Creating a Personalized Medication Experience to improve health outcomes
Today, almost half of patients are failing to take their medications as prescribed. This reduces the effectiveness of medicines resulting in needless deaths, hospitalisations and the waste of healthcare resources. Patients still relay on notes, reminders and assistant from their relatives or medical professionals. The current technology-driven solutions are also either too expensive to be accessible for the majority of the users or fail to be as effective.
We wanted to create an experience where the medication is intelligent. The mobile app is designed to amplify patient engagement in a humanized way. It offers a conversational experience to help users manage medication. It also helps them understand the medication and the reasons for taking them. Engaging with patients using natural language can positively impact their behavior and therefore seemed to be more effective than the costly technological solutions that exists today.
Everyone responds differently to treatment. Understanding medication and the way it works for individuals not only helps the healthcare workers but the patients themselves to enhance their health outcome. The mobile component of the system aims to build a bridge between the healthcare system and the patients in order to make it possible to observe, predict, and offer a personalized care to them.
Managing medications requires the user to remember simple things such as the last time a medication was taken or the exact doze for each intake. This is where machine learning can be put in practice. By training the models, the intelligent eye aims to assist the user with hints and suggestions that could essentially lower the mental load needed for managing medication.
Taking medications with confidence
Big Data and Personalized Medicine
Through personalized user engagement, PharmaWise can offer real-time insights into patient's behavior. Filling in the gaps in data allows the development of more effective and efficient interventions. By applying Machine Learning algorithms to the combined data we are able to generate insights for advanced pharmaceutical analytics and data-driven decisions making. We are moving towards creating valuable data for the future of personalized medication treatment. This is where an engaging experience can lead to a better collection of data which eventually will help the user improve their health outcomes.