Abstract
Purpose
The current study was done to identify individual- and group-level factors associated with health care service utilization among Korean medical aid beneficiaries by applying multilevel modeling.
Methods
Secondary data analysis was performed using data on health care service reimbursement and medical aid case management progress from 15,948 beneficiaries, and data from 229 regions were included in the analysis.
Results
Results of multilevel analysis showed an estimated intraclass correlation coefficient (ICC) of 18.1%, indicating that the group level accounted for 18.1% of the total variance in health care service utilization, and that beneficiaries within the region are more likely to share common features with regard to health care service utilization. At the individual level, existence of disability and types of medical aid beneficiaries showed a significant association, while, at the group level, social deprivation index, and the number of beneficiaries and case managers within the region showed a significant association with health care service utilization.
References
Cho S.H. 2003. Using multilevel analysis in patient and organizational outcomes research. Nursing Research. 52(1):61–65.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Eun S. J.., Hong J. Y.., Lee J. Y.., Lee J. S.., Kim Y.., Kim Y. I., et al2006. Differences in medical care utilization rates of the disabled and the non- disabled with ambulatory care sensitive conditions. Journal of Preventive Medicine and Public Health. 39(5):411–418.
Ahn Y. H.., Kim E. S.., Ham O. K.., Kim S. H.., Hwang S. S.., Chun S. H., et al2011. Factors associated with the overuse or underuse of health care services among medical aid beneficiaries in Korea. Journal of Community Health Nursing. 28:190–203. http://dx.doi.org/10.1080/07370016.2011.614837.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Bae S. S.., Jo H. S.., Kim D. H.., Choi Y. J.., Lee H.J.., Lee T. J., et al2008. Factors associated with gastric cancer screening of Koreans: Based on a socio-ecological model. Journal of Preventive Medicine & Public Health. 41(2):100–106.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Berben L.., Dobbels F.., Engberg S.., Hill M. N.., de Geest, S. 2012. An ecological perspective on medication adherence. Western Journal of Nursing Research. 34(5):635–653. http://dx.doi.org/10.1177/0193945911434518.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Chang, Y. 2012. Determinants of gastric cancer screening attendance in Korea: A multi-level analysis. Unpublished master’s thesis. Seoul National University;Seoul:
Cho S.H. 2003. Using multilevel analysis in patient and organizational outcomes research. Nursing Research. 52(1):61–65.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Eun S. J.., Hong J. Y.., Lee J. Y.., Lee J. S.., Kim Y.., Kim Y. I., et al2006. Differences in medical care utilization rates of the disabled and the non- disabled with ambulatory care sensitive conditions. Journal of Preventive Medicine and Public Health. 39(5):411–418.
Hanlon P.., Walsh D.., Whyte B. W.., Scott S. N.., Lightbody P.., Gilhooly M. L.M. 1998. Hospital use by an ageing cohort: An investigation into the association between biological, behavioural, and social risk markers and subsequent hospital utilization. Journal of Public Health Medicine. 20(4):467–476.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Kim E. Y.., Nam E. S.., Chae Y. R.., Lee H.K. 2008. Factors affecting the elderly’s preference for utilization of long-term care services based on Andersen’s Behavioral Model. Journal of the Korean Gerontological Society. 28(3):585–602.
Kim S.A. 2012. The effect of case management intervention by medical aid case manager: Centered on medical aid recipients with chronic disease. Unpublished master’s thesis. Hanyang University;Seoul:
Korea Ministry of Health & Welfare. 2010. 2010 medical aid program guide. Seoul: Author.
Lake E.T. 2006. Multilevel models in health outcomes research part II: Statistical and analytic issues. Applied Nursing Research. 19(2):113–115. http://dx.doi.org/10.1016/j.apnr.2006.01.001.
Lee H. J.., Oh J. J.., Choi J.M. 2010. Comparison of case management between tele care regions and general care regions in Korean Medicaid. Journal of Korean Academy of Nursing Administration. 16(4):381–388.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Lee S.H. 2009. Multi-level analysis of factors related to quality of service in long-term care hospitals. Journal of Korean Academy of Nursing. 39(3):409–421. http://dx.doi.org/10.4040/jkan.2009.39.3.409.
Lim S.J. 2010. Change in healthcare utilization by disease severity after case management for Medicaid. Journal of Korean Academy of Community Health Nursing. 21(3):321–332.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Medlensky L.., Esplen M. J.., Gallinger S.., McLaughlin J. R.., Goel, V. 2003. Relatives of colorectal cancer patients: Factors associated with screening behavior. American Journal of Preventive Medicine. 25(3):187–194. http://dx.doi.org/10.1016/S0749-3797(03)00202-2.
Park J. H.., Lee J. S.., Lee J. Y.., Hong J. Y.., Kim S. Y.., Kim S. O., et al2006. Factors affecting national health insurance mass screening participation in the disabled. Journal of Preventive Medicine and Public Health. 39(6):511–519.
Park S.., Lake E.T. 2005. Multilevel modeling of a clustered continuous outcome. Nursing Research. 54(6):406–413. http://dx.doi.org/10.1097/00006199-200511000-00007.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Sallis J. F.., Owen N.., Fisher E.B. 2008. Ecological models of health behavior. Glanz K., Rimer B.K., Viswanath K., editorsHealth behavior and health education: theory, research, and practice. 4th ed.San Fransisco: Jossey-Bass.
Shin S. M.., Kim E. S.., Park C. K.., Lee H.W. 2010a. The medical use of the disabled among overusers of medical aid in Korea. Journal of Preventive Medicine and Public Health. 43(1):35–41. http://dx.doi.org/10.3961/jpmph.2010.43.1.35.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Shin S. M.., Kim M. J.., Kim E. S.., Lee H. W.., Park C. G.., Kim H.K. 2010b. Medical aid service overuse assessed by case managers in Korea. Journal of Advanced Nursing. 66(10):2257–2265. http://dx.doi.org/10.1111/j.1365-2648.2010.05364.x.
![crossref](/image/icon/bnr_ref_cross.gif)
![crossref](/image/icon/bnr_ref_cross.gif)
Shin Y. J.., Yoon T. H.., Kim M. H.., Cho H. J.., Kim M. K.., Yoo W. S., et al2009. Health promotion strategies and programs development for health inequalities alleviation. Seoul: Industry-University Cooperation Foundation Hanyang University·Korea Health Promotion Foundation.
Song M.K. 2011. Factors related to competencies of medical aid case managers. Unpublished master’s thesis. Hanyang University;Seoul:
Statistics Korea. 2009. Database. Retrieved December 15, 2011, from. http://kostat.go.kr/portal/korea/index.action.
World Health Organization. 2002. World report on violence and health. Retrieved May 16, 2012, from. http://www.emro.who.int/violence-injuries-disabilities/health-topics/.
Table 1.
General Characteristics of Medical Aid Beneficiaries (N=15,948)
Individual variable | Distribution | n (%) | M±SD | Range |
---|---|---|---|---|
Age (year) | 66.93±12.51 | 11-100 | ||
Gender | Male | 5,667 (35.5) | ||
Female | 10,281 (64.5) | |||
Marital status | Married/cohabitating | 4,460 (28.0) | ||
Single | 977 (6.1) | |||
Widowed/divorced/separated | 6,171 (38.7) | |||
No response | 4,340 (27.2) | |||
Education (n=19,946) | None | 5,660 (35.5) | ||
≤9 years | 6,171 (38.7) | |||
≥10 years | 2,243 (14.1) | |||
No response | 1,874 (11.7) | |||
Disability | Yes | 6,702 (42.0) | ||
No | 9,246 (58.0) | |||
Beneficiary type | Type 1 | 11,255 (70.6) | ||
Type 2 | 1,737 (10.9) | |||
Person of national merit | 1,358 (8.5) | |||
Othera | 1,598 (10.0) | |||
Health care service utilization (days/6 months) | 1,235.99±585.99 | 1–15,872 |
Table 2.
Attributes of Group Level Characteristics according to the 229 Regions (N=15,948)
Group variables | Range | M±SD |
---|---|---|
SDI | −1.42-1.69 | −0.10±0.83 |
Population | 18,221-1,073,149 | 292,585.34±212,291.33 |
Number of beneficiaries | 468-27,773 | 10,214.73±6,034.24 |
Number of case managers | 1-10 | 3.40±2.78 |
Table 3.
Multilevel Analysis of Health Care Service Utilization according to the 229 Regions (N=15,948)
SDI=Social deprivation index. Variables: Gender 1=male, 2=female; education 1=less than or equal to 9 years, 2=more than 9 years; marriage1=without spouse (single, divorces, widowed, or separated), 2=with spouse; disability 0=not disabled, 1=disabled; beneficiary type 1=type 1, 2=other (type 2, those for persons of national merit, refugees, servicemen, and victims of natural disasters).