Identification of Design Requirements for a Software Application for Use by Clinicians That Collects Acute Stroke Treatment Data During Clinical Workflow: Pilot Study.

backgroundClinical registries are critical for monitoring processes of care in diseases and driving quality improvements. However, many smaller hospitals lack the required resources to collect the necessary data to contribute to registries.

objectiveThis study aims to design and evaluate a data collection tool for acute stroke treatment that streamlines the collection of process data and provides tools to aid clinician users while not interfering with clinical workflow. The evaluation will identify key design requirements that facilitate prospective data collection and add value for clinicians.

methodsWe developed a prototype tool for testing using Figma Pro for use on an iPad. Clinicians were recruited through convenience sampling to test the prototype's use in a small-scale simulated clinical field experiment, during which participant were asked to think aloud and then complete a series of tasks to mimic a mock stroke treatment while inputting the required data into the prototype. Follow-up semistructured interviews were conducted to gain feedback on how the prototype integrated into the workflow and on the aspects of the prototype they felt helped and hindered their use of it. Qualitative data analysis combined review of the experiment recordings to identify the most frequent errors made during the scenario and deductive thematic analysis from the follow-up interviews to determine user needs for the following prototype iteration. The insights from the feedback identified design requirements that were implemented in the iterated design and documented to provide a reference for future product designers.

resultsThree participants were recruited from 2 hospitals between April 18 and June 6, 2024, for the simulated field experiment. The scenario took 10-12 minutes, with 1.2-3.7 minutes spent using the prototype, depending on whether optional features such as the NIHSS (National Institute of Health Stroke Scale) calculator were used. The simple and condensed layout and features such as NIHSS calculators, benchmark metric timers, and the final pop-up summary received the most positive feedback from each participant. Issues identified included small target sizes causing higher error rates, lack of color in important features reducing their visibility, and grouping of mandatory and optional information field layouts leading to a disjointed flow. The key design requirements include prioritizing simple dynamic layouts, sufficient target sizes to prevent errors, useful features with clear visual cues, and prompt data feedback to facilitate seamless integration.

conclusionsA prospective data collection tool for clinicians to use during stroke treatment can add value for clinicians and, with further testing, can be integrated into workflow. The design requirements identified through this study can provide a basis for streamlining the collection of accurate data while increasing the value of the tool for users and should be considered by future product designers to add value to their software and improve user experience.