Home Does the Halo Effect for Level 1 Trauma Centers Apply to High-Acuity Nonsurgical Admissions?
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Does the Halo Effect for Level 1 Trauma Centers Apply to High-Acuity Nonsurgical Admissions?

  • Ann E. Hwalek , Anai N. Kothari , Elizabeth H. Wood , Barbara A. Blanco , McKenzie Brown , Timothy P. Plackett , Paul C. Kuo and Joseph Posluszny
Published/Copyright: May 1, 2020

Abstract

Context

The halo effect describes the improved surgical outcomes at trauma centers for nontrauma conditions.

Objective

To determine whether level 1 trauma centers have improved inpatient mortality for common but high-acuity nonsurgical diagnoses (eg, acute myocardial infarction [AMI], congestive heart failure [CHF], and pneumonia [PNA]) compared with non­–level 1 trauma centers.

Methods

The authors conducted a population-based, retrospective cohort study analyzing data from the Healthcare Cost and Utilization Project State Inpatient Database and the American Hospital Association Annual Survey Database. Patients who were admitted with AMI, CHF, and PNA between 2006-2011 in Florida and California were included. Level 1 trauma centers were matched to non–level 1 trauma centers using propensity scoring. The primary outcome was risk-adjusted inpatient mortality for each diagnosis (AMI, CHF, or PNA).

Results

Of the 190,474 patients who were hospitalized for AMI, CHF, or PNA, 94,037 patients (49%) underwent treatment at level 1 trauma centers. The inpatient mortality rates at level 1 trauma centers vs non–level 1 trauma centers for patients with AMI was 8.10% vs 8.40%, respectively (P=.73); for patients with CHF, 2.26% vs 2.71% (P=.90); and for patients with PNA, 2.30% vs 2.70% (P=.25).

Conclusion

Level 1 trauma center designation was not associated with improved mortality for high-acuity, nonsurgical medical conditions in this study.

Trauma centers have improved outcomes for moderate to severely injured patients when compared with non–trauma centers.1 Trauma centers in each state are categorized by the American College of Surgeons and by their particular state into levels of care based on a variety of requirements, such as their commitment, admission volume, physician coverage, hospital infrastructure and services, data collection, and quality improvement programs.1

The various requirements for trauma centers often overlap with those for the provision of care for other surgical conditions. The “halo effect” implies that the infrastructure associated with trauma center designation will also improve outcomes for other surgical diagnoses. This effect has been best demonstrated in patients with a ruptured abdominal aortic aneurysm (AAA), for whom the trauma center has been associated with improved mortality.3,4 Decreased mortality at trauma centers has been attributed to well-developed surgical systems and overall enhanced surgical expertise related to the higher volumes.5-7

The halo effect of trauma centers has not been shown to benefit patients who require less severe surgical procedures, such as appendectomy,8 colectomy for diverticulitis,9 and other emergency general surgery procedures.10,11 Most likely, given the more frequent presentation and limited resource needs associated with these less severe surgical diagnoses, the expanded resources and experience level of trauma center staff are unnecessary. Since the proposal of the halo effect, studies3,4,8-10 have only investigated its applicability to surgical diagnoses. It is unclear whether the infrastructure of a trauma center benefits patients with high-acuity, nonsurgical diagnoses.

Therefore, the objective of the present study was to compare mortality outcomes for common, but high-acuity, nonsurgical diagnoses of acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia (PNA) at hospitals with a level 1 trauma center with equivalent hospitals without level 1 trauma centers.12,13

Methods

A retrospective analysis was performed using combined patient- and hospital-level data from the Health Care and Utilization Project State Inpatient Database and the American Hospital Association Annual Survey Database for Florida and California from January 1, 2007, to December 31, 2011. The method for combining the databases has been previously described.14-16 This study was deemed exempt by the Loyola University Medical Center institutional review board because the publicly available records lacked patient identifiers.

Patients with AMI, CHF, and PNA on admission (index diagnosis-related group codes of 121:122:123, 127, and 89:90:91, respectively) were included for analysis, regardless of admitting service from the database. The patients were then linked to the hospital identifier for level 1 trauma centers, which is designated in the Trauma Information Exchange Program database.17 Patients younger than 18 years were excluded from the study.

The primary outcome was risk-adjusted inpatient mortality for each diagnosis (AMI, CHF, or PNA). Secondary outcomes included length of stay and trend in mortality during the 5-year study period.

Bivariate statistical testing for patient characteristics was conducted with a 1-way analysis of variance. Level 1 trauma centers were matched to all other hospitals (both non–level 1 trauma centers and non–trauma centers) using a modified hospital quality summary score that included the following: Joint Commission accreditation; high case-mix index; hospital admissions (percentage in highest quartile); membership to Council of Teaching Hospitals; physician-to-patient ratio; nurse-to-bed ratio; and resident-to-bed ratio from the Florida and California datasets.18 Multivariate analysis was conducted using mixed-effects methods (Table 1). Statistical analysis was performed with Stata/MP Version 13 (64-bit). Statistical significance was set at P<.05.

Table 1.

Baseline Characteristics of Patients at Level 1 and Non–Level 1 Trauma Centers

CharacteristicsOverall, No. (%)Level 1 trauma centers, No. (%)Non–level 1 trauma centers, No. (%)P value
Patients, n190,47494,037 (49)96,437 (51) 
Age, y, mean (SD)69.6 (16.7)69.8 (16)69 (16.6).001
Sex (% female)95,208 (49)46,732 (50)48,476 (52).051
Race/ethnicity 
 White108,565 (56)53,656 (57)54,909 (58) 
 African American25,589 (13)13,869 (15)11,720 (13)<.001
 Hispanic40,527 (21)18,615 (20)21,912 (23) 
 Other10,826 (6)5886 (6)4940 (5) 
Insurance type 
 Medicare127,513 (66)62,970 (67)64,543 (69) 
 Medicaid23,083 (12)11,091 (12)11,992 (13)<.001
 Private27,302 (14)13,348 (14)13,954 (15) 
 Other 
Alcohol abuse6620 (3)3571 (4)3049 (3)<.001
Anemias55,863 (29)27,205 (29)28,658 (31)<.001
Rheumatoid arthritis5881 (3)2891 (3)2990 (3).742
Chronic blood loss anemia1570 (0.8)759 (0.8)811 (0.9).414
Chronic pulmonary disease66,092 (34)31,664 (34)36,428 (39)<.001
Coagulopathy9875 (5)4895 (5)4980 (5).684
Depression15,140 (8)7856 (8)7554 (8).059
Diabetes, uncomplicated53,568 (28)24,373 (26)29,195 (31)<.001
Diabetes, with complications20,787 (11)10,981 (12)9806 (10)<.001
Drug abuse6371 (3)3656 (4)2715 (3)<.001
Hypertension125,643 (66)62,684 (67)62,959 (67)<.001
Hypothyroidism28,073 (15)13,771 (15)14,302 (15).252
Liver disease6422 (3)3556 (4)2866 (3)<.001
Lymphoma2549 (1)1367 (1)1182 (1)<.001
Fluid and electrolyte disorder52,911 (28)25,903 (28)26,981 (29).049
Metastatic cancer3931 (2)2079 (2)1852 (2)<.001
Neurologic disorder16,067 (8)8052 (9)8015 (9).048
Obesity25,008 (13)11,948 (13)13,060 (14)<.001
Paralysis4809 (3)2349 (3)2460 (3).462
Peripheral vascular disease18,864 (10)10,240 (11)8624 (9)<.001
Psychoses7562 (4)3926 (4)3636 (4)<.001
Pulmonary circulation disorders3571 (2)1955 (2)1616 (2)<.001
Renal failure58,115 (31)28,324 (30)29,791 (32)<.001
Solid tumor without metastasis4715 (2)2516 (3)2199 (2)<.001
Valvular disease5452 (3)2963 (3)2489 (3)<.001
Weight loss7184 (4)3252 (3)3932 (4)<.001
Charleston comorbidity index 
 <5161,015 (85)79,312 (84)81,703 (87)
 5-1029,927 (16)14,596 (16)15,331 (16).033
 >10233 (0.1)112 (0.1)121 (0.1)

Results

During the study period (2007-2011), 190,474 patients were hospitalized with AMI, CHF, and PNA at the selected 48 hospitals in Florida and California. Of these patients, 94,037 (49%) were treated at a hospital with a level 1 trauma center. The patients were mostly men (51%), white (56%), used Medicare as a payer source (66%), and had a mean age of 69 years (Table 1). The difference in comorbidities between the patients treated at the level 1 trauma centers compared with the non–level 1 trauma centers was statistically significant. An increased number of patients at the level 1 trauma center were treated for the following: alcohol abuse, diabetes, drug abuse, liver disease, lymphoma, metastatic cancer, neurologic disease, peripheral vascular disease, psychoses, pulmonary circulation disorders, solid tumor without metastasis, and valvular disease.

Fifteen of the hospitals were located in Florida and 33 in California. Twenty-four hospitals were level 1 trauma centers, with 10 in Florida and 14 in California. No significant differences were found between groups following a 1:1 propensity score matching based on the modified hospital summary score (Table 2).

Table 2.

Modified Hospital Quality Summary Score Factors for Propensity Score Matching

Modified hospital quality summary score factorsLevel 1 trauma centers, (n=24)Non–level 1 trauma centers, (n=24)P Value
UnmatchedMatched
Joint Commission accreditation24 (100%)24 (100%)
High case-mix index12.5 (52%)11.5 (48%).054.783
Hospital admissions20.4 (84%)18.2 (76%)<.001.490
Member of council on teaching hospitals4.8 (20%)6.7 (28%)<.001.518
Physician-to-patient ratio4444<.001.99
Nurse-to-bed ratio8080<.001.99
Resident-to-bed ratio4448.032.782

Abbreviations: AMI, acute myocardial infarction; CHF, congestive heart failure; PNA, pneumonia.

After risk-adjustment for demographics and comorbidities, inpatient mortality did not differ for patients admitted to level 1 trauma centers vs non–level 1 trauma centers for patients with AMI, 8.10% vs 8.40%, respectively (P=.73), patients with CHF, 2.26% vs 2.71% (P=.90), or patients with PNA, 2.30% vs 2.70% (P=.25; Table 3). The mortality rates during the study period at level 1 trauma centers and non–level 1 trauma centers trended toward an increase for patients with AMI (Figure 1A) and decrease for patients with PNA (Figure 1B). While the mortality rates for CHF trended down at non–level 1 trauma centers, the mortality rates increased at level 1 trauma centers during the 5-year period (Figure 1C). For patients with AMI, CHF, and PNA, the length of stays was shorter at level 1 trauma centers but was only significantly shorter for patients with AMI (P<.01; Table 3).

Figure 1. Annual mortality rates for level 1 trauma centers compared with non–level 1 trauma centers for (A) acute myocardial infarction, (B) congestive heart failure, and (C) pneumonia.
Figure 1.

Annual mortality rates for level 1 trauma centers compared with non–level 1 trauma centers for (A) acute myocardial infarction, (B) congestive heart failure, and (C) pneumonia.

Table 3.

Risk-Adjusted Mortality Rate and Length of Stay Outcomes at Level 1 Trauma Centers Compared With Non–Level 1 Trauma Centers

High-acuity nonsurgical diagnosesLevel 1 trauma centers, %Non–level 1 trauma centers, %P value
Risk-adjusted mortality rate, %
 AMI8.108.40.73
 CHF2.622.71.80
 PNA2.302.70.25
Length of stay, d mean (SD)
 AMI4.18 (4.53)4.43 (4.42)<.01
 CHF4.31 (45.6)4.66 (4.0).11
 PNA3.93 (61.7)4.49 (34.0).12

Abbreviations: AMI, acute myocardial infarction; CHF, congestive heart failure; PNA, pneumonia.

Discussion

In this study, a level 1 trauma center designation was not associated with improved mortality for high-acuity, nonsurgical diagnoses of AMI, CHF, or PNA. This study's finding is in line with other studies7-10 that have not shown improved morbidity or mortality for emergency general surgery procedures in trauma centers. Most likely, the significant infrastructure and experience of a trauma center are unnecessary for more routine medical and surgical diagnoses. The halo effect was demonstrated for ruptured AAA repairs during an era of open repair.2 The benefit may reflect similarities between the requirements for open repair of a ruptured AAA and the management of severe trauma. Both require an immediately available operating room, available surgical team, and a massive resuscitation of blood products. However, a 2016 study19 found no correlation between positive outcomes for pancreaticoduodenectomy, colectomy, AAA repair, or esophagectomy performed within the hospital system. This study expands the list of diagnoses that do not show a halo effect to include AMI, CHF, and PNA.

Rather than infrastructure or resources, trauma centers may benefit most from experience and expertise in resuscitation from hemorrhage. Most major hemorrhage resuscitation that occurs outside the operating room is handled by trauma and surgical intensive care units. Patients may also benefit from trauma teams that manage major nontraumatic hemorrhage.20 The benefit of hemorrhage resuscitation from the trauma team has not yet been explored but may be of value. Like many complex surgeries,21-23 volume may be a surrogate for experience and may be associated with improved outcomes. In this sense, the number of complex resuscitations a surgical team completes may correlate with the outcome and should prompt further study.

Protocols and cultural changes that correspond to best practice patterns may be of greater benefit to patients than increased hospital resources. Between 2006 and 2008, the Centers for Medicaid and Medicare Services instituted outcome tracking and best practice measures for cases of AMI, CHF, and PNA, with financial penalties starting in 2012 for poor performance.24 Most likely, hospitals of any size or resource level could institute new practices that allow for improved mortality and uniformity in outcomes for these diagnoses. A 2016 study25 showed a similar mortality rate between Veterans Affairs (VA) and non-VA hospitals for diagnoses of AMI, CHF, and PNA. The VA attributed this result to the implementation of improvement initiatives, and other large database studies showed overall decreases in inpatient mortality for AMI, CHF, and PNA from 2002 to 2012.26 As a whole, no obvious trend was found in mortality or length of stay for AMI, CHF, and PNA during the study period. This may be because of standardized best practice measures for these diagnoses.

This study had limitations. Although validated and often used, the administrative database supplied all of the data, making it difficult to capture the severity of illness using the International Statistical Classification of Diseases and Related Health Problems Ninth Revision codes. The years 2006-2011 were used because they were the most recently updated and released by the Health Care and Utilization Project at the time. The issue with coding errors in large patient and hospital databases has been well described in the literature.27,28 Additionally, hospitals that provide immediate percutaneous coronary intervention evaluation were not distinctly evaluated; they may have improved outcomes with AMI. Also, as in any study that uses diagnosis-related group codes, the severity of illness for AMI, CHF, and PNA cannot be assessed and would most likely affect mortality rates. Furthermore, within the dataset, there was no patient-level acuity data available for comparison, which made it challenging to associate mortality risk based on a diagnosis.

Conclusion

Level 1 trauma center designation is not associated with improved mortality for the diagnoses of AMI, CHF, and PNA. Further study of the nontrauma benefits of the resources of a level 1 trauma center needs to be performed.

Author Contributions

All authors provided substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; all authors drafted the article or revised it critically for important intellectual content; all authors gave final approval of the version of the article to be published; and all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.


From One:MAP Surgical Analytics (Drs Hwalek, Kothari, Wood, Kuo, and Posluszny) at the Department of Surgery at Loyola University Medical Center in Maywood, Illinois (Drs Hwalek, Kothari, Wood, Blanco, Plackett, Kuo, and Posluszny and Ms Brown).
Financial Disclosures: None reported.
Support: This work was funded, in part, by NIH training grant T32GM008750 (AEH, ANK).

*Address correspondence to Timothy P. Plackett, DO, MPH, 13 DuPont Pl, Fort Bragg, NC 28307-2012. Email:


References

1. MacKenzieEJ, RivaraFP, JurkovichGJ, et al.A national evaluation of the effect of trauma-center care on mortality. N Engl J Med. 2006;354(4):366-378. doi:10.1056/NEJMsa052049Search in Google Scholar PubMed

2. Site outcomes. American College of Surgeons website. https://www.facs.org/quality-programs/trauma/vrc/outcomes. Accessed January 20, 2019.Search in Google Scholar

3. UtterGH, MaierRV, RivaraFP, NathensAB. Outcomes after ruptured abdominal aortic aneurysms: the “halo effect” of trauma center designation. J Am Coll Surg. 2006;203(4):498-505. doi:10.1016/j.jamcollsurg.2006.06.011Search in Google Scholar PubMed

4. BounouaF, SchusterR, GrewalP, WaxmanK, CisekP.Ruptured abdominal aortic aneurysm: does trauma center designation affect outcome?Ann Vasc Surg. 2007;21(2):133-136. doi:10.1016/j.avsg.2007.01.003Search in Google Scholar PubMed

5. HalmEA, LeeC, ChassinMR. Is volume related to outcome in health care? a systematic review and methodologic critique of the literature. Ann Intern Med. 2002;137(6):511-520. doi:10.7326/0003-4819-137-6-200209170-00012Search in Google Scholar PubMed

6. BirkmeyerJD, SiewersAE, FinlaysonEVA, et al.. Hospital volume and surgical mortality in the United States. N Engl J Med. 2002;346(15):1128-1137. doi:10.1056/NEJMsa012337Search in Google Scholar PubMed

7. BirkmeyerJD, StukelTA, SiewersAE, GoodneyPP, WennbergDE, LucasFL. Surgeon volume and operative mortality in the United States. N Engl J Med. 2003;349(22):2117-2127. doi:10.1056.NEJMsa035205Search in Google Scholar

8. MetcalfeD, OlufajoO, Rios-DiazAJ, et al.Are appendectomy outcomes in level I trauma centers as good as we think?J Surg Res.2016;202(2):239-245. doi:10.1016/j.jss.2016.01.014Search in Google Scholar PubMed

9. NagarajanN, SelvarajahS, GaniF, et al.Halo effect” in trauma centers: does it extend to emergent colectomy?J Surg Res. 2016;203(1):231-237. doi:10.1016/j.jss.2016.01.037Search in Google Scholar PubMed

10. IngrahamAM, CohenME, RavalMV, KoCY, NathensAB. Effect of trauma center status on 30-day outcomes after emergency general surgery. J Am Coll Surg. 2011;212(3):277-286. doi:10.1016/j.jamcollsurg.2010.12.001Search in Google Scholar PubMed

11. NarayanM, TesorieroR, BrunsBR, KlyushnenkovaEN, ChenH, DiazJJ.Acute care surgery: defining mortality in emergency general surgery in the state of Maryland.J Am Coll Surg.2015;220(4):762-770. doi:10.1016/j.jamcollsurg.2014.12.051Search in Google Scholar PubMed

12. KrumholzHM, LinZ, KeenanPS, et al.. Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2013;309(6):587-593. doi:10.1001/jama.2013.333Search in Google Scholar PubMed PubMed Central

13. VenkatesanC, MishraA, MorganA, StepanovaM, HenryL, YounossiZM. Outcomes trends for acute myocardial infarction, congestive heart failure, and pneumonia, 2005-2009. Am J Manag Care. 2016;22(1):e9-e17.Search in Google Scholar

14. KothariAN, ZapfMA, BlackwellRH, et al.. Components of hospital perioperative infrastructure can overcome the weekend effect in urgent general surgery procedures. Ann Surg. 2015;262(4):683-691. doi:10.1097/SLA.000000000001436Search in Google Scholar

15. BlackwellRH, EllimoottilC, BajicP, et al.. Postoperative atrial fibrillation predicts long-term cardiovascular events after radical cystectomy. J Urol. 2015;194(4):944-949. doi:10.1016/j.juro.2015.03.109Search in Google Scholar PubMed

16. NassoiySP, BlackwellRH, KothariAN, et al.. New onset postoperative atrial fibrillation predicts long-term cardiovascular events following gastrectomy. Am J Surg. 2016;211(3):559-564. doi:10.016/j.amjsurg.2015.10.024Search in Google Scholar

17. Trauma information exchange program. American Trauma Society website. http://www.amtrauma.org/?page=TIEP. Accessed January 20, 2019.Search in Google Scholar

18. RajaramR, ChungJW, KinnierCV, et al.. Hospital characteristics associated with penalties in the Centers For Medicare & Medicaid Services Hospital-Acquired Condition Reduction Program. JAMA. 2015;314(4):375-383. doi:10.1001/jama.2015.8609.Search in Google Scholar PubMed

19. BrownEG, AndersonJE, BurgessD, BoldRJ. Examining the "halo effect" of surgical care within health systems.JAMA Surg.2016;151(10):983-984. doi:10.1001/jamasurg.2016.1000Search in Google Scholar PubMed

20. VuongP, SampleJ, ZimmermannME, SaldingerP.Trauma team activation: not just for trauma patients.J Emerg Trauma Shock. 2017;10(3):151-153. doi:10.4103/JETS.JETS_147_16Search in Google Scholar PubMed PubMed Central

21. van der GeestLGM, van RijssenLB, MolenaarIQ, et al.. Volume-outcome relationships in pancreatoduodenectomy for cancer. HPB (Oxford). 2016;18(4):317-324. doi:10.1016/j.hpb.2016.01.515Search in Google Scholar PubMed PubMed Central

22. MorcheJ, MathesT, PieperD. Relationship between surgeon volume and outcomes: a systematic review of systematic reviews. Syst Rev. 2016;5(1):204. doi:10.1186/s13643-016-0376-4Search in Google Scholar PubMed PubMed Central

23. LandonBE, O'MalleyAJ, GilesK, CotterillP, SchermerhornML.Volume-outcome relationships and abdominal aortic aneurysm repair.Circulation.2010;122(13):1290-1297. doi:10.1161/CIRCULATIONAHA.110.949172Search in Google Scholar PubMed

24. CheeTT, RyanAM, WafsyJH, BordenWB. Current state of value-based purchasing programs. Circulation. 2016;133(22):2197-2205. doi:10.116/CIRCULATIONAHA.115.010268Search in Google Scholar

25. NutiSV, QinL, RumsfeldJS, et al.. Association of admission to Veterans Affairs hospitals vs non-Veterans Affairs hospitals with mortality and readmission rates among older men hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2016;315(6):582-592. doi:10.1001/jama.2016.0278Search in Google Scholar PubMed PubMed Central

26. HinesAL, HeslinKC, JiangHJ, CoffeyR.Trends in Observed Adult Inpatient Mortality for High-Volume Conditions, 2002-2012: Statistical Brief #194. Health Care Cost and Utilization Project; 2015. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb194-Inpatient-Mortality-High-Volume-Conditions.jspSearch in Google Scholar

27. KhwajaHA, SyedH, CranstonDW.Coding errors: a comparative analysis of hospital and prospectively collected departmental data.BJU Int. 2002;89(3):178-180. doi:10.1046/j.1464-4096.2001.01428.xSearch in Google Scholar PubMed

28. PeabodyJ, LuckJ, JainS, BertenthalD, GlassmanP. Assessing the accuracy of administrative data in health information systems. Med Care. 2004;42(11):1066-1072.10.1097/00005650-200411000-00005Search in Google Scholar PubMed

Accepted: 2019-06-26
Published Online: 2020-05-01
Published in Print: 2020-05-01

© 2020 American Osteopathic Association

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