a study that aims to improve monitoring and patient outcomes in a cohort of women with gestational diabetes through a remote monitoring device involving big data technologies
Principal Investigator – Prof. Fionnuala Breathnach
Coordinator – Alma O’Reilly
BigMedilytics is an international collaboration between partners from academia and industry across Europe. It aims to transform Europe’s Healthcare sector by using state-of-the-art Big Data technologies to achieve breakthrough productivity in the sector by reducing cost, improving patient outcomes and delivering better access to healthcare facilities simultaneously, covering the entire Healthcare Continuum – from Prevention to Diagnosis, Treatment and Home Care throughout Europe.
In particular, we are focusing on applying latest big data and machine learning technologies to the use case nephrology to measure and analyze clinical performance indicators, integrate predicitive models, and measure their impact on clinical routine.
The purpose of the pilot being run in the Rotunda is to assess whether measuring blood sugar levels remotely improves management of gestational diabetes (GDM) and reduces the number of required hospital visits for women. Using technology in the healthcare setting is advantageous in its reduction of time and cost through delivery of products and services that are efficient, safe and acceptable to patients.
Currently, patients with GDM are required to attend a specialised diabetic clinic and a breakfast club meeting where they can be reviewed by obstetricians, endocrinologists and dieticians. These visits often involve long waiting times and pose difficulties for women who require time off work or help with child minding. Women then ring with their blood glucose measurements on a weekly basis – again this consumes patient and hospital resources and only provides a snapshot of diabetic control. Through the integration of app technology into GDM management the patient has a much more straightforward way of documenting their blood sugar results and these, in turn, are easily reviewed by clinicians who can then identify patients’ who require a face to face review.