Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience

dc.contributor.authorWomack, Dana M.
dc.contributor.authorMiech, Edward J.
dc.contributor.authorFox, Nicholas J.
dc.contributor.authorSilvey, Linus C.
dc.contributor.authorSomerville, Anna M.
dc.contributor.authorEldredge, Deborah H.
dc.contributor.authorSteege, Linsey M.
dc.contributor.departmentSchool of Nursing
dc.date.accessioned2024-06-12T16:39:55Z
dc.date.available2024-06-12T16:39:55Z
dc.date.issued2022-08
dc.description.abstractObjectives  The purpose of this study is to identify combinations of workplace conditions that uniquely differentiate high, medium, and low registered nurse (RN) ratings of appropriateness of patient assignment during daytime intensive care unit (ICU) work shifts. Methods  A collective case study design and coincidence analysis were employed to identify combinations of workplace conditions that link directly to high, medium, and low RN perception of appropriateness of patient assignment at a mid-shift time point. RN members of the study team hypothesized a set of 55 workplace conditions as potential difference makers through the application of theoretical and empirical knowledge. Conditions were derived from data exported from electronic systems commonly used in nursing care. Results  Analysis of 64 cases (25 high, 24 medium, and 15 low) produced three models, one for each level of the outcome. Each model contained multiple pathways to the same outcome. The model for “high” appropriateness was the simplest model with two paths to the outcome and a shared condition across pathways. The first path comprised of the absence of overtime and a before-noon patient discharge or transfer, and the second path comprised of the absence of overtime and RN assignment to a single ICU patient. Conclusion  Specific combinations of workplace conditions uniquely distinguish RN perception of appropriateness of patient assignment at a mid-shift time point, and these difference-making conditions provide a foundation for enhanced observability of nurses' work experience during hospital work shifts. This study illuminates the complexity of assessing nursing work system status by revealing that multiple paths, comprised of multiple conditions, can lead to the same outcome. Operational decision support tools may best reflect the complex adaptive nature of the work systems they intend to support by utilizing methods that accommodate both causal complexity and equifinality.
dc.eprint.versionFinal published version
dc.identifier.citationWomack, D. M., Miech, E. J., Fox, N. J., Silvey, L. C., Somerville, A. M., Eldredge, D. H., & Steege, L. M. (2022). Coincidence Analysis: A Novel Approach to Modeling Nurses’ Workplace Experience. Applied Clinical Informatics, 13(4), 794–802. https://doi.org/10.1055/s-0042-1756368
dc.identifier.urihttps://hdl.handle.net/1805/41473
dc.language.isoen_US
dc.publisherThieme
dc.relation.isversionof10.1055/s-0042-1756368
dc.relation.journalApplied Clinical Informatics
dc.rightsPublisher Policy
dc.sourcePMC
dc.subjectwork shifts
dc.subjectintensive care unit
dc.subjectnurse
dc.subjectdata analysis
dc.subjectinformation systems
dc.titleCoincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience
dc.typeArticle
ul.alternative.fulltexthttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433166/
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