Robot-based remote outpatient follow-up for stable cardiac conditions

Several cardiac conditions (e.g. aortic stenosis, aortic dilatation, biological valve prostheses, relatives at-risk for hereditary cardiac disease) require long-term follow-up with regular imaging/functional examinations to detect pathologic changes and timing of intervention. Regular and timely scheduling is thus essential. Currently, follow-up is often linked to outpatient clinical appointments, which may be postponed. As a result, the plan is not always upheld, and clinical decisions may rest on outdated examinations with long delays.

To design and test an automated digital follow-up model for asymptomatic, low-risk cardiac conditions clinically monitored for risk of deterioration. The purpose was to reduce workload for healthcare staff, create patient value and reduce outpatient visits.

We designed a process including manual workflow, referrals, information retrieval, patient interaction, and check points for clinical evaluation for robotic process automation (RPA). The process is initiated by the physician at first assessment and updated after each follow-up, working as follows: Patient data is retrieved from the administrative waiting-list, standardized referrals for echocardiography are created and sent to the clinical physiology provider. Status updates and scheduled appointments are continuously monitored. Upon detection, booking records are updated for administrative staff for scheduling for blood sampling (not automated). Finally, a digital symptom questionnaire is dispatched to the patient via a national healthcare platform. Collected data are provided for the responsible physician, human-in-the-loop, for clinical analysis and decision making. The follow-ups for decision making include echocardiography and laboratory results, review of symptom questionnaires, and patient communication, including updated care plans (Figure). Health economic effects were estimated using a budget impact analysis.

Approximately 212 patients at our unit were selected as suitable for the method. The budget impact analysis showed that assuming a 30% reduction in clinic visits during the first year, the system could save approximately 64 working hours for physicians and administrative staff, corresponding to 64 outpatient visits, with an estimated cost savings of € 40,488. We are continuously including clinically suitable patients to the workflow for collection of real-world results (Table).

Successful RPA deployment will ensure timely follow-up and coordinated evaluation, enhancing patient safety. The robot will reduce the workload for both physicians and administrative staff. Certain outpatient visits may be avoided, enabling prioritization of appointments for patients requiring direct physician contact, and contribute to reduced overall follow-up costs.