Organizations and groups use dashboards to provide updated reports resulting from changes in formula inputs, treatments, and sample groupings. Dashboards allow for the leverage of big data and facilitate decision making based on evidence. Effective workplace wellness programs (WWPs) realize the need to reconcile employee health, for which monitoring has been difficult, through wellness interventions and activities (Mattke et al., 2013).
Purpose: The purpose of this project is to describe the collaborative development of a Microsoft Excel dashboard to support and monitor an employee wellness program. The dashboard intended to expedite the review and management of a health program using biometric data within an easily accessible software application.
Methods: Specific steps in the iterative process of the dashboard development included: identifying key measures, identifying source(s) of data, determining optimal benchmarks or thresholds, identifying the timeframe for data inclusion and analysis, dashboard design, dashboard implementation, and review of dashboard monitoring (Russell, Hogg, Leach, Penman, & Friel, 2014; Spetz et al., 2014). Retrospective data vis-à-vis cardiac risk factors and lifestyle characteristics were gathered during employee health and wellness screenings. The raw data were downloaded into Microsoft Excel and organized. Later, data were cleaned, then explored by integrating data into specific cluster participation groups. Subject matter experts on the project team worked initially to identify key measures and associated thresholds (according the American Heart Association [2018] guidelines) related to cardiac risk factors.
Results: Cluster participation among subjects were directly determined by the thresholds, which were subject to ongoing deliberation in scientific discourse. Visual displays were automatically updated based on changes in the data and thresholds for variables. Descriptive statistics, visual sample summaries, and theoretical tests all reflected identified clusters. Thus, at any given threshold setting, the dashboard reflected the state of cluster membership as indicated by the metrics.
Conclusion: This demonstration, implemented with minimal resources, has implications for nursing research and practice. It illuminates how dashboards can help provide practice-based evidence, allowing employee health nurses to more expeditiously track the status of participants and to evaluate the impact on specific and targeted health initiatives in the workplace. These evaluations are based on sound and objective data for assessing participants’ health and lifestyle statuses. We will discuss data quality, dashboard utility, as well as lessons learned in the process. The extension and practical application of this dashboard will also be shared with participants.