Related Experiment Videos
Cancer Quality-ASSIST supportive oncology quality indicator set: feasibility, reliability, and validity testing
Sydney M Dy1, Karl A Lorenz, Sean M O'Neill
1Department of Health Policy and Management, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA. sdy@jhsph.edu
Cancer
|June 22, 2010
Summary
Researchers evaluated 92 quality indicators for advanced cancer care, finding 41 feasible, reliable, and valid for assessing symptom management and supportive care processes.
Area of Science:
- Oncology
- Healthcare Quality Improvement
- Palliative Care
Background:
- Measuring quality of symptom management and end-of-life care is crucial for improving supportive care in advanced cancer.
- Few quality indicators in this domain have been rigorously developed or evaluated.
Purpose of the Study:
- To pilot evaluate a comprehensive set of 92 supportive oncology quality indicators, named Cancer Quality-ASSIST.
- To assess the feasibility, inter-rater reliability, and validity of these indicators in advanced cancer patients.
Main Methods:
- Operationalized 92 indicators (Cancer Quality-ASSIST) covering symptoms, treatment toxicity, information, and care planning.
- Developed an electronic abstraction tool and training materials.
- Abstracted medical records for 356 advanced cancer patients across two healthcare settings.
Main Results:
- Successfully evaluated 78 indicators, with similar results in both settings.
- Identified 41 indicators as most promising for further testing and use, demonstrating sufficient feasibility, reliability, and validity.
- Achieved an overall kappa score of 0.85 for specified care, indicating good agreement.
Conclusions:
- 41 out of 92 Cancer Quality-ASSIST indicators are suitable for use in advanced cancer patients.
- This validated set of indicators can effectively describe key supportive care processes in advanced cancer settings.
Related Concept Videos
01:21Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
01:19Quality Assurance
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
01:29Reliability and Validity
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
01:17Cochran's Q Test
Cochran's Q Test is a nonparametric statistical test used to determine if there are potential differences in the outcomes of three or more related groups on a binary (yes/no) or dichotomous outcome. It is essentially an extension of the McNemar Test, which is limited to two related samples - Cochran's Q test can handle three or more related samples, making it more versatile in scenarios where subjects are measured under multiple conditions. The test statistic follows a Chi-Square distribution,...