Qualitative methods: what are they and why use them?

Robert P. Luciano Professor of Health Care Policy, School of Public Affairs, Baruch College, New York, New York 10010, USA.
Health Services Research (Impact Factor: 2.49). 01/2000; 34(5 Pt 2):1101-18.
Source: PubMed

ABSTRACT To provide an overview of reasons why qualitative methods have been used and can be used in health services and health policy research, to describe a range of specific methods, and to give examples of their application.
Classic and contemporary descriptions of the underpinnings and applications of qualitative research methods and studies that have used such methods to examine important health services and health policy issues.
Qualitative research methods are valuable in providing rich descriptions of complex phenomena; tracking unique or unexpected events; illuminating the experience and interpretation of events by actors with widely differing stakes and roles; giving voice to those whose views are rarely heard; conducting initial explorations to develop theories and to generate and even test hypotheses; and moving toward explanations. Qualitative and quantitative methods can be complementary, used in sequence or in tandem. The best qualitative research is systematic and rigorous, and it seeks to reduce bias and error and to identify evidence that disconfirms initial or emergent hypotheses.
Qualitative methods have much to contribute to health services and health policy research, especially as such research deals with rapid change and develops a more fully integrated theory base and research agenda. However, the field must build on the best traditions and techniques of qualitative methods and must recognize that special training and experience are essential to the application of these methods.

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    ABSTRACT: The Affordable Care Act includes provisions to standardize the collection of data on health care quality that can be used to measure disparities. We conducted a qualitative study among leaders of Medicaid managed care plans, that currently have access to standardized quality data stratified by race and ethnicity, to learn how they use it to address disparities. We conducted semi-structured interviews with 21 health plan leaders across 9 Medicaid managed care plans in California. We used purposive sampling to maximize heterogeneity in geography and plan type (e.g., non-profit, commercial). We performed a thematic analysis based on iterative coding by two investigators. We found 4 major themes. Improving overall quality was tightly linked to a focus on standardized metrics that are integral to meeting regulatory or financial incentives. However, reducing disparities was not driven by standardized data, but by a mix of factors. Data were frequently only examined by race and ethnicity when overall performance was low. Disparities were attributed to either individual choices or cultural and linguistic factors, with plans focusing interventions on recently immigrated groups. While plans' efforts to address overall quality were often informed by standardized data, actions to reduce disparities were not, at least partly because there were few regulatory or financial incentives driving meaningful use of data on disparities. Standardized data, as envisaged by the Affordable Care Act, could become more useful for addressing disparities if they are combined with policies and regulations that promote health care equity.
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