JMIR Publications

ABSTRACT

Background:

Information overload negatively affects clinicians’ decision effectiveness and ultimately impacts patient safety. Clinicians who are tasked with assessing patient outcomes are often required to use complex outcome and risk models in a spreadsheet format. In response to this challenge, we developed a mobile web model which simplifies the information presented to clinicians and expedites the decision process. However, new electronic technologies often face barriers to adoption which inhibits their use in clinical settings.

Objective:

This pilot study investigated sociotechnical factors that affect intention to use a simplified WebModel to support clinical decision making. We investigated factors from the UTAUT2 model, which are known to affect technology adoption.

Methods:

A WebModel is developed based on the results from a previously published work, to allow users to work with regression equations and their predictions to evaluate the impact of various characteristics or treatments on key outcomes (e.g. survival time) for chronic obstructive pulmonary disease (COPD). To test the WebModel a questionnaire was designed to probe the efficacy of the WebModel and to assess the usability and usefulness of the system. The questionnaire was administered online, and data from 550 clinical users who had access to the WebModel was captured. SPSS and R were used for statistical analysis.

Results:

The regression model developed from UTAUT2 constructs was found to be a fit, with five variables found to significantly predicts behavioural intention to sue the WebModel: Performance Expectancy, Effort Expectancy, Facilitating Conditions, Hedonic Motivation and Habit. Social Influence was not a significant factor, while Value had a significant negative influence on intention to use the WebModel. Multiple influences were found to impact the positive response to the system, many of which related to the efficiency of the interface to provide clear information. Given that this was a pilot test, and that the system was not used in a clinical setting factors related to actual workflow, or patient safety could not be examined.

Conclusions:

This study proves that the concept of a simplified WebModel could be effective and efficient in reducing information overload in complex clinical decision making. Further study to test this in a clinical setting, and gather qualitative data from users regarding the value of the tool in practice is recommended.