What factors influence the cost in treating maxillofacial fractures among pediatric patients?

doi:10.21203/rs.3.rs-1969900/v1

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What factors influence the cost in treating maxillofacial fractures among pediatric patients?

https://doi.org/10.21203/rs.3.rs-1969900/v1

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Purpose

The objective of the following study was to determine what factors, if any, are associated with increased hospitalization charges amongst pediatric patients who sustain maxillofacial fractures.

Methods

This retrospective cohort study was conducted using the Kids’ Inpatient Database (KID). The primary predictor variables were a set of heterogenous variables that included patient characteristics, injury characteristics, and hospitalization outcomes. The primary outcome variable was total charges (US dollars). Linear regression was used to determine independent risk factors for increased/decreased hospital charges.

Results

The final sample consisted of 50,434 pediatric patients who suffered at least one facial fracture. The mean age of the study sample was 9.72 years (SD, 6.84 years). Relative to Black patients, Hispanic patients added $12,812 (P < 0.05) in hospital charges. Relative to fall, motorcycle accident (P < 0.05), car accident (P < 0.05), and firearm assault (P < 0.05) were each independently associated with increased hospital charges. Mandible fractures (P < 0.05) added $12,208 in hospital whereas malar & maxillary fractures (P < 0.05) added $8,564 in hospital charges. Most notably, panfacial fractures (P < 0.05) added $32,364 in hospital charges. Other fractures of the body were each independently associated with increased hospital charges. Several internal organ injuries were each independently associated with increased hospital charges

Conclusion

There is an opportunity for cost reduction in the management of pediatric maxillofacial trauma. This includes promptness in definitive repair and easy access to interpreters for non-English speaking patients. Cost-efficient approaches to patient care should be recognized and utilized to the patient and family benefit whenever possible.

Pediatric maxillofacial trauma

facial Injuries

maxillofacial Surgery

hospital charges

panfacial fractures

Facial injuries are common in pediatric patients. The pediatric patient is characterized by unique facial anatomy, particularly the lack of sinus development, pronounced buccal fat pads, and unerupted dentition.^1,2 These anatomical features translate to increased bone strength and elasticity and decrease the risk of facial fracture.³ Nevertheless, the large head size relative to the body and decreased neck strength of pediatric patients increase the risk of head and neck injury.⁴ If a pediatric patient sustains significant maxillofacial trauma, there is a 10% chance of an associated cervical spine injury.⁵

Increase in age among children results in an increased participation in autonomous activities (i.e., driving, athletic activity), which places them at greater risk of facial trauma.⁶ Relative to their younger counterparts in supervised and sheltered environments, older children are more susceptible to facial trauma through occupational endeavors, interpersonal violence, or motor vehicle accidents.⁶ Additionally, the facial skeleton becomes more mineralized with age, rendering them less resistant to fractures.^7–12 Owing to the forementioned factors, less than 15% of all facial fractures occur among the pediatric population.¹³ Moreso, the incidence of pediatric facial fractures is estimated to range between 1% and 14.7% for patients under the age of 16 years and 0.87–1% for those under the age of five years.¹⁴

The management of craniomaxillofacial trauma poses a financial burden. Relative to a matched population that suffered non-craniomaxillofacial trauma, the management of patients that suffered craniomaxillofacial trauma was associated with significantly reduced reimbursement rate (17.25 vs. 29.61%, p < 0.0001).¹⁵ Further, reimbursement rate varies according to the patient’s payment method. A study on patients who underwent facial fracture management, uninsured patients had the lowest reimbursement rate (10%). This is concerning given that the rate of Americans who are uninsured has been increasing since 2016. As of 2020, 30 million US residents were uninsured.¹⁶ Moreover, DeLuke et al. showed that the treatment of maxillofacial trauma returns a net profit for the hospital, but not for the surgeon. As such, surgeons that address maxillofacial trauma are disincentivized to treat patients.¹⁷ Indeed, the existing opportunity cost is a threat to the sustainability of craniomaxillofacial trauma care.

Several studies have analyzed the cost of managing maxillofacial trauma and its predictors.^15,17−21 A retrospective review of the costs associated with treating isolated mandibular fractures, several variables were found to be predictors of increased costs. Dillon et al determined that number of fractures, increased length of hospital stay, treatment by otolaryngology service (relative to OMS), treatment by plastic surgery service (relative to OMS), arrival to the hospital via airlift (relative to privately owned vehicle) were each independently associated with increased costs. In contrast, treatment via closed reduction (relative to open reduction internal fixation) was independently associated with decreased costs.¹⁸ Direct admission from the emergency department for surgery was also found to be add $2000–4000 to the bill relative to patients who were electively managed in an outpatient setting.^19,22 Thus, elective surgical repair of facial fractures is advocated on the condition that the patient is clinically stable without other pressing comorbidities. To the authors’ best knowledge, no study has yet to explore the cost of managing maxillofacial trauma exclusively among pediatric patients.

The purpose of the following study was to answer the following question, “what factors are associated with increased hospitalization charges amongst pediatric patients who sustain maxillofacial fractures?” The authors hypothesized that a panfacial fracture would be a risk factor for increased hospital charges. It was also hypothesized that motor vehicle (cars, motorcycles) accident would be a risk factor for increased hospital charges. Specifically, the authors aimed to 1) identify all cases of maxillofacial fractures among pediatric patients that transpired between 2000–2012 2) characterize the patients according to their demographics, hospitalization, and mechanism of injury 3) identify any concomitant injuries that transpired 4) compare the hospitalization charges across all study variables 5) quantify risk factors for increased/decreased hospitalization charges.

This is a retrospective cohort study that was conducted using the Kids’ Inpatient Database (KID). The KID is the largest publicly available all-payer pediatric inpatient care database in the United States. It entails information on approximately three million pediatric discharges each year. Patients from the 2000–2012 KID datasets were selected if they were 18 years or younger and suffered a facial fracture(s). Table 1 illustrates all the diagnostic and procedure ICD-9 codes used to identify the study sample and variables of interest.

Table 1

ICD-9 codes used to identify subjects and define variables
Study Variable	ICD-9 Codes
Maxillofacial Fracture
Cranial Vault	800.00–800.99
Nasal fractures	802.0, 802.1
Mandible fractures	802.20, 802.21, 802.22, 802.23, 802.24, 802.25, 802.26, 802.27, 802.28, 802.29, 802.3, 802.31, 802.32, 802.33, 802.34, 802.35, 802.36, 802.37, 802.38, 802.39,
Malar & maxillary fractures	802.4, 802.5
Orbital floor (blow-out) fractures	802.6, 802.7
Other facial fractures	802.8, 802.9
Mechanism of Injury
Motorcycle accident	E810.2, E810.3 – E825.2, E825.3
Car accident	E810.0, E810.1, E810.4 – E825.0, E825.1, E825.4
Pedal cycle accident	E826.1
Animal riding accident	E8282
Fall	E880 – E888
Unarmed fight/brawl	E960.0
Firearm assault	E965.0 – E965.4
Blunt object assault	E968.2
Other
Alcohol abuse	305.0, 305.00, 305.01, 305.02
Cannabis abuse	305.2, 305.20, 305.21, 305.22, 305.23
Cocaine abuse	305.6, 305.60, 305.61
Attention Deficit Disorder of Childhood	314.0, 314.00, 314.01
Other Fractures
Skull Base Fracture	801
Vertebral Column Fracture	805, 806
Rib/Sternum/Larynx/Trachea Fracture	807
Pelvic Fracture	808
Upper Limb Fractures	810–819
Lower Limb Fractures	820–829
Intracranial Injury
Concussion	850
Cerebral laceration/contusion	851
Subarachnoid hemorrhage	852.00–852.19
Subdural hemorrhage	852.20–852.39
Extradural hemorrhage	852.40–852.59
Internal Organ Injury
Traumatic Pneumothorax/Hemothorax	860
Heart/Lung Injury	861
GI Injury	863, 864
Spleen Injury	865

The primary predictor variables were a set of heterogenous variables that were grouped into patient characteristics, injury characteristics, hospitalization characteristics. The primary outcome variable was total charges (US dollars). Net hospital charges do not include professional fees and non-covered charges. Any emergency department charges that were incurred before hospital admission may have been included in net charges. Patient characteristics included age group (0–2, 3–5, 5–12, 13–18 years), gender (male or female), race (White, Black, Hispanic, Asian, or other), median household income, location, payer information, number of chronic conditions, miscellaneous patient characteristics.

Injury characteristics included maxillofacial fracture (nasal, mandible, malar & maxillary, orbital floor, panfacial), other fractures (cranial vault, skull base, vertebral column, rib/sternum/larynx/trachea, pelvic, upper limb, lower limb), intracranial injury (concussion, cerebral laceration/contusion, subarachnoid hemorrhage, subdural hemorrhage, extradural hemorrhage), internal organ injury (pneumothorax/hemothorax, heart/lung injury, GI injury, spleen injury), and mechanism of injury (motorcycle accident, car accident, pedal cycle accident, animal riding accident, fall, unarmed fight/brawl, firearm assault, blunt object assault). Hospitalization characteristics included admission type, hospital region, hospital transfer (into/out), and hospitalization year (2000–2002, 2003–2005, 2006–2008, 2009–2011, 2012–2014).

Median household income was a categorical variable of income quartiles (Q1, Q2, Q3, and Q4) that was determined according to the patient’s ZIP Code. Location was a three-category scheme used to classify U.S. counties according to its population size and whether it is urban or rural. Payer information denotes the primary payer of treatment (Medicare/Medicaid, private, or self-pay). Number of chronic conditions was a categorical variable (one, two, three, four or more). The miscellaneous patient characteristics included common diagnoses identified in our study sample (alcohol abuse, cannabis abuse, cocaine abuse, or attention deficit disorder of childhood).

Panfacial fractures were defined as concurrent fracturing of the bones within the upper (frontal bone), middle (malar bone & maxilla, orbital floor), and lower thirds of the face (mandible). The ICD9 coding system codes for the cranial vault, which includes the bones of the upper third of the face, namely the frontal bone. Upper limb fractures included those to the clavicle, scapula, humerus, radius/ulna, carpal bones, metacarpal bones, and phalanges. Lower limb fractures included those to the femur, patella, tibia/fibula, ankle, tarsal bones, metatarsal bones, and phalanges of foot. Cerebral laceration and contusion included those to the cerebral cortices, cerebellum, or brainstem. The following structures were considered GI injury: liver, stomach, small intestine, large intestine, pancreas, and appendix. Admission type is binary (elective or emergency). Hospital region is a four-category variable (Northeast, Midwest, South, West).

Descriptive statistics (mean, frequency, range, standard deviations) were computed for all study variables when possible. Independent sample t test and ANOVA were used to determine significant differences in hospital charges for all predictor variables. Linear regression was used to determine independent risk factors for increased/decreased hospital charges. A P value of less than 0.05 was considered statistically significant. We used SPSS version 28 for Mac (IBM Corp., Armonk, NY, USA) to perform all statistical analyses. Since the KID is a database that is both publicly available and anonymized, we did not require institutional board review consistent with our medical center’s policy.

The 2000–2012 KID database included 15,235,214 pediatric patients with inpatient hospital stays. After selecting for patients 18 years of age or younger who sustained at least one facial fracture, the final sample consisted of 50,434 patients. The mean age of the study sample was 9.72 years (SD, 6.84 years). Most patients were white (55.8%) males (68.7%) from large metro areas (60.2%). Fall (22.0%) was the most common mechanism of injury. Mandible fractures (23.5%) were the most common maxillofacial fracture. Only 670 patients sustained a panfacial fracture (1.3%). Concerning other fractures, cranial vault fracture (45.8%) was the most common. Concussion (6.2%) was the most common intracranial injury. Heart or lung injury (5.0%) was the most common internal organ injury (Table 2).

Table 2

Patient characteristics, hospitalization outcomes, and mechanism of injury, and panfacial fracture.
	Number of patients, n (%)
Total	50,434
Age (years), mean ± SD	9.72 ± 6.84
Age group
Infants & Toddlers (0–2 years)	13,426 (26.6)
Preschooler (3–5 years)	3,802 (7.5)
Grade-schooler (5–12 years)	9,981 (19.8)
Teenager (13–18 years)	23,225 (46.1)
Gender
Male	34,412 (68.7)
Female	15,681 (31.3)
Race
White	22,846 (55.8)
Black	6,837 (16.7)
Hispanic	7,713 (18.8)
Asian	900 (2.2)
Other	2,625 (6.4)
Median household income
Quartile 1	13,031 (26.6)
Quartile 2	12,663 (25.8)
Quartile 3	12,095 (24.6)
Quartile 4	11,282 (23.0)
Location
Large metro areas ( > = 1 million population)	17,593 (60.2)
Small metro areas (50,000-999,999 population)	8,533 (29.2)
Micropolitan counties	3,094 (10.6)
Payer information
Medicare or Medicaid	18,287 (38.5)
Private Insurance	26,035 (54.9)
Self-pay	3,119 (6.6)
Admission type
Elective	2,444 (5.9)
Emergency	38,671 (94.1)
Hospital region
Northeast	1,843 (18.5)
Midwest	2,139 (21.5)
South	3,329 (33.4)
West	2,649 (26.6)
Transferred into hospital
Yes	3,826 (18.3)
No	17,086 (81.7)
Transferred out of hospital
Yes	9,332 (6.3)
No	624 (93.7)
Number of chronic conditions
Zero	13,420 (63.8)
One	4,588 (21.8)
Two	1,829 (8.7)
Three or more	1,186 (5.6)
Hospitalization year
2000–2002	8,624 (17.1)
2003–2005	10,030 (19.9)
2006–2008	10,757 (21.3)
2009–2011	11,063 (21.9)
2012–2014	9,960 (19.7)
Mechanism of Injury
Motorcycle accident	675 (1.3)
Car accident	9001 (17.8)
Pedal cycle accident	1,458 (2.9)
Animal riding accident	244 (0.5)
Fall	11,094 (22.0)
Unarmed fight/brawl	2,879 (5.7)
Firearm assault	507 (1.0)
Blunt object assault	1,013 (2.0)
Miscellaneous patient characteristics
Alcohol Abuse	1,234 (2.4)
Cannabis abuse	772 (1.5)
Cocaine abuse	134 (0.3)
Attention Deficit Disorder of Childhood	1,123 (2.2)
Maxillofacial Fracture
Nasal fractures	7,621 (15.1)
Mandible fractures	11,855 (23.5)
Malar & maxillary fractures	6,606 (13.1)
Orbital floor (blow-out) fractures	6,006 (11.9)
Panfacial Fracture	670 (1.3)
Other Fractures
Cranial vault	23,100 (45.8)
Skull Base Fracture	10,016 (19.9)
Vertebral Column Fracture	1,993 (4.0)
Rib/Sternum/Larynx/Trachea Fracture	1,531 (3.0)
Pelvic Fracture	1,276 (2.5)
Upper Limb Fractures	4,084 (8.1)
Lower Limb Fractures	3,446 (6.8)
Intracranial Injury
Concussion	3,105 (6.2)
Cerebral laceration/contusion	721 (1.4)
Subarachnoid hemorrhage	379 (0.8)
Subdural hemorrhage	416 (0.8)
Extradural hemorrhage	139 (0.3)
Internal Organ Injury
Traumatic Pneumothorax/Hemothorax	1,585 (3.1)
Heart/Lung Injury	2,524 (5.0)
GI Injury	1,125 (2.2)
Spleen Injury	917 (1.8)

To identify significant predictors of increased/decreased hospital charges, we compared the hospital charges across all study variables. Age group, race, median household income, payer information, admission type, hospital region, transferred into hospital, transferred out of hospital, number of chronic conditions, hospitalization year, mechanism of injury, alcohol abuse, cannabis abuse, cocaine abuse, attention deficit disorder of childhood, nasal fracture, mandible fracture, malar & maxillary fracture, orbital floor fracture, panfacial fracture, skull base fracture, vertebral column fracture, rib/sternum/larynx/trachea fracture, upper limb fracture, lower limb fracture, concussion, cerebral laceration/contusion, subarachnoid hemorrhage, subdural hemorrhage, pneumothorax/hemothorax, heart/lung injury, GI injury, spleen injury were all significant predictors (P < 0.05) of hospital charges (Table 3) and were further analyzed via univariate linear regression (Table 4).

Table 3. Comparison of hospital charges for each of the predictor variables

	Hospital Charges (US $), Mean ± SD	p-value
Total	35,662 ± 63,977	-
Age group		<0.001*
Infants & Toddlers (0-2 years)	22,416 ± 45,071
Preschooler (3-5 years)	33,229 ± 60,204
Grade-schooler (5-12 years)	37,044 ± 62,827
Teenager (13-18 years)	43,091 ± 72,528
Gender		0.703
Male	35,641 ± 63,964
Female	35,879 ± 64,353
Race		<0.001*
White	35,998 ± 64,732
Black	34,913 ± 60,766
Hispanic	42,748 ± 77,658
Asian	40,926 ± 75,809
Other	38,022 ± 67,721
Median household income		0.003*
Quartile 1	36,800 ± 61,703
Quartile 2	34,724 ± 60,930
Quartile 3	36,665 ± 66,816
Quartile 4	34,392 ± 67,662
Location		0.340
Large metro areas (>=1 million population)	41,618 ± 73,744
Small metro areas (50,000-999,999 population)	40,476 ± 68,942
Micropolitan counties	40,102 ± 65,201
Payer information		<0.001*
Medicare or Medicaid	35,981 ± 66,124
Private Insurance	35,257 ± 61,575
Self-pay	27,329 ± 42,331
Admission type		<0.001*
Elective	28,096 ± 41,130
Emergency	38,624 ± 68,209
Hospital region		<0.001*
Northeast	42,934 ± 77,042
Midwest	40,848 ± 61,798
South	45,109 ± 71,976
West	59,523 ± 101,976
Transferred into hospital		<0.001*
Yes	37,267 ± 67,635
No	45,244 ± 78,259
Transferred out of hospital		<0.001*
Yes	176,496 ± 200,921
No	38,961 ± 54,877
Number of chronic conditions		<0.001*
Zero	29,419 ± 40,952
One	50,013 ± 75,830
Two	78,186 ± 118,033
Three or more	130,314 ± 171,777
Hospitalization year		<0.001*
2000-2002	22,278 ± 41,328
2003-2005	29,691 ± 52,765
2006-2008	35,463 ± 58,260
2009-2011	40,445 ± 72,761
2012-2014	47,547 ± 80,266
Mechanism of Injury		<0.001*
Motorcycle accident	61,923 ± 92,361
Car accident	57,453 ± 82,692
Pedal cycle accident	26,862 ± 49,722
Animal riding accident	34,786 ± 45,468
Fall	20,221 ± 38,873
Unarmed fight/brawl	22,888 ± 21,525
Firearm assault	89,843 ± 125,462
Blunt object assault	30,377 ± 47,603
Miscellaneous patient characteristics
Alcohol Abuse	42,458 ± 60,562	<0.001*
Cannabis abuse	44,715 ± 73,815	<0.001*
Cocaine abuse	46,696 ± 67,331	0.046*
Attention Deficit Disorder of Childhood	39,531 ± 55,324	0.042*
Facial Fracture
Nasal fracture	40,024 ± 68,272	<0.001*
Mandible fracture	39,496 ± 65,185	<0.001*
Malar & maxillary fracture	54,388 ± 80,065	<0.001*
Orbital floor (blow-out) fracture	44,689 ± 72,955	<0.001*
Panfacial fracture	103,285 ± 113,289	<0.001*
Other Fractures
Cranial vault	36,264 ± 71,159	0.054
Skull Base Fracture	54,038 ± 85,695	<0.001*
Vertebral Column Fracture	92,175 ± 116,460	<0.001*
Rib/Sternum/Larynx/Trachea Fracture	83,866 ± 114,078	<0.001*
Pelvic Fracture	91,441 ± 109,245	<0.001*
Upper Limb Fractures	60,442 ± 84,197	<0.001*
Lower Limb Fractures	77,210 ± 101,233	<0.001*
Intracranial Injury
Concussion	32,296 ± 54,410	0.003*
Cerebral laceration/contusion	71,975 ± 108,211	<0.001*
Subarachnoid hemorrhage	73,143 ± 97,812	<0.001*
Subdural hemorrhage	65,416 ± 84,359	<0.001*
Extradural hemorrhage	39,198 ± 42,975	0.517
Internal Organ Injury
Traumatic Pneumothorax/Hemothorax	100,914 ± 117,059	<0.001*
Heart/Lung Injury	94,808 ± 113,994	<0.001*
GI Injury	90,004 ± 109,779	<0.001*
Spleen Injury	95,036 ± 119,245	<0.001*

*, statistically significant (p<0.05)

Table 4

Univariate linear regression model for hospital charges
	Hospital Charges (US $), Mean ± SD	p-value
Total	35,662 ± 63,977	-
Age group		< 0.001*
Infants & Toddlers (0–2 years)	22,416 ± 45,071
Preschooler (3–5 years)	33,229 ± 60,204
Grade-schooler (5–12 years)	37,044 ± 62,827
Teenager (13–18 years)	43,091 ± 72,528
Gender		0.703
Male	35,641 ± 63,964
Female	35,879 ± 64,353
Race		< 0.001*
White	35,998 ± 64,732
Black	34,913 ± 60,766
Hispanic	42,748 ± 77,658
Asian	40,926 ± 75,809
Other	38,022 ± 67,721
Median household income		0.003*
Quartile 1	36,800 ± 61,703
Quartile 2	34,724 ± 60,930
Quartile 3	36,665 ± 66,816
Quartile 4	34,392 ± 67,662
Location		0.340
Large metro areas ( > = 1 million population)	41,618 ± 73,744
Small metro areas (50,000-999,999 population)	40,476 ± 68,942
Micropolitan counties	40,102 ± 65,201
Payer information		< 0.001*
Medicare or Medicaid	35,981 ± 66,124
Private Insurance	35,257 ± 61,575
Self-pay	27,329 ± 42,331
Admission type		< 0.001*
Elective	28,096 ± 41,130
Emergency	38,624 ± 68,209
Hospital region		< 0.001*
Northeast	42,934 ± 77,042
Midwest	40,848 ± 61,798
South	45,109 ± 71,976
West	59,523 ± 101,976
Transferred into hospital		< 0.001*
Yes	37,267 ± 67,635
No	45,244 ± 78,259
Transferred out of hospital		< 0.001*
Yes	176,496 ± 200,921
No	38,961 ± 54,877
Number of chronic conditions		< 0.001*
Zero	29,419 ± 40,952
One	50,013 ± 75,830
Two	78,186 ± 118,033
Three or more	130,314 ± 171,777
Hospitalization year		< 0.001*
2000–2002	22,278 ± 41,328
2003–2005	29,691 ± 52,765
2006–2008	35,463 ± 58,260
2009–2011	40,445 ± 72,761
2012–2014	47,547 ± 80,266
Mechanism of Injury		< 0.001*
Motorcycle accident	61,923 ± 92,361
Car accident	57,453 ± 82,692
Pedal cycle accident	26,862 ± 49,722
Animal riding accident	34,786 ± 45,468
Fall	20,221 ± 38,873
Unarmed fight/brawl	22,888 ± 21,525
Firearm assault	89,843 ± 125,462
Blunt object assault	30,377 ± 47,603
Miscellaneous patient characteristics
Alcohol Abuse	42,458 ± 60,562	< 0.001*
Cannabis abuse	44,715 ± 73,815	< 0.001*
Cocaine abuse	46,696 ± 67,331	0.046*
Attention Deficit Disorder of Childhood	39,531 ± 55,324	0.042*
Facial Fracture
Nasal fracture	40,024 ± 68,272	< 0.001*
Mandible fracture	39,496 ± 65,185	< 0.001*
Malar & maxillary fracture	54,388 ± 80,065	< 0.001*
Orbital floor (blow-out) fracture	44,689 ± 72,955	< 0.001*
Panfacial fracture	103,285 ± 113,289	< 0.001*
Other Fractures
Cranial vault	36,264 ± 71,159	0.054
Skull Base Fracture	54,038 ± 85,695	< 0.001*
Vertebral Column Fracture	92,175 ± 116,460	< 0.001*
Rib/Sternum/Larynx/Trachea Fracture	83,866 ± 114,078	< 0.001*
Pelvic Fracture	91,441 ± 109,245	< 0.001*
Upper Limb Fractures	60,442 ± 84,197	< 0.001*
Lower Limb Fractures	77,210 ± 101,233	< 0.001*
Intracranial Injury
Concussion	32,296 ± 54,410	0.003*
Cerebral laceration/contusion	71,975 ± 108,211	< 0.001*
Subarachnoid hemorrhage	73,143 ± 97,812	< 0.001*
Subdural hemorrhage	65,416 ± 84,359	< 0.001*
Extradural hemorrhage	39,198 ± 42,975	0.517
Internal Organ Injury
Traumatic Pneumothorax/Hemothorax	100,914 ± 117,059	< 0.001*
Heart/Lung Injury	94,808 ± 113,994	< 0.001*
GI Injury	90,004 ± 109,779	< 0.001*
Spleen Injury	95,036 ± 119,245	< 0.001*
*, statistically significant (p < 0.05)
†, reference group was patients that did not have the specific characteristic/injury at hand

After controlling for all variables, we conducted a multivariate linear regression. Relative to Black patients, Hispanic patients added $12,812 (P < 0.05) in hospital charges. Relative to the Midwest, the Northeast added $7,223 (P < 0.05) in hospital charges while the West added $15,994 (P < 0.05) in hospital charges. Patients who were transferred into the hospital (P < 0.05) were independently associated with decreased hospital charges whereas patients who were transferred out of the hospital (P < 0.05) were independently associated with increased hospital charges. Relative to zero chronic conditions, one (P < 0.05), two (P < 0.05), and three or more (P < 0.05) chronic conditions were independently associated with increased hospital charges. Relative to fall, motorcycle accident (P < 0.05), car accident (P < 0.05), and firearm assault (P < 0.05) were each independently associated with increased hospital charges. Alcohol abuse (P < 0.05), cannabis abuse (P < 0.05), and ADHD (P < 0.05) were each independently associated with decreased hospital charges (Table 5).

Table 5

Multiple linear regression model for hospital charges
	Hospital Charges
	Coefficient	95% CI	p-value
Age	1,261	1,179, 1,343	< 0.001*
Gender
Male	Ref	-	-
Female	238	-985, 1,461	0.703
Race
Black	Ref	-	-
White	1,085	-749, 2,919	0.246
Hispanic	7,835	5,616, 10,055	< 0.001*
Asian	6,013	1,266, 10,761	0.013*
Other	3,109	62, 6,157	0.046*
Median household income for patient’s ZIP Code
Quartile 4	Ref	-	-
Quartile 3	2,273	605, 3,942	0.008*
Quartile 2	332	-1,318, 1,982	0.693
Quartile 1	2,408	772, 4,044	0.004*
Payer information
Self-pay	Ref	-	-
Medicare or Medicaid	8,652	6,262, 11,043	< 0.001*
Private Insurance	7,928	5,588, 10,268	< 0.001*
Admission type
Elective	Ref	-	-
Emergency	10,528	7,767, 13,289	< 0.001*
Hospital region
Midwest	Ref	-	-
Northeast	2,086	-2,928, 7,101	0.415
South	4,261	-120, 8,643	0.057
West	18,675	14,043, 23,306	< 0.001*
Transferred into hospital	-7,977	-10,694, -5,260	< 0.001*
Transferred out of hospital	137,535	131,551, 143,518	< 0.001*
Number of chronic conditions
Zero	Ref	-	-
One	20,594	18,165, 23,024	< 0.001*
Two	48,767	45,224, 52,309	< 0.001*
Three or more	100,895	96,576, 105,213	< 0.001*
Hospitalization year
2000–2002	Ref	-	-
2003–2005	7,413	5,547, 9,280	< 0.001*
2006–2008	13,185	11,350, 15,021	< 0.001*
2009–2011	18,168	16,343, 19,993	< 0.001*
2012–2014	25,269	23,399, 27,139	< 0.001*
Mechanism of Injury
Fall	Ref	-	-
Motorcycle accident	41,703	36,946, 46,459	< 0.001*
Car accident	37,232	35,530, 38,934	< 0.001*
Pedal cycle accident	6,641	3,292, 9,990	< 0.001*
Animal riding accident	14,565	6,828, 22,302	< 0.001*
Unarmed fight/brawl	2,667	151, 5,183	0.038*
Firearm assault	69,622	64,140, 75,104	< 0.001*
Blunt object assault	10,156	6,211, 14,100	< 0.001*
Miscellaneous patient characteristics
Alcohol Abuse †	6,969	3,338, 10,599	< 0.001*
Cannabis abuse †	9,194	4,599, 13,789	< 0.001*
Cocaine abuse †	11,064	177, 21,952	0.046*
Attention Deficit Disorder of Childhood †	3,958	145, 7,772	0.042*
Facial Fracture
Nasal fracture †	5,142	3,568, 6,715	< 0.001*
Mandible fracture †	5,011	3,680, 6,342	< 0.001*
Malar & maxillary fracture †	21,562	19,903, 23,221	< 0.001*
Orbital floor (blow-out) fracture †	10,255	8,519, 11,992	< 0.001*
Panfacial Fracture †	68,541	63,668, 73,414	< 0.001*
Other Fractures
Skull Base fracture †	22,964	21,567, 24,360	< 0.001*
Vertebral Column fracture †	58,853	56,012, 61,694	< 0.001*
Rib/Sternum/Larynx/Trachea Fracture †	49,729	46,486, 52,973	< 0.001*
Pelvic fracture †	57,223	53,659, 60,787	< 0.001*
Upper Limb fracture †	26,956	24,898, 29,014	< 0.001*
Lower Limb fracture †	44,595	42,393, 46,797	< 0.001*
Intracranial Injury
Concussion †	-3,588	-5,928, -1,248	0.003*
Cerebral laceration/contusion †	36,838	32,086, 41,590	< 0.001*
Subarachnoid hemorrhage †	37,765	31,230, 44,300	< 0.001*
Subdural hemorrhage †	30,003	23,782, 36,224	< 0.001*
Internal Organ Injury
Traumatic Pneumothorax/Hemothorax †	67,387	64,221, 70,554	< 0.001*
Heart/Lung Injury †	62,295	59,778, 64,812	< 0.001*
GI Injury †	55,585	51,798, 59,372	< 0.001*
Spleen Injury †	60,469	56,271, 64,668	< 0.001*
*, statistically significant (p < 0.05)
†, reference group was patients that did not have the specific characteristic/injury at hand

Mandible fractures (P < 0.05) added $12,208 in hospital whereas malar & maxillary fractures (P < 0.05) added $8,564 in hospital charges. Most notably, panfacial fractures (P < 0.05) added $32,364 in hospital charges. Skull base fractures (P < 0.05), vertebral column fractures (P < 0.05), rib/sternum/larynx/trachea fractures (P < 0.05), pelvic fractures (P < 0.05), and lower limb fractures (P < 0.05) were each independently associated with increased hospital charges. Concussion reduced hospital charges by $8,301 (P < 0.05). Pneumothorax/hemothorax (P < 0.05), heart/lung injury (P < 0.05), GI injury (P < 0.05), and spleen injury (P < 0.05) were each independently associated with increased hospital charges (Table 5).

The purpose of this study was to determine what factors were associated with increased hospitalization charges amongst pediatric patients who sustained maxillofacial fractures. Ultimately, the authors rejected the null hypothesis. Panfacial fractures added over $30,000 in hospital charges. Motorcycle accidents and car accidents each added over $20,000 in hospital charges. The authors also identified other significant factors associated with increased hospital charges, which included specific racial groups, hospital regions, mechanisms of injury, maxillofacial fractures, other fractures, intracranial injuries, and internal organ injuries.

Rising healthcare costs have been a topic of debate for the better part of the past three decades. Costs have continued to balloon despite innovations in treatments that have reduced morbidity, mortality, and length of hospitalization. Pediatric trauma is the most preventable healthcare utilization in the United States today.¹⁴ The epidemiologic findings of this study are in line with a multitude of other research related to pediatric trauma populations that have found a disposition towards males, with mandible fractures as the most common fracture- identified in 20–33% of cases^14,23. Cranial vault fractures were found to be the most common fracture outside of the maxillofacial region, and concussion as the most common associated injury.¹³ Falls were also found to be the most common etiology in other maxillofacial literature, but trends were variable based on the region of study.^13,24

Hispanic patients were found to be associated with increased hospitalization charges compared to their White and Black counterparts. This is a finding that has been documented in other studies on adult populations.²⁵ The underlying cause of this has been attributed to a multitude of factors- including Hispanic patients being disproportionately treated in hospitals that ranked lower on the HQA (Hospital Quality Alliance) hospital quality scale.²⁶ These hospitals frequently did not have medical ICUs necessary to deliver the adequate level of care to the complex patients they were treating. Adult Hispanic patients were also found to have longer lengths of stay following acute MI when controlling for comorbidities and procedural utilization, directly affecting cost of treatment.²⁷

Additional research has shown language barriers to be a significant source of increased medical cost and decreased perceived quality of care.^28,29 Language barrier was found to be associated with higher resource usage for diagnostic studies and longer emergency visits.³⁰ The authors of this study believe that these factors seen in the adult Hispanic population can be extrapolated to the pediatric population and may explain the increased financial burden found among this population.

Regional healthcare cost variation found in this study persists when evaluating patient care of all ages. A 2019 survey of average daily inpatient hospital costs by the AHA found 12 of the top 15 states (and Washington DC) were on the west and east coasts.³¹ Besides this data from the AHA, there is a paucity of information delving into the driving forces behind these regional cost increases.

Pan-facial fractures and concomitant injuries (i.e., pelvic fracture) were risk factors for increased hospital charges. In a study on patients who suffered isolated mandibular fractures, Dillon et al determined that each additional fracture added $2,672 to the cost of treatment.¹⁸ It stands to reason that patients with multi-system trauma generally had more severe injuries requiring an increase in utilization of resources, consultations, and length of stay that would all lead to greater costs of hospitalization. These more severe and multi-system traumas were correlated with certain mechanisms of injury, usually those that entail a high velocity and magnitude of kinetic energy. Motor vehicle collisions, motorcycle collisions, and firearm injuries were associated with not only increased severity of injury, but also increased cost and length of stay of hospitalization when compared to low energy mechanisms such as falls. These findings are consistent with the pediatric maxillofacial trauma literature.²⁴ In a sample of pediatric patients who suffered traumatic injuries, Dueck et al determined that injury severity score (ISS) (p < 0.001) and the presence of extremity injury (p < 0.001) positively correlated with cost. This study confirms these findings, as pan-facial fractures and high-velocity mechanisms are statistically significant causes of increased hospital-related costs.

Previous literature in adult mandibular trauma has shown that outpatient treatment is a viable option for cost-reduction without sacrificing quality of care.¹⁹ However, in the pediatric population, a more prompt approach is the standard of care to reduce the overall treatment time which would lend towards admission. The tendency of pediatric fractures to greenstick decreases the overall need for operative repair. However, in cases where occlusion cannot be reproduced or there is obvious displacement of the fracture, operative management is warranted. Operative repair is associated with increased healthcare costs.³² Dodson et al. showed that rigid fixation averaged $1,468 more per patient than for nonrigid fixation.³³

The present study determined that patient transfer was associated with increased hospital charges. Amongst a sample of patients who suffered Le Fort fractures, Lee et al. determined that patient transfer independently added $8,611 to the total charges.³⁴ Transfers to a level 1 trauma center can potentially decrease the mortality risk in acutely injured patient and is warranted to improve survival. Nonetheless, Dillion et al. urge competent providers to treat patients when the severity of does not exceed the facility’s resources instead of unnecessarily transferring them to higher level facilities.¹⁸

It is crucial to interpret the results of this study within the confines of its limitations. We did not have insight into hospitalization trauma level (Level 1, 2, 3), whether Neurosurgery or Neurotrauma services were consulted, or whether there were any postoperative complications. The ICD-9 diagnostic codes for the injuries and mechanisms of injury may not have been reported, underestimating the injury/mechanism. The authors believe this was the case for the mechanisms of injury studied, explaining their relatively low numbers in our study sample. It is also important to consider the possibility that of inaccuracies with the diagnostic codes. Withstanding these limitations, the KID contains data on patients throughout the US, instead of being confined to a certain city or state, reinforcing the external validity of our results.

In summary, there is an opportunity for cost reduction in the management of pediatric maxillofacial trauma. Reduction through appropriate preventative measures such as seatbelt wearing, helmet wearing, and pacification measures during inter-personal violence is ideal. However, knowing these injuries will continue to happen, it is appropriate to focus on cost reduction measures. This can include having promptness in definitive repair and easy access to interpreters for non-English speaking patients. Certain factors, such as multi-system injury and severity of injury, are cost factors that are out of the provider’s loci of control. However, cost-efficient approaches to patient care should be recognized and utilized to the patient and family benefit whenever possible.

Funding

The authors confirm that no funds, grants, or other support was received during the completion of this project and manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

Dani Stanbouly conceived the study idea and conducted the statistical analyses. Andrew J. Deek drafted the discussion. Abdalla M. Asi drafted the discussion. Ahmad Minhas revised the manuscript according to revisions from senior authors. Nicolas Graillon revised the manuscript and provided suggestions. Neeraj Panchal revised the manuscript and provided suggestions. Sung-Kiang Chuang revised the manuscript and provided the final approval for submission.

Ethics approval

Because the KID is a database that is both publicly available and anonymized, we did not require institutional board review (IRB).

Consent to participate

Not applicable. Data was acquired from a database, not patient charts.

Consent to publish

Not applicable. Data was acquired from a database, not patient charts.

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No competing interests reported.

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What factors influence the cost in treating maxillofacial fractures among pediatric patients?

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