Our proposed basic research program will enhance the scientific application of social network analysis (SNA) to health care in several ways: First, we will compare information sharing and decision-making networks in hospital nursing units (wards) to further clarify how these network structures and processes relate to nursing- sensitive patient outcomes. Second, we will use *ORA, a dynamic network analysis tool, to identify a robust, but parsimonious, set of network properties (i.e., metrics or sets of metrics) that measure network stability and congruence (fit) with unit environmental features and association with patient safety and quality outcomes. Finally, we will use the new metrics to test a novel model of network stability and congruence based on a variety of hospital nursing units over time and under variations in unit physical layout, workgroup characteristics, staff expertise, communication technology, and workflow exceptions as a means to develop new theory. We have 4 specific aims:
Aim 1. Compare the structure of nursing unit decision making and information sharing networks within and across shifts.
Aim 2. Identify a robust, but parsimonious, set of key network metrics that can be used to measure information sharing and decision-making network stability longitudinally.
Aim 3. Identify network metrics to measure congruence of nursing unit information sharing and decision- making networks to nursing unit contextual features (unit type, physical layout, workgroup characteristics, staff expertise, and communication technology).
Aim 4. Develop and investigate nursing unit information sharing and decision-making network stability and congruence profiles associated with high and low levels of nursing-sensitive patient safety and quality outcomes. Our highly experienced team was the first to use SNA to explore how nursing unit information sharing networks relate to nursing-sensitive patient outcomes. Accomplishing these 4 specific aims will build on our previous findings to improve our understanding of how changes in information-sharing and decision-making networks over time and across shifts relate to patient safety and quality outcomes. Although hospital nursing units provide the context for this research, the problems we are addressing are generic in SNA research;therefore, we expect our results to generalize broadly and thereby expand the applicability of SNA to the healthcare arena.
The proposed basic research will enhance the scientific application of social network analysis (SNA) to health care The proposed research will enhance scientific knowledge by identifying a robust, but parsimonious set of network properties that are associated with patient safety and quality outcomes and are relatively stable over time, something about which little is known, as well as have congruence (fit) with unit environmental features. Finally, we will use the new metrics to test a novel model of network stability and congruence based on a variety of hospital nursing units over time and under variations in unit physical layout, workgroup characteristics, staff expertise, communication technology, and workflow exceptions as a means to develop new theory.
| Brewer, Barbara B; Carley, Kathleen M; Benham-Hutchins, Marge M et al. (2018) Relationship of Staff Information Sharing and Advice Networks to Patient Safety Outcomes. J Nurs Adm 48:437-444 |
