which the EC was staffed with less personnel (both nurses and physicians) or at which times there was limited or no access to facility resources such as laboratory testing and computed tomography. Larger studies, such as one demonstrating a 49% increased mortality risk among Italian trauma patients admitted at nighttime (and even higher for transferred trauma patients) [16] and one demonstrating a 9% absolute increase in mortality rate among nighttime presentations in Qatar [17], have assessed off-hour mortality trends – though preventable mortality association with off-hour or low-resourced time periods has not previously been examined. Yet, evidence remains mixed, as other reports from mature trauma systems have failed to identify off-hour effects on mortality [18–20]. Because our study only included cases of patients who died, the vast majority of whom (84%) arrived to ECs during less-resourced time periods, the analysis is likely limited by the small sample size of patients arriving during higher-resourced times. Interestingly, one retrospective review in Korea at a level 1 trauma centre demonstrated increased risk of missed injury thought to be attributable to times of reduced staffing [21]. Our analysis did not assess for such morbidity impacts.

These results notably add to existing evidence by uniquely assessing association of interfacility transfer with preventable mortality. Prolonged EC length of stay has been previously linked to increased odds of in-hospital morbidity and mortality [22, 23]. Yet, in consideration of this known association, we found nearly 3-fold higher odds of preventable death among patients undergoing IFT even independent of first emergency centre length of stay and anatomic injury severity. Importantly, this finding should not be interpreted as evidence that interfacility transfer itself causes preventable mortality. The expert reviewer panel previously noted multiple factors related to preventable deaths, including limited front line provider training to facilitate early recognition of critical illness, gaps in initial resuscitation, lack of monitoring equipment, and delays to imaging – all elements of care that may impact patients that require an IFT [13]. Furthermore, ongoing diagnostic uncertainty may serve as both an indication for IFT and a confounder for this analysis. Rather, this signal likely represents a marker of the complexity of the trauma care continuum in this setting, including prolonged exposure to care processes and vulnerability to breakdowns across multiple phases of care for patients undergoing IFT.

Though some individuals with non-survivable injury may succumb to their injuries prior to planned transfer, thus impacting this association, several other factors likely also contribute to the increased preventable mortality identified in our analysis among patients undergoing IFT. Significant delays in both initiating and completing transfer processes may result in prolonged periods of care at the initial site of contact (Personal Communication: Dr. Heike Geduld, Provincial Emergency Medicine Specialist, 26 January 2026). This may be particularly true for intubated or other high acuity patients requiring advanced-level transport teams (Personal Communication: Dr. Elmin Steyn, Head of Surgery at Tygerberg Hospital, 28 January 2026). Resource limitations may result in little or no monitoring, as well as little or no advanced therapeutic care, for patients earmarked for transfer at initial health facilities and during periods of actual transport between facilities [24, 25]. Furthermore, IFTs expose patients to repeated handovers and communication breakdowns [26, 27].

While two prior reviews – which incorporated many studies conducted in HICs – reported no clear association between transfer and trauma mortality, a 2023 systematic review and meta-analysis of relevant studies in LMICs demonstrated significantly increased odds of mortality among patients undergoing inter-facility transfer to a trauma center compared to those directly transported from the scene of injury to a trauma center [28, 29]. Authors felt this conclusion reflected “the immature trauma systems of the countries from which studies were included,” attributing mortality to inadequate care at the pre-transfer hospitals, limited trauma training of frontline health providers, and inefficiencies in trauma processes [12]. Although the Western Cape benefits from a more structured and coordinated prehospital and inter-facility trauma system than many other sub-Saharan regions, several systemic and contextual factors still contribute to delays in accessing definitive diagnostic and therapeutic care, particularly for patients initially seen outside tertiary centres [30]. Even at district and regional hospitals with some surgical capability and frontline providers able to perform life-saving emergency procedures (e.g. intubation, intercostal drains, fluid resuscitation), trauma care capacity is often constrained by high patient to staff ratios, reduced monitoring capability, limited blood product availability, scarce ICU or high-acuity bed availability, minimal advanced diagnostic capability after-hours (e.g. CT), and minimal or no access to specialty services (e.g. neurosurgery) [24, 25].

Importantly, it remains unfeasible for all major trauma patients in the Western Cape to be cared for at referral trauma centres. Thus, our findings suggest the need for additional efforts aimed at strengthening trauma care proximally (i.e., prior to arrival at tertiary centers) and optimizing trauma transfer criteria to ensure the patients who may benefit the most are those transferred to trauma centres.

Limitations

Eligible cases were restricted by the EpiC study’s inclusion and exclusion criteria; therefore, decedents reviewed by the expert panel do not represent all injury-related deaths within the Western Cape health system. A major limitation of this study is that the health system variables of interest were defined by study investigators, these definitions may not be generalizable outside of this study context. Higher rates of penetrating trauma in this setting may also limit generalizability to other resource-limited trauma systems that experience a higher proportion of blunt injuries. Though a significant association between IFT and preventability was measured in both the univariate and multivariable models, the small sample size for this secondary analysis does present a limitation. Finally, the observational nature of the EpiC study prevents an analysis on true causality of preventable deaths.

Conclusion

In this study from the Western Cape of South Africa, we found a significant association between dying from a preventable death and IFT. These findings likely demonstrate IFT as a marker of increased trauma system complexity and extended exposure to system vulnerabilities across multiple phases of care. While the underlying root causes and scale of this effect require further investigation, tiered trauma systems in resource-constrained settings should consider the increased odds of preventable death among patients undergoing IFT in healthcare system design and routine operations.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

CHC

Community Health Centre

CNS

Central Nervous System

CTD

Catastrophic Tissue Destruction

EC

Emergency Centre

EMS

Emergency Medical Services

EpiC

Epidemiology and outcomes of prolonged trauma care

FPS

Forensic Pathology Services

ICU

Intensive Care Unit

IFT

Inter-facility transport

LMIC

Low-Middle-income countries

OT

Operating Theatre

WHO

World Health Organization

Author contributions

M.R, J.D, and N.K.M.M conceptualized the work. M.R analyzed the data and prepared tables and figures. M.R, A.M, and J.D drafted the first version of the manuscript. M.D.R assisted with data curation (dataset creation and data cleaning) and data analysis. All authors made substantial contributions to the acquisition of the data. All authors reviewed, edited and approved of the final version of the manuscript and attest to their contributions and the accuracy of the manuscript.

Funding

United States Defense Health Agency award numbers/grant log numbers: W81XWH-20-2-0042.

Data availability

Data is provided within the manuscript or supplementary information files. Public access to the dataset is closed due to contractual limitations. The datasets included and/or analysed during the current study are available from the corresponding author upon reasonable request and upon satisfying contractual and regulatory requirements.

Declarations

Ethics approval and consent to participate

The Health Research Ethics Committee at Stellenbosch University, Western Cape Provincial Health Research Committee and all individual facilities and agencies approved all study activities (Ethics Reference No. N20/03/036). A waiver of informed consent was used for this study as approved by Stellenbosch University Human Research Ethics Committee (SUHREC) with a reliance agreement provided by the Colorado Multiple Institute Review Board (COMIRB #20–2176). Due to the high patient acuity and challenging emergency care environments, an exemption from obtaining informed consent was granted by the primary ethics board. For this study records were accessed between 1 January 2023 and 30 April 2024. The study adhered to the Helsinki Declaration for research conducted on humans.

Consent for publication

Not applicable.

Disclaimer

No artificial intelligence assisted technologies were used in the production of the submitted work. The findings, views, and conclusions presented are those of the authors and do not represent the official policy or position of the United States Defense Health Agency or the Western Cape Department of Health and Wellness.

Competing interests

The authors declare no competing interests.