18374143. ASSESSING A SUBJECT'S ADHERENE TO A TREATMENT FOR A CONDITION simplified abstract (KONINKLIJKE PHILIPS N.V.)
Contents
ASSESSING A SUBJECT'S ADHERENE TO A TREATMENT FOR A CONDITION
Organization Name
Inventor(s)
NICOLAAS GREGORIUS PETRUS Den Teuling of EINDHOVEN (NL)
ANGELA Grassi of EINDHOVEN (NL)
IOANNA Sokoreli of EINDHOVEN (NL)
CLAIRE YUNZHU Zhao of BOSTON MA (US)
ASSESSING A SUBJECT'S ADHERENE TO A TREATMENT FOR A CONDITION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18374143 titled 'ASSESSING A SUBJECT'S ADHERENE TO A TREATMENT FOR A CONDITION
Simplified Explanation
The patent application describes a computer-implemented method for assessing a subject's adherence to a treatment for a condition by analyzing adherence data, medical data, and generating a priority classification to be delivered as an instruction signal to a recipient.
- Simplified Explanation:
- Method to assess subject's adherence to treatment - Analyze past adherence data and medical data - Determine non-adherence and adverse event risk scores - Generate priority classification and instruction signal
- Potential Applications:
This technology could be applied in healthcare settings to improve patient outcomes by identifying individuals at risk of non-adherence to treatment and adverse medical events.
- Problems Solved:
- Identifying patients at risk of non-adherence - Predicting likelihood of adverse medical events - Providing personalized interventions based on risk assessment
- Benefits:
- Improved patient adherence to treatment - Early identification of potential adverse events - Tailored interventions for at-risk individuals
- Potential Commercial Applications:
"Enhancing Patient Adherence and Safety in Healthcare with Advanced Risk Assessment Technology"
- Possible Prior Art:
Prior art may include similar methods for assessing patient adherence and predicting adverse events in healthcare settings.
- Unanswered Questions
- How does this technology impact patient outcomes in the long term?
The article does not delve into the long-term effects of using this technology on patient outcomes. Further research and studies may be needed to determine the sustained benefits of this approach.
- What are the potential limitations or challenges in implementing this technology in real-world healthcare settings?
The article does not address the practical challenges or limitations that may arise when implementing this technology in healthcare settings. Factors such as data privacy, integration with existing systems, and healthcare provider adoption may need to be considered.
Original Abstract Submitted
According to an aspect, there is provided a computer-implemented method () for assessing a subject's adherence to a treatment for a condition, the method comprising receiving () adherence data indicative of the subject's past adherence to the treatment; receiving () medical data indicative of physiological details and a medical history of the subject; determining (), based on the received adherence data, a non-adherence risk score indicative of a likelihood that the subject will not adhere to the treatment within a defined time period in the future; determining (), based on the medical data, an adverse event risk score indicative of a likelihood that the subject will experience an adverse medical event; determining (), based on the non-adherence risk score and the adverse event risk score, a priority classification to be assigned to the subject; and generating (), based on the priority classification, an instruction signal to be delivered to a recipient
