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Objective: To investigate the relationship between emergency department (ED) design and performance under different conditions of clinical uncertainty - respiratory disease (high uncertainty) and minor injuries (low uncertainty) - within the Department of Veterans Affairs (VA) healthcare system. Methods: ED design features were identified using an information processing approach based on structural contingency theory. The first aim considered net effects of individual design features on performance (admission and 72-hour return rates) using multivariate linear regression. The second aim considered causal complexity and measured the effect of design combinations on high performance using fuzzy-set qualitative comparative analysis. Organizational characteristics were obtained from 2007 Survey of Emergency Departments and Urgent Care Clinics in VHA data from 95 VA EDs, which were linked to secondary VA clinical data for a sub-set of patients with a VA ED encounter between 10/1/2007 and 6/30/2008. Results: Net effects of individual design features (regression results) showed weak empirical support for hypotheses. High use of information technology was associated with slightly lower 72-hour return rates while high guideline use was associated with slightly higher admission rates under different conditions of uncertainty. EDs with both an observation unit and high guideline use had better performance on admission rates under high uncertainty conditions than EDs using only one of the design features. Qualitative comparative analysis results indicate that observation units are a sufficient measure for high performance in the high uncertainty group. No other single design feature was consistently associated with high performance. Several design combinations were consistently associated with high performance at different levels of uncertainty. Conclusions: Empirical support for the theoretical approach was mixed. While the effect of individual ED design features on high performance is influenced by the level of task uncertainty, in practice these features do not occur in isolation and performance is influenced by combinations of design features. A variety of design combinations can lead to the same level of performance which has important implications for work performance, resource allocation, quality improvement and implementation of services. Understanding how different levels of uncertainty influence care delivery can aide in designing more efficient operations across a range of patients. |
