JMIR Publications

ABSTRACT

Background:

Closing the gap between care recommended by evidence-based guidelines and care delivered in practice is an ongoing challenge across systems and delivery models. Clinical decision support systems (CDSSs) are widely deployed to augment clinicians in their complex decision-making processes. Despite published success stories, the poor usability of many CDSSs has contributed to fragmented workflows and alert fatigue.

Objective:

The aim of this study was to validate the application of a user-centered design (UCD) process in the development of a standards-based medication recommender for type 2 diabetes mellitus (T2DM app) in a simulated setting. The prototype app was evaluated for effectiveness, efficiency, and user satisfaction.

Methods:

We conducted interviews with 8 clinical leaders along with 8 rounds of iterative user testing with 2–8 prescribers in each round to inform app development. With the resulting prototype app, we conducted a validation study with 43 participants (21 MDs and 22 non-MD providers). The providers were assigned to one of two groups and completed a 2-hour remote user testing session. Both groups reviewed mock patient facts and ordered diabetes medications for the patients. The Traditional group used a mock EHR for the review in Period 1 and used the prototype app in Period 2, while the Tool group used the prototype app during both time periods. The perceived cognitive load associated with task performance during each period was assessed with the NASA Task Load Index (TLX). Participants completed the System Usability Scale (SUS) questionnaire and the Kano Survey.

Results:

Average SUS scores from the questionnaire, taken at the end of 5 of the 8 user testing sessions, ranged from 68–86 . The validation study demonstrated the following results: percent adherence to evidence-based guidelines was greater with the use of the prototype app than with the EHR across time periods with the Traditional group (protoype app mean 96.2 versus EHR mean 72.0, P < .001) and between groups during Period 1 (Tool group mean 92.6 versus Traditional group mean 72.0, P < .001). Task completion times did not differ between groups (P =.23), but the Tool group completed medication ordering more quickly in Period 2 (Period 1 mean 130.7 seconds versus Period 2 mean 107.7 seconds, P < .001). Based on adjusted alpha level due to violating the assumption of homogeneity of variance (Ps > .03), there was no effect on screens viewed. There also was no effect on perceived cognitive load (all Ps > .14).

Conclusions:

Through deployment of the UCD process, a point-of-care medication recommender application holds promise of improving adherence to evidence-based guidelines, in this case those from the American Diabetes Association (ADA). Task-time performance suggests that with practice the T2DM app may support a more efficient ordering process for providers, and SUS scores indicate provider satisfaction with the app.