The Trend of Risk-adjusted Hospital Mortality Rates of Coronary Artery Bypass Graft Patients from 2001 to 2003

위험도가 보정된 의료기관 관상동맥우회로술 사망률의 3년간(2001년-2003년) 추세분석

  • Lee, Kwang-Soo (Department of Hospital Management, College of Medicine, Eulji University, Health Insurance Review Agency)
  • 이광수 (을지대학교 의과대학 병원경영학과, 건강보험 심사평가원)
  • Published : 2007.01.31

Abstract

Objectives : To assess whether the risk-adjusted in-hospital mortality rates for non-emergent and isolated coronary artery bypass graft surgery (CABG) patients exhibited a consistent trend from 2001 to 2003. Methods : The data used in this study came from CABG claims that were submitted to a Korean Health Insurance Review Agency (HIRA) in 2001, 2002, and 2003. Study datasets included data from 17 tertiary hospitals, which had at least 25 claims each year over 3 years. The inter-hospital differences in patients' risk-factors were identified and controlled in the risk-adjustment model. Actual and predicted mortality rates for each hospital were calculated in 2001, 2002, 2003, and 2001+2002, and were then examined to identify consistent rate patterns over time. Kappa analysis was applied to assess the agreements between rates. Results : Hospitals with lower-than-expected inpatient mortality rates showed more consistent rates than those with higher-than-expected mortality rates. The mortality rates that were calculated based on data obtained over multiple years had less variation among hospitals than rates based on single year data. Based on the Kappa score, the highest agreement was found when the rates were compared between the 2-year combined data (2001+2002) and 2003. Conclusions : Consistent patterns over 3 years were most evident for hospitals which had lower-than expected mortality rates. Policy makers can use this information to identify the degree of outcomes in hospitals and help motivate or channel the behaviors of providers.

Keywords

References

  1. Lee, KS, Lee SI. Does a higher coronary artery bypass graft surgery always have a low inhospital mortality rate in Korea? J Prev Med Public Health 2006; 39(1): 13-20 (Korean)
  2. Park HK, Ahn HS, Kwon YD, Shin YC, Lee JS, Kim HJ, Sohn MJ. Severity-adjusted mortality rates: The case of CABG surgery. Korean J Prev Med 2001; 34(1): 21-27 (Korean)
  3. Kwon YD, Ahn HS, Shin YS. Severity measurement methods and comparing hospital death rates. Korean J Prev Med 2001; 34(3): 244-252 (Korean)
  4. Hannan EL, O'Donnell JF, Kilburn H Jr, Bernard HR, Yazici A. Investigation of the relationship between volume and mortality for surgical procedures performed in New York state. JAMA 1989; 262(4): 503-510 https://doi.org/10.1001/jama.262.4.503
  5. Hannan EL, Kilburn H, Bernard H, O'donnell JF, Lukacik G, Shields EP. Coronary artery bypass surgery: The relationship between inhospital mortality rate and surgical volume after controlling for clinical risk factors. Med Care 1991; 29(11): 1094-1107 https://doi.org/10.1097/00005650-199111000-00003
  6. Nallamothu BK, Saint S, Ramsey SD, Hofer TP, Vijan S, Eagle KS. The role of hospital volume in coronary artery bypass grafting: Is more always better? J Am Coll Cardio 2001; 38(7): 1923-1930 https://doi.org/10.1016/S0735-1097(01)01647-3
  7. Showstack JA, Rosenfeld KE, Garnick DW, Luft HS, Schaffarzick RW, Fowles. Association of volume with outcome of coronary artery bypass graft surgery. JAMA 1987; 257(6): 785- 789 https://doi.org/10.1001/jama.257.6.785
  8. Park RE, Brook RH, Kosecoff J, Keesey J, Rubenstein J, Keeler E, Kahn KL, Rogers WH, Chassin MR. Explaining variations in hospital death rates. Randomness, severity of illness, quality of care. JAMA 1990; 264(4): 484-490 https://doi.org/10.1001/jama.264.4.484
  9. Berwick DM, Wald DL. Hospital leaders’ opinions of the HCFA mortality data. JAMA 1990; 263(2): 247-249 https://doi.org/10.1001/jama.263.2.247
  10. Luft, HS, Romano PS. Chance, continuity, and change in hospital mortality rates-coronary artery bypass graft patients in California hospitlas, 1983-1989. JAMA 1993; 370(3); 331-337
  11. AHRQ Quality Indicators-Guide to Inpatient Quality Indicators: Quality of Care in Hospitals-Volume, Mortality, and Utilization. Rockville, MD: Agency for Healthcare Research and Quality, 2002. AHRQ Pub. No. 02-RO204
  12. Iezzoni LI. Risk Adjustment for Measuring Healthcare Outcomes, 2nd ed. Chicago, Illinois: Health Administration Press: 1997, 349.12
  13. Landis JR, Koch G. The measurement of observer agreement for categorical data. Biometrics 1977; 33(1): 159-174 https://doi.org/10.2307/2529310