Quali-quantitative analysis: a new model for evaluation of unusual cases in hospital performance?

Abstract

This paper aims to provide hospital administrators and others making decisions about hospital error funding, as well as researchers, with information about what good hospital error research looks like. It offers a selective review of how the error literature has approached hospital error, which is used to develop five criteria for sound hospital error research. It also explores the potential for better hospital error research of quali-quantitative analysis (QQA), an innovative social sciences research method. In a context in which other methodologies all have their shortcomings, QQA appears to go some way toward meeting the five criteria for sound hospital error research. Ideally, QQA would be used in combination with other approaches to answer the kinds of questions that are important to hospital administrators when they are faced with high-stakes CONSIDERABLE MEDIA AND POLICY attention is given to the high stakes "unusual cases" (such as error and/or professional misconduct) in hospital service delivery. But how can hospital administrators and policy decision makers prevent such cases from happening in the first place? This paper describes the research methods that have been used to understand hospital error. It also explores the potential of a transdisciplinary research method (quali-quantitative analysis[QQA]) for understanding hospital error and its causes, particularly in small-N studies.Without sound practices for investigating and preventing errors, the most accurate and full error reporting systems are meaningless. Knowledge about what works and what doesn't in error research methodology is critical to managing error. Accordingly, this paper aims to provide information and criteria for deciding on the kind of study of hospital error likely to deliver sound evidence for policy and practice. The paper should also be of interest to researchers of hospital error interested in questions of research technique.

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“…Quali-quantitative analysis complements the systematicity of quantitative research -most often through the adoption of digital tools for data gathering, analysis, or data visualization -with the interpretative focus of qualitative research. An additional advantage is that this qualitative interpretation of data can enrich the typical statistical analyses of quantitative research, in which data is usually homogenized, and critical details may be overlooked (Bell, 2007;Moats & Borra, 2018) To illustrate, Moats and Borra consider network analysis to be an ultimate example of quali-quantitative research, given the possibilities it provides for data visualization, the discovery of broader patterns, and the detailed exploration of connections between the data.…”