The explosive adoption of wearable ‘health’ trackers reminded me of when the iPhone first debuted. From the 50 year old marathoner to the twentysomething professional, it seemed like everywhere I went, someone was adorned with a fitness tracker. Individuals were amassing data on steps taken, blood pressure (sometime inaccurate), heart rate and calories burned. This new type of patient generated health data spurred a number of health technology startups that promoted their ability to integrate and analyze this data and report insights to physicians, payers and pharmaceutical companies.
As a clinical research professional I knew this type of patient generated data would only have a limited impact. My dentist, PCP and colleagues wore these trackers, but more importantly do you know wasn’t wearing one? My diabetic and stroke survivor father, his neighbor with COPD and my mentor with rheumatoid arthritis. Fitness wearables aren’t tracking glucose levels, medication compliance or side effects.
Patient generated health data that captures data from chronic disease patients is truly valuable. We can observe how a patient is managing their disease and medications with this type of data. In combination with data collected by physicians and payers, this type of data can provide a better picture of population health. Specifically, more complete health data can help us monitor patient outcomes with medications. In drug safety this is called real world evidence of a drug’s true effectiveness.
Clinical trials help determine the safety and effectiveness of a medicine, but this is in a controlled environment with a limited number of subjects. Additionally, there are medicines that subjects are prohibited from taking during a trial, but once the drug is approved these same limitations don’t always exists. This is why it is important to monitor how drugs perform in the real world, you have a larger population of people taking the drug for an extended amount of time and this is how additional side effects are revealed.
Currently, the identification of the real world effects of a drug an expensive and reactive process. Companies rely on adverse events reported to the FDA, post market surveillance data and additional clinical trials to obtain these insights. My company, MobiDox Health Technologies, Inc is developing an analytical platform to help identify Real World Evidence of drug safety and efficacy. Our algorithms and models identify unknown or underreported adverse events of selected medications. We identify the costs associated with these adverse events and serious adverse events and quantify how effective these medications are in the real world.
Initially we are comparing the safety and effectiveness of medications by analyzing EHR, lab, claims, prescription and patient generated health data. We have developed algorithms that can identify unknown or underreported adverse events of selected medications. Our solution will help to identify the costs associated with these adverse events and serious adverse events and quantify how effective these medications are in the real world.
Reimbursement for medication is shifting to a pay per performance whereas depending upon how the medications perform in the real world will determine how much or how little Payers will reimburse the manufacturers for the drug. Pharmaceutical Companies are also focusing on creating medications with fewer serious adverse events and better outcomes- which would correlate with better patient compliance and adherence.
We see patient generated health data as a valuable resource in identifying real world evidence of medicine and MobiDox Health Technologies, Inc will use the next generation of health devices, wearables, and applications, to not just capture activity, but capture real patient outcomes of a medicine’s overall performance.