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Big Data in Healthcare — Friend, Foe, or Fiction?

While the theme for PMSA’s Annual Conference last week was Analyze/Influence/Innovate, there was no mistaking the unspoken theme was, “Big Health Data.” Now we have all been overwhelmed by the (over)use of big data in almost every aspect of business, it is important that we take time to understand exactly what it means in Health and Pharmaceutical analytics. With dramatically increased adoption of Electronic Medical Records (EMR)/Electronic Health Records (EHR) across the US and more powerful computing capability helping us to better understand unstructured data, the opportunities for analysis and insight continue to evolve. Whether it is developing a better understanding of the patient journey or simply what drives physicians to make certain decisions by leveraging health data (e.g. EMR/EHR data and patient claims data) in all of its forms, a bright future for data-driven health care insight is forecast.

Traditional Rx data only shows us the changes in physicians’ behavior. We don’t know:

  • Which patient conditions or PRO (patient reported outcomes) drives physicians’ decisions
  • Which patient profiles/segments they consider most appropriate for certain treatment
  • If an OTC product may be recommended instead of a prescription drug
  • Why they may discontinue treatment for certain patients and not others

Using claims data, we can also see the complete patient journey: from diagnosis to prescription to hospitalization and post-discharge treatment. Without understanding these underlying factors, we run the risk of over- or under-estimating physicians’ response to brand marketing communications, which may lead to sub-optimal budget allocation.

Combining claims data and EMR/EHR data, we can identify patients who are most likely receiving treatment with the specific treatment concerns of their physician. This allows us to do a better job of targeting relevant patients, which can in turn target correct messaging to physicians by addressing their unique concerns. In addition, understanding the needs of physicians and patients better, we can provide a portfolio of better patient/physician support rather than just being a drug seller.

While preparing to embrace the broader data universe, we should realize that there is still a long way to go to fully integrate EMR/EHR data into our analysis as the inputs remain unstructured and complex and can certainly send us in the wrong direction if analyzed/interpreted incorrectly. While we continue to explore the value of “Big Health Data,” we need to keep our eyes on the goal, pulling in the appropriate variables that will complement and direct relevant, timely, and actionable insight. 

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