ORIGINAL C O N T R I B U T I O N tr~um~
A d u l t Minor TraumaPatients: Good Outcome in Small Hospitals From the Division of Emergency
Jerris R Hedges, MD, MS, FACEP *§
Medicine;* the Departments of
Harold R Osterud, MD t
Preventive Medicine and Public
Richard J Mullins, MD *§
Health,t and Surgery; .`+.and the Oregon Health Sciences University Trauma Program,§ Portland. Received for publication August 14, 1991. Revision received December 9, 1991. Accepted for publication December 30, 1991. Presented at the Society for Academic Emergency Medicine Annual Meeting in Minneapolis, .Minnesota, May 1990.
Study purpose: Todetermine if adult minor injury trauma admissions to small hospitals have a mean length of stay (LOS) and fatality rate similar to those of admissions to larger hospitals. Population: The first 10,000 Oregon hospital trauma discharges during 1987. Exclusions were age of 17 years or younger, an Injury Severity Score (ISS) of more than 10, transfer to another health care facility, and leaving against medical advice. There were 6,739 patients meeting study criteria. Methods: This study was a retrospective cohort analysis of a hospital discharge data base. Outcome measures were LOS for survivors and fatality rate. Predictor variables included patient age, hospital bed size, Level I or II trauma facility, designation, and county population. ;(2 and analysis of variance were used to test significance (P< .05). Results: Two of 72 hospitals were US-government-sponsored facilities and showed a longer mean LOS (21.3 and 16.4 vs 6.5 days for all other hospitals; P< .005). Mean LOS correlated positively with patient age, ISS, and hospital bed size (P< .0001). There were 136 deaths in this Iow-ISS population. The fatality rate was independent of hospital size and trauma facility designation. Age was significantly greater for patients who died versus survivors (76.2 vs 49.1 years; P< .0001). Conclusion: For minor trauma patients, smaller hospitals have a shorter mean LOS and a similar fatality rate when compared with larger hospitals and Level I and II trauma facilities. Despite a low ISS, admitted elderly patients have a higher death rate regardless of hospital size. [Hedges JR, Osterud HR, Mullins RJ: Adult minor trauma patients: Good outcome in small hospitals. Ann EmergMedApril 1992;21: 402-406.]
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MINOR TRAUMA
Hedges, Osterud & MuUins
INTRODUCTION A number of premises are fundamental to the concept of an effective statewide t r a u m a system. Minor t r a u m a patients can have a good outcome at all participating hospitals. Major t r a u m a patients are identified in the prehospital setting and in emergency departments of smaller hospitals with a low-level t r a u m a designation (other than Level I or II), and these patients receive timely triage to higher-level t r a u m a facilities. Major t r a u m a patients have better outcomes at the higher level (Level I and II) t r a u m a facilities. P r i o r studies of regional t r a u m a systems have focused on the third assumption. ~,2 Such studies have shown a reduction in preventable deaths when higher-level t r a u m a facilities are used appropriately. Studies also have addressed means of recognizing the seriously i n j u r e d patient who requires triage directly from the prehospital setting to a t r a u m a hospital. 3-5 However, there is little information regarding the outcome of patients who have sustained minor t r a u m a and were admitted to small and often r u r a l hospitals. We performed a retrospective statewide review of patients discharged with injury diagnosis codes from acute care hospitals. We sought to determine whether adult minor t r a u m a patients (defined as patients having an I n j u r y Severity Score [ISS] of 10 or less) fared as well in small hospitals as in other facilities using fatality rate and mean hospital length of stay (LOS) for survivors to characterize outcome.
MATERIALS AND METHODS This study was derived from a hospital discharge data base collected yearly and provided by the Oregon Association of Hospitals. Use of the data base required that the investigators not identify specific participating hospitals. The most current year of t r a u m a - r e l a t e d hospital discharges available (1987) was used for analysis. The d a t a base contained the first 10,000 patients discharged from Oregon hospitals in 1987 with discharge i n j u r y diagnosis codes. The data base included the patient's admission and discharge dates, birth date, diagnosis codes (using the International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9CM]),6 gender, and discharge disposition. The patient's age and LOS were calculated from the admission and b i r t h dates and from the admission and discharge dates, respectively. The computer p r o g r a m of MacKenzie et al 7 was used to convert the ICD-9CM diagnosis codes into Abbreviated I n j u r y Scale (AIS) scores, a The AIS is an ordinal scale ranging from 1 (minor injury) to 6 (nonsurvivable injury) based on anatomic regions. The p r o g r a m of MacKenzie et al also was used to convert the AIS scores into an ISS.7 Numerically, the ISS is the sum of the squares of the maximum AIS scores of the three most severely i n j u r e d body regions; the ISS has been shown to correlate with mortality and is commonly used to stratify the severity of injury. 9,10 The conversion program of MacKenzie et al has been shown to slightly
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underestimate ISS values compared with ISS values assigned by a nurse performing a chart review. 7 A p p r o v e d hospital bed size was obtained from the Oregon Association of Hospitals, and the population of the county served by each hospital was obtained from the 1987 Oregon state census. 11 Patients were included in the study if they had an ISS of 10 or less, were more than 17 years old, and had a hospital ICD-9CM discharge diagnosis in the range of 800 to 959. Patients were excluded from the study if they left the hospital against medical advice, had incomplete data (ie, no discharge date or discharge disposition code), or were transferred to another facility (ie, second hospital, skilled nursing facility, or rehabilitation facility). Following the a p p r o a c h of Morris et al, 12 patients with ICD-9CM diagnosis codes only for late effects (ICD-9CM codes 905 to 909) or foreign bodies (ICD-9CM codes 930 to 939) also were excluded from analysis. Seventy-two acute care hospitals were grouped according to a p p r o v e d acute care bed size and t r a u m a hospital designation: less than 100 beds (41), 100 to 200 beds (18), more than 200 beds and not designated as a t r a u m a hospital (nine), and more than 200 beds and designated as a t r a u m a hospital (four). A hospital was considered a t r a u m a hospital if it had been designated by the Oregon State Health Division as a Level I or II t r a u m a facility at the time of the study. All designated Level I or II t r a u m a hospitals had more than 200 beds. The Oregon State Health Division follows the American College of Surgeons criteria for designation of Level I and II t r a u m a hospitals. 13A4 LOS for patients discharged from the hospital and the fatality rate (ratio of patient deaths to patients discharged plus deaths) were the p r i m a r y study outcome measures. One-way analysis of variance was used to compare continuous variables. The Newman-Keuls test was used to compare group means. The Z2 test was used to analyze discontinuous data. F o r w a r d linear regression analysis was used to assess the dependence of LOS on the other variables. A significance level of P < .05 and a two-sided analysis were used throughout. Values are r e p o r t e d as mean + SEM.
RESULTS There were 6,603 adult minor t r a u m a patients who survived to hospital discharge and an additional 136 who died in the hospital during the study period. The distribution of cases among the hospital groups is shown (Tables 1 and 2). There was a significant difference in mean LOS of survivors between the four hospital groups (P < .0001). The smallest hospitals had the shortest mean LOS (Table 1). Although the larger hospitals (more than 200 beds) without t r a u m a hospital designation had the longest mean LOS, two unique hospitals contributed significantly to the mean LOS for this hospital group. These two US-government-sponsored hospitals had mean LOS values of 21.3 and 16.4 days. Excluding these two hospitals with unique referral and transfer restric•
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tions, the mean LOS for the larger hospitals without t r a u m a hospital designation was 5.7 days, which is essentially identical to the mean LOS for the t r a u m a hospitals. The overall mean LOS for the entire group of survivors was 5.5 days. The difference between median LOS for the groups paralleled the difference in mean LOS for the groups. The median LOS was one day for hospitals with less than 100 beds, two days for hospitals with less than 200 beds, three days for nontrauma hospitals with more than 200 beds (including the two US government hospitals), and two days for t r a u m a hospitals with more than 200 beds. Interestingly, the smaller hospitals had both a slightly higher mean ISS and patient age. Hence, the a p p a r e n t small LOS advantage seen at these hospitals cannot be attributed to a younger or less injured patient population. Overall, LOS correlated positively with patient age (F1,6600 = 163), ISS (F1,66o0 = 4 0 ) , and hospital bed size (F1,66o0 = 154) and correlated negatively with the population estimate of the county served by the hospital (F 1,6600 = 3 5 ) . Although these correlations were statistically significant, they accounted for only 6% of the regression variance. When the two US-government-sponsored hospitals were removed from the correlation analysis, LOS remained correlated positively with patient age (F1,634o = 184), ISS (F1,634o = 6 0 ) , and hospital bed size (F1,634o = 123). This correlation still accounted for only 6% of the regression variance, thus suggesting the importance of other factors such as underlying health, injury disability, and social support mechanisms in the determination of LOS. In the above LOS analysis, patients who died in the hospital were excluded. A separate analysis of those patients who died showed no correlation of LOS to death with hospital bed size or county population. Similarly, LOS to death was not significantly longer at n o n t r a u m a hospitals (7.5 + 0.8 days) than at Level I (5.6 + 2.4 days) or Level II t r a u m a hospitals (8.8 + 2.6 days). However, the mean age for those who died at the Level I t r a u m a hospitals was significantly lower (59.3 + 7.7 years) than at the n o n t r a u m a (77.7 + 1.4 years) and Level II hospitals (77.1 + 3.6 years; P < .01).
Although the larger hospitals numerically had a slightly smaller fatality rate (Table 2), the difference was not statistically significant (X2 = 2.3; 3 df). Mean age was significantly greater for patients who died versus those who were discharged home (76.2 + 16.3 vs 49.1 _+16.3 years; P < .0001). DISCUSSION
Our data suggest that for the outcomes studied (fatality rate and LOS for survivors), adult patients with minor t r a u m a (ISS of 10 or less) fare as well at small hospitals as at larger designated t r a u m a hospitals. These data support the concept of managing patients with m i n o r t r a u m a at small hospitals. This concept is complementary to earlier studies of regional t r a u m a systems that advocate transporting patients with m a j o r t r a u m a to designated t r a u m a hospitals. 1,2 This concept is relevant to those planning regional and statewide t r a u m a systems. As noted by others, minor t r a u m a patients account for the majority of t r a u m a admissions and costs. 15 Our data suggest that prehospital triage criteria that identify candidates for immediate transportation to higher-level t r a u m a hospitals should avoid overtriage of minor t r a u m a patients to these hospitals. 5 Such overtriage has the potential for over-burdening the higher-level t r a u m a hospitals with less severe t r a u m a and for taxing interhospital transfer programs. Care of minor t r a u m a patients at local small hospitals may be convenient for the patients and their families. When that care is within the treating physicians' scope of practice, our data suggest that care of the minor t r a u m a patient at small hospitals also is justified on the basis of measurable outcomes. We focused our analysis on t r a u m a patients with an ISS of 10 or less because these patients are often managed at small hospitals. F u r t h e r m o r e , these patients are unlikely to be t r a n s f e r r e d from the initial receiving hospital after their acute management. 16 F r o m the original sample of 10,000 patients, only 174 who met our other criteria were excluded because of an interhospital transfer. The possibility that these t r a u m a transfers may help keep fatality rates and LOS down at small hospitals requires further evaluation. I~
Table 1.
Comparison of hospital groups (survivors only) Hospital Group
LOS
> 200 Beds--trauma hospital (1,282survivors) > 200 Beds--nontrauma hospital (1,949su rvivo rs) 100-200 Beds (2,011 survivors) < 100 Beds (1,361 survivors)
ISS
Age (yr)
5.6 + 0.2*
3.7 + 0.t~
45.0 _+0.6II
7.3 + 0.3** 4.6+0.1' 4.0 + 0.1
3.8 + 0.1§ 4.3+0.1 4.2 + 0.1
49.4 + 0.5 50.6+0.5 50.6 + 0.6
* P< .01, statistically different from the hospital group with less than 100 beds.. When the US government hospitals were removed from the analysis, mean LOS for this group was 5.5 days. * P< .05,statistically different from the hospital group with less than 100 beds. P< .01,statistically different from the hospital groups with less than 100 and 100to 200 beds. ii p< .01, statistically different from all other hospital groups.
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Table 2.
Comparison of hospital group deaths Hospital Group > 200 Beds--trauma hospital (1,306 patients) > 200 Beds--nontrauma hospital (1,983 patients) 100-200 Beds (2,059 patients) < 100 Beds (1,391 patients)
No. of Patient Deaths*
No. of Patients Discharged
Fatality Rate (%)
24
1,282
1.84
34 48 30
1,949 2,011 1,361
1.71 2.33 2.16
*Deaths, number of patient deaths during hospitalization in each group; discharged, number of patients released home for the hospital group; fatality rate, ratio of the number of deaths to number of patients in each hospital group expressed as a percentage.
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MINOR TRAUMA Hedges, Osterud & Mullins
An essential aspect of this analysis is stratification of hospitals based on n u m b e r of acute care beds or bed size of hospitals. Bed size is a useful, but imprecise, method for categorizing hospital resources. Although hospitals in r u r a l communities are small, some of the smaller hospitals included in this analysis were in major metropolitan areas and in close proximity to Level I trauma hospitals. Therefore, not all small hospitals may have managed similar patients. To address this issue, we also correlated LOS for survivors with the population of the county served. When the US government hospitals are included, the multiple linear regression model for LOS shows a negative correlation with county population size, suggesting that the more r u r a l small hospitals may manage a different spectrum of patients. Furthermore, in 1987, the Oregon State Health Division had only begun to designate Level III and IV trauma facilities. A future analysis that incorporates stratification for both c u r r e n t level of trauma care resources and the population served should further clarify the delivery of minor trauma care in rural hospitals. There are other study limitations. We evaluated only patients who were admitted to the hospital. Deaths that occurred in the prehospital setting or in the ED would be excluded by this technique. However, analyzing only patients who survive to admission is appropriate when assessing the merits of inpatient care for patients with minor trauma at small hospitals compared with transport of all such patients to a Level I or II trauma hospital. We also excluded patients transferred to rehabilitation centers because smaller, more r u r a l hospitals may have more difficulty arranging for patient transfer to these facilities. Also, we were dependent on discharge diagnoses to assign the magnitude of injury. Because an AIS can be assigned only to confirmed diagnoses and because autopsies were not routine, some "minor" trauma fatalities may have had more serious injuries that were not recognized as such. This fact does not detract from the comparatively low fatality rates and shorter LOS seen at the smaller hospitals. This study did not account for prehospital care or physiological status on patient arrival. 10 We chose to use ISS to characterize the degree of injury. There is a difference in fatality risk between an elderly patient with a hip fracture and a young patient with a simple pneumothorax despite having the same ISS. Similarly, we did not characterize patients by pre-existing conditions that appear to affect outcome. 12,17 Therefore, there may be patients with specific injuries or pre-existing conditions who, despite having an ISS of 10 or less, may benefit from rapid transport to a Level I trauma hospital. Furthermore, some of the smaller hospitals contributed very few patients to the analysis; therefore, this analysis is relevant to the aggregate and not to a specific hospital. Nevertheless, we believe that our results provide a basis on which future studies that focus on patient groups with specific injuries or pre-existing conditions can be developed.
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Future studies also should address other differences between the populations served by smaller hospitals and u r b a n t r a u m a hospitals. The importance of insurance status, self-employment, and social support mechanisms on LOS in the communities served by the hospitals should be assessed. The extended LOS noted for the US government hospitals may be a reflection of the limited social support otherwise available for the i n j u r e d veteran population. This association requires further evaluation. Our data also highlight the increased fatality risk of elderly patients who sustain minor trauma. Morris et al found that 8.5% of all trauma deaths in California occurred in patients more than 55 years old with an ISS of less than 9 and that an additional 34.1% occurred in patients more than 55 years old with an ISS of 9 to 12.12 We found that 90% and 83%, respectively, of all minor trauma deaths occurred in patients more than 55 and 65 years old. Future studies should assess the potential for identifying the elderly minor trauma patient who exhibits risk factors for in-hospital mortality. This patient population may benefit from Level I trauma hospital care with aggressive monitoring and rehabilitation to optimize outcome when maintenance of a functional status is expected. CONCLUSION
Hospital LOS for surviving minor trauma patients was shorter in small hospitals than in larger hospitals in Oregon. The mortality rate was similar for the different sized hospitals and was influenced by patient age. Despite a low ISS, admitted elderly patients were at increased risk of death regardless of hospital admission site. Although the contribution of anatomic i n j u r y distribution and pre-existing medical conditions, and the role of selected patient transfers on the lower LOS and similar fatality rates in small hospitals need further investigation, our data support the concept of a statewide trauma system in which patients with minor injuries are managed primarily at local hospitals, independent of hospital size. •
The assistance of the Oregon Association of Hospitals is gratefully noted. Data entry was facilitated by Houtan Sabahi, MD. REFERENCES 1. Shaekford SR, Hollingworth-Fridlund P, Cooper 6F, et al: The effect of regionalization upon the quality of trauma care as assessed by c'oncurrent audit before and after institution of a trauma system: A preliminary report. J Trauma 1986;26:812-820. 2. Cales RH, Trunkey DD: Preventable trauma deaths: A review of trauma care systems development. JAMA 1985;254:1059-1063. 3. Hedges JR, Feero S, Moore B, et al: Comparison of prehospital triage instruments in a semirural population. J Emerg Med 1907;5:197-208. 4. Clemmer TP, Orme JF, Thomas F, et al: Prospective evaluation of the CRAMS scale for triaging major trauma. J Trauma 1985;25:188-191. •
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5. Knopp R, Yanagi A, Kallsen G, et al: Mechanism of injury and anatomic injury as criteria for prehospital trauma triage. Ann Emerg Mad 1988;17:895-902.
Address for reprints: Jerris R Hedges, MD, MS, FACEP, Oregon Health
6. International Classification of Diseases, 9th Revision, Clinical Modification. Washington, DC, US Department of Health and Human Services, Publication No. PHS 80-1260, 1980.
Jackson Park Drive, Portland, Oregon 97201-3098.
Sciences University, Division of Emergency Medicine, 3181 Southwest Sam
7. MacKenzie EJ, Steinwachs DM, Shankar BS: Classifying trauma severity based on hospital discharge diagnosis: Validation of an ICD-9-CM to AIS-85 conversion table. Med Care 1989;27:412-422. 8. Committee on Injury Scaling. The Abbreviated Injury Scale (1985Revision).Arlington Heights, Illinois, American Association of Automotive Medicine, 1985. 9. Baker SP, O'Neill B: The Injury Severity Score: An update. J Trauma 1976;16:882-885. 19. Murphy J6, Cayten CG, Stahl WM: Controlling for the severity of injuries in emergency medicine research. Am J Emerg Med 1990;8:484-491. 11. Center for Population Research and Census: Population Estimates for Oregon, 1980--1990. Portland, Oregon, Portland State University Press, 1991, p 12. 12. Morris JA Jr, MacKenzie EJ, Edelstein SL: The effect of preexisting conditions on mortality in trauma patients. JAMA 1990;263:1942-1946. 13.America n College of Surgeons, Committee on Trauma: Hospital and Prehospital Resourcesfor Optimal Care of the Injured Patient: Appendices A Through J. Chicago, ACS, 1987. 14. Emergency cardiac and trauma care in rural areas, in: Rural Emergency Medical Services. Washington, DC, US Congress, Office of Technology Assessment, November, 1989, p 48-51. 15. MacKenzie EJ, Morris JA, Smith GS, et ah Acute hospital costs of trauma in the United States: Implications for regionalized systems of care. J Trauma 1990;30:1096-1101. 16. MacKenzie EJ, Steinwachs DM, Ramzy Ah Evaluating performance of statewide ragionalized systems of trauma care. J Trauma 1999;30:681-688. 17. MacKenzie EJ, Morris JA, Edelstein SL: Effect of preexisting disease on length of hospital stay in trauma patients. J Trauma 1989;29:757-765.
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77
A d u l t Minor TraumaPatients: Good Outcome in Small Hospitals From the Division of Emergency
Jerris R Hedges, MD, MS, FACEP *§
Medicine;* the Departments of
Harold R Osterud, MD t
Preventive Medicine and Public
Richard J Mullins, MD *§
Health,t and Surgery; .`+.and the Oregon Health Sciences University Trauma Program,§ Portland. Received for publication August 14, 1991. Revision received December 9, 1991. Accepted for publication December 30, 1991. Presented at the Society for Academic Emergency Medicine Annual Meeting in Minneapolis, .Minnesota, May 1990.
Study purpose: Todetermine if adult minor injury trauma admissions to small hospitals have a mean length of stay (LOS) and fatality rate similar to those of admissions to larger hospitals. Population: The first 10,000 Oregon hospital trauma discharges during 1987. Exclusions were age of 17 years or younger, an Injury Severity Score (ISS) of more than 10, transfer to another health care facility, and leaving against medical advice. There were 6,739 patients meeting study criteria. Methods: This study was a retrospective cohort analysis of a hospital discharge data base. Outcome measures were LOS for survivors and fatality rate. Predictor variables included patient age, hospital bed size, Level I or II trauma facility, designation, and county population. ;(2 and analysis of variance were used to test significance (P< .05). Results: Two of 72 hospitals were US-government-sponsored facilities and showed a longer mean LOS (21.3 and 16.4 vs 6.5 days for all other hospitals; P< .005). Mean LOS correlated positively with patient age, ISS, and hospital bed size (P< .0001). There were 136 deaths in this Iow-ISS population. The fatality rate was independent of hospital size and trauma facility designation. Age was significantly greater for patients who died versus survivors (76.2 vs 49.1 years; P< .0001). Conclusion: For minor trauma patients, smaller hospitals have a shorter mean LOS and a similar fatality rate when compared with larger hospitals and Level I and II trauma facilities. Despite a low ISS, admitted elderly patients have a higher death rate regardless of hospital size. [Hedges JR, Osterud HR, Mullins RJ: Adult minor trauma patients: Good outcome in small hospitals. Ann EmergMedApril 1992;21: 402-406.]
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MINOR TRAUMA
Hedges, Osterud & MuUins
INTRODUCTION A number of premises are fundamental to the concept of an effective statewide t r a u m a system. Minor t r a u m a patients can have a good outcome at all participating hospitals. Major t r a u m a patients are identified in the prehospital setting and in emergency departments of smaller hospitals with a low-level t r a u m a designation (other than Level I or II), and these patients receive timely triage to higher-level t r a u m a facilities. Major t r a u m a patients have better outcomes at the higher level (Level I and II) t r a u m a facilities. P r i o r studies of regional t r a u m a systems have focused on the third assumption. ~,2 Such studies have shown a reduction in preventable deaths when higher-level t r a u m a facilities are used appropriately. Studies also have addressed means of recognizing the seriously i n j u r e d patient who requires triage directly from the prehospital setting to a t r a u m a hospital. 3-5 However, there is little information regarding the outcome of patients who have sustained minor t r a u m a and were admitted to small and often r u r a l hospitals. We performed a retrospective statewide review of patients discharged with injury diagnosis codes from acute care hospitals. We sought to determine whether adult minor t r a u m a patients (defined as patients having an I n j u r y Severity Score [ISS] of 10 or less) fared as well in small hospitals as in other facilities using fatality rate and mean hospital length of stay (LOS) for survivors to characterize outcome.
MATERIALS AND METHODS This study was derived from a hospital discharge data base collected yearly and provided by the Oregon Association of Hospitals. Use of the data base required that the investigators not identify specific participating hospitals. The most current year of t r a u m a - r e l a t e d hospital discharges available (1987) was used for analysis. The d a t a base contained the first 10,000 patients discharged from Oregon hospitals in 1987 with discharge i n j u r y diagnosis codes. The data base included the patient's admission and discharge dates, birth date, diagnosis codes (using the International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9CM]),6 gender, and discharge disposition. The patient's age and LOS were calculated from the admission and b i r t h dates and from the admission and discharge dates, respectively. The computer p r o g r a m of MacKenzie et al 7 was used to convert the ICD-9CM diagnosis codes into Abbreviated I n j u r y Scale (AIS) scores, a The AIS is an ordinal scale ranging from 1 (minor injury) to 6 (nonsurvivable injury) based on anatomic regions. The p r o g r a m of MacKenzie et al also was used to convert the AIS scores into an ISS.7 Numerically, the ISS is the sum of the squares of the maximum AIS scores of the three most severely i n j u r e d body regions; the ISS has been shown to correlate with mortality and is commonly used to stratify the severity of injury. 9,10 The conversion program of MacKenzie et al has been shown to slightly
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underestimate ISS values compared with ISS values assigned by a nurse performing a chart review. 7 A p p r o v e d hospital bed size was obtained from the Oregon Association of Hospitals, and the population of the county served by each hospital was obtained from the 1987 Oregon state census. 11 Patients were included in the study if they had an ISS of 10 or less, were more than 17 years old, and had a hospital ICD-9CM discharge diagnosis in the range of 800 to 959. Patients were excluded from the study if they left the hospital against medical advice, had incomplete data (ie, no discharge date or discharge disposition code), or were transferred to another facility (ie, second hospital, skilled nursing facility, or rehabilitation facility). Following the a p p r o a c h of Morris et al, 12 patients with ICD-9CM diagnosis codes only for late effects (ICD-9CM codes 905 to 909) or foreign bodies (ICD-9CM codes 930 to 939) also were excluded from analysis. Seventy-two acute care hospitals were grouped according to a p p r o v e d acute care bed size and t r a u m a hospital designation: less than 100 beds (41), 100 to 200 beds (18), more than 200 beds and not designated as a t r a u m a hospital (nine), and more than 200 beds and designated as a t r a u m a hospital (four). A hospital was considered a t r a u m a hospital if it had been designated by the Oregon State Health Division as a Level I or II t r a u m a facility at the time of the study. All designated Level I or II t r a u m a hospitals had more than 200 beds. The Oregon State Health Division follows the American College of Surgeons criteria for designation of Level I and II t r a u m a hospitals. 13A4 LOS for patients discharged from the hospital and the fatality rate (ratio of patient deaths to patients discharged plus deaths) were the p r i m a r y study outcome measures. One-way analysis of variance was used to compare continuous variables. The Newman-Keuls test was used to compare group means. The Z2 test was used to analyze discontinuous data. F o r w a r d linear regression analysis was used to assess the dependence of LOS on the other variables. A significance level of P < .05 and a two-sided analysis were used throughout. Values are r e p o r t e d as mean + SEM.
RESULTS There were 6,603 adult minor t r a u m a patients who survived to hospital discharge and an additional 136 who died in the hospital during the study period. The distribution of cases among the hospital groups is shown (Tables 1 and 2). There was a significant difference in mean LOS of survivors between the four hospital groups (P < .0001). The smallest hospitals had the shortest mean LOS (Table 1). Although the larger hospitals (more than 200 beds) without t r a u m a hospital designation had the longest mean LOS, two unique hospitals contributed significantly to the mean LOS for this hospital group. These two US-government-sponsored hospitals had mean LOS values of 21.3 and 16.4 days. Excluding these two hospitals with unique referral and transfer restric•
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tions, the mean LOS for the larger hospitals without t r a u m a hospital designation was 5.7 days, which is essentially identical to the mean LOS for the t r a u m a hospitals. The overall mean LOS for the entire group of survivors was 5.5 days. The difference between median LOS for the groups paralleled the difference in mean LOS for the groups. The median LOS was one day for hospitals with less than 100 beds, two days for hospitals with less than 200 beds, three days for nontrauma hospitals with more than 200 beds (including the two US government hospitals), and two days for t r a u m a hospitals with more than 200 beds. Interestingly, the smaller hospitals had both a slightly higher mean ISS and patient age. Hence, the a p p a r e n t small LOS advantage seen at these hospitals cannot be attributed to a younger or less injured patient population. Overall, LOS correlated positively with patient age (F1,6600 = 163), ISS (F1,66o0 = 4 0 ) , and hospital bed size (F1,66o0 = 154) and correlated negatively with the population estimate of the county served by the hospital (F 1,6600 = 3 5 ) . Although these correlations were statistically significant, they accounted for only 6% of the regression variance. When the two US-government-sponsored hospitals were removed from the correlation analysis, LOS remained correlated positively with patient age (F1,634o = 184), ISS (F1,634o = 6 0 ) , and hospital bed size (F1,634o = 123). This correlation still accounted for only 6% of the regression variance, thus suggesting the importance of other factors such as underlying health, injury disability, and social support mechanisms in the determination of LOS. In the above LOS analysis, patients who died in the hospital were excluded. A separate analysis of those patients who died showed no correlation of LOS to death with hospital bed size or county population. Similarly, LOS to death was not significantly longer at n o n t r a u m a hospitals (7.5 + 0.8 days) than at Level I (5.6 + 2.4 days) or Level II t r a u m a hospitals (8.8 + 2.6 days). However, the mean age for those who died at the Level I t r a u m a hospitals was significantly lower (59.3 + 7.7 years) than at the n o n t r a u m a (77.7 + 1.4 years) and Level II hospitals (77.1 + 3.6 years; P < .01).
Although the larger hospitals numerically had a slightly smaller fatality rate (Table 2), the difference was not statistically significant (X2 = 2.3; 3 df). Mean age was significantly greater for patients who died versus those who were discharged home (76.2 + 16.3 vs 49.1 _+16.3 years; P < .0001). DISCUSSION
Our data suggest that for the outcomes studied (fatality rate and LOS for survivors), adult patients with minor t r a u m a (ISS of 10 or less) fare as well at small hospitals as at larger designated t r a u m a hospitals. These data support the concept of managing patients with m i n o r t r a u m a at small hospitals. This concept is complementary to earlier studies of regional t r a u m a systems that advocate transporting patients with m a j o r t r a u m a to designated t r a u m a hospitals. 1,2 This concept is relevant to those planning regional and statewide t r a u m a systems. As noted by others, minor t r a u m a patients account for the majority of t r a u m a admissions and costs. 15 Our data suggest that prehospital triage criteria that identify candidates for immediate transportation to higher-level t r a u m a hospitals should avoid overtriage of minor t r a u m a patients to these hospitals. 5 Such overtriage has the potential for over-burdening the higher-level t r a u m a hospitals with less severe t r a u m a and for taxing interhospital transfer programs. Care of minor t r a u m a patients at local small hospitals may be convenient for the patients and their families. When that care is within the treating physicians' scope of practice, our data suggest that care of the minor t r a u m a patient at small hospitals also is justified on the basis of measurable outcomes. We focused our analysis on t r a u m a patients with an ISS of 10 or less because these patients are often managed at small hospitals. F u r t h e r m o r e , these patients are unlikely to be t r a n s f e r r e d from the initial receiving hospital after their acute management. 16 F r o m the original sample of 10,000 patients, only 174 who met our other criteria were excluded because of an interhospital transfer. The possibility that these t r a u m a transfers may help keep fatality rates and LOS down at small hospitals requires further evaluation. I~
Table 1.
Comparison of hospital groups (survivors only) Hospital Group
LOS
> 200 Beds--trauma hospital (1,282survivors) > 200 Beds--nontrauma hospital (1,949su rvivo rs) 100-200 Beds (2,011 survivors) < 100 Beds (1,361 survivors)
ISS
Age (yr)
5.6 + 0.2*
3.7 + 0.t~
45.0 _+0.6II
7.3 + 0.3** 4.6+0.1' 4.0 + 0.1
3.8 + 0.1§ 4.3+0.1 4.2 + 0.1
49.4 + 0.5 50.6+0.5 50.6 + 0.6
* P< .01, statistically different from the hospital group with less than 100 beds.. When the US government hospitals were removed from the analysis, mean LOS for this group was 5.5 days. * P< .05,statistically different from the hospital group with less than 100 beds. P< .01,statistically different from the hospital groups with less than 100 and 100to 200 beds. ii p< .01, statistically different from all other hospital groups.
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Table 2.
Comparison of hospital group deaths Hospital Group > 200 Beds--trauma hospital (1,306 patients) > 200 Beds--nontrauma hospital (1,983 patients) 100-200 Beds (2,059 patients) < 100 Beds (1,391 patients)
No. of Patient Deaths*
No. of Patients Discharged
Fatality Rate (%)
24
1,282
1.84
34 48 30
1,949 2,011 1,361
1.71 2.33 2.16
*Deaths, number of patient deaths during hospitalization in each group; discharged, number of patients released home for the hospital group; fatality rate, ratio of the number of deaths to number of patients in each hospital group expressed as a percentage.
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MINOR TRAUMA Hedges, Osterud & Mullins
An essential aspect of this analysis is stratification of hospitals based on n u m b e r of acute care beds or bed size of hospitals. Bed size is a useful, but imprecise, method for categorizing hospital resources. Although hospitals in r u r a l communities are small, some of the smaller hospitals included in this analysis were in major metropolitan areas and in close proximity to Level I trauma hospitals. Therefore, not all small hospitals may have managed similar patients. To address this issue, we also correlated LOS for survivors with the population of the county served. When the US government hospitals are included, the multiple linear regression model for LOS shows a negative correlation with county population size, suggesting that the more r u r a l small hospitals may manage a different spectrum of patients. Furthermore, in 1987, the Oregon State Health Division had only begun to designate Level III and IV trauma facilities. A future analysis that incorporates stratification for both c u r r e n t level of trauma care resources and the population served should further clarify the delivery of minor trauma care in rural hospitals. There are other study limitations. We evaluated only patients who were admitted to the hospital. Deaths that occurred in the prehospital setting or in the ED would be excluded by this technique. However, analyzing only patients who survive to admission is appropriate when assessing the merits of inpatient care for patients with minor trauma at small hospitals compared with transport of all such patients to a Level I or II trauma hospital. We also excluded patients transferred to rehabilitation centers because smaller, more r u r a l hospitals may have more difficulty arranging for patient transfer to these facilities. Also, we were dependent on discharge diagnoses to assign the magnitude of injury. Because an AIS can be assigned only to confirmed diagnoses and because autopsies were not routine, some "minor" trauma fatalities may have had more serious injuries that were not recognized as such. This fact does not detract from the comparatively low fatality rates and shorter LOS seen at the smaller hospitals. This study did not account for prehospital care or physiological status on patient arrival. 10 We chose to use ISS to characterize the degree of injury. There is a difference in fatality risk between an elderly patient with a hip fracture and a young patient with a simple pneumothorax despite having the same ISS. Similarly, we did not characterize patients by pre-existing conditions that appear to affect outcome. 12,17 Therefore, there may be patients with specific injuries or pre-existing conditions who, despite having an ISS of 10 or less, may benefit from rapid transport to a Level I trauma hospital. Furthermore, some of the smaller hospitals contributed very few patients to the analysis; therefore, this analysis is relevant to the aggregate and not to a specific hospital. Nevertheless, we believe that our results provide a basis on which future studies that focus on patient groups with specific injuries or pre-existing conditions can be developed.
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Future studies also should address other differences between the populations served by smaller hospitals and u r b a n t r a u m a hospitals. The importance of insurance status, self-employment, and social support mechanisms on LOS in the communities served by the hospitals should be assessed. The extended LOS noted for the US government hospitals may be a reflection of the limited social support otherwise available for the i n j u r e d veteran population. This association requires further evaluation. Our data also highlight the increased fatality risk of elderly patients who sustain minor trauma. Morris et al found that 8.5% of all trauma deaths in California occurred in patients more than 55 years old with an ISS of less than 9 and that an additional 34.1% occurred in patients more than 55 years old with an ISS of 9 to 12.12 We found that 90% and 83%, respectively, of all minor trauma deaths occurred in patients more than 55 and 65 years old. Future studies should assess the potential for identifying the elderly minor trauma patient who exhibits risk factors for in-hospital mortality. This patient population may benefit from Level I trauma hospital care with aggressive monitoring and rehabilitation to optimize outcome when maintenance of a functional status is expected. CONCLUSION
Hospital LOS for surviving minor trauma patients was shorter in small hospitals than in larger hospitals in Oregon. The mortality rate was similar for the different sized hospitals and was influenced by patient age. Despite a low ISS, admitted elderly patients were at increased risk of death regardless of hospital admission site. Although the contribution of anatomic i n j u r y distribution and pre-existing medical conditions, and the role of selected patient transfers on the lower LOS and similar fatality rates in small hospitals need further investigation, our data support the concept of a statewide trauma system in which patients with minor injuries are managed primarily at local hospitals, independent of hospital size. •
The assistance of the Oregon Association of Hospitals is gratefully noted. Data entry was facilitated by Houtan Sabahi, MD. REFERENCES 1. Shaekford SR, Hollingworth-Fridlund P, Cooper 6F, et al: The effect of regionalization upon the quality of trauma care as assessed by c'oncurrent audit before and after institution of a trauma system: A preliminary report. J Trauma 1986;26:812-820. 2. Cales RH, Trunkey DD: Preventable trauma deaths: A review of trauma care systems development. JAMA 1985;254:1059-1063. 3. Hedges JR, Feero S, Moore B, et al: Comparison of prehospital triage instruments in a semirural population. J Emerg Med 1907;5:197-208. 4. Clemmer TP, Orme JF, Thomas F, et al: Prospective evaluation of the CRAMS scale for triaging major trauma. J Trauma 1985;25:188-191. •
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5. Knopp R, Yanagi A, Kallsen G, et al: Mechanism of injury and anatomic injury as criteria for prehospital trauma triage. Ann Emerg Mad 1988;17:895-902.
Address for reprints: Jerris R Hedges, MD, MS, FACEP, Oregon Health
6. International Classification of Diseases, 9th Revision, Clinical Modification. Washington, DC, US Department of Health and Human Services, Publication No. PHS 80-1260, 1980.
Jackson Park Drive, Portland, Oregon 97201-3098.
Sciences University, Division of Emergency Medicine, 3181 Southwest Sam
7. MacKenzie EJ, Steinwachs DM, Shankar BS: Classifying trauma severity based on hospital discharge diagnosis: Validation of an ICD-9-CM to AIS-85 conversion table. Med Care 1989;27:412-422. 8. Committee on Injury Scaling. The Abbreviated Injury Scale (1985Revision).Arlington Heights, Illinois, American Association of Automotive Medicine, 1985. 9. Baker SP, O'Neill B: The Injury Severity Score: An update. J Trauma 1976;16:882-885. 19. Murphy J6, Cayten CG, Stahl WM: Controlling for the severity of injuries in emergency medicine research. Am J Emerg Med 1990;8:484-491. 11. Center for Population Research and Census: Population Estimates for Oregon, 1980--1990. Portland, Oregon, Portland State University Press, 1991, p 12. 12. Morris JA Jr, MacKenzie EJ, Edelstein SL: The effect of preexisting conditions on mortality in trauma patients. JAMA 1990;263:1942-1946. 13.America n College of Surgeons, Committee on Trauma: Hospital and Prehospital Resourcesfor Optimal Care of the Injured Patient: Appendices A Through J. Chicago, ACS, 1987. 14. Emergency cardiac and trauma care in rural areas, in: Rural Emergency Medical Services. Washington, DC, US Congress, Office of Technology Assessment, November, 1989, p 48-51. 15. MacKenzie EJ, Morris JA, Smith GS, et ah Acute hospital costs of trauma in the United States: Implications for regionalized systems of care. J Trauma 1990;30:1096-1101. 16. MacKenzie EJ, Steinwachs DM, Ramzy Ah Evaluating performance of statewide ragionalized systems of trauma care. J Trauma 1999;30:681-688. 17. MacKenzie EJ, Morris JA, Edelstein SL: Effect of preexisting disease on length of hospital stay in trauma patients. J Trauma 1989;29:757-765.
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