Decision support system in medical oncology
El presente proyecto pretende desarrollar un aplicativo, que permita al oncólogo tener una visión integral y ágil, con toda la información necesaria disponible para el seguimiento del paciente oncológico, a lo largo de los distintos ciclos de tratamiento.
Oncological illnesses have a big impact on population. The practice of medical oncology has progressed in the last years with new treatments and technology that has improved prognosis of patients. However, ageing of population, certain risk factors, and earlier detection have not reduced the total number of cases, and even in certain types of cancer it has increased. This resulting an increase in welfare pressure with the same or even less resources, often due to economical conditioning.
Monitoring information of the evolution of the disease the oncologist handles can be classified into four categories: diagnosis information, information about the treatment, symptoms of the disease, and toxicological effects of the treatment. The oncologist has access to diagnosis information, and knows exactly about the treatment if it is carried out in hospital, but often from different sources and having no integral vision of the case. Still, information on symptoms and toxicology is incomplete and biased, and it is based on the patient’s witness along a period of time. If treatment is carried out at home, there is no adherence information. All this plus a big welfare pressure and complexity and variability of cases make the practice of medical oncology difficult, as there are no products in the market that solve this necessity in an effective way.
The aim of this project is to develop an app, called ONKO, that will help the oncologist have an integral and agile vision to monitor the oncological patient, having every information available to monitor the patient throughout the different cycles of the treatment. From the clinical point of view, the goal is to make decisions with wider and more accessible information, that make it easier and more reliable to value the efficiency vs. toxicity balance in each case. The most suitable treatment for each patient does not only rely on approved or recommended therapies by clinical guides. They are mainly guided by specific situations/characteristics of each patient (such as morbidity, balance between toxicity and quality of life, benefits for patients…). The assessment of the four categories above explained, together with close interaction with the patient may tremendously help when making joint-decisions. For this purpose, information regarding the evolution of image diagnostic tests will be added, and will be presented in a more flexible way to strengthen the improvement in patient-attention and monitoring of treatments. Also a monitoring tool will be included. This tool will monitor the evolution of the symptoms of the disease, the toxicological effects, and adherence. Based on an app, it will allow a better monitoring of the patient, who will in turn receive better attention, and will therefore become backbone of the system.
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