The Development and Usability of the AMPREDICT Decision Support Tool: A Mixed Methods Study

Amputation level decision making in patients with chronic limb threatening ischaemia is challenging. Currently, evidence relies on published average population risks rather than individual patient risks. The result is significant variation in the distribution of amputation levels across health systems, geographical regions, and time. Clinical decision support has been shown to enhance decision making, especially complex decision making. The goal of this study was to translate the previously validated AMPREDICT prediction models by developing and testing the usability of the AMPREDICT Decision Support Tool (DST), a novel, web based, clinical DST that calculates individual one year post-operative risk of death, re-amputation, and probability of achieving independent mobility by amputation level.

A mixed methods approach was used. Previously validated prediction models were translated into a web based DST with additional content and format developed by an expert panel. Tool usability was assessed using the Post-Study System Usability Questionnaire (PSSUQ; a 16 item scale with scores ranging from 1 to 7, where lower scores indicate greater usability) by 10 clinician end users from diverse specialties, sex, geography, and clinical experience. Think aloud, semi-structured, qualitative interviews evaluated the AMPREDICT DST's look and feel, user friendliness, readability, functionality, and potential implementation challenges.

The PSSUQ overall and subscale scores were favourable, with a mean overall total score of 1.57 (standard deviation [SD] 0.69) and a range from 1.00 to 3.21. The potential clinical utility of the DST included (1) assistance in counselling patients on amputation level decisions, (2) setting outcome expectations, and (3) use as a tool in the academic environment to facilitate understanding of factors that contribute to various outcome risks.

After extensive iterative development and testing, the AMPREDICT DST was found to demonstrate strong usability characteristics and clinical relevance. Further evaluation will benefit from integration into an electronic health record with assessment of its impact on physician and patient shared amputation level decision making.