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Resilient healthcare research focuses on everyday clinical work and a system’s abilities to adopt or absorb disturbing conditions as opposed to risk management approaches, which are based on retrospective analyses of errors. After more than a decade of theoretical development and a large quantity of empirical work, the field of resilience is beginning to recognize the methodological challenges related to operationalizing and designing studies of complexity. This paper reviews a sample of empirical articles on studies of resilient healthcare to describe and synthesize their methodological strategies. The review found that data collection by resilient healthcare studies has predominantly been conducted at the micro level (e.g. frontline clinical staff). Data sources at the meso level (i.e. hospital/institution) have been limited, and no studies were found that collected macro-level data. We argue that the methodological focus in the field should increase its embrace of complexity and the adaptive capacities of the system as a whole by integrating data sources at the micro, meso, and macro levels. To improve the methodological designs, we argue that the resilience construct, in which the complexity of multiple levels is integrated, must be developed. Improving the transparency and quality of future resilient healthcare research might be accomplished by reporting thorough descriptions of analytical strategies, in-depth descriptions of research design and sampling strategies, and discussing internal and external validity and reflexivity.
Berg et al. (Wed,) studied this question.