Qualitative research methods

焦点小组 质量(理念) 定性研究 利益相关者 定性性质 医疗保健 过程管理 知识管理 数据收集 质量管理 集合(抽象数据类型) 最佳实践 计算机科学 管理科学 营销 业务 公共关系 工程类 哲学 统计 数学 管理 认识论 服务(商务) 机器学习 社会学 政治学 经济 程序设计语言 经济增长 社会科学
作者
Shoshanna Sofaer
出处
期刊:International Journal for Quality in Health Care [Oxford University Press]
卷期号:14 (4): 329-336 被引量:250
标识
DOI:10.1093/intqhc/14.4.329
摘要

The use of rigorous qualitative research methods can enhance the development of quality measures, the development and dissemination of comparative quality reports, as well as quality improvement efforts. This paper describes how such methods have been and can be used, and identifies how to improve the use of such methods in studying quality of care. Focus groups and cognitive interviews are now a standard part of the development of valid and reliable survey instruments. They are particularly useful in developing surveys to gather data on the experiences and responses of patients and consumers to plans, services, and providers. These two methods have also been adapted and applied to improve the development and dissemination of comparative quality reports to consumers and other audiences, while key informant interviews and focus groups have been critical in the exploratory assessment of stakeholder responses to reports and their effects on consumers. Interviews have also been used to identify best practices found in health plans receiving high scores on the Consumer Assessment of Health Plans Surveys and measures of effectiveness in the Health Employer Data and Information Set. It would be valuable to widen the use of qualitative methods, especially structured observations, to document in detail the delivery of services designed to improve quality, so the implementation of complex processes can be more carefully measured and related to outcomes. The design and conduct of rigorous qualitative research takes a skilled and experienced team. Issues commonly faced in quantitative work must also be addressed in qualitative studies, including study design, specification of the unit of analysis, sampling, instrument design and administration, and, in particular, data analysis. It is especially critical that the analysis and interpretation process be deliberate and thorough to avoid the use of initial impression rather than detailed examination of the raw data.

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