AI Basics: The Value of Medical Data

By
Arjen Mol - Medical Data Specialist
Date:
October 14, 2024
Reading time:
3 min

Pacmed was founded in 2014 through the National ThinkTank, with a clear mission: how can we use big data to make healthcare smarter and better? Since then, we have been involved in numerous projects to make healthcare more “data-informed.” What have we learned? Medical data is incredibly powerful. It can not only improve the quality of care but also help keep healthcare accessible and affordable.

In this article, we take you into the world of medical data. We show how data can add value to healthcare—for patients, healthcare professionals, hospitals, and researchers alike.

What is Medical Data?

Medical data encompasses all information stored about patients. This includes personal data such as gender, height, and weight, as well as clinical observations like level of consciousness, measurements like blood pressure, and lab results such as glucose levels. This information is stored in hospitals in electronic patient records (EHR) and/or patient data management systems (PDMS), special systems used on f.e. the ICU and OR. The primary purpose of this data is to optimize patient care and facilitate the transfer of information between healthcare professionals.

Leveraging on Historical Data to improve treatments

Analyzing historical medical data provides insights into the effects of treatment choices. This helps evaluate outcomes and identify opportunities for improvement for medical treatments. For example, when deciding to perform a CT scan, it’s crucial that the medical information gained helps an accurate diagnosis and leads to actionable insights (the principle of meaningful care). By analyzing the outcomes of the intervention, the impact on the patient journey can be measured, informing future care processes.

Currently, analyzing medical data to understand the impact of previous decisions on patient health is mainly done by researchers. By making medical data more accessible and standardized, healthcare professionals can increasingly use data to achieve better outcomes for patients. Curious about how data is prepared for insights? Check out our ‘Platform Services’ page or our article: AI Basics: From Data to Insights.

Decision Support for Current Patients

Medical data can also contribute to making better decisions in the present. For example, in deciding whether an ICU patient can be extubated, the medical data of thousands of past patients, combined with the patient’s own data, can predict the risk of reintubation in the short term. If the risk is high, a healthcare professional will be more cautious about removing the tube than if the risk is low.


Capacity Planning Based on Predicted Medical Procedures

In addition to decision support, medical data can be used to measure and predict the severity of care a patient requires. By forecasting patient inflow and outflow and making predictions about care intensity per patient, hospitals can better align their scheduling with the care needed. This helps to efficiently deploy staff such as nurses and other healthcare professionals.


Treatment Suggestions

With a patient’s medical data, AI modules developed for this purpose can selectively retrieve knowledge from protocols and scientific literature. This leads to personalized treatment suggestions.


Quality Dashboards

Medical data can also be used to measure and compare the performance of healthcare processes in real-time with past data. This provides valuable insights into the quality of care and identifies areas where improvements are possible.


Medical Data is Powerful! But how can we use it?

Read more in the next blog post: Pacmed Basics: From Data to Insights. Do you have questions or disagree with the article? Shoot us a message through our Contact page or LinkedIn.