Manifestations and implications of uncertainty for improving healthcare systems: an analysis of observational and interventional studies grounded in complexity science

Implementation Science

Reuben R McDaniel⁶  Kurt C Stange⁷  William L Miller²  Paul A Nutting⁸  Benjamin F Crabtree¹  Ruth A Anderson⁵  Michael Parchman⁴  Jacqueline A Pugh³  Holly J Lanham⁶  Luci K Leykum⁶ 

[1] Department of Family Medicine, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, New Brunswick, NJ, USA;Lehigh Valley Health Network, Lehigh, PA, USA;University of Texas Health Science Center at San Antonio, San Antonio, TX, USA;MacColl Center for Health Care Innovation, Group Health Research Institute, Seattle, WA, USA;Duke University, Durham, NC, USA;The University of Texas at Austin, Austin, TX, USA;Case Western Reserve University, Cleveland, OH, USA;Department of Family Medicine, University of Colorado School of Medicine, Aurora, CO, USA

关键词: Implementation;    Healthcare systems;    Uncertainty;    Relationships;    Complexity science;   

Others  :  1139483
DOI  :  10.1186/s13012-014-0165-1

 received in 2014-06-13, accepted in 2014-10-27,  发布年份 2014

【 摘 要 】

Background

The application of complexity science to understanding healthcare system improvement highlights the need to consider interdependencies within the system. One important aspect of the interdependencies in healthcare delivery systems is how individuals relate to each other. However, results from our observational and interventional studies focusing on relationships to understand and improve outcomes in a variety of healthcare settings have been inconsistent. We sought to better understand and explain these inconsistencies by analyzing our findings across studies and building new theory.

Methods

We analyzed eight observational and interventional studies in which our author team was involved as the basis of our analysis, using a set theoretical qualitative comparative analytic approach. Over 16 investigative meetings spanning 11 months, we iteratively analyzed our studies, identifying patterns of characteristics that could explain our set of results.

Our initial focus on differences in setting did not explain our mixed results. We then turned to differences in patient care activities and tasks being studied and the attributes of the disease being treated. Finally, we examined the interdependence between task and disease.

Results

We identified system-level uncertainty as a defining characteristic of complex systems through which we interpreted our results. We identified several characteristics of healthcare tasks and diseases that impact the ways uncertainty is manifest across diverse care delivery activities. These include disease-related uncertainty (pace of evolution of disease and patient control over outcomes) and task-related uncertainty (standardized versus customized, routine versus non-routine, and interdependencies required for task completion).

Conclusions

Uncertainty is an important aspect of clinical systems that must be considered in designing approaches to improve healthcare system function. The uncertainty inherent in tasks and diseases, and how they come together in specific clinical settings, will influence the type of improvement strategies that are most likely to be successful. Process-based efforts appear best-suited for low-uncertainty contexts, while relationship-based approaches may be most effective for high-uncertainty situations.

【 授权许可】

   
2014 Leykum et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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