DOI QR코드

DOI QR Code

The impact of comorbidity (the Charlson Comorbidity Index) on the health outcomes of patients with the acute myocardial infarction(AMI)

급성심근경색증 환자의 동반상병지수에 따른 건강결과 분석

  • Lim, Ji-Hye (Department of Health and Medical Administration, Dongju College) ;
  • Park, Jae-Yong (Department of Public Health Graduate School, Kyungpook National University)
  • 임지혜 (동주대학교 보건의료행정과) ;
  • 박재용 (경북대학교 대학원 보건학과)
  • Received : 2011.08.24
  • Accepted : 2011.11.28
  • Published : 2011.12.31

Abstract

This study aimed to investigate health outcome of acute myocardial infarction (AMI) patients such as mortality and length of stay in hospital and to identify factors associated with the health outcome according to the comorbidity index. Nation-wide representative samples of 3,748 adult inpatients aged between 20-85 years with acute myocardial infarction were derived from the Korea National Hospital Discharge Injury Survey, 2005-2008. Comorbidity index was measured using the Charlson Comorbidity Index (CCI). The data were analyzed using t-test, ANOVA, multiple regression, logistic regression analysis in order to investigate the effect of comorbidity on health outcome. According to the study results, the factors associated with length of hospital stay of acute myocardial infarction patients were gender, insurance type, residential area scale, admission route, PCI perform, CABG perform, and CCI. The factors associated with mortality of acute myocardial infarction patients were age, admission route, PCI perform, and CCI. CCI with a higher length of hospital stay and mortality also increased significantly. This study demonstrated comorbidity risk adjustment for health outcome and presented important data for health care policy. In the future study, more detailed and adequate comorbidity measurement tool should be developed, so patients' severity can be adjusted accurately.

Keywords

References

  1. 권영대. 중증도 측정도구를 이용한 관상동맥우회로조성술의 보정사망률에 관한 연구. 서울대학교 대학원, 1998.
  2. 권영대, 안형식, 신영수. 관상동맥우회술의 중증도 측정과 병원 사망률 비교에 관한 연구. 예방의학회지 2001; 34(3): 244-252.
  3. 김경훈, 안이수. 건강보험 청구자료에서 동반질환 보정방법과 관찰기간 비교 연구: 경피적 관상동맥 중재술을 받은 환자를 대상으로. 예방의학회지 2009; 42(4): 267-273.
  4. 김경훈. 급성심근경색증 환자의 사회경제적 수준에 따른 사망률 연구[박사학위 논문]. 서울 : 고려대학교 대학원; 2010.
  5. 김세원. 폐암수술 환자의 동반상병지수에 따른 건강결과영향 연구[석사학위 논문]. 서울 : 고려대학교 보건대학원; 2008.
  6. 김은정. 동반질환 및 동반상병 지수와 수술한 암의 질병부담 간의 관련성[박사학위 논문]. 서울 : 고려대학교 대학원; 2011.
  7. 김재용, 김혜영, 김화영, 민경완, 박석원, 박이병 등. 우리나라 당뇨병환자의 외래이용 지속성이 건강결과 (health outcome)와 의료비에 미치는 영향: 건강보험청구자료 분석결과. 당뇨병 2006;30:377-387.
  8. 박이병, 김대중, 김재용, 김혜영, 김화영, 민경환 등. 당뇨병환자에서 아스피린 사용현황 및 동반질환: 건강보험청 구자료 분석결과. 당뇨병 2006; 30: 363-371.
  9. 서현주. Charlson comorbidity index를 이용한 폐암수술환자에서의 의료결과 예측에 관한 연구;의 무기록자료와 행정자료 비교[박사학위 논문]. 서울: 고려대학교 대학원; 2009.
  10. 서희석, 이강홍, 김희철, 유창식, 김진천. 대장암 수술에서 동반질환의 영향. 대한대장항문학회지 2003; 19: 299-306.
  11. 윤석준. 건강결과 연구에 대한 소개. 한국의료QA학회 2007; 13(1).
  12. 이광수, 이상일. 관상동맥우회로술 환자의 위험도에 따른 수술량과 병원내 사망의 관련성. 예방의학회지 2006; 39(1): 13-20.
  13. 최원호. Charlson Comorbidity Index를 활용한 고관절치환술 환자의 건강결과 예측에 관한 연구[박사학위 논문]. 서울 : 고려대학교 대학원; 2008.
  14. 최희주. 급성심근경색증 환자의 진료비용과 진료결과와의 관련성[박사학위 논문]. 인천: 가천의과대학교 대학원; 2007.
  15. 황세민, 윤석준, 안형식, 안형진, 김상후, 경민호 등. 위암 수술 환자의 건강결과 측정을 위한 동반상병 측정도구의 유용성 연구. 예방의학회지 2009; 42(1): 49-58.
  16. Ahn HS, Yoon SJ, Jo HY, Lee HY, Lee J, Seo HJ. Association between unplanned readmission rate and volume of breast cancer operation cases. Int J Clin Pract 2006; 60(1): 32-35. https://doi.org/10.1111/j.1368-5031.2006.00736.x
  17. Blumberg MS. Risk adjusting health care outcomes: a methodologic review. Med Care Rev 1986; 43(2): 351-393. https://doi.org/10.1177/107755878604300205
  18. Charlson ME, Pompei P, Ales K, Mackenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis 1987; 40(5):373-383. https://doi.org/10.1016/0021-9681(87)90171-8
  19. Charlson ME, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol 1994; 47(11): 1245-1251. https://doi.org/10.1016/0895-4356(94)90129-5
  20. DesHarnais SI, Forthman MT, Homa-Lowry JM, Wooster LD. Risk-adjusted quality outaome measures: Indexes for benchmarking rates of mortality, complications and readmissions. Qual Manag Health Care 1997; 5(2): 80-87. https://doi.org/10.1097/00019514-199705020-00009
  21. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD9-CM administrative databases. J Clin Epidemiol 1992; 45(6): 613-619. https://doi.org/10.1016/0895-4356(92)90133-8
  22. Extermann M, Overcash J, Lyman GH, et al. Comorbidity and functional status are independent in older cancer patients. J Clin Oncol 1998; 16: 1582-1587. https://doi.org/10.1200/JCO.1998.16.4.1582
  23. Humphries KH, Rankin JM, Carere RG, Buller CE, Kiely FM, Spinelli JJ. Co-morbidity data in outcomes research: are clinical data derived from administrative databases a reliable alternative to chart review? J Clin Epidemiol 2000; 53(4): 343-349. https://doi.org/10.1016/S0895-4356(99)00188-2
  24. Iezzoni LI. Risk adjustment for measuring health care outcomes, second edition. Health Administrative Press, Ann Arbor, Michigan, 1997.
  25. Kieszak SM, Flanders WD, Kosinski AS, Shipp CC, Karp H. A comparison of the CCI derived from medical record data and administrative billing data. J Clin Epidemiol 1999; 52: 137-142. https://doi.org/10.1016/S0895-4356(98)00154-1
  26. Klabunde CN, Harlan LC, Warren JL. Data sources for measuring comorbidity a comparison of hospital records and medicare claims for cancer patients. Med Care 2006; 44: 921-928. https://doi.org/10.1097/01.mlr.0000223480.52713.b9
  27. Ko C, Chaudhry S. The need for a multidisciplinary approach to cancer care. J Surg Res 2002;105(1): 53-57. https://doi.org/10.1006/jsre.2002.6449
  28. Librero J, Peiro'S, Ordinana R. Chronic comorbidity and outcomes of hospital care: Length of stay, mortality, and readmission at 30 and 365 days. J Clin Epidemiol 1999; 52(3): 171-179. https://doi.org/10.1016/S0895-4356(98)00160-7
  29. Nagel G, Wedding U, Hoyer H, Rohrig B, Katenkamp, D, The impact of comorbidity on the survival of postmenopausal women with breast cancer. Res Clin Oncol 2004; 130(11): 664-670. https://doi.org/10.1007/s00432-004-0594-3
  30. Newschaffer CJ, Bush TL, Penberthy LT. Comorbidity measurement in elderly female breast cancer patients with administrative and medical records data. J Clin Epidemiol 1997; 50(6): 725-733. https://doi.org/10.1016/S0895-4356(97)00050-4
  31. Nuttall M, van der Meulen J, Emberton M, Charlson scores based on ICD-10 administrative data were valid in assessing comorbidity in patients undergoing urological cancer surgery. J Clin Epidemiol. 2006; 59(3): 265-273. https://doi.org/10.1016/j.jclinepi.2005.07.015
  32. Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New Icd-10 version of CCI predicted in-hospital Mortality. J Clin Epidemiol 2004; 57(12): 1288-1294. https://doi.org/10.1016/j.jclinepi.2004.03.012