Identifying patients for rare diseases

The clients of healthcare industry are having two issues in the area of rare disease.

1.   First hurdle is in development side in getting the protocols which work in real world. It is difficult because markers are very difficult.

2.   Once the medicine has approved from FDA, second obstacles comes with its marketing and the right patient’s identification.

According to the prevalence, around 4 patients per 100,000 patients and the average miss-diagnosis of the patients is four times. It’s fatal in those conditions if not treated. To overcome those situations, IQVIA has used its owned EMR data of over six hundred million de-identified patients’ records to combine the two problem solutions. Here by placing on their predictive algorithm that helps to control a group that is diagnosed. The healthcare professionals find two things by taking that control group to a broader population set.

The physicians found that the volume of the patients that are sponsoring the case thought was higher. Most important part that IQVIA plays is that they shape the message of the sponsors to physicians where the patients are. These are de-identified patients data but there are areas of the country where they know about the centers and residential of the patients. Healthcare professionals are hoping to half the rare disease diagnosis rate over the course of five years by better educating the professionals.

These are the available technology AI and machine learning transformations for the benefits of patients and life science companies. Its main utility comes with benefiting the payers and providers.


Leave a Comment

Please fill the form below to post a comment.