Hospitals are discharging many patients that are in need of aftercare, e.g., requiring a bed in a nursing home. The timely transfer of those patients to the correct type of aftercare is of utmost importance to ensure the quality of care, i.e., that the patient receives the right treatment at the right time, as well as the quality of staffing, i.e., that the capacity and staff in the hospitals and the aftercare organizations are used efficiently. If patients do not receive timely treatment, it may negatively impact their recovery journey. Further, they stay in the hospital bed longer than necessary, producing so-called bed-blocking days. These blocked beds are not available to other patients in need, and highly trained and costly staff needs to take care of those patients instead of performing tasks corresponding to their skill set.
This project focuses on developing models to predict demand for nursing home care originating from hospitals on different time scales (long-term, mid-term, and short-term). Those hospital predictions will be made available to nearby nursing homes in order to support their capacity and staff planning. By accurately predicting demand and aligning resources accordingly, the project seeks to reduce bed-blocking, improve patient outcomes, and enhance the efficiency of staff planning in nursing homes and hospitals. The project involves collaboration with multiple hospitals to ensure its applicability and aims to develop a prototype prediction tool for immediate use, with the long-term goal of integrating the models into hospital information systems for widespread implementation.
Funding
Pioneers in Healthcare voucher