One of the most important parts of patient satisfaction in the health sector, based on general knowledge, is accessibility. Accessibility consists of a set of factors that describe the effort needed from a patient as well as the procedures a patient needs to complete, in order to receive health services from an organization. Some of the most important aforementioned factors are: waiting times, ease of appointment scheduling and appointment confirmation, ease of access to a clinic, etc. In the model of patient satisfaction, an equally important role play the notions of effectiveness, training and availability, which refer to the efforts of organizations to maintain high levels of diagnostic capabilities and provision of medical care. Examples of these are the availability of the required exam time depending on the type of disease, accuracy in diagnosis, avoidance of errors, provision of detailed explanations of the procedures and methods of treatment in patients, etc.

The current situation, in a number of institutions in our country, unfortunately contradicts the above mentioned, as a) there is a particular difficulty in planning the appointments with the medical clinics; b) due to the lack of an organized planning process, waiting time for patients is often very long (c) due to the lack of medical and non-medical staff, the necessary time to properly examine and inform patients is not available, and in addition, the already limited and valuable time is lost, for collecting or informing medical histories of patients from the point of view of medical staff. Given all the above, this proposal proposes the development of an intelligent system based on Artificial Intelligence (AI) and Data Analysis techniques, which will be a useful tool for both physicians and patients, with the final goal being to upgrade the efficiency of the operations of medical care providers as well as increase the quality time spent between a doctor and a patient. Through the proposed system, patients will be able to schedule their upcoming appointments with the desired provider faster and easier, through a user-friendly application. After the appointment is confirmed, the patient will be able to chat with a smart and fully automated interactive conversational agent which, carrying out the role of a physician, will ask the patient appropriate questions about the course of the disease. The patient’s answers (written and spoken) will be collected, processed and presented to the attending physician before the appointment with the patient. At the end of the procedure, patients will receive all the necessary information they need about what to expect from the upcoming appointment in order to be properly prepared. Also, upon completion of the appointment and after confirmation, the patient will be able to evaluate the services he has received, while the attending physician will be able to add appointment notes, which he may choose to send, if he wants it, and to the patient. Finally, a Business Intelligence system will also be developed, which will include a dashboard where the appropriate data will be displayed and visualized, based on patient evaluation data.


Title: ClinApp

Agreement ID: Τ2ΕΔΚ-04937

Duration: 01/06/2020 - 01/06/2023

Funded under: NSRF 2014-2020

Coordinator: Aristotle University of Thessaloniki, GR