Objective: This study outlines predictors of cancer patients' overall perceptions of the quality of care.
Design And Setting: Our sample included 2790 patients who received cancer care services during 2004 in 15 comprehensive cancer programmes across Ontario, Canada. Patients were classified into three groups: those receiving both chemotherapy and radiotherapy (n = 752), those receiving only chemotherapy (n = 1044), and those receiving only radiotherapy (n = 994). An ordinal logistic regression model for each patient group was performed to determine which variables most affected the probabilities of the patients' overall evaluations of the quality of care. Potential control variables were patients' age, sex, type of cancer, self-assessed health, and who completed the survey.
Results: Among seven common predictors of the overall quality perception across the three models, four should be of particular interest because patients perceived them as relatively problematic aspects of care. These are 'was informed about follow-up care after completing treatment', 'knew next step in care', 'knew who to go to with questions', and 'providers were aware of test results'. These predictors explained between 25 and 34% of the variance (depending on the model) of the overall perception of quality. The explanatory power of these predictors did not change across sex and age group. 'Self-assessed health' was the only control variable that remained in all three models.
Conclusions: From a practical perspective, improvement efforts are best focused on factors that are strong predictors as well as on those for which there is a low score. Thus, on the basis of this study, practitioners' improvement efforts might be constructively focused on the four predictors mentioned above.
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http://dx.doi.org/10.1093/intqhc/mzl014 | DOI Listing |
World J Surg Oncol
January 2025
Department of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China.
Objective: This study aimed to evaluate and compare the clinicopathologic features of primary fallopian tubal carcinoma (PFTC) and high-grade serous ovarian cancer (HGSOC) and explore the prognostic factors of these two malignant tumors.
Methods: Fifty-seven patients diagnosed with PFTC from 2006 to 2015 and 60 patients diagnosed with HGSOC from 2014 to 2015 with complete prognostic information were identified at Women's Hospital of Zhejiang University. The clinicopathological and surgical data were collected, and the survival of the patients was followed for 5 years after surgery.
BMC Health Serv Res
January 2025
Institute for Health and Nursing Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
Background: Cancer requires interdisciplinary intersectoral care. The Care Coordination Instrument (CCI) captures patients' perspectives on cancer care coordination. We aimed to translate, adapt, and validate the CCI for Germany (CCI German version).
View Article and Find Full Text PDFJ Med Case Rep
January 2025
Department of Pathology and Laboratories, University Hospital Fundación Santa Fe de Bogotá, Bogotá, DC, Colombia.
Background: Adenoid cystic carcinoma of the breast is a rare subtype, constituting less than 3.5% of primary breast carcinomas. Despite being categorized as a type of triple-negative breast cancer, it generally has a favorable prognosis.
View Article and Find Full Text PDFWorld J Surg Oncol
January 2025
Institute of Oncology, Tel Aviv Sourasky Medical Center, Weizmann St 6, Tel Aviv, Israel.
Background: De-intensification of anti-cancer therapy without significantly affecting outcomes is an important goal. Omission of axillary surgery or breast radiation is considered a reasonable option in elderly patients with early-stage breast cancer and good prognostic factors. Data on avoidance of both axillary surgery and radiation therapy (RT) is scarce and inconclusive.
View Article and Find Full Text PDFBiomark Res
January 2025
Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.
Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.
Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).
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