Han, Kyu-Tae
(Division of Cancer Management, National Cancer Center)
,
Park, Eun-Cheol
(Institute of Health Services Research, Yonsei University College of Medicine)
,
Nam, Chung-Mo
(Department of Preventive Medicine, Yonsei University College of Medicine)
,
Kim, Tae-Hyun
(Institute of Health Services Research, Yonsei University College of Medicine)
,
Hahm, Myung-Il
(Department of Health Administration and Management, Soonchunhyang University)
,
Lee, Sang-Gyu
(Institute of Health Services Research, Yonsei University College of Medicine)
Purpose: The objective of this study was to publicly report the hospital-level surgical volume for 7 types of surgery including gastrectomy. Also, to investigate the changes in patient behaviors after the public reporting among patients with gastrectomy. Methods: This study used data from the Nation...
Purpose: The objective of this study was to publicly report the hospital-level surgical volume for 7 types of surgery including gastrectomy. Also, to investigate the changes in patient behaviors after the public reporting among patients with gastrectomy. Methods: This study used data from the National Health Insurance Service Cohort. The data comprised of 2,214 patients who were diagnosed with gastric cancer and underwent gastrectomy during 2004-2012. An interrupted time series analysis was performed to investigate the association between patients' choice and public reporting. Results: 79.27% of the patients visited a hospital with high surgical volume. The time trend after introduction of public reporting was positively associated with visiting a high volume hospital (per 1 month, RR: 1.004, p=0.0329). However, after adjusting the health policies by reducing copayment, public reporting on surgical volume was not associated with visiting a high volume hospital. Sub-group analyses had also similar results. Conclusion: Patients were more affected by policies on economic support than on public reporting, and the changes in treatment options may have been affected by the increasing preference for large size hospitals. Thus, public reporting did not significantly improve the options available for patients and their decision making on health care utilization.
Purpose: The objective of this study was to publicly report the hospital-level surgical volume for 7 types of surgery including gastrectomy. Also, to investigate the changes in patient behaviors after the public reporting among patients with gastrectomy. Methods: This study used data from the National Health Insurance Service Cohort. The data comprised of 2,214 patients who were diagnosed with gastric cancer and underwent gastrectomy during 2004-2012. An interrupted time series analysis was performed to investigate the association between patients' choice and public reporting. Results: 79.27% of the patients visited a hospital with high surgical volume. The time trend after introduction of public reporting was positively associated with visiting a high volume hospital (per 1 month, RR: 1.004, p=0.0329). However, after adjusting the health policies by reducing copayment, public reporting on surgical volume was not associated with visiting a high volume hospital. Sub-group analyses had also similar results. Conclusion: Patients were more affected by policies on economic support than on public reporting, and the changes in treatment options may have been affected by the increasing preference for large size hospitals. Thus, public reporting did not significantly improve the options available for patients and their decision making on health care utilization.
* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.
문제 정의
Table 2. The median and IQR of surgical volume for stomach cancer in this study.
Public reporting about hospital performance might affect patient’s criteria for choosing a hospital, because patients could get more information and make an informed choice by using a public report rather than basing it on reputation or experience [7-8]. The purpose of this study was to investigate the changes in patient behaviors after public reporting of hospital-level surgical volume among patients who received gastrectomy. This study identified the association between patients’ choice of hospital, as an indicator of patient behavior, and introduction of public reporting.
가설 설정
However, the data used in this study did not include the information about cancer staging. In this study, to solve the limitations on cancer staging, we considered types of surgery and types of treatment as independent variables [24]. Fourth, in the methods, we defined the outcome variable based on the first quartile value of surgical volume in the previous year, because the criteria for better hospitals in the public reporting about surgical volume was defined based the quartile of surgical volume.
제안 방법
As the public reporting was introduced into several disease categories including gastric cancer after 2007, we additionally analyzed the association between patients’ choice of hospitals and the introduction of public reporting in colon cancer patients to support the results of gastric cancer. Finally, we performed a sub-group analysis, to examine the differences in association with public reporting according to income level, types of insurance coverage, region, types of treatment, and types of surgery.
In the analysis on patients’ choice, we first examined the frequencies and percentages of each categorical variable by whether patients visited the hospital with surgical volume above that of the first quartile of the previous year, and performed the chi-square test to examine the distribution of visits to a hospital with high volume according to each categorical variable.
Thus, the results of this study could be used in making evidence-based healthcare policy or programs. Next, in the statistical analysis, we performed the interrupted time series analysis. This method was useful in measuring the impact of the policy or intervention even though this method could not reflect the linear trend in each segment.
Next, we performed the interrupted time series analysis using the Generalized Estimated Equation (GEE) model with Poisson distribution and log link function adjusting patient-level variables to investigate the association between patients’ choice of hospitals and the public reporting [9].
Table 7. Results of the sub-group analysis for the interrupted time series analysis according to income, types of insurance coverage, region, and types of treatment or surgery.
This study identified the association between patients’ choice of hospital, as an indicator of patient behavior, and introduction of public reporting.
대상 데이터
Finally, the data comprised 2,214 patients who were diagnosed with gastric cancer and underwent gastrectomy in 105 hospitals during 2004–2012.
후속연구
Second, it is the first attempt to evaluate the impact of public reporting about surgical volume among cancer patients, in particular, gastric cancer patients. Thus, the results of this study could be used in making evidence-based healthcare policy or programs. Next, in the statistical analysis, we performed the interrupted time series analysis.
참고문헌 (24)
Ministry of Health and Welfare. Cancer Registration Statistics 1999-2014 [cited 2016 28 Sep]. Available from: http://kosis.kr/statHtml/statHtml.do?orgId117&tblIdDT_117N_A00022&-conn_pathI2.
Health Insurance Review & Assessment Service. Statistics for diseases 2014 [cited 2016 28 Sep]. Available from: http://www.hira.or.kr/eng/index.html.
Yoo KY. Cancer control activities in the Republic of Korea. Japanese Journal of Clinical Oncology. 2008;38(5):327-33.
Han KT, Kim J, Nam CM, Moon KT, Lee SG, Kim SJ, et al. Association between reduction in copayment and gastric cancer patient concentration to the capital area in South Korea: NHI cohort 2003？2013. Health Policy. 2016;120(6):580-9.
Han KT, Kim J, Nam CM, Moon KT, Lee SG, Kim SJ, et al. Association between reduction in copayment and gastric cancer patient concentration to the capital area in South Korea: NHI cohort 2003-2013. Health Policy. 2016;120(6):580-9.
Park EC, Jang SI. The diagnosis of healthcare policy problems in Korea. Journal of the Korean Medical Association/Taehan Uisa Hyophoe Chi. 2012;55(10):932
Akinci F, Esatoglu AE, Tengilimoglu D, Parsons A. Hospital choice factors: a case study in Turkey. Health Marketing Quarterly. 2005;22(1):3-19.
Lane PM, Lindquist JD. Hospital choice: A summary of the key empirical and hypothetical findings of the 1980s. Journal of Health Care Marketing. 1988;8(4):5.
Wagner AK, Soumerai SB, Zhang F, RossDegnan D. Segmented regression analysis of interrupted time series studies in medication use research. Journal of Clinical Pharmacy and Therapeutics. 2002;27(4):299-309.
Massarweh NN, Flum DR, Symons RG, Varghese TK, Pellegrini CA. A critical evaluation of the impact of Leapfrog's evidence-based hospital referral. Journal of the American College of Surgeons. 2011;212(2):150-9.e1.
Ross JS, Sheth S, Krumholz HM. State-sponsored public reporting of hospital quality: results are hard to find and lack uniformity. Health Affairs. 2010;29(12):2317-22.
Bloom PN. Studying consumer responses to the changing information environment in health care: A research agenda. NA-Advances in Consumer Research Volume 24. 1997;24:360-65
Kim S, Kwon S. Impact of the policy of expanding benefit coverage for cancer patients on catastrophic health expenditure across different income groups in South Korea. Social Science Medicine Journal. 2015;138:241-7.
Kim S, Kwon S. The effect of extension of benefit coverage for cancer patients on health care utilization across different income groups in South Korea. International Journal of Health Care Finance and Economics. 2014;14(2):161-77.
Han KT, Kim J, Nam CM, Moon KT, Lee SG, Kim SJ, et al. Association between reduction in copayment and gastric cancer patient concentration to the capital area in South Korea: NHI cohort 2003-2013. Health Policy. 2016.
Kim SJ, Han K-T, Park E-C, Park S, Kim TH. Copayment policy effects on healthcare spending and utilization by Korean lung cancer patients at end of life: a retrospective cohort design 2003-2012. Asian Pacific Journal of Cancer Prevention. 2013;15(13):5265-70.
Pross C, Averdunk L-H, Stjepanovic J, Busse R, Geissler A. Health care public reporting utilization- user clusters, web trails, and usage barriers on Germany's public reporting portal Weisse-Liste. de. BMC Medical Informatics and Decision Making. 2017;17(1):48.
Casalino LP, Elster A, Eisenberg A, Lewis E, Montgomery J, Ramos D. Will pay-for-performance and quality reporting affect health care disparities? Health Affairs(Millwood). 2007;26(3) w405-w414.
Behague DP, Victora CG, Barros FC. Consumer demand for caesarean sections in Brazil: informed decision making, patient choice, or social inequality? A population based birth cohort study linking ethnographic and epidemiological methods. BMJ. 2002;324:942.
Farley DO, Short PF, Elliott MN, Kanouse DE, Brown JA, Hays RD. Effects of CAHPS health plan performance information on plan choices by New Jersey Medicaid beneficiaries. Health Services Research Journal. 2002;37(4):985-1007.
Davies HT, Washington AE, Bindman AB. Health care report cards: implications for vulnerable patient groups and the organizations providing them care. Journal of Health Politics, Policy and Law. 2002;27(3):379-400.
Faber M, Bosch M, Wollersheim H, Leatherman S, Grol R. Public reporting in health care: How do consumers use quality-of-care information?: A systematic review. Medical Care. 2009;47(1):1-8.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.