Abstract
Background:
The aim of this study is to define the cost of rib fracture hospitalization by single, multiple, and flail type using a nationally representative sample.
Methods:
The national inpatient sample (NIS) was used to identify patients with a primary diagnosis of rib fracture hospitalization 2007–2016. International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes were used to characterize patients as having single, multiple, or flail chest rib fractures. Patients with only trauma related diagnosis groups (DRG) at the time discharge were included in the final sample. The cost of hospitalization was obtained by converting reported charges into cost using the all-payer inpatient cost-to-charge ratio (CCR) for all hospitals in the NIS data. The log of cost was modeled using multivariate linear regression. The rib fracture type was the primary predictor in the model.
Results:
There were 373,053 rib fracture admissions during 2007–2016. The average cost per hospitalization was $10,169 (95%Confidence Interval [CI]: 9,942–10,395), which translated into a national expenditure of $3.64 billion over 10 years. The cost of rib fracture hospitalization increased from $209 million in 2007 to $469 million in 2016. Compared to single rib fracture patients, the cost of hospitalization for multiple rib fractures and flail chest was 3% (p = 0.001) and 5% (p = 0.02) higher, respectively. Higher injury severity score, total number of body regions injured and longer length of stay were associated with higher rib fracture hospitalization cost.
Conclusions:
Rib fractures affect ~22,000–45,000 people per year in the United States. The cost of rib fractures is over $469 million per year and is increasing over time. Multiple rib fractures and flail chest rib fractures are associated with increased cost. Pathways to improve care in patients with rib fractures should consider the cost of treatment.
Keywords: Financial Cost, Thoracic injury, Rib fracture, Length of stay, Injury severity score
Introduction
Thoracic injury is the second leading cause of injury-related morbidity and mortality in the United States (US), second only to head injury-related deaths [1]. Rib fractures are common among trauma patients with an incidence ranging from 10–26% [1–4]. Rib fractures have significant impact on morbidity and mortality. Several factors, including the number of ribs fractured, are associated with mortality and prolonged hospitalization [1]. Despite improvement in the management of rib fractures, these injuries can result in both acute complications (pneumonia, prolonged mechanical ventilation, and death) and chronic disability (pain, dyspnea, and loss of productivity) [5].
Although multiple studies have evaluated the effectiveness of surgical interventions used for rib fracture treatment, there is a paucity of data regarding the economic impact of rib fracture hospitalization and the patient characteristics that influence the cost of care. No studies have estimated the national burden of rib fracture cost. Furthermore, there is no clear distinction of cost estimates by the type of rib fracture injury including single rib fractures, multiple rib fractures, and flail chest injuries. The aim of this study are threefold: 1) to describe the cost of rib fractures by injury type, 2) to determine which demographic, clinical, and injury-related characteristics affect the cost, and 3) to define the national burden of rib fracture economics. We hypothesized that demographic characteristics and rib fracture type would impact hospitalization costs.
Methods
Data Source
We used the 2007–2016 National Inpatient Sample (NIS) database to estimate the national cost of rib fracture. The NIS database is a part of the Healthcare Cost and Utilization Project (HCUP) and maintained by the Agency for Healthcare Research and Quality (AHRQ) [6,7].
This NIS provides separate cost-to-charge ratio (CCR) data from each hospital. CCR is used to estimate the cost of resource usage for inpatient hospital stays and its variation across hospitals and conditions based on the reported total charge. Costs reflect the actual expenses incurred in the production of hospital services, such as wages, supplies, and utility costs; charges represent the amount a hospital billed for the case. We linked the CCR file with the NIS dataset using the unique hospital identification number to obtain CCR values for converting charges to cost. In this study, the cost of rib fracture hospitalization was estimated by multiplying total charge by all-payer inpatient cost/charge ratio [8].
Study population
In the NIS-HCUP database, the first listed diagnosis is the primary diagnosis defined as “the condition established after study to be chiefly responsible for occasioning the admission of the patient to the hospital for care.” We identified patients with rib fractures using the primary diagnosis code [9]. This study included patients’ ≥18 years with primary diagnosis of single, multiple, or flail chest rib fracture from 2007 to 2016 NIS data.
The patients were identified using International Classification of Diseases, Ninth Revision, (ICD-9) and International Classification of Diseases, Tenth Revision (ICD-10) codes. The ICD-9 codes for a single rib fracture were 807.00 and 807.01, multiple rib fractures were 807.02, 807.03, 807.04, 807.05, 807.06, 807.07, 807.08, 807.09, and flail chest was 807.4. The ICD-10 codes for a single rib fracture were S22.3, S22.31, S22.32, S22.39, for multiple rib fractures were S22.4, S22.41, S22.42, S22.43, S22.49, and for flail chest was S22.5. Rib fracture patients with only trauma related diagnosis groups (DRG) at the time discharge were included in the final sample. The ICD-9 DRG codes were 83, 84, 183, 184, 185, 205, 206, 957, 958, 959, 963, 964, 965 and the ICD-10 DRG codes were 183, 184, 185, 205, 206, 957, 958, 959, 963, 964, 965. The description of these codes is provided elsewhere [10].
Outcome variable
The main outcome of interest was cost of hospitalization due to primary cause of single, multiple, or flail chest rib fracture. The cost for each year was calculated using 2016-dollar value after adjusting for inflation according to the latest consumer price index data released by the US government [11].
Statistical analysis
Demographic and clinical characteristics were summarized using descriptive statistics. The continuous variables are presented as means (95% Confidence Interval (CI)) and categorical variables are presented as percentages (95% CI). Three-group comparison analyses were performed using ANOVA and Rao Scott Chi Square test. For comparison of medians, the Kruskal-Wallis test was used. Fisher’s exact test was used in case of cell values <5. We modeled cost of hospitalization due to rib fracture type using a multivariate linear regression. Logarithmic (log) transformation of cost was used due to its non-normal distribution [12].
Regression model 1 included rib fracture patients with chest and other body injuries. Model 1 was accounted for patients’ demographics, comorbidities and injury related characteristics including age, sex, hospital length of stay (LOS), total number of procedures performed, insurance type, hospital region, Elixhauser comorbidity and mortality score, total number of body regions injured other than chest, and injury severity score (ISS). Regression model 2 was restricted to isolated chest injury rib fracture patients. This model was also accounted for patients’ demographics and comorbidities.
The Elixhauser comorbidity and mortality score was calculated using HCUP comorbidity software (13). We translated the ICD injury diagnosis codes into standard ISS using the open access program ICDPIC-R (14). The ISS was categorized as mild (<9), moderate [9–15], severe (16–24), and profound (≥25). Because the NIS is an approximately 20% weighted sample of hospital admissions, total national costs were estimated using predefined weighting estimates provided by HCUP-NIS [15]. All the complete case analyses were performed in SAS version 9.4 statistical software [16], using SURVEY procedures, with two-tailed p < 0.05 considered statistically significant. This study was Institutional Review Board (IRB) exempt.
Results
We identified 75,995 inpatient adult admissions with a primary diagnosis of single, multiple, or flail chest rib fractures in the NIS from 2007–2016. This represents an estimate of 373,053 inpatient admissions nationally. Of these, single rib fracture patients accounted for 10,350 (13%) admissions, multiple rib fracture patients accounted for 64,411 (85%) admissions, and flail chest rib fracture patients accounted for 1,234 (2%) admissions. Table 1 provides a descriptive summary of the patients’ characteristics. The average age varied by rib fracture type, lowest mean age was observed in flail chest rib fracture patients (60.3 yrs. vs 66.9 yrs. multiple vs 68.9 yrs. single; p < 0.001). Among flail chest rib fracture patients, the proportion male and female was 68.5% and 31.5%, respectively (p < 0.001). The hospital LOS varied by fracture type, and was highest among flail chest rib fracture patients (8.2 days vs 4.1 days multiple vs 3.3 days single; p < 0.001).
Table 1.
Demographics and clinical characteristics of the patients (unweighted frequencies) n = 75,995.
| Fracture Type | |||||||
|---|---|---|---|---|---|---|---|
| Single | Multiple | Flail | p value | ||||
| n = 10,350 | n = 64,411 | n = 1,234 | |||||
| n | Frequency % (95% CI) | n | Frequency % (95% CI) | n | Frequency % (95% CI) | ||
| Age, mean | 10350 | 68.94 (68.48 – 69.40) | 64411 | 66.92 (66.62 – 67.23) | 1234 | 60.36 (59.43 – 61.30) | <0.001 |
| Age, median (IQR) | 10350 | 73.04 (55.00 – 84.39) | 64411 | 68.18 (53.20 – 82.18) | 1234 | 58.57 (48.46 – 72.87) | <0.001* |
| <65 Years | 3848 | 37.21 (36.08 – 38.35) | 27947 | 43.38 (42.62 – 44.14) | 754 | 61.12 (58.35 – 63.90) | <0.001 |
| ≥ 65 Years | 6502 | 62.79 (61.65 – 63.92) | 36464 | 56.62 (55.85 – 57.38) | 480 | 38.88 (36.10 – 41.65) | |
| Sex | |||||||
| Male | 4948 | 47.79 (46.78 – 48.81) | 36441 | 56.59 (56.09 – 57.10) | 845 | 68.49 (65.92 – 71.06) | <0.001 |
| Female | 5402 | 52.20 (51.19 – 53.22) | 27970 | 43.41 (42.90 – 43.91) | 389 | 31.51 (28.94 – 34.08) | |
| Cost (2016 USD), mean | 9795 | 8008 (7719 – 8297) | 61978 | 10142 (9920 – 10364) | 1195 | 29037 (27024 – 31049) | <0.001 |
| Cost (2016 USD), median (IQR) | 9795 | 6497 (4376 – 9657) | 61978 | 7771 (5117 – 12052) | 1195 | 17176 (9290 – 35314) | <0.001* |
| Total Number of Procedures, median (IQR) | 10350 | 0 (0 – 1) | 64411 | 0 (0 – 1) | 1234 | 1 (0 – 5) | <0.001 |
| Length of Stay, mean | 10350 | 3.29 (3.23 – 3.36) | 64411 | 4.10 (4.07 – 4.14) | 1234 | 8.24 (7.85 – 8.62) | <0.001 |
| Length of Stay, median (IQR) | 10350 | 2.23 (1.04 – 3.68) | 64411 | 2.77 (1.48 – 4.68) | 1234 | 5.95 (3.13 – 10.38) | <0.001 |
| ISS Category | |||||||
| Mild ( <9) | 8900 | 86.03 (85.27 – 86.78) | 26946 | 41.87 (41.13 – 42.62) | 0 | - | <0.001* |
| Moderate (9–15) | 1299 | 12.51 (11.80 – 13.22) | 28421 | 44.07 (43.60 – 44.53) | 199 | 16.29 (13.98 – 18.60) | |
| Severe (16–24) | 130 | 1.26 (1.04 – 1.48) | 8225 | 12.78 (12.29 – 13.26) | 844 | 68.23 (65.40 – 71.05) | |
| Profound ( ≥25) | 21 | 0.20 (0.12 – 0.29) | 819 | 1.28 (1.17 – 1.39) | 191 | 15.48 (13.37 – 17.59) | |
| AIS Category | |||||||
| Minor-Moderate (1–2) | 9064 | 87.60 (86.90 – 88.31) | 29000 | 45.07 (44.34 – 45.81) | 0 | - | <0.001* |
| Serious-Severe (3–4) | 1275 | 12.29 (11.59 – 12.98) | 35276 | 54.71 (53.98 – 55.45) | 1210 | 98.05 (97.28 – 98.82) | |
| Critical-Maximal (5–6) | 11 | 0.11 (0.04 – 0.17) | 135 | 0.21 (0.16 – 0.25) | 24 | 1.95 (1.18 – 2.72) | |
| Chest Injury Only | 6607 | 63.72 (62.71 – 64.73) | 33291 | 51.65 (50.93 – 52.37) | 366 | 29.74 (27.12 – 32.35) | <.0001 |
| Head and Neck Injury | 676 | 6.60 (6.08 – 7.11) | 7117 | 11.10 (10.73 – 11.48) | 296 | 24.07 (21.63 – 26.52) | <0.001 |
| Face Injury | 174 | 1.69 (1.43 – 1.95) | 1929 | 3.01 (2.85 – 3.17) | 66 | 5.35 (4.11 – 6.60) | <0.001 |
| Extremities | 315 | 3.11 (2.71 – 3.50) | 3131 | 4.95 (4.59 – 5.32) | 160 | 13.10 (10.98 – 15.22) | <0.001 |
| Abdominal Injury | 769 | 7.43 (6.90 – 7.97) | 8276 | 12.88 (12.46 – 13.29) | 430 | 34.89 (32.18 – 37.60) | <0.001 |
| External and Other Injuries | 2693 | 26.00 (25.07 – 26.93) | 21665 | 33.55 (32.80 – 34.29) | 564 | 45.51 (42.60 – 48.42) | <0.001 |
| Total Body Regions Injured, Median (IQR) | 10350 | 1 (1 – 2) | 64411 | 1 (1 – 2) | 1234 | 2 (1 – 3) | <0.001 |
| Elixhauser Readmit Score, mean | 10350 | 12.91 (12.61 – 13.21) | 64411 | 10.62 (10.48 – 10.77) | 1234 | 9.02 (8.46 – 9.58) | <0.001 |
| Elixhauser Mortality Score, mean | 10350 | 4.01 (3.84 – 4.18) | 64411 | 3.19 (3.11 – 3.27) | 1234 | 3.47 (3.06 – 3.88) | <0.001 |
| Diabetes Without Chronic Complications | 1931 | 18.61 (17.82 – 19.40) | 10537 | 16.35 (16.05 – 16.65) | 142 | 11.43 (9.66 – 13.20) | <0.001 |
| Diabetes With Chronic Complications | 394 | 3.82 (3.44 – 4.20) | 2181 | 3.40 (3.24 – 3.56) | 35 | 2.87 (1.94 – 3.80) | 0.054 |
| Chronic Pulmonary Disease | 2354 | 22.70 (21.80 – 23.59) | 11615 | 18.03 (17.67 – 18.39) | 177 | 14.46 (12.50 – 16.42) | <0.001 |
| Congestive Heart Failure | 1226 | 11.86 (11.17 – 12.54) | 5629 | 8.74 (8.48 – 9.00) | 62 | 5.05 (3.81 – 6.28) | <0.001 |
| Valvular Disease | 538 | 5.21 (4.75 – 5.67) | 2533 | 3.94 (3.78 – 4.11) | 28 | 2.25 (1.43 – 3.07) | <0.001 |
| Renal Fail | 1056 | 10.27 (9.67 – 10.87) | 5190 | 8.08 (7.83 – 8.33) | 55 | 4.49 (3.34 – 5.63) | <0.001 |
| Liver Disease | 344 | 3.32 (2.97 – 3.68) | 1775 | 2.78 (2.64 – 2.91) | 27 | 2.20 (1.35 – 3.04) | 0.004 |
| Deficiency Anemias | 1303 | 12.57 (11.88 – 13.26) | 6430 | 9.98 (9.67 – 10.29) | 94 | 7.60 (6.06 – 9.13) | <0.001 |
| Alcohol Abuse | 928 | 9.00 (8.44 – 9.57) | 6424 | 9.99 (9.73 – 10.26) | 127 | 10.32 (8.67 – 11.98) | 0.006 |
| Drug Abuse | 343 | 3.33 (2.96 – 3.70) | 1911 | 2.98 (2.82 – 3.14) | 44 | 3.51 (2.50 – 4.52) | 0.107 |
| Hypertension | 5831 | 56.40 (55.33 – 57.47) | 33768 | 52.45 (51.90 – 53.01) | 469 | 38.04 (35.22 – 40.86) | <0.001 |
| Insurance Type | |||||||
| Medicare | 6156 | 59.61 (58.44 – 60.78) | 32936 | 51.30 (50.51 – 52.09) | 415 | 33.81 (31.11 – 36.51) | <0.001 |
| Medicaid | 738 | 7.18 (6.63 – 7.74) | 3951 | 6.18 (5.90 – 6.45) | 94 | 7.70 (6.15 – 9.24) | |
| Private Insurance | 2318 | 22.41 (21.47 – 23.34) | 19231 | 29.94 (29.29 – 30.59) | 508 | 41.28 (38.44 – 44.11) | |
| Uninsured | 604 | 5.84 (5.29 – 6.38) | 4149 | 6.44 (6.14 – 6.75) | 97 | 7.85 (6.38 – 9.33) | |
| Other | 510 | 4.96 (4.49 – 5.42) | 3950 | 6.14 (5.83 – 6.44) | 116 | 9.36 (7.68 – 11.03) | |
| Region | |||||||
| Northeast | 2500 | 24.34 (22.32 – 26.35) | 14617 | 22.85 (21.53 – 24.17) | 191 | 15.6360 (13.04 – 18.23) | <0.001 |
| Midwest | 2480 | 23.86 (22.50 – 25.22) | 14279 | 22.10 (21.04 – 23.16) | 297 | 24.01 (21.17 – 26.84) | |
| South | 3160 | 30.59 (28.96 – 32.22) | 21476 | 33.30 (31.79 – 34.81) | 394 | 31.83 (28.64 – 35.01) | |
| West | 2210 | 21.21 (19.58 – 22.83) | 14039 | 21.75 (20.40 – 23.10) | 352 | 28.53 (25.39 – 31.67) | |
| Disposition | |||||||
| Routine | 5615 | 54.15 (53.02 – 55.29) | 35479 | 55.07 (54.32 – 55.82) | 661 | 53.57 (50.76 – 56.39) | <0.001* |
| Transfer to Short-term Hospital | 142 | 1.37 (1.13 – 1.60) | 1078 | 1.67 (1.54 – 1.80) | 53 | 4.26 (3.12 – 5.41) | |
| Transfer to Skilled Nursing Facility (SNF), Intermediate Care Facility (ICF), Another Type of Facility | 3066 | 29.70 (28.68 – 30.71) | 19108 | 29.70 (29.11 – 30.28) | 325 | 26.38 (23.90 – 28.86) | |
| Home Health Care (HHC) | 1326 | 12.88 (12.16 – 13.61) | 7551 | 11.74 (11.39 – 12.08) | 114 | 9.20 (7.47 – 10.92) | |
| Against Medical Advice (AMA) | 135 | 1.31 (1.08 – 1.55) | 559 | 0.87 (0.80 – 0.95) | - | - | |
| Died | - | - | 596 | 0.93 (0.85 – 1.00) | - | - | |
| Discharge alive, destination unknown | - | - | 16 | 0.03 (0.01 – 0.04) | 0 | - | |
CI, Confidence Interval, p values for ANOVA, Rao-Scott Chi-square test, or.
Cell values less than or equal to 10 and the second lowest cell values are masked for privacy protection.
Kruskal-Wallis or Fisher’s Exact test, with p < 0.05 considered significant.
Overall flail rib fracture patients had a higher percentage of head and neck (24%), face (5%), abdominal (35%), and external and other trauma injuries (45%), and extremities (13%) compared to single and multiple rib fracture patients. Of the total rib fracture patient population, 53% (40,264) of the patients had isolated chest injuries, representing a national estimate of 197,471 inpatient admissions. A higher proportion of isolated chest injuries occurred in single rib fracture patients (64%) followed by multiple rib fracture patients (52%) and only a 30% of the flail rib fracture patients had isolated chest injuries.
The overall mean cost for primary rib fracture hospitalization from 2007 to 2016 was $10,169 (median $7,628). The mean cost for hospitalization was the highest in flail chest rib fracture patients accounting for $29,037 (median $17,178), followed by multiple rib fracture patients at $10,142 (median $7,770) and single rib fracture patients at $8,008 (median $6,502) (p < 0.001). A histogram of hospitalization cost by fracture type is shown in Fig. 1 and it shows that the range of the flail chest rib fracture cost was the widest falling within ~$8,00 0 to $68,000. The total national cost of hospitalization for patients with a primary diagnosis of rib fracture was $3,643,762,702 ($3.64 billion) over the study period. The total nationwide cost during the study period for single rib fractures was $383,933,751 ($383.9 million), for multiple rib fractures, it was $3,088,108,451 ($3.08 billion), and for flail chest rib fractures, it was $171,720,500 ($171.7 million). The yearly nationwide cost for rib fracture hospitalization increased from $209.3 million in 2007 to $469.1 million in 2016 (Fig. 2).
Figure 1.
Distribution of rib fracture cost in 2016-dollar value by fracture type (cost >$80,000 is not added in this figure due to overdispersion, total 225 observations omitted; single n = 7, multiple n = 132, flail n = 86).
Figure 2.
Trends of inflation adjusted rib fracture cost presented in 2016-dollar value by fracture type (single, multiple, and flail), 2007–2016.
We performed a multivariable regression analysis to predict the cost for hospitalization by fracture type adjusting for patient demographics, comorbidities, and injury related characteristics. Among rib fracture patients with chest and other body injuries (“Model 1”, Table 2) multiple and flail chest rib fracture injuries were associated with higher cost than single rib fractures (3% p = 0.001 and 5% p = 0.02, respectively). Relative to the mild injury category, moderate, severe, and profound injury categories were associated with higher costs (6%, 18%, 26%, respectively, p < 0.001). Compared to only chest injuries, 1–2 and 3–5 body region injuries were significantly associated with higher cost (17% and 32% respectively < 0.001). Cost of hospitalization also increased incrementally for each day increase in LOS by 10% (p < 0.001) and the number of procedures performed during the hospitalization by 7% (p < 0.001). Increasing Elixhauser readmission and mortality scores also increased the cost by 0.3% and 0.1%, respectively (p < 0.001). Younger age was significantly associated with a 0.3% increase in the rib fracture cost (p < 0.001). Patients with private insurance had 6% higher total charges compared to those with Medicare (p < 0.001). The western hospital region was also significantly associated with a 25% higher rib fracture hospitalization cost compared to the northeast region (p < 0.001).
Table 2.
Multivariate linear regression for factors predicting the cost of rib fracture hospitalization among rib fracture patients with other body regions injured (n = 72,754).
| Parameters | Exp* | 95% CI | p value | |
|---|---|---|---|---|
| Fracture Type | Single | Ref | ||
| Multiple | 1.03 | (1.01 – 1.04) | 0.001 | |
| Flail | 1.05 | (1.01 – 1.09) | 0.022 | |
| ISS Category | Mild (1–8) | Ref | ||
| Moderate (9–15) | 1.06 | (1.05 – 1.07) | <0.001 | |
| Severe (16–24) | 1.18 | (1.16 – 1.20) | <0.001 | |
| Profound (25–75) | 1.26 | (1.22 – 1.30) | <0.001 | |
| Total No. of Body Regions Injured | Only chest injuries | Ref | ||
| 1–2 | 1.17 | (1.16 – 1.18) | <0.001 | |
| 3–5 | 1.32 | (1.29 – 1.34) | <0.001 | |
| Age | 0.997 | (0.995 – 0.998) | <0.001 | |
| Length of Stay | 1.1 | (1.09 – 1.11) | <0.001 | |
| Total number of procedures | 1.07 | (1.06 – 1.08) | <0.001 | |
| Elixhauser Readmit Score | 1.003 | (1.002 – 1.004) | <0.001 | |
| Elixhauser Mortality Score | 1.001 | (1.0005 – 1.002) | 0.001 | |
| Sex | Female | Ref | ||
| Male | 1.01 | (1.004 – 1.02) | 0.004 | |
| Insurance Type | Medicare | Ref | ||
| Medicaid | 1.01 | (0.98 – 1.03) | 0.504 | |
| Private Insurance | 1.06 | (1.05 – 1.07) | <0.001 | |
| Uninsured | 1.04 | (1.02 – 1.06) | 0.001 | |
| Other | 1.06 | (1.04 – 1.08) | <0.001 | |
| Hospital Region | Northeast | Ref | ||
| Midwest | 0.94 | (0.93 – 0.98) | 0.001 | |
| South | 0.85 | (0.82 – 0.89) | <0.001 | |
| West | 1.25 | (1.20 – 1.29) | <0.001 |
CI, Confidence Interval.
R2 = 0.5018.
Represents exponentiated regression coefficients obtained from the multivariate regression analysis. These values represent the percentage difference in costs between categories. For example, the difference in costs between single and flail rib fracture was 5% (exp = 1.05).
Among rib fracture patients with isolated chest injuries (“Model 2”, Table 3), relative to single rib fracture patients, multiple rib fracture accounted for 6% (p < 0.001) higher hospitalization cost, and flail chest rib fracture accounted for 12% (p = 0.001) higher hospitalization cost. Apart from type of rib fracture, hospital LOS (11% increase per day; p < 0.001) and western hospital region (22% increase; p < 0.001) compared to the northeastern region were the major significant contributors of higher hospitalization cost.
Table 3.
Multivariate linear regression for factors predicting the cost of rib fracture hospitalization among rib fracture patients with isolated chest injury (n = 38,505).
| Parameters | Exp* | 95% CI | p value | |
|---|---|---|---|---|
| Fracture Type | Single | Ref | ||
| Multiple | 1.06 | (1.04 – 1.07) | <0.001 | |
| Flail | 1.12 | (1.06 – 1.19) | 0.001 | |
| Age | 0.997 | (0.995 – 0.998) | <0.001 | |
| Length of Stay | 1.11 | (1.10 – 1.12) | <0.001 | |
| Total number of procedures | 1.07 | (1.06 – 1.08) | <0.001 | |
| Elixhauser Readmit Score | 1.003 | (1.002 – 1.004) | <0.001 | |
| Elixhauser Mortality Score | 1.002 | (1.001 – 1.003) | <0.001 | |
| Sex | Female | Ref | ||
| Male | 1.02 | (1.01 – 1.03) | 0.001 | |
| Insurance Type | Medicare | Ref | ||
| Medicaid | 0.98 | (0.96 – 1.01) | 0.17 | |
| Private Insurance | 1.06 | (1.04 – 1.08) | <0.001 | |
| Uninsured | 1.03 | (0.99 – 1.06) | 0.053 | |
| Other | 1.05 | (1.02 – 1.08) | <0.001 | |
| Hospital Region | Northeast | Ref | ||
| Midwest | 0.92 | (0.88 – 0.95) | <0.001 | |
| South | 0.81 | (0.78 – 0.84) | <0.001 | |
| West | 1.22 | (1.17 – 1.54) | <0.001 |
CI, Confidence Interval.
R2 = 0.4354.
Represents exponentiated regression coefficients obtained from the multivariate regression analysis. These values represent the percentage difference in costs between categories. For example, the difference in costs between single and flail rib fracture was 12% (exp = 1.12).
Discussion
This analysis demonstrates that rib fracture hospitalizations are a public health burden to the US health care system with more than 373,000 hospitalizations with a primary diagnosis of rib fracture over the period of 2007–2016. During the study period, the estimated national cost for rib fracture hospitalizations increased more than 124% from $209 million in 2007 to $469 million in 2016, for total expenses of over $3.64 billion. In contrast, the overall US hospital spending increased only 38% from $788 billion to $1,089 billion from 2007 to 2016, respectively [17]. This cost estimation is still an underestimate of the total rib fracture costs since our analysis does not include physician fees or post-hospitalization care and, importantly, only includes patients with primary diagnosis of rib fracture. The cost was associated with several factors, with more severe rib fracture type, injury severity categories, and number of body regions injured contributing most dramatically. Additionally, LOS, comorbidity and mortality score, number of procedures performed, type of insurance, and regional variations all contributed to the increased cost.
In our study flail chest was associated with higher hospitalization cost among rib fracture patients with other body injuries and isolated chest injury rib fracture patients. Several studies have examined care pathways in patients with flail chest. Several trials have examined the effect of epidural anesthesia on outcomes of patients with flail chest [18–21]. These and other studies led to an Eastern Association for the Surgery Trauma (EAST) guideline on this subject, which conditionally recommended regional epidural anesthesia over non-regional modalities [22]. Meta-analysis of randomized trials also suggests that surgical stabilization of rib fractures (SSRF) for patients with flail chest can lead to several benefits, including decreased rate of pneumonia, decreased duration of mechanical ventilation and decreased hospital LOS [23]. A current practice management guideline conditionally recommends surgical SSRF for patients with flail chest based on these and other benefits [24]. A study of the cost-effectiveness of SSRF in flail chest demonstrated higher overall cost, but superior outcomes and calculated an incremental cost-effectiveness ratio of $8,577/QALY [25]. Despite being an evidence-based practice for patients with flail chest, adherence to evidence-based care is poor among trauma centers in the US. A recent study by Tignanelli and colleagues [26] showed that only 14% of the patients with traumatic rib fracture injuries received SSRF for flail chest from January 2007, through December 2014. Lack of adherence to evidence based care can potentially contribute to longer LOS, thus consequently increase the cost of rib fracture care among flail chest patients.
The largest total cost is attributable to the group of patients with multiple non-flail fractures, which accounted for more than 84% of the total costs in this study. There are relatively few studies which address care in patients with these non-flail injuries. A study by Dalton and colleagues [27] suggested that patients admitted for a primary diagnosis of multiple rib fractures could be safely discharged within three days of hospitalization, which was associated with significant cost savings to the hospitals. In that study, multimodal pain management, aggressive pulmonary toilet, and early communication with patients to establish realistic goals and expectations were methods used to reduce LOS. In the present study, more than 50% of the patients with multiple non-flail fractures had moderate to profound injuries. Moderate or more severe injuries may have a significant effect on the LOS; despite these severe injuries, we believe that expedited discharge are still feasible. A study by Dalton et al. [27] corroborates this, and indicated that elevated ISS did not reduce the rate of expedited discharges among patients with non-flail multiple rib fracture injuries. In addition, a trial of SSRF in patients with non-flail injuries also demonstrated benefit in pain control and respiratory quality of life associated with SSRF without an effect on hospital LOS [28]. Considering that the majority of costs are associated with non-flail injuries, we advocate for evaluation of care pathways in this group of patients as well.
This study has several limitations that merit discussion. First, the NIS is an administrative database. Although one NIS entry is equivalent to one hospitalization, one rib fracture patient may contribute to multiple entries if that patient was transferred from one hospital to another. Patients readmitted with recurrent disease would also be counted, and this may lead to the overestimation of cost. However, only 1.8% of the total sample was transferred to another facility, and in theory, costs incurred at each facility would still be valid representations of costs incurred during care before and after transfer. Second, only patients with a primary diagnosis of rib fracture cases were included in the study; this may cause a dramatic underestimation of rib fracture cases. We also have not attempted to analyze the cost of care which occurs after discharge and may be significant. Third, to convert the charges into cost using CCR assumes that all hospitalizations at a particular hospital have the same markup price. Charges may vary across departments within a hospital; therefore, this may lead to under- or over-estimation of costs for some patients. Nevertheless, the hospital-wide CCRs provided by the NIS are validated and found to be more accurate than gross charges, despite being known to be less accurate when compared with department-based CCRs [8]. Fourth, the cost is not adjusted for other unmeasured confounding variables, which may affect conclusions regarding the impact of demographics on cost. Fifth, the cost pertains to payer estimates; however, NIS-HCUP data provides a reliable overview of national expenditure. Sixth, the cost is derived from hospital charges and cost-to-charge ratios; thus, the cost estimations may not solely be attributed to a rib fracture diagnosis and includes the cost of an entire hospitalization. Seventh, the rib fracture type was characterized using the primary admitting ICD code from the NIS data, this leads to the possibility that a patient could have a secondary diagnosis of a chest injury. Nonetheless, from the total sample of 75,995 patients with a primary diagnosis of rib fracture, less than half a percent of the patients (n = 313; 0.41%) had a secondary diagnosis of rib fracture injury. Finally, secondary methods were used to calculate the ISS; this may lead to some inaccuracy to the ISS score, which could affect our conclusions regarding the effect of ISS on costs.
Conclusions
Rib fracture hospitalizations are a large cost burden on the US healthcare system. Our analysis, which is likely an underestimate, suggests cost in excess of $460 million per year and increasing. This study also confirms that the cost of rib fracture hospitalization is independently associated with rib fracture type, injury severity categories and number of body regions injured with a predominant modifiable factor of LOS. The combined effect of these factors may synergistically increase costs. The future studies should define care algorithms using risk stratification models that consider these factors to develop efficient and effective patient care pathways to improve patient outcomes and reduce the cost.
Footnotes
Declaration of Competing Interest
VPH is supported by the Clinical and Translational Science Collaborative of Cleveland, KL2TR002547 from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health. VPH spouse is consultant for Zimmer Biomet, Medtronic, Atricure, and Sig Medical. CWT is consultant for Zimmer Biomet, Medtronic, Atricure, and Sig Medical.
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