ORTEC.
Clinical decision support
Clinical Decision Support may sound like a distant prospect for some, but there are already real-world examples of clinical solutions based on relevant, efficiently processed data that support physicians and patients in the decision-making process. Such solutions are developed in collaboration with research groups at university hospitals, for instance. ORTEC Logiqcare contributes Data Science expertise to research projects and translates innovations into user applications that can be tailored to specific research groups and used in every healthcare institution. UMC Utrecht’s U-Prevent is a great example of such an innovation, and it has already been applied in the field of cardiovascular risk management.
GDPR compliance
In the Netherlands, large sums of public money are invested in healthcare innovation. On the one hand, this is driven by the need to limit further increases in total healthcare costs, whilst on the other hand offering opportunities to improve the quality of patient care. In recent years, attention to the GDPR has slowed down the implementation of innovations. How do you implement and sustainably operate innovations whilst also complying with the GDPR? In the meantime, new insights have led to the development of a more nuanced approach, and innovations that use patient data are prioritized more and more.
Challenge in applying Data Science
For innovations to succeed, more is needed than just a successful implementation: they also need high-quality, accurate data. Unfortunately, politicians opted not to introduce a nationwide Electronic Health Record (EHR) in 2011, prompting every healthcare institution in the country to implement its own EHR. As a result, no two EHRs are the same, not even if they were made by the same developer, which means that the patient data contained therein can neither be compared nor easily combined. Not only that, these data were never recorded with the purpose of being used for Data Science. Briefly put, the application of Data Science faces several major challenges.
Clinical-Decision Support
With its vast experience in Data Science, ORTEC focuses on developing clinical solutions that support physicians and patients in decision-making: Clinical Decision Support. Such solutions are developed in collaboration with research groups at university hospitals, for instance. ORTEC Logiqcare contributes Data Science expertise to research projects and translates innovations into user applications that can be tailored to specific research groups and used in every healthcare institution. Together with the research group, we then invest in continued development and innovation.
In practice: U-Prevent
UMC Utrecht’s U-Prevent is a great example of such an innovation, and it has already been applied in the field of cardiovascular risk management. U-Prevent supports physicians and patients in determining cardiovascular risk and gives the physician easy access to a list of available resources and medication that can be used to reduce the risk. As a result, physicians and patients can work together to prevent future problems and disorders that may lead to unnecessary care costs.
Blog U-Prevent
Blog U-Prevent
ORTEC in healthcare
ORTEC provides data science services and data-driven decision solutions for many different fields, including healthcare logistics and medical care. In the medical sector, ORTEC Logiqcare works closely with highly specialized medical experts. In medicine, like other businesses, ORTEC combines the triangle business, mathematic and ICT for the best results. These can be used to support medics with clinical-decision making tools, support for medical care and scientific research.
ORTEC blogs
Please find the original blog here.
Blogs are written by ORTEC including John Jacobs.
John Jacobs is the product owner of Logiqcare and U-Prevent at ORTEC
ORTEC Health combines data & math to leverate value for the medical domain.
Blogs are written by ORTEC including John Jacobs.
John Jacobs is the product owner of Logiqcare and U-Prevent at ORTEC
ORTEC Health combines data & math to leverate value for the medical domain.
John Jacobs, 2019-2020
