Integrated innovative solutions to improve healthcare scheduling

Abstract

The paper presents a new scheduling method of medical appointments for chronic patients. Taking into account the current situation, in which, especially due to the growing number of chronic patients, both hospitals and primary care units have to cope with a permanently increasing number of appointments, one of the main goals of the proposed method is to balance the workload of the medical staff. A fuzzy based approach was chosen and many factors such as epidemiological context, current medical staff workload, individual preferences, holiday's periods and seasonal variations of patients' number were considered in the planning process. These factors were divided in groups and the fuzzy inference rules were applied in two stages. First, different loads of the appointment schedule for context dependent, predefined time intervals were determined. In the second stage, considering the characteristic features of the chronic disease and the current individual evolutions, the patients were distributed in the previous established time frames. Fuzzy Petri Nets were used to model the application. The proposed method is flexible, offering the opportunity to use some specific features of a corresponding monitoring of chronic patients in order to improve and specially to balance the workload of the medical staff.