Let’s start with “what is dark data?”
Dark data has many definitions. For our purposes here, dark data is simply data that is not being used to its full potential and has gone "dark." Many organizations and businesses do collect, process and store data, but fail to leverage it effectively for other purposes. This includes GPS tracking data that often serves no purpose once the route has ended, or social media and purchase decisions that stay within the sites that collected the information and then go "dark."
The hype around hyper-personalization
You’ve probably noticed when companies strive to provide you with a more personalized experience. Examples include music or movie recommendations on your streaming platform based on past preferences or targeted ads on your phone app based on your GPS location or recent browser search.
But how does this relate to healthcare? If your healthcare provider had access to your non-clinical dark data—like travel and social media information—they could combine it with your clinical information to hyper-personalize treatment. For example, imagine you need to fly to Seattle on a work trip. As soon as you book your trip, you post a trip notice on social media. This notifies your healthcare provider and triggers them to text you a flu-shot recommendation as a flu outbreak has been noticed in Seattle. Or someone in Atlanta who usually buys allergy medication for high-pollen season can be alerted that a high-pollen count has been forecasted and it’s time to pick up a refill.
Ultimately, by combining dark data and clinical data, healthcare treatment can become even more hyper-personalized to reach the right patients, at the right time, with the right treatment at the right dose.
What's the prognosis for leveraging dark data for hyper-personalization?
Let's look at just the impact from early intervention or prevention of influenza (flu), the common cold and allergic rhinitis (allergies) on presenteeism (present at work while sick) and absenteeism (sick days taken).
Cutting down the 197 million days of lost productivity due to absenteeism and 419 million days of diminished productivity due to presenteeism from the flu, cold and allergies would represent about $200 billion in productivity gains from 2018-2030.
View the infographic
More information = smarter healthcare = less sick days
Hyper-personalization will result in services particular to patients’ specific needs. This includes:
- Earlier identification and treatment of common illnesses
- More accurate treatment, medicines and dosages
- Less work (and non-work) days missed or suffering from illness
- More proactive and personalized healthcare
What needs to happen to make this hyper-personalization a reality?
Amongst many things, the healthcare industry will need to address the following in order to take advantage of dark data, utilizing it to improve hyper-personalization:
- Process and procedures for driving patient consent for using their non-clinical data
- Rules and regulations to address and protect patient privacy
- Adequate data storage that’s structured for quick access to information and insights
- Incentives to participate that ensure gains across all stakeholders