Methodological Challenges of Validating a Clinical Decision-Making Tool in the Practice Environment. (April 2015)

• Record Type: Journal Article
• Authors: Brennan, Caitlin W.; Daly, Barbara J.
• Is Part Of: Western journal of nursing research. Volume 37:Number 4(2015)
• Page Start: 536
• Page End: 545
• Publication Date: 2015-04
• Subjects: oncology -- acute care -- instrument development -- nurse staffing -- acuity; Nursing -- Research -- Periodicals; Nursing -- Periodicals; Nursing -- Research -- West (U.S.) -- Periodicals; Nursing -- West (U.S.) -- Periodicals; Nursing -- Periodicals; Nursing Research -- Periodicals; Soins infirmiers -- Recherche -- Périodiques; Soins infirmiers -- Périodiques; Soins infirmiers -- Recherche -- États-Unis (Ouest) -- Périodiques; Soins infirmiers -- États-Unis (Ouest) -- Périodiques; Soins infirmiers; Recherche; États-Unis (Ouest); Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 610.730702
• DOI: 10.1177/0193945914539738
• Languages: English
• ISSNs: 0193-9459

Abstract

Validating a measurement tool intended for use in the practice environment poses challenges that may not be present when validating a tool intended solely for research purposes. The aim of this article is to describe the methodological challenges of validating a clinical decision-making tool, the Oncology Acuity Tool, which nurses use to make nurse assignment and staffing decisions prospectively each shift. Data were derived from a larger validation study, during which several methodological challenges arose. Revisions to the tool, including conducting iterative feedback cycles with end users, were necessary before the validation study was initiated. The "true" value of patient acuity is unknown, and thus, two approaches to inter-rater reliability assessment were used. Discordant perspectives existed between experts and end users. Balancing psychometric rigor with clinical relevance may be achieved through establishing research–practice partnerships, seeking active and continuous feedback with end users, and weighing traditional statistical rules of thumb with practical considerations.