It is estimated that 50% of patients do not take their medications as prescribed due to these problems:
-Prescription of complex drug regimens (multiple medications can be overwhelming)
-Communication barriers (complex language)
-Lack of involvement in the treatment decisions
-Patients need more information about the medications they take (adverse effects, drug interactions, best time to take for effectiveness, etc…)
Most of the prescription management apps (i.e: Medisafe, CareZone, My PillBox) currently suffer the same problems:
-Data entry on mobile phone is painful with a small keyboard and hard to spell medication names.
-Barcodes take valuable space on a prescription bottle and are systems/platforms specific.
-Lack of security (no login in some cases)
-Easy to mix up patient information (enter information from someone else's prescription)
-Limited to mobile app
-Complex to use
-In trying to monetize, they evolve into full-blown pharmacies and prescription delivery services which adds more cost to the healthcare system.
-Wearables/Hardware platforms also add more cost to the healthcare system.
Medviv is a HIPAA compliant, cloud-synced platform that helps patients easily stay on top of their health.
We're using machine learning and computer vision to extract information from a patient's prescription/cabinet using their smartphone camera to create a personalized plan to manage their health. We're using the same technology that's used in self driving cars to detect obstacles and maneuver around them. Information include:
-Patient name, address, etc.
-Dosage (i.e.: 300 mg)
-Directions (i.e.: Take 1 tablet a day for 10 days)
-Patient can override the information if incorrect
-Find more information about the medications (effective time, meals, etc.)
In addition to automatically organizing their medications, we're building a unique solution that leverages existing smart devices to easily track a patient's health over time and be able to connect with their doctor when they need more information.
In the future, we'd like to build a database of medications/pills and be able to identify them using image recognition from the patient's mobile camera. We can leverage the National Library of Medicine's developer RxIMAGE API to obtain images and pills data that are already classified: lhncbc.nlm.nih.gov/rximage-api.
That can help with medications safety (i.e: taking the wrong medication, risk of overdose, etc.)
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