Méthode d’opérationnalisation de mesures de la performance sensibles aux soins infirmiers basées sur des données de routine
Author:
Rapin Joachim,Santos Gabrielle Cécile,Pouzols Sophie,D’Amour Danielle,Dubois Carl-Ardy,Mabire Cédric
Abstract
Introduction: The operationalization of nursing-sensitive performance measures has been highly variable. It results in measures that are sometimes suboptimal and difficult for managers and nurses to access. The objective is to propose a rigorous method for operationalizing nurse-sensitive performance measures based on routine data. Source of Information: The primary source of information for this article is an operationalization method adapted from a reporting guide and performance measure evaluation instrument. It includes 7 processes and 33 interrelated quality attributes. The application of this operationalization method was successfully tested in a university hospital. Discussion: Operationalization of nursing-sensitive performance measures is a complex process. This method is an original proposal that allows for the justification and argumentation of the choices made. We discuss how this method is a response to 3 methodological issues: (1) heterogeneous and poorly detailed operationalization methods; (2) critical attributes (e.g., relevance, scientific validity, feasibility) that lack consensus and (3) heterogeneous data architecture models. Implication and conclusion: This operationalization method provides a systematic and transparent approach to generating nursing-sensitive performance measures from routine data. It could improve their operationalization, facilitate their understanding and evaluation.
Publisher
Consortium Erudit
Reference58 articles.
1. Aiken, L. H. (2008). Economics of nursing. Policy, Politics, & Nursing Practice, 9(2), 73-79. https://doi.org/10.1177/1527154408318253 2. Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., & Silber, J. H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA: Journal of the American Medical Association, 288(16), 1987-1993. https://doi.org/10.1001/jama.288.16.1987 3. Aiken, L. H., Sloane, D., Griffiths, P., Rafferty, A. M., Bruyneel, L., McHugh, M., Maier, C. B., Moreno-Casbas, T., Ball, J. E., Ausserhofer, D., & Sermeus, W. (2016). Nursing skill mix in European hospitals: cross-sectional study of the association with mortality, patient ratings, and quality of care. BMJ Quality & Safety, 26(7), 559-568. http://dx.doi.org/10.1136/bmjqs-2016-005567 4. Baernholdt, M., Dunton, N., Hughes, R. G., Stone, P. W., & White, K. M. (2018). Quality Measures: A Stakeholder Analysis. Journal of Nursing Care Quality, 33(2). https://doi.org/10.1097/NCQ.0000000000000292 5. Barchielli, C., Rafferty, A. M., & Vainieri, M. (2022). Integrating Key Nursing Measures into a Comprehensive Healthcare Performance Management System: A Tuscan Experience. International Journal of Environmental Research and Public Health, 19(3), 1373. https://www.mdpi.com/1660-4601/19/3/1373
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