Trauma is a leading cause of death and disability in the United States (US). This analysis describes trends and annual changes in in-hospital trauma morbidity and mortality; evaluates changes in age and gender specific outcomes, diagnoses, causes of injury, injury severity and surgical procedures performed; examines the role of teaching hospitals and Level 1 trauma centers in the care of severely injured patients.
Methods
We conducted a retrospective descriptive and analytic epidemiologic study of an inpatient database representing 20,659,684 traumatic injury discharges from US hospitals between 2000 and 2011. The main outcomes and measures were survey-adjusted counts, proportions, means, standard errors, and 95% confidence intervals. We plotted time series of yearly data with overlying loess smoothing, created tables of proportions of common injuries and surgical procedures, and conducted survey-adjusted logistic regression analysis for the effect of year on the odds of in-hospital death with control variables for age, gender, weekday vs. weekend admission, trauma-center status, teaching-hospital status, injury severity and Charlson index score.
Results
The mean age of a person discharged from a US hospital with a trauma diagnosis increased from 54.08 (s.e.= 0.71) in 2000 to 59.58 (s.e. = 0.79) in 2011. Persons age 45 to 64 were the only age group to experience increasing rates of hospital discharges for trauma. The proportion of trauma discharges with a Charlson Comorbidity Index score greater than or equal to 3 nearly tripled from 0.048 (s.e. = 0.0015) of all traumatic injury discharges in 2000 to 0.139 (s.e. = 0.005) in 2011. The proportion of patients with traumatic injury classified as severe increased from 22% of all trauma discharges in 2000 (95% CI 21, 24) to 28% in 2011 (95% CI 26, 30). Level 1 trauma centers accounted for approximately 3.3% of hospitals. The proportion of severely injured trauma discharges from Level 1 trauma centers was 39.4% (95% CI 36.8, 42.1). Falls, followed by motor-vehicle crashes, were the most common causes of all injuries. The total cost of trauma-related inpatient care between 2001 and 2011 in the US was $240.7 billion (95% CI 231.0, 250.5). Annual total US inpatient trauma-related hospital costs increased each year between 2001 and 2011, more than doubling from $12.0 billion (95% CI 10.5, 13.4) in 2001 to 29.1 billion (95% CI 25.2, 32.9) in 2011.
Conclusions
Trauma, which has traditionally been viewed as a predicament of the young, is increasingly a disease of the old. The strain of managing the progressively complex and costly care associated with this shift rests with a small number of trauma centers. Optimal care of injured patients requires a reappraisal of the resources required to effectively provide it given a mounting burden.
Keywords: Injury, Trauma, Epidemiology
Introduction
Trauma is a leading cause of death and disability in the United States (US). For children and adults younger than age 45, trauma accounts for an estimated 79,000 deaths each year, compared to 49,000 non-communicable disease deaths and 15,000 infectious disease deaths.1 In the US, trauma is the single most important cause of potential years of life lost for persons under age 65.2
There have been notable advances in our knowledge of the epidemiology of trauma in the US since Donald Trunkey declared “We simply do not know what the incidence of trauma is in this country, or where it occurs”. 3 The advent of national registries coupled with improved hospital record keeping and standardized billing over the past decade has led to the accumulation of a vast amount of information on trauma in the US. Numerous studies in the past five years have utilized databases such as the National Trauma Data Bank (NTDB) and Healthcare Cost and Utilization Project (HCUP) to investigate a wide range of trauma-related injuries and treatments. The nationwide scope of these studies and their findings inform clinicians, researchers, and policy makers alike.
Most studies utilizing large databases have focused on specific injuries such as vascular trauma to the extremities,4 spinal cord injuries, 5 and penetrating abdominal injury. 6 Other studies have concentrated on specific populations, such as the elderly, 7, 8 and adolescents. 9 Still other studies have used these databases to evaluate specific treatment protocols10 or policy changes. 11
Those studies that have taken a broader view of the epidemiology of trauma in the US have generally concentrated on mortality, 12 and have been either largely based on trauma registry data, 13 single institutions,14 or have been based on literature review.15 While informative in their own right, these studies fail to capture the full spectrum of the evolving patterns of trauma morbidity in the US over time.
In this paper, we present a large-data, nationally-representative, population-based study evaluating the descriptive epidemiology and trends of the inpatient incidence of trauma morbidity in the US between 2000 and 2011. We examine changes in the demographic characteristics of inpatient trauma, injury severity, the role of Level 1 trauma centers, the type of trauma (e.g. crush, burn, fracture), the most common causes of trauma, the most common trauma-related surgical procedures performed, and the hospital costs for the care of trauma patients. We believe it presents one of the fullest, most expansive recent pictures of a critically important cause of morbidity and mortality in the US.
Methods
Discharge Data
Data were obtained from the US Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Nationwide Inpatient Sample for the years 2000 to 2011. HCUP is a group of inpatient and outpatient files created by AHRQ. The Nationwide Inpatient Sample (NIS) is a 20% weighted sample of the State Inpatient Database. It is released yearly and appropriate for analysis at the national, regional and census area level. The Nationwide Inpatient Sample (NIS) is a stratified, single-cluster sample design (geographic area, urban/rural, ownership, teaching status, bed size). It is based on a sampling frame of all community hospitals in the US and is designed to be a 20% sample of all community hospitals in the US. Community hospitals are defined as non-Federal general and specialty hospitals including public hospitals and academic medical centers. A complete census of discharges for each sampled hospital is included in the database. Weights must be applied to each entry to get national or regional estimates.
Injury Classifications
Raw data were read into a comma-separated file, and national survey adjusted estimates for individual years were verified against estimates obtained from a publicly available HCUP online query system. 16 Trauma discharges were identified using principal or first-listed international classification of diseases 9th edition 17 diagnosis codes for acute injury 800–904.9, 909.4, 909.9, 910–994.9, 995.5–995.59, and 995.80–995.85. As noted in the HCUP documentation “The ICD-9-CM coding guidelines define principal diagnosis as “that condition established after study to be chiefly responsible for occasioning the admission of the patient to the hospital for care.”“ 18 Discharges with codes for “late effect” primary diagnoses (ICD 905.0–909.9), insect bites (910.4, 910.5, 9114, 911.5, 912.4, 912.5, 913.4, 913.5, 914.4, 914.5, 915.4, 915.5, 916.4, 916.5, 917.4, 917.5, 919.4, 919.5), poisonings (960.0–964.9, 965.00–965.02, 965.09, 965.1, 965.4, 965.5, 965.61, 965.69, 965.7–969.0, 969.00–969.09, 969.70–969.73, 969.1–969.7, 967.0–967.9, 969.79, 969.8–980.9, 970.81, 970.89, 981, 982.0–985.9, 986, 987.0–989.7, 989.81:989.89, 989.9, 990, 991.0–995.2, 995.20–995.29, 995.3, 995.4), anaphylaxis (995.60–995.69,995.7) and some additional miscellaneous diagnoses (malignant hyperthermia, systemic inflammatory response syndrome, malfunctioning cardiac devices, 995.86–996.00) were removed. The R 19 “icd9” 20 package was used to apply descriptors to the diagnostic ICD9 codes and external cause of injury E-codes.
Primary ICD9 codes were categorized according to the Barell Matrix, an injury diagnosis matrix tool used internationally to standardize the classification of ICD-9 injury codes 800 to 995 according to 12 nature-of-injury columns and 36 body-location rows.21, 22 Injury severity was quantified using the ICD-derived Injury Severity Score (ICISS).23 In this approach, “survival risk ratios (are) calculated as the ratio of the number of times a given ICD-9 code occurs in a surviving patient in a cohort or data set to the total number of occurrences of that code. ICISS calculations were based on all listed diagnoses for all patients during the entire study period. The ICISS is a probability that ranges from 0 to 1, and is defined as the product of all the survival risk ratios for each of an individual patient’s injuries (for as many as ten different injuries)”. 24 Patients (discharges) with severe injuries were defined as those with an ICISS below 0.94. 25 The Charlson comorbidity index score was calculated for each discharge using listed ICD-9 codes. 20 The score was then categorized into an indicator variable for patients with a Charlson comorbidity index greater than or equal to 3.
Trauma Center Classifications and Costs
Information on 2040 US trauma centers was obtained from the American Trauma Society website. 26 27 The data consisted of both American College of Surgeons verified and state designated trauma centers and included all levels. These data were matched on name and address to 3,706 HCUP-sampled US hospitals in the study data set. The matching process returned 1,038 hospitals that were present in both the ATS database and the NIS study sample. The hospitals were assigned trauma center level designations 1 to 5 as reported by the ATS. Hospitals that did not match were assumed to non-trauma centers. A full description of the matching process and a link to the code is available as supplementary material. Teaching hospitals were identified by an NIS variable. Income quartiles were based on an NIS variable that assigns a quartile classification of the estimated median household income of residents in the patient’s ZIP Code. Hospital submitted charges were available for the period 2001–2011. Hospital reported charges were converted to costs with the AHRQ HCUP cost-to-charge ratio files using the group weighted average cost-to-charge ratio variable. Costs were then adjusted for inflation and standardized to 2010 US dollars based the all-item average yearly consumer price index obtained from the Bureau of Labor Statistics.28 We used the HCUP Clinical Classification Software system was used to categorize procedure codes.
Analyses
Statistical analysis consisted of survey-adjusted counts, proportions, means, standard errors, and 95% confidence intervals. Annual rates were calculated using US Census data obtained from the Agency for Healthcare Research and Quality as part of the HCUP family of data products. We analyzed yearly data with overlying loess smoothing lines and present tables of the proportion of common injuries and surgical procedures. We assessed strength and statistical significance of the beta coefficient for bivariate linear association between year and annual incidence rates. The importance of geographic region on this association was assessed with an interaction term for geographic region. We conducted a survey-adjusted logistic regression analysis for the effect of year on the odds of in-hospital death with control variables for age, gender, weekday vs. weekend admission, injury severity, trauma-center status, teaching-hospital status, injury severity and Charlson index score. We used the R “survey” package29 to adjust for the complex sampling design of NIS and conduct analyses. We tested for the assumption of linearity of the year variable and controled for year-to-year variability in the survey results using an approach recommended by the Centers for Disease Control and Prevention. 30, 31
A complete set of notes and code to reproduce or adapt the study methods are available at http://www.injuryepi.org/resources/Misc/knitHCUPCode.pdf. The study was approved by the New York University School of Medicine Institutional Review Board as exempt.
Results
Descriptive Statistics and Incidence Rates
There were 20,659,684 (se = 266,857) inpatient traumatic injury discharges in the US between 2000 and 2011, representing 4.4 % (95% CI 4.3, 4.5) of the total 465,342,651 (se = 2,635,360) all-cause hospital discharges during that time. For all traumatic injury discharges, the proportion of male and female discharges was approximately evenly split, with 50.2% female (sd = .4%). In Level 1 trauma centers, the proportion of female patients was 38.2% (sd=1.0%). For severely injured patients (ICISS <0.94), the proportion of female patients was 36.9% (sd=0.4%). The mean age of traumatic injury discharges over the study period increased from 54.08 (se= 0.71) in 2000 to 59.58 (se = 0.79) in 2011, or approximately 6 months per year. The median age of traumatic injury discharges increased from 56 in 2000 to 65 in 2011. During the same time period, the median age for all US hospital discharges increased from 50 to 54.
The average annual rate of trauma discharges remained steady at 524.3 per 100,000 population (95% CI 483.3, 505.4) (β for effect of year on trauma discharge rate −1.67, se=1.76, p=0.364). An interaction term for census region by year was statistically significant for a higher trend over the study period for the South (β = 14.5, se=3.8, p < 0.0005) and West (β = 11.1, se=3.8, p = 0.0006) census regions. (Figure 1) U.S. Population-based rates of traumatic injury discharges for children and younger adults declined during the study period, while rates for older adults held constant. (Figure 2) The only group that experienced increasing rates of trauma discharges were those aged 45-64.
