STATISTICAL BRIEF #130
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May 2012
Josh Breslau, Ph.D., Elizabeth Stranges, M.S., Matthew Gladden, Ph.D., and Herbert Wong, Ph.D. Introduction All-terrain vehicles (ATVs) are small open motorized vehicles designed with large low-pressure tires for off-road use. ATVs are commonly used for both agricultural and recreational purposes. Because of the relatively small size of ATV motors, their use is not restricted by age or licensure. However, they can attain high speeds with rapid acceleration raising concerns for their safety, particularly for children. The Consumer Product Safety Commission estimates that there were 10.2 million 4-wheel ATVs in use in the United States in 2008.1 Three-wheel ATVs were removed from the market due to safety concerns in 1988,2 but a small number of 3-wheel ATVs may remain in use. ATV-injury related emergency department (ED) visits and hospitalizations increased along with the increasing popularity of ATVs. Between 2000 and 2004 the number of hospitalizations for ATV-related injury rose from 8,232 to 15,630.3 Hospitalizations for ATV injury among children ages 0-17 rose from 1,618 in 1997 to 4,039 in 2006.4 In addition to the removal of 3-wheel ATVs from the market, numerous state and local policies have attempted to reduce ATV-related injury by requiring helmet use and promoting safer use through educational programs,5 but the effectiveness of these measures remains in doubt. 6,7 This report provides an update on recent emergency room visits and hospitalizations for ATV-related injury in the United States, drawing on data from the Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) and the Nationwide Emergency Department Sample (NEDS) for years between 1993 and 2009.8 The report focuses on the age and geographic distribution of ATV injuries and on the time trends in the number of ED visits and hospitalizations for ATV injuries and their associated costs. Findings ATV-related emergency department visits, 2009 In 2009 there were about 115,200 emergency room visits for ATV injuries in the United States, around 315 visits per day. Table 1 shows characteristics of these visits in comparison with all other injury-related emergency room visits. ATV injury related ED visits were slightly more likely than the average injury-related visit to result in a hospitalization (13.5 percent versus 10.4 percent). About one in every 1,000 ED visits for an ATV-related injury ended in death. ATV injury victims seen in the ED were about a decade younger than other injury victims seen in the ED (27.1 years versus 36.3 years), and they were much more likely to be male (71.7 percent versus 51.9 percent). The large majority of ATV injury victims lived in relatively rural areas: 38.5 percent lived in micropolitan and non-core areas and an additional 34.4 percent lived in medium and small metropolitan areas. ED visits for ATV injuries were more likely to occur on a weekend than the total of other injury-related ED visits (47.0 percent versus 30.5 percent). |
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Table 1. Characteristics of ATV-related injuries treated in emergency departments, 2009 | |||
ATV-related ED visits | All other injury-related ED visits | ||
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Total number of visits | 115,200 | 29,858,700 | |
Rate per 100,000 population | 37.9 | 9,819.80 | |
Utilization characteristics | |||
Percentage treated and released | 86.1% | 89.1% | |
Percentage admitted to the hospital | 13.5% | 10.4% | |
Percentage died in ED | 0.1% | 0.1% | |
Other | 0.3% | 0.4% | |
Patient characteristics | |||
Mean age, years | 27.1 | 36.3 | |
Gender (percentage distribution) | |||
Males | 71.7% | 51.9% | |
Females | 28.3% | 48.1% | |
Patient residence (percentage distribution) | |||
Large central metro (urban) | 10.5% | 24.8% | |
Large fringe metro (suburban) | 16.6% | 22.4% | |
Medium and small metro | 34.4%* | 32.3% | |
Micropolitan and noncore (rural) | 38.5%* | 20.6% | |
Community-level income (percentage distribution) | |||
1st Quartile (lowest, under $39,999) | 30.9%* | 29.6% | |
2nd Quartile | 33.5%* | 28.7% | |
3rd Quartile | 22.4%* | 23.0% | |
4th Quartile (highest) | 13.2%* | 18.8% | |
Admission day (percentage distribution) | |||
Weekday (Monday-Friday) | 53.0% | 69.5% | |
Weekend (Saturday-Sunday) | 470% | 30.5% | |
*Difference from all other injury-related ED visits not statistically significant at p < 0.05. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009 |
Rates of ATV-related ED visits, 2009
As shown in figure 1, there is a strong relationship between age and the rate of ATV-injury-related ED visits. The rate of visits peaks in the 13 to 15 year age range at 10.2 per 100,000 population. Relative to older age groups, the rate of visits is also high for individuals ages 16 to 18 years (9.2 visits per 100,000 population), individuals ages 19 to 24 years (7.5 visits per 100,000 population), and individuals ages 10 to 12 years (6.2 visits per 100,000 population). |
Figure 1. Rate of ED visits for ATV-related injuries by age, 2009. Bar chart; ED visits per 100,000 population; ages 0 to 9, 2.2; ages 10 to 12, 6.2; ages 13 to 15, 10.2; ages 16 to 18, 9.2; ages 19 to 24, 7.5; ages 25 to 34, 5.8; ages 35 to 44, 3.6; ages 45 to 54; 2.1; age 55 and older, 1.0. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009. |
There is an enormous disparity in the population rates of ATV-injury related ED visits between urban and rural residents with the rate at only 7.3 per 100,000 among residents of urban areas and 227.2 among residents of rural areas, over a 30-fold difference (figure 2).
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Figure 2. Rate of ED visits for ATV-related injuries by patient residence, 2009. Bar chart; ED visits per 100,000 population; Large central metro, 7.3; large fringe metro (suburbs), 20.9; medium and small metro, 126.7; micropolitan and noncore (rural), 227.2;. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009. |
Distribution of ATV-related ED by payer, 2009
Figure 3 shows the primary expected payers for ATV injury related ED visits and all other injury related ED visits in 2009. Compared with all injury related visits, those for ATV injuries were more likely to be covered by private insurance (48.1 percent versus 38.1 percent) and more likely to be uninsured (22.9 percent versus 17.4 percent). ATV injury related ED visits were less likely than other injury related visits to be covered by Medicare, probably as a result of the low average age of ATV injury victims. |
Figure 3. Distribution of ATV-related ED visits and all other injury-related visits by expected payer, 2009. Stacked column bar chart; percentage share; ATV related ED visits; Medicare, 4.5%, 5.2%; 22.9%; 19.3%; 48.1%; Stacked column bar chart; percentage share; All other injury- related ED visits; Medicare, 16.6%, 8.1%; 17.4%; 19.8%; 38.1%. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009. |
ATV-related hospital stays, 2009
ATV injury related hospitalizations differ from other injury related hospitalizations in several ways. First, the patients tend to be much younger, averaging 34.1 years of age, compared with the average of 58.1 years of age for all other injury related hospitalizations (table 2). ATV injury related hospitalizations are shorter on average (4.3 days) than other injury hospitalizations (5.6 days), but there is no statistically significant difference among most age groups. On average, the costs associated with each day of hospitalization for an ATV injury is about 30 percent higher than the average for all other injury related hospitalizations ($3,000 versus $2,300). As a result, ATV injury related hospitalizations cost nearly the same amount as the average injury related hospitalization, despite the shorter mean length of stay. The estimated annual cost for all ATV injury related hospitalizations is $166.6 million. |
Table 2. Characteristics of ATV-related inpatient hospital stays, 2009 | |||
ATV-related hospital stays | Hospital stays for all other injuries | ||
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Total number of discharges | 12,800 | 3,413,900 | |
Rate per 100,000 population | 4.2 | 1,122.7 | |
Patient characteristics | |||
Mean age, years | 34.1 | 58.1 | |
Utilization characteristics | |||
Mean length of stay, days | 4.3 | 5.6 | |
Mean length of stay by age, days | |||
0 to 9 | 2.6 | 5.3 | |
10 to 12 | 4.3* | 4.3 | |
13 to 15 | 3.5* | 4.2 | |
16 to 18 | 3.4 | 4.3 | |
19 to 24 | 4.2* | 4.4 | |
25 to 34 | 4.3* | 4.6 | |
35 to 44 | 4.6* | 5.0 | |
45 to 54 | 4.5 | 5.6 | |
55 and Older | 5.4* | 6.1 | |
Average cost per stay | $13,000* | $13,100 | |
Average cost per day | $3,000 | $2,300 | |
Aggregate costs (million $) | $167 | $44,730 | |
Discharge status (percentage distribution) | |||
Routine | 82.0% | 52.9% | |
Transfer to short-term hospital or other facility | 10.5% | 31.9% | |
Home health | 5.6% | 11.4% | |
Against medical advice | 0.7% | 1.2% | |
Died | 1.2% | 2.6% | |
*Difference from all other injury-related inpatient stays not statistically significant at p < 0.05. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 2009 |
Trends in hospitalizations for ATV-related injuries, 1993-2009
Between 1993 and 2004, the number of hospitalizations for ATV-related injuries more than quadrupled, and aggregate costs increased ten-fold. Since 2004 the number of hospitalizations for ATV injuries has declined. In the most recent year for which data are available, 2009, the number of these hospitalizations had declined 18 percent from the peak in 2004. From 2004 to 2009, aggregate costs of ATV-related hospital stays declined by 3 percent. |
Figure 4. Number and aggregate costs of ATV-related hospital stays, 1993-2009;. Trend line; number of stays; aggregate costs (millions of dollars); in 1993, stays, 2,962; costs, 15; in 1994, stays, 3,728; costs, 21; in 1995, stays, 7,166; costs, 34; in 1996, stays, 4,708; costs, 26; in 1997, stays, 5,642; costs, 36; in 1998, stays, 6,655; costs, 43; in 1999, stays, 7,009; costs, 50; in 2000, stays, 8,577; costs, 57; in 2001, stays, 10,424; costs, 82; in 2002, stays, 11,679; costs, 102; in 2003, stays, 12,999; costs, 122; in 2004, stays, 15,697; costs, 171; in 2005, stays, 13,990; costs, 152; in 2006, stays, 14,483; costs, 162; in 2007, stays, 13,266; costs, 153; in 2008, stays, 14,787; costs, 211; in 2009, stays, 12,794; costs, 167. Source: AHRQ, Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 1993-2009.
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Data Source The estimates in this Statistical Brief are based upon data from the HCUP 2009 NIS and 2009 NEDS. Historical data were drawn from the 1993-2009 NIS. Supplemental sources included data from the U.S. Census Bureau, Population Division, Annual Estimates of the Population for the United States, Regions, and Divisions and U.S. Census Bureau, Current Population Reports, P60-226, Coverage by Type of Health Insurance.Definitions Diagnoses, ICD-9-CM, and Clinical Classifications Software (CCS)The principal diagnosis is that condition established after study to be chiefly responsible for the patient's admission to the hospital. Secondary diagnoses are concomitant conditions that coexist at the time of admission or that develop during the stay. ICD-9-CM is the International Classification of Diseases, Ninth Revision, Clinical Modification, which assigns numeric codes to diagnoses. There are about 13,600 ICD-9-CM diagnosis codes. CCS categorizes ICD-9-CM diagnoses into a manageable number of clinically meaningful categories.9 This "clinical grouper" makes it easier to quickly understand patterns of diagnoses. CCS categories identified as "Other" are typically not reported; these categories include miscellaneous, otherwise unclassifiable diagnoses that may be difficult to interpret as a group. Case definition The External Cause of Injury codes (E-codes) used to define ATV-related injuries were the following: E821.0, E821.1, E821.8, and E821.9. Types of hospitals included in HCUP HCUP is based on data from community hospitals, defined as short-term, non-Federal, general and other hospitals, excluding hospital units of other institutions (e.g., prisons). HCUP data include obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are long-term care, rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. However, if a patient received long-term care, rehabilitation, or treatment for psychiatric or chemical dependency conditions in a community hospital, the discharge record for that stay will be included in the NIS. Unit of analysis The unit of analysis is the hospital discharge (i.e., the hospital stay), not a person or patient. This means that a person who is admitted to the hospital multiple times in one year will be counted each time as a separate "discharge" from the hospital. Costs and charges Total hospital charges were converted to costs using HCUP Cost-to-Charge Ratios based on hospital accounting reports from the Centers for Medicare & Medicaid Services (CMS).10 Costs will 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. For each hospital, a hospital-wide cost-to-charge ratio is used. Hospital charges reflect the amount the hospital billed for the entire hospital stay and do not include professional (physician) fees. For the purposes of this Statistical Brief, costs are reported to the nearest hundred. Mean cost per day is calculated as the mean cost per stay divided by the mean length of stay. Location of patients' residence Place of residence is based on the urban-rural classification scheme for U.S. counties developed by the National Center for Health Statistics (NCHS). For this Statistical Brief, we collapsed the NCHS categories into either urban or rural according to the following: Urban:
Median community-level income is the median household income of the patient's ZIP Code of residence. The cut-offs for the quartile designation are determined using ZIP Code demographic data obtained from Claritas. The income quartile is missing for homeless and foreign patients. Payer Payer is the expected primary payer for the hospital stay. To make coding uniform across all HCUP data sources, payer combines detailed categories into more general groups:
About HCUP HCUP is a family of powerful healthcare databases, software tools, and products for advancing research. Sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP includes the largest all-payer encounter-level collection of longitudinal healthcare data (inpatient, ambulatory surgery, and emergency department) in the United States, beginning in 1988. HCUP is a Federal-State-Industry Partnership that brings together the data collection efforts of many organizations—such as State data organizations, hospital associations, private data organizations, and the Federal government—to create a national information resource. HCUP would not be possible without the contributions of the following data collection Partners from across the United States: Alaska State Hospital and Nursing Home Association (ASHNA) Arizona Department of Health Services Arkansas Department of Health California Office of Statewide Health Planning and Development Colorado Hospital Association Connecticut Hospital Association Florida Agency for Health Care Administration Georgia Hospital Association Hawaii Health Information Corporation Illinois Department of Public Health Indiana Hospital Association Iowa Hospital Association Kansas Hospital Association Kentucky Cabinet for Health and Family Services Louisiana Department of Health and Hospitals Maine Health Data Organization Maryland Health Services Cost Review Commission Massachusetts Division of Health Care Finance and Policy Michigan Health & Hospital Association Minnesota Hospital Association Mississippi Department of Health Missouri Hospital Industry Data Institute Montana MHA — An Association of Montana Health Care Providers Nebraska Hospital Association Nevada Department of Health and Human Services New Hampshire Department of Health & Human Services New Jersey Department of Health and Senior Services New Mexico Health Policy Commission New York State Department of Health North Carolina Department of Health and Human Services Ohio Hospital Association Oklahoma State Department of Health Oregon Health Policy and Research Pennsylvania Health Care Cost Containment Council Rhode Island Department of Health South Carolina State Budget & Control Board South Dakota Association of Healthcare Organizations Tennessee Hospital Association Texas Department of State Health Services Utah Department of Health Vermont Association of Hospitals and Health Systems Virginia Health Information Washington State Department of Health West Virginia Health Care Authority Wisconsin Department of Health Services Wyoming Hospital Association About the MIS The HCUP Nationwide Inpatient Sample (NIS) is a nationwide database of hospital inpatient stays. The NIS is nationally representative of all community hospitals (i.e., short-term, non-Federal, nonrehabilitation hospitals). The NIS is a sample of hospitals and includes all patients from each hospital, regardless of payer. It is drawn from a sampling frame that contains hospitals comprising about 95 percent of all discharges in the United States. The vast size of the NIS allows the study of topics at both the national and regional levels for specific subgroups of patients. In addition, NIS data are standardized across years to facilitate ease of use. About the NEDS The HCUP State Inpatient Databases (SID) are hospital inpatient databases from data organizations participating in HCUP. The SID contains the universe of the inpatient discharge abstracts in the participating HCUP States, translated into a uniform format to facilitate multi-state comparisons and analyses. Together, the SID encompasses 95 percent of all U.S. community hospital discharges in 2009. The SID can be used to investigate questions that are unique to one State; to compare data from two or more states; to conduct market area variation analyses; and to identify State-specific trends in inpatient care utilization, access, charges, and outcomes. For More Information For more information about HCUP, visit http://www.hcup-us.ahrq.gov. For additional HCUP statistics, visit HCUPnet, our interactive query system, at www.hcup.ahrq.gov. For information on other hospitalizations in the U.S., download HCUP Facts and Figures: Statistics on Hospital-Based Care in the United States in 2009, located at http://www.hcup-us.ahrq.gov/reports.jsp. For a detailed description of HCUP, more information on the design of the NIS, and methods to calculate estimates, please refer to the following publications: Introduction to the HCUP Nationwide Inpatient Sample, 2009. Online. May 2011. U.S. Agency for Healthcare Research and Quality. Available at http://www.hcup-us.ahrq.gov/db/nation/nis/NIS_2009_INTRODUCTION.pdf . (Accessed March 22, 2012). Introduction to the HCUP Nationwide Emergency Department Sample, 2009. Online. September 2011. U.S. Agency for Healthcare Research and Quality. Available at http://hcup-us.ahrq.gov/db/nation/neds/NEDS_Introduction_2009.pdf. (Accessed March 22, 2012). Houchens, R., Elixhauser, A. Final Report on Calculating Nationwide Inpatient Sample (NIS) Variances, 2001. HCUP Methods Series Report #2003-2. Online. June 2005 (revised June 6, 2005). U.S. Agency for Healthcare Research and Quality. Available at http://www.hcup-us.ahrq.gov/reports/methods/2003_02.pdf. (Accessed March 22, 2012). Houchens R.L., Elixhauser A. Using the HCUP Nationwide Inpatient Sample to Estimate Trends. (Updated for 1988-2004). HCUP Methods Series Report #2006-05. Online. August 18, 2006. U.S. Agency for Healthcare Research and Quality. Available at http://www.hcup-us.ahrq.gov/reports/methods/2006_05_NISTrendsReport_1988-2004.pdf. (Accessed March 22, 2012) Suggested Citation Breslau J. (RAND), Stranges E. (Thomson Reuters), Gladden M. (CDC), and Wong H. (AHRQ). Emergency Department Visits and Inpatient Hospital Stays for All-Terrain-Vehicle-Related Injuries, 2009. HCUP Statistical Brief #130. May 2012. Agency for Healthcare Research and Quality. Rockville, MD. Available at http://www.hcup-us.ahrq.gov/reports/statbriefs/sb130.pdf. Acknowledgements The authors would like to acknowledge Nils Norstrand and Lindsay Terrel for their assistance. *** AHRQ welcomes questions and comments from readers of this publication who are interested in obtaining more information about access, cost, use, financing, and quality of healthcare in the United States. We also invite you to tell us how you are using this Statistical Brief and other HCUP data and tools, and to share suggestions on how HCUP products might be enhanced to further meet your needs. Please e-mail us at hcup@ahrq.gov or send a letter to the address below:Irene Fraser, Ph.D., Director Center for Delivery, Organization, and Markets Agency for Healthcare Research and Quality 540 Gaither Road Rockville, MD 20850 1 Garland, S. (2010). Annual Report of ATV-Related Deaths and Injuries. Bethesda, MD, Consumer Product Safety Commission. 2 Sawyer, J. R., D. M. Kelly, et al. (2011). "Orthopaedic Aspects of All-terrain Vehicle-related Injury." Journal of the American Academy of Orthopaedic Surgeons 19(4): 219-225. 3 Helmkamp, J. C., P. M. Furbee, et al. (2008). "All-terrain vehicle-related hospitalizations in the United States, 2000-2004." American Journal of Preventive Medicine 34(1): 39-45. 4 Bowman, S. M. and M. E. Aitken (2010). "Still Unsafe, Still in Use: Ongoing Epidemic of All-Terrain Vehicle Injury Hospitalizations Among Children." Journal of Trauma-Injury Infection and Critical Care 69(6): 1344-1349. 5 Aitken, M. E., C. J. Graham, et al. (2004). "All-terrain vehicle injury in children: strategies for prevention." Injury Prevention 10(5): 303-307. 6 Winfield, R. D., D. W. Mozingo, et al. (2010). "All-Terrain Vehicle Safety in Florida: Is Legislation Really the Answer?" American Surgeon 76(2): 149-153. 7 McBride, A. S., D. M. Cline, et al. (2011). "Pediatric All-Terrain Vehicle Injuries Does Legislation Make a Dent?" Pediatric Emergency Care 27(2): 97-101. 8 Garland, S. (2010). Annual Report of ATV-Related Deaths and Injuries. Bethesda, MD, Consumer Product Safety Commission. 9 HCUP Clinical Classifications Software (CCS). Healthcare Cost and Utilization Project (HCUP). U.S. Agency for Healthcare Research and Quality, Rockville, MD. Available at http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Updated March 2012. (Accessed March 22, 2012). 10 HCUP Cost-to-Charge Ratio Files (CCR). Healthcare Cost and Utilization Project (HCUP). 2001-2009. U.S. Agency for Healthcare Research and Quality, Rockville, MD. Available at http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp. Updated August 2011. (Accessed March 22, 2012). |
Internet Citation: Statistical Brief #130. Healthcare Cost and Utilization Project (HCUP). April 2012. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb130.jsp. |
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