Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers. (December 2018)

• Record Type: Journal Article
• Authors: Chen, Ying; Kao, Shih Ling; Tan, Maudrene; Ning, Yilin; Salloway, Mark; Wee, Hwee Lin; Venkataraman, Kavita; Khoo, Eric Yin Hao; Chow, Yeow Leng; Tai, E-Shyong; Tan, Chuen Seng
• Is Part Of: International journal of medical informatics. Volume 120(2018)
• Page Start: 172
• Page End: 178
• Publication Date: 2018-12
• Subjects: ADA American Diabetes Association -- AIC akaike information criterion -- BG blood glucose -- cdf plot cumulative density function plot -- GEE generalized estimating equations -- OR odds ratio -- pdf plot probability density function plot; Data visualization -- Health personnel -- Guideline adherence -- Perception -- Task performance and analysis -- Quality improvement; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2018.09.006
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Majority of nurses and doctors are familiar with 2 of the 4 plots for distributions. Their performance in identifying adherence to clinical protocols with plots is poor. Their perception on the usability of these plots to monitor adherence is also poor. However, knowing two or more of these plots improves perception. Abstract: Background: Measuring adherence to processes is one of the established ways to quantify the quality of healthcare. Providing timely feedback to healthcare workers on the level of adherence can improve process measures. However, it is challenging to present data on adherence to repetitive time-sensitive tasks in a clear manner. Objectives: We used inpatient glucose monitoring as a test case to explore the feasibility of using visualizations to communicate adherence to repetitive scheduled tasks to healthcare workers. Methods: We selected four candidate plots that represented distribution across time: histogram, probability density function plot (pdf plot), violin plot and cumulative density function plot (cdf plot). Doctors and nurses involved in inpatient diabetes care in a tertiary hospital were invited to complete a self-administered questionnaire that measured self-reported baseline knowledge, performance, and perception towards the visualizations. Performance was assessed by determining if a participant was able to correctly identify visualizations representing protocol adherence. We also assessed the perception of usability of these visualizations for monitoring protocol adherence. Binomial regression models were used to identify factors associated with overall performance and perception. Logistic regression models with generalized estimating equation were used to compare performance and perception between visualizations, and identify effect modifiers. Results: A total of 57 doctors and nurses completed the questionnaire. Participants were most familiar with histogram (87.7%), followed by cdf plot (61.4%), pdf plot (40.4%), and violin plot (7%). However, the percentages of participants who identified non-adherence using these plots were generally lower, ranging from 29.8% to 40.4%. Participants' perception of usability ranged from 14% to 17.5% across these visualizations. More favorable perceptions were found among participants with baseline knowledge for two or more visualizations (adjusted odds ratio: 3.21; 95%CI: 1.29, 7.96; p-value: 0.012) and having identified two or more non-adherent visualizations (adjusted odds ratio: 4.23; 95%CI: 1.95, 9.16; p-value: < 0.001). Conclusions: Adherence to repetitive time-sensitive tasks can be presented in the form of visualizations. However, nurses' and doctors' knowledge and understanding of these visualizations are generally poor. This may influence their perception of usability of these plots. Therefore, these visualizations need to be implemented in tandem with training on their interpretation, to enhance the usefulness of these plots in motivating quality improvement.