Many describe the shift to value-based healthcare as a transition from volume to value. Instead of measuring the quantity of services delivered, payors, providers, and device and drug manufacturers are increasingly being pressured to measure the value provided to patients.
Leaders of the value-based care movement argue that changing the focus of what gets measured can make all the difference. Michael Porter, co-author of Redefining Health Care, has stated, “Where we see systematic measurement of results in health care, no matter what country, we see those results improve.”[i] In principle, changing what you measure is simple, but measuring value is not simple. If measuring value were easy, everyone would already be doing it. Counting how many pills someone takes is a lot easier than figuring out how much those pills improved a person’s life.
QUANTIFYING VALUE
Robert W. Dubois, the Chief Science Officer of the National Pharmaceutical Council explains the challenge pharmaceutical companies face when trying to measure how taking a drug affects a person’s life, “To determine how patients did, requires a lot of data. Clinical data, volume data, some of it is easy to collect, and a lot of it is very hard to collect.”[ii] Value-based care depends upon that ’hard to collect’ data.
“The promise of value-based care hinges on the healthcare industry’s ability to collect real-world data."
Focusing on the value of healthcare treatments requires a mindset that goes beyond the traditional model of clinical trials and post-market surveillance. Measuring the actual value of treatments will depend almost entirely on real-world data. The FDA describes real-world data, also known as real-world evidence, as, “Healthcare information derived from multiple sources outside of typical clinical research settings.” This includes data from EMRs, insurance data, product and disease registries, data from smartwatches and fitness trackers, and much more.[iii] In order to show that your devices, drugs, and services are adding value to patients’ lives, you need to collect real-world data, and you need to start doing it now. The promise of value-based care hinges on the healthcare industry’s ability to collect real-world data.
ALL DATA IS HEALTH DATA
The definition of “healthcare data” is widening rapidly. The Apple Watch’s ability to conduct an ECG has demonstrated that data from smartwatches should be considered healthcare data. Studies that have shown social media behavior can be used to predict mental health diagnoses have pulled browsing history and all other online behavior into the realm of healthcare data as well. Anything that can be tracked digitally, can be leveraged for health-related insights. The potential for this data to improve the quality of healthcare outcomes is so great that it makes navigating the HIPPA complications that accompany these nontraditional data sources worth the hassle.
“Healthcare businesses need to think creatively and quickly to figure out the most effective, efficient, and ethical ways to collect the data sets that can demonstrate the value of the treatments they provide."
With the advancement of the internet of things, beacon technology, and the 5G network, anything and everything can be tracked. Healthcare businesses need to think creatively and quickly to figure out the most effective, efficient, and ethical ways to collect the data sets that can demonstrate the value of the treatments they provide.
THE DATA COLLECTION COMPETITION
Healthcare companies are currently at a disadvantage because consumer tech companies already have public-facing interfaces and greater brand awareness. Consumer tech companies are in a better position than traditional health-related companies for making discoveries that could improve the value and quality of healthcare.
Look at Google for example, ten years ago they were already publishing about their ability to use search history data to predict influenza outbreaks 7-10 days ahead of the CDC.[iv] The Google Flu Trends project demonstrated that if you have enough data, and analysts capable of making sense of it, any data set can be used to make an impact in the healthcare industry.
“Consumer–tech companies have proven it is possible to collect real-world data and use it to make meaningful health-related discoveries.“
Google’s claim of over 90% of the world’s search data, combined with their acquisition of Nest and their growing market share of smart speakers that double as surveillance devices, puts them in control of more real-world health data than any healthcare company.[v] Apple, Facebook, Amazon, Microsoft, and a handful of others also have data sets that dwarf that of most healthcare companies. Consumer-tech companies have proven it is possible to collect real-world data and use it to make meaningful health-related discoveries.
THE WORRELL SHARE STUDY (AN EXAMPLE OF REAL WORLD DATA COLLECTION IN ACTION)
Part of what makes real-world data collection so difficult is that it requires a wide variety of skill sets. In order to succeed with real-world data collection, you need expertise in user experience, user interface design, software development, and data analysis.
SHARE is a recent example of a real-world data project we’re conducting at Worrell. Although it didn’t launch as part of a value-based care project, it demonstrates the amount of vertical integration needed to effectively collect the real-world data that’s necessary to quantify the value of care. The goal of SHARE, which stands for Stress Heartrate Activity Rest Evaluation, is to explore the connections between a person’s heart rate variability and their self-reported stress levels.

First, we determined that working within a consumer-facing platform would be quicker and more cost-effective than developing our own devices. We decided to use the Apple HealthKit to design our program and use the Apple Watch to collect heart rate data. The AppleWatch was already part of people’s lives, so research participants didn’t need to change any of their habits. The biosensors within the Apple Watch allowed us to passively collect the users’ steps, calories burned, and heart rate variability.
We also needed to include an active form of data collection. We wanted to see if people’s self-reported levels of stress would correlate with the biomarkers collected passively. From previous research, we knew the design and usability of the app would have a major effect on participant compliance. To make the reporting of stress levels as easy as possible for the research participants, our UX team designed a very sleek and usable app and integrated a Google Skill that would periodically walk participants through survey questions to measure their current level of stress. We leveraged the voice capabilities of Google Skills, so participants could fill out the survey on their device by clicking and writing or by speaking.

A benefit of real-world data collection is that you can collect the data and start analyzing it while the study is still active. As the devices collect data and the participants complete surveys, our digital solutions team analyzes the data to find out how heart rate variability correlates with self-reported stress levels. (Since this study is still ongoing, we are not publishing the findings yet.) The amount of data the Apple Watch collects will also allow us to detect other patterns we weren’t originally looking for such as how a person’s heart rate variability relates to the number of steps taken in a day. Our multidisciplinary approach to the SHARE project allowed us to maximize the amount of data we collect, and the more data we collected the more valuable insights we can discover.
MOVING FORWARD
The potential for value-based care to improve the quality of healthcare outcomes and lower healthcare costs has been well documented. All those benefits will only come to fruition if healthcare companies can figure out a way to quantify the impact of their treatments. Now, it’s time for the healthcare industry to rise to the occasion and start developing their own systems of data collection for proving and improving the value of their products and services.
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[i] Lee, T. H., & Porter, M. E. (2015, September 14). The Strategy That Will Fix Health Care. Retrieved from https://hbr.org/2013/10/the-strategy-that-will-fix-health-care
[ii] npcnow. (2015, September 15). Risk-Sharing Agreements in the US: Trends, Barriers and Prospects. Retrieved from https://www.youtube.com/watch?time_continue=111&v=vVLFNNWaEOQ
[iii] Cavlan, O., Chilukuri, S., & Westra, A. (2018, May). Real-world evidence: From activity to impact in healthcare decision making. Retrieved from https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/real-world-evidence-from-activity-to-impact-in-healthcare-decision-making
[iv] Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012–1014. doi: 10.1038/nature07634
[v] statcounter. (2019, August). Search Engine Market Share Worldwide. Retrieved from http://gs.statcounter.com/search-engine-market-share