Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
권호 표지
DOI QR코드

DOI QR Code

The Effect of Geographic Units of Analysis on Measuring Geographic Variation in Medical Services Utilization

  • Kim, Agnus M. (Department of Health Policy and Management, Seoul National University College of Medicine) ;
  • Park, Jong Heon (Big Data Steering Department, National Health Insurance Service) ;
  • Kang, Sungchan (Institute of Health Policy and Management, Seoul National University Medical Research Center) ;
  • Hwang, Kyosang (Department of Industrial & Systems Engineering, Korea Advanced Institute of Science and Technology) ;
  • Lee, Taesik (Department of Industrial & Systems Engineering, Korea Advanced Institute of Science and Technology) ;
  • Kim, Yoon (Department of Health Policy and Management, Seoul National University College of Medicine)
  • Received : 2016.03.28
  • Accepted : 2016.07.14
  • Published : 2016.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

Objectives: We aimed to evaluate the effect of geographic units of analysis on measuring geographic variation in medical services utilization. For this purpose, we compared geographic variations in the rates of eight major procedures in administrative units (districts) and new areal units organized based on the actual health care use of the population in Korea. Methods: To compare geographic variation in geographic units of analysis, we calculated the age-sex standardized rates of eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee-replacement surgery, caesarean section, hysterectomy, computed tomography scan, and magnetic resonance imaging scan) from the National Health Insurance database in Korea for the 2013 period. Using the coefficient of variation, the extremal quotient, and the systematic component of variation, we measured geographic variation for these eight procedures in districts and new areal units. Results: Compared with districts, new areal units showed a reduction in geographic variation. Extremal quotients and inter-decile ratios for the eight procedures were lower in new areal units. While the coefficient of variation was lower for most procedures in new areal units, the pattern of change of the systematic component of variation between districts and new areal units differed among procedures. Conclusions: Geographic variation in medical service utilization could vary according to the geographic unit of analysis. To determine how geographic characteristics such as population size and number of geographic units affect geographic variation, further studies are needed.

Keywords

References

  1. Wennberg JE. Tracking medicine: a researcher's quest to understand health care. New York: Oxford University Press; 2010, p. 4.
  2. Love T, Ehrenberg N; Health Quality & Safety Commission New Zealand. Addressing unwarranted variation: literature review on methods for influencing practice. Wellington: Health Quality & Safety Commission; 2014, p. 3.
  3. Thygesen LC, Baixauli-Perez C, Librero-Lopez J, Martinez-Lizaga N, Ridao-Lopez M, Bernal-Delgado E, et al. Comparing variation across European countries: building geographical areas to provide sounder estimates. Eur J Public Health 2015;25 Suppl 1:8-14. https://doi.org/10.1093/eurpub/cku229
  4. Bernal-Delgado E, Christiansen T, Bloor K, Mateus C, Yazbeck AM, Munck J, et al. ECHO: health care performance assessment in several European health systems. Eur J Public Health 2015;25 Suppl 1:3-7.
  5. Volinn E, Diehr P, Ciol MA, Loeser JD. Why does geographic variation in health care practices matter? (And seven questions to ask in evaluating studies on geographic variation). Spine (Phila Pa 1976) 1994;19(18 Suppl):2092S-2100S. https://doi.org/10.1097/00007632-199409151-00012
  6. Korea Health Industry Development Institute. Report on demand and supply of hospital beds in Korea 2012 [cited 2015 Dec 11]. Available from: http://www.khanews.com/news/download.php?subUploadDir=201210/&savefilename= 85541_37.pdf&filename=2012%B3%E2%BA%B4%BB%F3%BC%F6%B1%DE%BD%C7%C5%C2%BA%D0%BC%AE%B0%E1%B0%FA.pdf&idxno=85541 (Korean).
  7. Lee HK, Moon OR, Lee KH. Geographic variations in tonsillectomy and adnoidectomy (T & A) and appendectomy in Korea. Korean J Prev Med 1993;26(3):430-441 (Korean).
  8. Moon YO, Park EC, Shin HR, Won YJ, Jung KW, Lee JH, et al. Regional variation in accessing regional hospitals for cancer patients. Korean J Epidemiol 2006;28(2):152-161 (Korean).
  9. Seo YS, Lee KS, Park JH, Kang SH. A study on regional medical utilization variation of hospital inpatients in Korea. J Korea Acad Ind Coop Soc 2010;11(4):1511-1519 (Korean). https://doi.org/10.5762/KAIS.2010.11.4.1511
  10. Shin HS, Lee SH. Factors affecting spatial distance to outpatient health services. ournal title. Health Policy Manag 2011; 21(1):23-43 (Korean). https://doi.org/10.4332/KJHPA.2011.21.1.023
  11. Lee YH, Choi KS, Lee HY, Jun JK. Current status of the National Cancer Screening Program for cervical cancer in Korea, 2009. J Gynecol Oncol 2012;23(1):16-21. https://doi.org/10.3802/jgo.2012.23.1.16
  12. Choi YH, Na BJ, Lee JY, Hwang JH, Lim NG, Lee SK. Obstetric complications by the accessibility to local obstetric service. J Agr Med Community Health 2013;38(1):14-24 (Korean). https://doi.org/10.5393/JAMCH.2013.38.1.014
  13. Kim YM, Cho DG, Kang SH. An empirical analysis on geographic variations in the prevalence of diabetes. Health Soc Welf Rev 2014;34(3):82-105 (Korean). https://doi.org/10.15709/hswr.2014.34.3.82
  14. Hong JS, Kang HC. Regional differences in treatment frequency and case-fatality rates in korean patients with acute myocardial infarction using the Korea national health insurance claims database: findings of a large retrospective cohort study. Medicine (Baltimore) 2014;93(28):e287. https://doi.org/10.1097/MD.0000000000000287
  15. Ahn HS, Kwon YD, Lee YS, Kim MK, Kim YI, Shin YS. Analysis of institutional factors influencing regional variations in the cesarean section rate. Korean J Health Policy Adm 1991;1(1):27-41 (Korean).
  16. Cho WH, Lee SH, Park EC, Sohn MS, Kim SR. An Analysis of small area variations of hospital services utilization in Korea. Korean J Prev Med 1994;27(3):609-626 (Korean).
  17. Kim YM, Yang BM. Small area variation in rates of common surgery in general surgery department. Korean J Health Policy Adm 2004;14(2):138-162 (Korean). https://doi.org/10.4332/KJHPA.2004.14.2.138
  18. Shin HY, Ahn HS, Lee CS. Estimation of social welfare loss due to small area variations in health care utilization. Health Soc Welf Rev 2007;27(1):52-80 (Korean). https://doi.org/10.15709/hswr.2007.27.1.52
  19. Kim JH, Cho BM, Hwang IK, Sohn MJ, Yoon TH. Trends of health care utilization and relevance index of stroke inpatients among the self-employed insured and their dependents of national health insurance (1998-2005). Korean J Health Policy Adm 2008;18(4):66-84 (Korean). https://doi.org/10.4332/KJHPA.2008.18.4.066
  20. Park SK, Lee SH, Chung AR, Cha YK, Myoung HB, Na BJ. Study on developing health service area on the health service utilization and supply. Seoul: Korea Health Industry Development Institue; 2011, p. 58-76, 103-108 (Korean).
  21. Song YJ. The South Korean health care system. Japan Med Assoc J 2009;52(3):206-209.
  22. Organisation for Economic Cooperation and Development. Focus on health: geographic variations in health care; 2014 [cited 2016 Jul 19]. Available from: https://www.oecd.org/els/health-systems/FOCUS-on-Geographic-Variations-in-Health-Care.pdf.
  23. Kim Y, Lee TS, Lee H, Kwak MY, Lee S, Park S, et al. Constructing the KNHI Atlas for health map service. Seoul: Korea National Health Insurance: 2015, p. 48 (Korean).
  24. Guidoum AC. Kernel estimator and bandwidth selection for density and its derivatives; 2015 [cited 2016 Jul 19]. Available from: https://cran.r-project.org/web/packages/kedd/vgnettes/kedd.pdf.
  25. Kazandjian VA, Durance PW, Schork MA. The extremal quotient in small-area variation analysis. Health Serv Res 1989;24 (5):665-684.
  26. Sorensen JB. The use and misuse of the coefficient of variation in organizational demography research. Sociol Methods Res 2002;30(4):475-491. https://doi.org/10.1177/0049124102030004001
  27. Appleby J, Raleigh V, Frosini F, Bevan G, Gao H, Lyscom T. Variations in health care: the good, the bad and the inexplicable; 2011 [cited 2016 Jul 19]. Available from: http://www.kings-fund.org.uk/sites/files/kf/Variations-in-health-care-good-bad-inexplicable-report-The-Kings-Fund-April-2011.pdf.
  28. McPherson K, Wennberg JE, Hovind OB, Clifford P. Small-area variations in the use of common surgical procedures: an international comparison of New England, England, and Norway. N Engl J Med 1982;307(21):1310-1314. https://doi.org/10.1056/NEJM198211183072104
  29. Brownlee S, Wennberg JE, Barry MJ, Fisher ES, Goodman DC, Bynum JP. Improving patient decision-making in health care: a 2011 Dartmouth Atlas report highlighting Minnesota [cited 2016 Jul 19]. Avaiable from: http://www.dartmouthatlas.org/downloads/reports/Decision_making_report_022411.pdf.
  30. Dieppe P, Basler HD, Chard J, Croft P, Dixon J, Hurley M, et al. Knee replacement surgery for osteoarthritis: effectiveness, practice variations, indications and possible determinants of utilization. Rheumatology (Oxford) 1999;38(1):73-83. https://doi.org/10.1093/rheumatology/38.1.73
  31. Tu JV, Ko DT, Guo H, Richards JA, Walton N, Natarajan MK, et al. Determinants of variations in coronary revascularization practices. CMAJ 2012;184(2):179-186. https://doi.org/10.1503/cmaj.111072
  32. Hawker GA. Who, when, and why total joint replacement surgery? The patient’s perspective. Curr Opin Rheumatol 2006;18 (5):526-530.

Cited by

  1. Evaluation of Geographic Indices Describing Health Care Utilization vol.50, pp.1, 2016, https://doi.org/10.3961/jpmph.16.099
  2. Senior high-cost healthcare users’ resource utilization and outcomes: a protocol of a retrospective matched cohort study in Canada vol.7, pp.12, 2017, https://doi.org/10.1136/bmjopen-2017-018488
  3. Regional Differences in Years of Life Lost in Korea from 1997 to 2015 vol.33, pp.53, 2016, https://doi.org/10.3346/jkms.2018.33.e330
  4. Regional variation in healthcare spending and mortality among senior high-cost healthcare users in Ontario, Canada: a retrospective matched cohort study vol.18, pp.None, 2016, https://doi.org/10.1186/s12877-018-0952-7
  5. Geographic variation in health insurance benefits in Qianjiang District, China: a cross-sectional study vol.17, pp.None, 2016, https://doi.org/10.1186/s12939-018-0730-3
  6. A framework for the identification and classification of homogeneous socioeconomic areas in the analysis of health care variation vol.17, pp.None, 2016, https://doi.org/10.1186/s12942-018-0162-8
  7. Regional Differences in Years of Life Lost in Korea from 1997 to 2015 vol.34, pp.suppl1, 2019, https://doi.org/10.3346/jkms.2019.34.e91
  8. An ecological study of geographic variation and factors associated with cesarean section rates in South Korea vol.19, pp.None, 2016, https://doi.org/10.1186/s12884-019-2300-0
  9. Hospitalizations for ambulatory care sensitive conditions as an indicator of access to primary care and excess of bed supply vol.19, pp.None, 2016, https://doi.org/10.1186/s12913-019-4098-x
  10. Factors associated with the rates of coronary artery bypass graft and percutaneous coronary intervention vol.19, pp.1, 2016, https://doi.org/10.1186/s12872-019-1264-3
  11. A spatial analysis of geographic variation and factors associated with hospitalization for bacterial pneumonia in Korea vol.19, pp.None, 2016, https://doi.org/10.1186/s12890-019-0798-6
  12. Geographic variation and factors associated with rates of knee arthroplasty in Korea-a population based ecological study vol.20, pp.1, 2019, https://doi.org/10.1186/s12891-019-2766-y
  13. Regional Variation of Hospitalization Rates for Asthma in Korea: Association with Ambient Carbon Monoxide and Health Care Supply vol.17, pp.4, 2016, https://doi.org/10.3390/ijerph17041244
  14. Healthcare utilization among children and young people with life-limiting conditions: Exploring palliative care needs using National Health Insurance claims data vol.10, pp.None, 2020, https://doi.org/10.1038/s41598-020-59499-x