Clinical outcome measures are well-established quantitative assessments of medical treatment that are crucial for understanding the effectiveness of prescribed drugs. However, recent studies suggest that timely and long-term clinical outcome measures are not usually found in the patient records. The study attributes the lack of quantitative follow-up to the reluctance of the clinicians treating the patients, whose active schedules incline them to use (insufficient) brief descriptions of the cases, greatly reducing the quality of care. To ease the clinicians burden and improve the process of patient follow-up while simultaneously dealing with the complexity of our domain, we designed and deployed a multi-agent platform to automate the process of collecting patient-provided clinical outcome measures without clinicians intervention. The system also acts as a mediator between patients and scientists, by seeking patient consent to incorporate anonymised versions of the collected data into scientific studies to which the patients are found eligible. This paper presents the design, prototype and deployment results of our system, highlighting foreseen clinical merits and documenting challenges faced throughout our experience.
['Zina M. Ibrahim', 'Lorena Fernández de la Cruz', 'Argyris Stringaris', 'Robert Goodman', 'Michael Luck', 'Richard Dobson']
A Multi-Agent Platform for Automating the Collection of Patient-Provided Clinical Feedback