A Usability Evaluation of READY: An Electronic Data Collection Tool to Assess Rheumatoid Arthritis

The advancement of technology and increase use of mobile applications has impacted the healthcare system. This study evaluates the usability of an application called READY (RhEumAtic Disease ActivitY). RhEumAtic Disease ActivitY (READY) was designed for in-office use to allow Rheumatoid Arthritis patients and clinicians to input, track, and manage clinical outcomes, such as global pain, fatigue, and various disease activity indices. The study focuses on physicians’ interaction with READY. Think-aloud protocol was used to capture physicians’ feedback and provide potential solutions to improve READY. Although usability issues were found, READY received positive feedback in its ability to benefit both patients and physicians. Running Head: USABILITY EVALUATION OF READY 4 Chapter I: Statement of the Problem Introduction The use of technology has been rapidly increasing and has had a big impact on the healthcare system (Free et al., 2012). Mobile applications can wirelessly communicate to a patient’s electronic health record, offering users easy and convenient access to this information (Plaza et al., 2013). They offer the opportunity to improve the communication between healthcare providers and patients (Ozdalga et al., 2012). These applications for mobile devices such as smart phones and tablets provide healthcare professionals and patients with a growing number of specialized tools and resources (Patrick et al., 2008). These applications encourage and promote the user to engage in more healthy behavior and the clinician can deliver health interventions (Blake, 2008). Usability evaluation is a systematic way of assessing to what degree the application is effective (i.e. how well the application fills the desired need of the user), efficient (i.e. how much effort or time is needed to perform a specific task), and satisfactory to the user (i.e. does the user favor this application) (Wood, 1998). Usability testing help determine whether a product works for its intended user in a laboratory setting or in a real world setting. Usability testing is evaluating a product by testing it with its intended user and involves evaluation of its design, implementation, and evaluation of the system (Kushniruk & Boycki, 2014). For example, in this project, usability testing involves an observer and the user (e.g. physician) while they interact with a mobile application system (e.g. a mobile application) and perform a specific task (e.g. entering medication dosage) (Neilson, 1994). By performing usability testing, it ensures Running Head: USABILITY EVALUATION OF READY 5 the uses of medical applications are adapted to the users, the task they are performing, and that there are no negative or harmful outcomes (Bastein, 2010). If the usability of the mobile application does not work for its intended use, significant errors could lead to negative outcomes for the patient (Kushniruk et al, 2005). Usability testing is vital to designing all informatics applications (Wakefield et al., 2015) and is critical that important information is presented in an effective way [Jaspers, 2009). To perform a usability study, a number of usability evaluation methods are available (Peute et al., 2015). However, some of these methods are limited by practicality, accessibility of required human resources, and time to perform the evaluation study [Peute et al., 2015). The most preferred method of data collection is using the think aloud protocol. It is a wellrecognized method and can provide information about the cognitive processes of subjects pertaining to usability problems (Peute et al., 2015). Thoughts that may be verbalized are feelings of frustration, confusion, or even relief when a task was easy to perform. Patient Reported Outcomes Patient reported outcomes via technology “generate a color-coded report reflecting an individual’s patient’s survey results over time and efficient depicts how different symptom items change in relation to each other...” (Smith et al., 2013). Research has shown when it comes to treating arthritis patients early diagnosis and prompt aggressive treatment substantially improve patient functional outcome and morbidity (Davis & Matteson, 2012). Treatment decisions should be made based on quantitative assessments of the patient’s disease activity (Saag et al., 2008). For example, the Health Assessment Questionnaire (HAQ) is Running Head: USABILITY EVALUATION OF READY 6 a comprehensive outcome measurement that assesses the hierarchy of patient outcomes in mostly two domains: disability and discomfort and pain (Ramey et al., 1992). Disability is assessed by eight categories: dressing, arising, eating, walking, hygiene, reach, grip, and common activities. Discomfort is determined by the presence of pain and its severity, location, and time of the day (Ramey et al., 1992). The time frame for disability and discomfort is based on the past week. The questionnaire is a paper and pencil selfadministered survey that is given in an out-patient clinic to each RA patient before their appointment (See Figure 1). While electronic health record system (EHR) was implemented in more and more hospitals, additional data entry is required to transfer the patient reported outcomes on paper into the EHR. RhEumAtic Disease ActivitY (READY) The Ohio State University and the University of Alabama Birmingham received funding from the Agency for Healthcare Research and Quality (AHRQ) and together has developed an application for handheld devices for patients with rheumatoid arthritis. RhEumAtic Disease ActivitY (READY) is designed for in-office use to allow patients and clinicians to manually input data through a set of questionnaires. The clinicians can track patient data and their clinical Figure 1 Running Head: USABILITY EVALUATION OF READY 7 outcomes. It enables collection, storage, and trending over time of information on validated disease measures such as global pain, fatigue, and various disease activity indices. The benefit of using READY is that the patient’s scores are automatically calculated and their disease activity is stored in a graph so a trend can be seen over time. More importantly, medications and their doses are recorded in the graph which allows easier analysis of whether or not certain medications are working.