Health Services Research 

About: Health Services Research is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Health care & Medicaid. It has an ISSN identifier of 0017-9124. Over the lifetime, 4160 publications have been published receiving 194456 citations. The journal is also known as: HSR.

Enhancing the quality and credibility of qualitative analysis.

Abstract: Varying philosophical and theoretical orientations to qualitative inquiry remind us that issues of quality and credibility intersect with audience and intended research purposes. This overview examines ways of enhancing the quality and credibility of qualitative analysis by dealing with three distinct but related inquiry concerns: rigorous techniques and methods for gathering and analyzing qualitative data, including attention to validity, reliability, and triangulation; the credibility, competence, and perceived trustworthiness of the qualitative researcher; and the philosophical beliefs of evaluation users about such paradigm-based preferences as objectivity versus subjectivity, truth versus perspective, and generalizations versus extrapolations. Although this overview examines some general approaches to issues of credibility and data quality in qualitative analysis, it is important to acknowledge that particular philosophical underpinnings, specific paradigms, and special purposes for qualitative inquiry will typically include additional or substitute criteria for assuring and judging quality, validity, and credibility. Moreover, the context for these considerations has evolved. In early literature on evaluation methods the debate between qualitative and quantitative methodologists was often strident. In recent years the debate has softened. A consensus has gradually emerged that the important challenge is to match appropriately the methods to empirical questions and issues, and not to universally advocate any single methodological approach for all problems.

Qualitative data analysis for health services research: developing taxonomy, themes, and theory.

Abstract: Qualitative research is increasingly common in health services research (Shortell 1999; Sofaer 1999). Qualitative studies have been used, for example, to study culture change (Marshall et al. 2003; Craigie and Hobbs 2004), physician–patient relationships and primary care (Flocke, Miller, and Crabtree 2002; Gallagher et al. 2003; Sobo, Seid, and Reyes Gelhard 2006), diffusion of innovations and quality improvement strategies (Bradley et al. 2005; Crosson et al. 2005), novel interventions to improve care (Koops and Lindley 2002; Stapleton, Kirkham, and Thomas 2002; Dy et al. 2005), and managed care market trends (Scanlon et al. 2001; Devers et al. 2003). Despite substantial methodological papers and seminal texts (Glaser and Strauss 1967; Miles and Huberman 1994; Mays and Pope 1995; Strauss and Corbin 1998; Crabtree and Miller 1999; Devers 1999; Patton 1999; Devers and Frankel 2000; Giacomini and Cook 2000; Morse and Richards 2002) about designing qualitative projects and collecting qualitative data, less attention has been paid to the data analysis aspects of qualitative research. The purpose of this paper is to offer practical strategies for the analysis of qualitative data that may be generated from in-depth interviewing, focus groups, field observations, primary or secondary qualitative data (e.g., diaries, meeting minutes, annual reports), or a combination of these data collection approaches.

Achieving Integration in Mixed Methods Designs—Principles and Practices

Abstract: Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs—exploratory sequential, explanatory sequential, and convergent—and through four advanced frameworks—multistage, intervention, case study, and participatory. Integration at the methods level occurs through four approaches. In connecting, one database links to the other through sampling. With building, one database informs the data collection approach of the other. When merging, the two databases are brought together for analysis. With embedding, data collection and analysis link at multiple points. Integration at the interpretation and reporting level occurs through narrative, data transformation, and joint display. The fit of integration describes the extent the qualitative and quantitative findings cohere. Understanding these principles and practices of integration can help health services researchers leverage the strengths of mixed methods.

Development of the Patient Activation Measure (PAM): Conceptualizing and Measuring Activation in Patients and Consumers

Abstract: Two significant emerging policy directions put patients and consumers in a key role for influencing health care quality and costs. First, consumer-directed health plans rely on informed consumer choices to contain costs and improve the quality of care. This approach assumes that consumers will make more prudent health and health care choices when they are given financial incentives along with access to comparative cost and quality information. This approach also assumes that the combination of financial incentives and relevant information will increase their “activation” (Gabel, Lo Sasso, and Rice 2002). Second, the Chronic Illness Care Model (Bodenheimer et al. 2002) emphasizes patient-oriented care, with patients and their families integrated as members of the care team. A critical element in the model is activated patients, with the skills, knowledge, and motivation to participate as effective members of the care team (Von Korff et al. 1997). A key health policy question is, what would it take for consumers to become effective and informed managers of their health and health care? What skills, knowledge, beliefs, and motivations do they need to become “activated” or more effectual health care actors? These are essential questions if we hope to improve the health care process, the outcomes of care, and control costs. This is true especially with regard to the 99 million Americans with a chronic disease. Because those with chronic illness need ongoing care, account for a large portion of health care costs, and must play an important role in maintaining their own functioning, encouraging their activation should be a priority. Even though patient activation is a central concept in both the consumer driven health care approach and the chronic illness care models, it remains conceptually and empirically underdeveloped. There has been a lack of conceptual clarity regarding “activation,” and thus a lack of adequate measurement. There are a number of existing methods for assessing different aspects of activation, such as health locus of control (Wallston, Stein, and Smith), self-efficacy in self-managing behaviors (Lorig et al. 1996), and readiness to change health-related behaviors (DiClemente et al. 1991; Prochaska, Redding, and Evers 1997), but these measures tend to focus on the prediction of a single behavior. Moreover, there is no existing measure that includes the broad range of elements involved in activation, including the knowledge, skills, beliefs, and behaviors that a patient needs to manage a chronic illness. In this paper we describe the development of the Patient Activation Measure (PAM), a measure of activation that is grounded in rigorous conceptualization and appropriate psychometric methods. The PAM was developed in four stages: Stage 1.Conceptually defining activation involved a literature review, systematic consultation with experts using a “consensus method,” and consultation with individuals with chronic disease using focus groups. Stage 2.Preliminary scale development began by building on the domains identified in stage one and operationalizing them with survey items within each domain. Steps included generating, refining, and testing a large item pool. We used Rasch psychometric methods to develop the scale and test the preliminary measure's psychometric properties. Stage 3.Stage three involved exploring the possibility of extending the range of the measure, refining the response categories, and testing whether the measure could be used with respondents who had no chronic illnesses. Stage 4.In the fourth and final stage a national probability sample was used to assess the performance of the measure across different subsamples in the population and to assess the construct validity of the measure.

A framework for the study of access to medical care.

Abstract: Definitions and aspects of the concept of access to medical care are reviewed and integrated into a framework that views health policy as designed to affect characteristics of the health care delivery system and of the population at risk in order to bring about changes in the utilization of health care services and in the satisfaction of consumers with those services. Indicators are suggested for the measurement of the various relevant aspects of access, with the system and population descriptors seen as process indicators and utilization and satisfaction as outcome indicators in a theoretical model of the access concept.