Free Apple Watch! and other ways Aetna is embracing digitization
Aetna is using digital technologies to create efficiencies in the health insurance supply chain.
The health insurance industry can be thought of as a marketplace: on one side, customers pay for coverage of healthcare costs and seek a variety of providers. On the other side, providers look to the marketplace for patient volume and accept a discounted rate for services. Payers intermediate between the two, bearing risk and providing liquidity.[1] Thus, for payers, the supply chain can be conceived of as streams of services and payments.
Figure 1. Illustration of payer supply chain
Source: Author’s diagram based on Bardey and Rochet, “Competition between HMO and PPO,” Journal of Economics and Management Strategy, 2010.
In the health insurance market, supply chain efficiencies are realized by increasing visibility into future demand (underwriting advantages) and/or reducing coverage costs. Digitization will reward payers who can deploy technologies to increase supply chain efficiency.[2] Aetna, the third-largest health insurance payer in the U.S., has embraced digitization in order to realize supply chain benefits for patients, providers, and shareholders. Aetna has created current, near-term, and medium-term partnerships to encourage development and adoption of digital initiatives, including:
- Developing digital therapeutics to manage chronic conditions[3]: A pilot study of a device-app combination providing mobile monitoring and coaching to patients with Type 2 diabetes aims to measure how digital health devices can improve patient outcomes and reduce care costs.[4],[5]
- Partnering with providers to expand applications of telemedicine: Next year, Aetna members will receive behavioral health, dermatological, and caregiver telemedicine services.[6] This expands patient access, enables clinicians to serve more patients, and reduces costs of clinical visits.[7]
- Leveraging big data to predict treatment outcomes[8]: A 2014 longitudinal study of members to predict pre-diabetes allowed Aetna to design and launch customized interventions and quantify returns on program investment.[9] Today, Aetna’s business unit Healthagen Outcomes uses member data to validate new therapies, technologies, and care models.[10]
- Offer discounted Apple Watches to members to predict risk and more[11]: Aetna is betting that wearables can provide insight into coverage risk of members; in the future, wearables could also to facilitate proactive interventions before patients get sick, potentially avoiding dangerous and expensive complications.[12] However, the type of data collected, the precision with which it is measured, and the security with which it is transmitted will all impact how and when these types of applications can occur.
From both the top line (expanding access) and bottom line (improving visibility and reducing costs), these potential improvements in supply chain efficiency can add value for all stakeholders. However, there are additional efficiencies that digitization can bring to the health insurance market. In the near-term, Aetna should incentivize partners to upgrade closed EMR systems to open, networked systems to facilitate claims submissions and remittances; this will reduce costs associated with billing and may facilitate provider adoption of existing digital innovations. With the industry move to value-based healthcare in the medium term, Aetna should also harness big data and predictive analytics to improve population health management.
Despite the innovations described above, there are many uncertainties in health insurance markets that may influence benefits or adoption of digitization: we will likely see regulatory changes in the next several years, as well as burgeoning issues of cybersecurity. How these trends impact supply chains of payers like Aetna remains to be seen.
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End Notes
[1] Bardey, D. and Rochet, J.C., 2010, “Competition among Health Plans: A Two‐Sided Market Approach,” Journal of Economics & Management Strategy, 19(2), pp.435-451. Vancouver, http://idei.fr/sites/default/files/medias/doc/by/rochet/bardey_hmo_ppo_020209.pdf, accessed November 2017.
[2] La Paz, H., “Data, devices, apps & access: 4 ways tech is transforming health care,” October 2, 2017, on Aetna website, https://news.aetna.com/2017/01/data-devices-apps-access-4-ways-tech-is-transforming-health-care/, accessed November 2017.
[3] Olson, P., “Wearable Tech Is Plugging Into Health Insurance,” Forbes, June 19, 2014, https://www.forbes.com/sites/parmyolson/2014/06/19/wearable-tech-health-insurance/#5ac405d918bd, accessed November 2017.
[4] “Innovation Health Announces Pilot Program with Sanofi to Improve Care Delivery for People Living with Type 2 Diabetes,” BusinessWire, September 25, 2017, http://www.businesswire.com/news/home/20170925005100/en/Innovation-Health-Announces-Pilot-Program-Sanofi-Improve, accessed November 2017.
[5] “Innovation Health testing tech to manage diabetes,” press release, October 24, 2017, on Aetna website, https://news.aetna.com/2017/10/innovation-health-testing-tech-to-manage-diabetes/, accessed November 2017.
[6] “Aetna offers members expanded services through Teladoc,” press release, October 2, 2017, on Aetna website, https://news.aetna.com/2017/09/aetna-offers-members-expanded-services-teladoc/, accessed November 2017.
[7] “Teledermatology: less wait time, saves costs,” press release, October 2, 2017, on Aetna website, https://news.aetna.com/2017/07/teledermatology-less-wait-times-saves-costs/, accessed November 2017.
[8] Goyal, N., “4 Trends In Digital Health To Keep An Eye On In 2018,” Forbes, September 29, 2017, https://www.forbes.com/sites/quora/2017/09/29/4-trends-in-digital-health-to-keep-an-eye-on-in-2018/#210f577d64ac, accessed November 2017.
[9] Steinberg, G., et. al., “Novel Predictive Models for Metabolic Syndrome Risk: A “Big Data” Analytic Approach,” The American Journal of Managed Care, June 2014, http://www.ajmc.com/journals/issue/2014/2014-vol20-n6/novel-predictive-models-for-metabolic-syndrome-risk-a-big-data-analytic-approach, accessed November 2017.
[10] “About Us,” Helthagen website, http://www.healthagen.com/, accessed November 2017.
[11] Farr, C., “Aetna scoops up rising star from Wal-Mart’s health group to lead Apple Watch partnership,” August 29, 2017, https://www.cnbc.com/2017/08/29/aetna-hires-ben-wanamaker-to-lead-its-joint-venture-with-apple.html, accessed November 2017.
[12] “Wearables technology can help healthcare go from reactive to proactive,” April 24, 2017, on Aetna website, https://news.aetna.com/2017/04/wearables-technology-can-help-health-care-go-from-reactive-to-proactive/, accessed November 2017.
While data undoubtedly opens up new avenues for patient management and disease prevention, there should be cause for concern when it comes to appropriate use of patient data. Devices and applications that collect patient data (Fitbit, Apple Watch, etc.) are not only accessible by payors but also third-party groups like advertising companies, some of which are subsidiaries of digital analytics and tracking groups, including device manufacturers like Apple and Google. In today’s digital world, almost no level of data is truly private. When consumers are trying to leverage data to improve outcomes, those who are not healthy risk having their data fall into the hands of large payors who might use that data to set policy premiums. Being the stakeholder who is providing economic distribution of health gadgets as well the stakeholder controlling healthcare expenses, insurance companies have a large responsibility to remain ethical when analyzing patient data. As both payors and providers seek new avenues to learn more about customer behaviour, it possible that there will be large-scale consolidation between health insurance providers and healthcare companies, further blurring the ethical line to gaining patient data. If the stakeholders can keep data safeguarded in the right ways, devices like Apple Watch have the opportunity to course correct America’s dire status with chronic illnesses. The FDA has made significant strides in regulating patient data in mobile health and health IT solutions but much still remains to be established in the field. Who will stand up for policing the ecosystem? Can we develop programs that make it possible for patients to control when data is released? Technology will move very fast, but the challenge still remains to have all the other pieces of the ecosystem keep pace so we don’t miss out on the opportunity to bring quality health back into the hands of the patient.
I agree with your assessment that assumption of data privacy in this day and age is at best naive; however, I would argue that the items you point out as “ethical concerns” are the primary reasons a company like Aetna would pursue this kind of partnership and innovation. Aetna can learn more about the risk profiles of the pools of patients it is insuring, thus allowing it to charge premiums most in line with the predicted costs of coverage. I also disagree that consolidation between payors and providers implies an ethical concern. I think that in the healthcare industry, maximum transparency and alignment of incentives will result in the most utilitarian outcomes. Especially when it comes to HMOs, I think that aligning payor and provider incentives encourages preventative health programs, prevents unnecessary procedures and treatments, and reduces total costs in the system.
Big data and telemedicine innovations are definitely game-changers in the health insurance industry. In addition to risk prediction, data collection via wearables can also incentivize desirable behavior and provide input for dynamic pricing of insurance products based on the customer’s activity. Some health insurance players in Asia (e.g., Manulife) have innovated on pricing programs that offer discounts to the customer based on their exercise progress monitored by a fitness wearable device that comes free with the insurance product.
The industry is also seeing vertical integration and online-to-offline integration across the supply chain as evident from CVS’ recent acquisition discussions with Aetna and Amazon’s moves in recruiting health insurance experts to potentially enter the healthcare space. It will be critical for health insurance players to develop analytics capabilities and meaningful e-commerce and telemedicine partnerships to sustain a competitive advantage. Data privacy will be a major concern, especially in developed markets like the US, and the speed of regulatory development and security sophistication of players make a huge difference in whether this will take off.
Thank you for your insights here Christina. This was an opportunity that my last company (high touch primary care for seniors with multiple chronic conditions) thought about very closely. I agree that some wearables can flag health concerns and play a role in prevention but as I think about the healthcare cost equation, I worry that they might not be well poised to really make a dent. The bulk of the Medicare cost to the US healthcare system comes from seniors with multiple chronic conditions. While wearables could play an important role in monitoring their health, adoption has been slow for this population and they struggle with utilizing the devices appropriately.I would personally love to get a discounted Apple watch from my insurer but then again, I am not a part of a population that is really contributing to the high cost of healthcare in the US. I fear that companies may invest in wearables and not see significant results where it counts from an overall cost standpoint.
I agree that the overall industry should move toward value-based, consumer-driven healthcare, and that collecting patient data through wearables has many interesting applications.
My cousin ran a study at UCSF last year to evaluate whether giving away free Fitbits to adult Type 2 diabetic women would increase weight loss. In addition to incentivizing healthy behavior (which it effectively did), it provided health care providers with accurate, reliable data on consumer behavior.
HBS professor Regina Herzlinger has long-advocated for consumer-driven healthcare, which she illustrates through a case on South African insurer Vitality [1]. Essentially, she thinks that consumers should get paid if they take care of their diseases. If you have asthma and quit smoking, you get paid. If you have diabetes, and go to the gym, you should be compensated. The financial return to employers for participating in these systems is in increased employee productivity; for example, fewer employees have back problems that distract them from work.
Tying this back to wearables – if you subsidize the cost of wearables, you can collect better data on whether patients are actually participating in some of these activities, and compensate them for that. On the mental health side, innovative upstarts like Ginger.io have developed algorithms that monitor your activity through mobile or wearable devices and notify your close-ones to intervene if you’re exhibiting behavior predictive of a mental health episode.
[1] https://hbswk.hbs.edu/item/making-health-insurance-that-consumers-actually-like
Thanks Christina for this research! It is very interesting to see the efforts Aetna and other payers are putting into technology partnerships. One of my concerns regarding some of these efforts is the impact. For example, while wearables are enabling more technology adoption by users, the data from wearables has not made its way into EHRs and therefore has not led to action taken by patients. [1] I can see a future in which this information can be incredibly useful and actionable. However, given that at this time it is not being used, I worry that the hype and interest in wearables will deteriorate ultimately making it much harder to convince users to readopt the wearables once the technology is more advanced.
Another concern is the recommendation for Aetna to harness big data and predictive analytics. While I agree that this would be ideal, given that data is stored on hardware on-site and has limited standardization, it would be incredibly challenging to accumulate the data to do this analysis. From my perspective, until there is more regulated standardization across healthcare, the compilation of data will continue to be an incredibly manual burdensome process. [2] [3]
[1] http://www.modernhealthcare.com/article/20170930/NEWS/170929877
[2] https://healthitanalytics.com/news/top-10-challenges-of-big-data-analytics-in-healthcare
[3] https://revcycleintelligence.com/features/why-healthcare-needs-value-based-supply-chain-management
Thanks for such interesting thoughts Christina!
The health insurance system is indeed undergoing a digital revolution that will profoundly affect the health care of Americans. I share some of the concerns that Ruksi mentioned, that an overall challenge is that is actually quite difficult to share information between electronic records systems, so the promise of having data follow patients has so far proved elusive. Also, some electronic health records are complex and difficult to use. This is frustrating for doctors and nurses, slows them down, and can even cause safety issues. Still a third problem is that comparatively few records have added on the software – so called decision support – that could help process digitized health data and make it useful for providers and patients. [1]
[1] https://hbr.org/2016/02/speeding-up-the-digitization-of-american-health-care