Research of the relationship among quality of care and quality of life in patients with breast cancer: Application of core measures indicators and multilevel analysis

• Main Authors: Wan-Lin Tang, 湯婉琳
• Other Authors: 鍾國彪
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/13914918214731462898

碩士 === 國立臺灣大學 === 健康政策與管理研究所 === 100 === Background: Quality of care and quality of life in patients with breast cancer are becoming important in every contries. And there are some treatment guidelines for patients with breast cancer. In order to improve care quality and benchmark among cancer care hospitals, the Bureau of Health Promotion supported a project for quality improvement mechanism that included establishing six cancer core measure sets by research team of College of Public Health, National Taiwan University. There are more breast cancer researches than other kinds of cancers. However, there are limited searches to discuss the relationship between quality of care and quality of life. This study attempt to using breast cancer core measure set to measure the quality of care in patients with breast cancer, and investigate the relationship among quality of care and quality of life in ptients. Furthermore, it also verifies the influence of hospital-level on patient-level. Method: This is a cross-sectional study. The patients were recruited at 19 hospitals in Taiwan. All samples came from convenient sampling. There were 670 valid samples with collection period from January first to July 31, year 2011. The study divided into two parts. The first part, a survey was conducted by using structured questionnaires to collect patients’ demographic, clinical characteristics and quality of life. The second part, we using TCDB and NHI database to collect patients’ demographic and clinical characteristics, hospital characteristics and volume, as well as the treatment. To measure the quality of care, this study use case-based approach to find out the care services each patient received in the whole care process from pretreatment to treatment. Quality of life was measured by the EORTC QLQ-C30 and QLQ-BR23. The subjective core measure compliance was obtained from questionnaires, and the objective core measure compliance was obtained from database. The data is analyzed by methods of descriptive statistics, independent-samples t-test, one-way ANOVA, and Hierarchical Linear Modeling(HLM). Results: In the first part, a total of 670 samples were valid at 19 hospitals. And in the second part, a total of 204 samples were valid. From multiple regression analysis, after controlled for patients’ demographic, clinical characteristics and hospital characteristics, patient’s subjective core measure compliance is related to 10 dimensions in QLQ-C30 and QLQ-BR23. The predictive power of whole model toward quality of life crossed from 15.3%-44.2%. However, patient’s objective core measure compliance is related to 4 domains in QLQ-C30 and QLQ-BR23. The predictive power of whole model toward quality of life crossed from 15.3%-44.2%. From HLM, the cross-level effect for “hospital-level variables” is confirmed between “patient-level variables” and “quality of life’’ in this research. Conclusion: In regression models, higher core measure compliance was associated with better overall QOL, role functioning, emotional functioning, body image, sexual functioning, sexual enjoyment, future perspective, pain, financial difficulties, systemic therapy side effects and breast symptoms, controlling for covariates. And the hospital-level variables (hospital accreditation level and location), does not only explain the different quality of life (physical functioning, financial difficulties, sexual functioning, future perspective) of patients among across the hospital, but also moderate the association between the patients’ demographic (education attainment, and household income), clinical characteristics (stage) and core measure compliance.