Passive sensor technology interface to assess elder activity in independent living

Abstract

Background: The effectiveness of clinical information systems to improve nursing and patient outcomes depends on human factors, including system usability, organizational workflow, and user satisfaction.

Objective: The aim of this study was to examine to what extent residents, family members, and clinicians find a sensor data interface used to monitor elder activity levels usable and useful in an independent living setting.

Methods: Three independent expert reviewers conducted an initial heuristic evaluation. Subsequently, 20 end users (5 residents, 5 family members, 5 registered nurses, and 5 physicians) participated in the evaluation. During the evaluation, each participant was asked to complete three scenarios taken from three residents. Morae recorder software was used to capture data during the user interactions.

Results: The heuristic evaluation resulted in 26 recommendations for interface improvement; these were classified under the headings content, aesthetic appeal, navigation, and architecture, which were derived from heuristic results. Total time for elderly residents to complete scenarios was much greater than for other users. Family members spent more time than clinicians but less time than residents did to complete scenarios. Elder residents and family members had difficulty interpreting clinical data and graphs, experienced information overload, and did not understand terminology. All users found the sensor data interface useful for identifying changing resident activities.

Discussion: Older adult users have special needs that should be addressed when designing clinical interfaces for them, especially information as important as health information. Evaluating human factors during user interactions with clinical information systems should be a requirement before implementation.

Figure 1

The Nurse-Patient Trajectory Framework

Figure 2

Figure 2a: Activity Motion Sensor Data Figure 2b: Bed Breathing Sensor Data

Figure 2

Figure 2a: Activity Motion Sensor Data Figure 2b: Bed Breathing Sensor Data