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Benchmarking of Trauma Care Worldwide: The Potential Value of an International Trauma Data Bank (ITDB)

World Journal of Surgery volume 38, pages 1882–1891 (2014)Cite this article

Abstract

Background

National trauma registries have helped improve patient outcomes across the world. Recently, the idea of an International Trauma Data Bank (ITDB) has been suggested to establish global comparative assessments of trauma outcomes. The objective of this study was to determine whether global trauma data could be combined to perform international outcomes benchmarking.

Methods

We used observed/expected (O/E) mortality ratios to compare two trauma centers [European high-income country (HIC) and Asian lower-middle income country (LMIC)] with centers in the North American National Trauma Data Bank (NTDB). Patients (≥16 years) with blunt/penetrating injuries were included. Multivariable logistic regression, adjusting for known predictors of trauma mortality, was performed. Estimates were used to predict the expected deaths at each center and to calculate O/E mortality ratios for benchmarking.

Results

A total of 375,433 patients from 301 centers were included from the NTDB (2002–2010). The LMIC trauma center had 806 patients (2002–2010), whereas the HIC reported 1,003 patients (2002–2004). The most important known predictors of trauma mortality were adequately recorded in all datasets. Mortality benchmarking revealed that the HIC center performed similarly to the NTDB centers [O/E = 1.11 (95 % confidence interval (CI) 0.92–1.35)], whereas the LMIC center showed significantly worse survival [O/E = 1.52 (1.23–1.88)]. Subset analyses of patients with blunt or penetrating injury showed similar results.

Conclusions

Using only a few key covariates, aggregated global trauma data can be used to adequately perform international trauma center benchmarking. The creation of the ITDB is feasible and recommended as it may be a pivotal step towards improving global trauma outcomes.

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References

  1. World Health Organization (2010) Injuries and violence: the facts [Internet]. http://whqlibdoc.who.int/publications/2010/9789241599375_eng.pdf. Accessed 7 Jul 2013

  2. Marciniak TA, Ellerbeck EF, Radford MJ et al (1998) Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project. JAMA 79(17):1351–1357

    Article  Google Scholar 

  3. MacKenzie EJ, Rivara FP, Jurkovich GJ et al (2006) A national evaluation of the effect of trauma-center care on mortality. N Engl J Med 354(4):366–378

    CAS  PubMed  Article  Google Scholar 

  4. MacKenzie EJ, Weir S, Rivara FP et al (2010) The value of trauma center care. J Trauma 69(1):1–10

    PubMed  Article  Google Scholar 

  5. Khuri SF, Daley J, Henderson WG (2002) The comparative assessment and improvement of quality of surgical care in the Department of Veterans Affairs. Arch Surg 137(1):20–27

    PubMed  Article  Google Scholar 

  6. DiRusso S, Holly C, Kamath R et al (2001) Preparation and achievement of American College of Surgeons level I trauma verification raises hospital performance and improves patient outcome. J Trauma 51(2):294–299 discussion 299–300

    CAS  PubMed  Article  Google Scholar 

  7. Haut ER, Lau BD, Kraenzlin FS et al (2012) Improved prophylaxis and decreased rates of preventable harm with the use of a mandatory computerized clinical decision support tool for prophylaxis for venous thromboembolism in trauma. Arch Surg 147(10):901–907

    PubMed  Article  Google Scholar 

  8. Juillard CJ, Mock C, Goosen J et al (2009) Establishing the evidence base for trauma quality improvement: a collaborative WHO-IATSIC review. World J Surg 33(5):1075–1086. doi:10.1007/s00268-009-9959-8

    PubMed  Article  Google Scholar 

  9. Dumont A, Gaye A, de Bernis L et al (2006) Facility-based maternal death reviews: effects on maternal mortality in a district hospital in Senegal. Bull World Health Organ 84(3):218–224

    PubMed Central  PubMed  Article  Google Scholar 

  10. Ifenne D, Essien E, Golji N et al (1997) Improving the quality of obstetric care at the teaching hospital, Zaria, Nigeria. Int J Gynaecol Obstet 59(Suppl 2):S37–S46

    PubMed  Article  Google Scholar 

  11. Mbaruku G, Bergström S (1995) Reducing maternal mortality in Kigoma, Tanzania. Health Policy Plan 10(1):71–78

    CAS  PubMed  Article  Google Scholar 

  12. Ronsmans C (2001) How can we monitor progress towards improved maternal health goals? Stud HSO&P 17:317–342

    Google Scholar 

  13. Hashmi ZG, Haider AH, Zafar SN et al (2013) Hospital-based trauma quality improvement initiatives: first step toward improving trauma outcomes in the developing world. J Trauma Acute Care Surg 75(1):60–68

    PubMed  Article  Google Scholar 

  14. U.S. Department of Health & Human Services (2013) Health Resources and Services Administration (HRSA) clinical quality & performance measures supplemental technical assistance: quality improvement [Internet]. Available at: http://www.hrsa.gov/quality/toolbox/methodology/qualityimprovement/index.html. Accessed 17 Jul 2013

  15. Varkey P, Reller MK, Resar RK (2007) Basics of quality improvement in health care. Mayo Clin Proc 82(6):735–739

    PubMed  Article  Google Scholar 

  16. Donabedian A (2005) Evaluating the quality of medical care. 1966. Milbank Q 83(4):691–729

    PubMed Central  PubMed  Article  Google Scholar 

  17. Moore L, Clark DE (2008) The value of trauma registries. Injury 39(6):686–695

    PubMed  Article  Google Scholar 

  18. European Trauma Registry Network (2013) Trauma Registries worldwide [Internet]. http://www.eurotrauma.net/site2/index.php?option=com_content&view=article&id=54&Itemid=59. Accessed 17 Jul 2013

  19. Jurkovich GJ, Mock C (1999) Systematic review of trauma system effectiveness based on registry comparisons. J Trauma 47(3 Suppl):S46–S55

    CAS  PubMed  Article  Google Scholar 

  20. Patel HC, Bouamra O, Woodford M et al (2005) Trends in head injury outcome from 1989 to 2003 and the effect of neurosurgical care: an observational study. Lancet 366(9496):1538–1544

    CAS  PubMed  Article  Google Scholar 

  21. Fuller G, Bouamra O, Woodford M et al (2012) Recent massive blood transfusion practice in England and Wales: view from a trauma registry. Emerg Med J 29(2):118–123

    PubMed  Article  Google Scholar 

  22. Lecky F, Woodford M, Yates DW (2000) Trends in trauma care in England and Wales 1989-97. UK Trauma Audit and Research Network. Lancet 355(9217):1771–1775

    CAS  PubMed  Article  Google Scholar 

  23. Siman-Tov M, Radomislensky I, Peleg K (2012) Reduction in trauma mortality in Israel during the last decade (2000-2010): The impact of changes in the trauma system. Injury 44(11):1448–1452

    PubMed  Article  Google Scholar 

  24. Ringdal KG, Lossius HM, Jones JM et al (2011) Collecting core data in severely injured patients using a consensus trauma template: an international multicentre study. Crit Care 15(5):R237

    PubMed Central  PubMed  Article  Google Scholar 

  25. Zafar H, Rehmani R, Raja AJ et al (2002) Registry-based trauma outcome: perspective of a developing country. Emerg Med J 19(5):391–394

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  26. Noordin S, Allana S, Ahmad T et al (2011) Evolution of trauma management at a tertiary care hospital: a cohort study. Int J Surg 9(1):75–78

    PubMed  Article  Google Scholar 

  27. American College of Surgeons (2010) National Trauma Data Bank: NTDB Research Data Set Admission Year 2010, Annual Report. American College of Surgeons, Chicago

    Google Scholar 

  28. American College of Surgeons. National Trauma Data Standard [Internet]. Available at: http://www.ntdsdictionary.org/index.html. Accessed 30 Aug 2013

  29. Kardooni S, Haut ER, Chang DC et al (2008) Hazards of benchmarking complications with the National Trauma Data Bank: numerators in search of denominators. J Trauma 64(2):273–277 discussion 277–279

    PubMed  Article  Google Scholar 

  30. Nathens AB, Jurkovich GJ, Maier RV et al (2001) Relationship between trauma center volume and outcomes. JAMA 285(9):1164–1171

    CAS  PubMed  Article  Google Scholar 

  31. Haider A, Hashmi Z, Zafar S et al (2014) Developing best practices to study trauma outcomes in large data bases: an evidence based approach to determine the best mortality risk adjustment model. J Trauma Acute Care Surg 76(4):1061–1069

    PubMed  Article  Google Scholar 

  32. Nathens AB, Cryer HG, Fildes J (2012) The American college of surgeons Trauma quality improvement program. Surg Clin North Am 92(2):441–454 x–xi

    PubMed  Article  Google Scholar 

  33. Haider AH, Saleem T, Leow JJ et al (2012) Influence of the National Trauma Data Bank on the study of trauma outcomes: is it time to set research best practices to further enhance its impact? J Am Coll Surg 214(5):756–768

    PubMed Central  PubMed  Article  Google Scholar 

  34. Baker SP, O’Neill B, Haddon W et al (1974) The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma 14(3):187–196

    CAS  PubMed  Article  Google Scholar 

  35. Osler T, Baker SP, Long W (1997) A modification of the injury severity score that both improves accuracy and simplifies scoring. J Trauma 43(6):922–925 discussion 925–926

    CAS  PubMed  Article  Google Scholar 

  36. Kilgo PD, Meredith JW, Osler TM (2006) Incorporating recent advances to make the TRISS approach universally available. J Trauma 60(5):1002–1008 discussion 1008–1009

    PubMed  Article  Google Scholar 

  37. Osler T, Glance L, Buzas JS et al (2008) A trauma mortality prediction model based on the anatomic injury scale. Ann Surg 247(6):1041–1048

    PubMed  Article  Google Scholar 

  38. Glance LG, Osler TM, Mukamel DB et al (2009) TMPM-ICD9: a trauma mortality prediction model based on ICD-9-CM codes. Ann Surg 249(6):1032–1039

    PubMed  Article  Google Scholar 

  39. Haider AH, Villegas CV, Saleem T et al (2012) Should the IDC-9 Trauma Mortality Prediction Model become the new paradigm for benchmarking trauma outcomes? J Trauma Acute Care Surg 72(6):1695–1701

    PubMed  Article  Google Scholar 

  40. Osler T, Rutledge R, Deis J et al (1996) ICISS: an international classification of disease-9 based injury severity score. J Trauma 41(3):380–386 discussion 386–388

    CAS  PubMed  Article  Google Scholar 

  41. Clarke JR, Ragone AV, Greenwald L (2008) 5) Comparisons of survival predictions using survival risk ratios based on International Classification of Diseases, Ninth Revision and Abbreviated Injury Scale trauma diagnosis codes. J Trauma 59(3):563–567 discussion 567–569

    Google Scholar 

  42. Lavoie A, Moore L, LeSage N et al (2004) The New Injury Severity Score: a more accurate predictor of in-hospital mortality than the Injury Severity Score. J Trauma 56(6):1312–1320

    PubMed  Article  Google Scholar 

  43. Meredith JW, Evans G, Kilgo PD et al (2002) A comparison of the abilities of nine scoring algorithms in predicting mortality. J Trauma 53(4):621–628 discussion 628–629

    PubMed  Article  Google Scholar 

  44. Stephenson SCR, Langley JD, Civil ID (2002) Comparing measures of injury severity for use with large databases. J Trauma 53(2):326–332

    PubMed  Article  Google Scholar 

  45. Sullivan T, Haider A, DiRusso SM et al (2003) Prediction of mortality in pediatric trauma patients: new injury severity score outperforms injury severity score in the severely injured. J Trauma 55(6):1083–1087 discussion 1087–1088

    PubMed  Article  Google Scholar 

  46. Newgard CD, Fildes JJ, Wu L et al (2013) Methodology and analytic rationale for the American College of Surgeons Trauma Quality Improvement Program. J Am Coll Surg 216(1):147–157

    PubMed  Article  Google Scholar 

  47. Hashmi ZG, Dimick JB, Efron DT (2013) Reliability adjustment: a necessity for trauma center ranking and benchmarking. J Trauma Acute Care Surg 75(1):166–172

    PubMed  Article  Google Scholar 

  48. Glance LG, Osler TM, Mukamel DB et al (2009) Impact of statistical approaches for handling missing data on trauma center quality. Ann Surg 249(1):143–148

    PubMed  Article  Google Scholar 

  49. Oyetunji TA, Crompton JG, Ehanire ID et al (2011) Multiple imputation in trauma disparity research. J Surg Res 165(1):e37–e41

    PubMed  Article  Google Scholar 

  50. Edwards A, Di Bartolomeo S, Chieregato A et al (2007) A comparison of European Trauma Registries. The first report from the EuroTARN Group. Resuscitation 75(2):286–297

    PubMed  Article  Google Scholar 

  51. Ringdal KG, Lossius HM (2007) Feasibility of comparing core data from existing trauma registries in Scandinavia. Reaching for a Scandinavian major trauma outcome study (MTOS). Scand J Surg 96(4):325–331

    CAS  PubMed  Google Scholar 

  52. Dick WF, Baskett PJ (1999) Recommendations for uniform reporting of data following major trauma–the Utstein style. A report of a working party of the International Trauma Anaesthesia and Critical Care Society (ITACCS). Resuscitation 42(2):81–100

    CAS  PubMed  Article  Google Scholar 

  53. Ringdal KG, Coats TJ, Lefering R et al (2008) The Utstein template for uniform reporting of data following major trauma: a joint revision by SCANTEM, TARN, DGU-TR and RITG. Scand J Trauma Resusc Emerg Med 16:7

    PubMed Central  PubMed  Article  Google Scholar 

  54. Coats TJ (2010) A revised Utstein Template for trauma. Emerg Med J 27(5):339

    PubMed  Article  Google Scholar 

  55. Nathens AB, Xiong W, Shafi S (2008) Ranking of trauma center performance: the bare essentials. J Trauma 65(3):628–635

    PubMed  Article  Google Scholar 

  56. Salottolo K, Settell A, Uribe P et al (2009) The impact of the AIS 2005 revision on injury severity scores and clinical outcome measures. Injury 40(9):999–1003

    PubMed  Article  Google Scholar 

  57. Palmer CS, Niggemeyer LE, Charman D (2010) Double coding and mapping using Abbreviated Injury Scale 1998 and 2005: identifying issues for trauma data. Injury 41(9):948–954

    PubMed  Article  Google Scholar 

  58. Palmer CS, Franklyn M (2011) Assessment of the effects and limitations of the 1998 to 2008 Abbreviated Injury Scale map using a large population-based dataset. Scand J Trauma Resusc Emerg Med 19(1):1

    PubMed Central  PubMed  Article  Google Scholar 

  59. Palmer CS, Franklyn M, Read-Allsopp C et al (2011) Development and validation of a complementary map to enhance the existing 1998 to 2008 Abbreviated Injury Scale map. Scand J Trauma Resusc Emerg Med 19:29

    PubMed Central  PubMed  Article  Google Scholar 

  60. MacLeod JBA, Kobusingye O, Frost C (2003) A comparison of the Kampala Trauma score (KTS) with the revised Trauma score (RTS), Injury Severity Score (ISS) and the TRISS method in a Ugandan Trauma registry. Eur J Trauma 29(6):392–398

    Article  Google Scholar 

  61. Moore L, Stelfox HT, Boutin A et al (2013) Trauma center performance indicators for nonfatal outcomes: a scoping review of the literature. J Trauma Acute Care Surg 74(5):1331–1343

    PubMed  Article  Google Scholar 

  62. Santana MJ, Stelfox HT (2013) Development and evaluation of evidence-informed quality indicators for adult injury care. Ann Surg 259(1):186–192

    Article  Google Scholar 

  63. Glance LG, Dick AW, Meredith JW et al (2011) Variation in hospital complication rates and failure-to-rescue for trauma patients. Ann Surg 253(4):811–816

    PubMed  Article  Google Scholar 

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Acknowledgment

The authors thank Mary Lodenkemper for her editorial assistance and coordination. National Institutes of Health/NIGMS K23GM093112-01 and American College of Surgeons C. James Carrico Fellowship for the study of Trauma and Critical Care (Dr. Haider); Agency for Healthcare Research & Quality K081K08HS017952-01 (Dr. Haut).

Conflict of interest

None of the authors report any potential or real conflicts of interest.

Author information

Affiliations

  1. Department of Surgery, Center for Surgical Trials and Outcomes Research, The Johns Hopkins School of Medicine, Sheikh Zayed Tower 1800 Orleans Street, Suite 6107, Baltimore, MD, 21287-4688, USA

    Adil H. Haider, Zain G. Hashmi, Sonia Gupta, David T. Efron, Kent A. Stevens, Eric B. Schneider & Elliott R. Haut

  2. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Adil H. Haider

  3. Department of Anesthesiology & Critical Care Medicine, The Johns Hopkins School of Medicine, Baltimore, MD, USA

    Adil H. Haider, David T. Efron, Kent A. Stevens & Elliott R. Haut

  4. Department of Surgery, Howard University College of Medicine, Washington, DC, USA

    Syed Nabeel Zafar

  5. Department of Anesthesiology and Critical Care Medicine, Lyon Sud Hospital, Hospices Civils de Lyon (HCL), Pierre Benite, France

    Jean-Stephane David

  6. Charles Merieux Lyon-Sud School of Medicine, University Lyon 1, Oullins, France

    Jean-Stephane David

  7. Department of Surgery, Aga Khan University Hospital, Karachi, Pakistan

    Hasnain Zafar

  8. Department of Surgery, Trauma and Emergency Surgery Unit, Lyon Sud Hospital (HCL), Pierre Benite, France

    Eric Voiglio

  9. Lyon-Est School of Medicine, University Lyon 1, Lyon, France

    Eric Voiglio

  10. Department of Surgery, UC San Diego, School of Medicine, San Diego, CA, USA

    Raul Coimbra

Authors
  1. Adil H. Haider
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  2. Zain G. Hashmi
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  3. Sonia Gupta
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  4. Syed Nabeel Zafar
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  5. Jean-Stephane David
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  6. David T. Efron
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  7. Kent A. Stevens
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  8. Hasnain Zafar
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  9. Eric B. Schneider
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  10. Eric Voiglio
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  11. Raul Coimbra
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  12. Elliott R. Haut
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Corresponding author

Correspondence to Adil H. Haider.

Additional information

This work was declared as the best oral presentation at the International Association for Trauma Surgery and Intensive Care/the American Association for the Surgery of Trauma (IATSIC/AAST) Scientific Paper Session at the International Surgical Week (ISW) 2013, Helsinki, Finland.

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Haider, A.H., Hashmi, Z.G., Gupta, S. et al. Benchmarking of Trauma Care Worldwide: The Potential Value of an International Trauma Data Bank (ITDB). World J Surg 38, 1882–1891 (2014). https://doi.org/10.1007/s00268-014-2629-5

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Keywords

  • Injury Severity Score
  • Trauma Center
  • Trauma Care
  • Abbreviate Injury Scale
  • Trauma Registry