Personalized Care: CVS’s Transformation in Data Analytics

In recent years, CVS has launched a series of digital transformations such as telehealth, personalized healthcare to enhance its human-centric service. The digital transformation demonstrates effectiveness during COVID-19 and continues to provide better care for its customers.

In the era of big data and analytics, healthcare has emerged as a promising field for digital transformation. During the pandemic, digital tools such as case trend prediction and virtual healthcare have demonstrated the power of digitalization in the healthcare field.

CVS: A Health Care Giant

CVS Health, founded in 1963 and headquartered in Woonsocket, Rhode Island, is one of the largest healthcare companies in the world. It contains several areas of services such as CVS Pharmacy, a retail pharmacy chain; CVS Caremark, a pharmacy benefits manager; and Aetna, a health insurance provider.1 As Amazon becomes a more and more competitive player in the pharmacy field, CVS Health has made significant strides in its digital-first, technology-centric strategy for healthcare, streamlining services with innovative digital capabilities.

With a large customer base, CVS harnesses the powerful breadth of consumer, patient, and healthcare data. Realizing the potential in harnessing the big data, in 2022 alone, CVS invested more than $3 billion dollars in expanding and optimizing their digital systems. CVS employed cutting-edge data science methods such as AI, machine learning, cloud migration, and natural language processing to streamline the processes, and maximize the result.6

Personalized Care from Data Analytics

CVS has successfully utilized its data and the advanced analytics tool to improve its personalized care. In December 2016, CVS’ pharmacy benefit manager launched Transform Diabetes Care. The program uses rich member-specific data such as medical and pharmacy claims, demographics, and biometric information to build a predictive model with machine learning. As a result, the model informs risk levels and corresponding prevention methods for diabetes.3 The personalized program demonstrated great success: During the first two years since the launch of the program, 50% of members suffering from uncontrolled diabetes got to transition to a controlled status.4

Following the success, in December 2019, CVS launched Transform Oncology Care to inform cancer timing and treatment. The program utilizes AI to accelerate the prescribing process and matching eligible patients to clinical trials from genomic testing results. It helps manage the complex cancer journey and is expected to deliver up to a $32M reduction in drug and medical costs per 1M lives. 5

In 2021, CVS partnered with IBM Watson Advertising to build a campaign of personalized mobile messaging on The Weather Channel app. This campaign identifies customers in high-flu areas and engages them with flu shot offerings and flu remedies available at nearby CVS Pharmacy stores. Through this channel, CVS generated over 59 million views on their “Daily Details” page through CVS media outreach. With the advance of AI, CVS utilizes AI to make more informed and personalized health decisions for patients in many fields.

More Robust Data Platforms

CVS Health experienced a 600% increase in the utilization of their retail health clinics through telehealth services and saw a substantial rise in home delivery of prescriptions in May 2020 compared to the same period in 2019. How could CVS maximize the potential of the large database?

CVS Health harnesses the power of Databricks and Microsoft’s Azure to create robust data platforms integral to their personalized customer strategy. CVS wants to measure, for example, the probability of a customer buying a particular drug or when to remind a patient to pick up their medication. However, the complexity and scale of data for its 80 million customers in about 10,000 stores made it difficult to run on CVS’s own environment. As a result, in 2018, CVS decided to transition to a Microsoft Azure Databricks platform to scale its personalized offers. The new, collaborative cloud environment also allowed teams to work together and boosted efficiency. The improved personalization process demonstrated a 1.6% improvement in medication adherence.2 Roshan Navagamuwa, CVS’ chief information officer, said that “Microsoft’s capabilities and the Azure cloud computing service will provide CVS with a ‘technology-forward, digital-first’ foundation as it works to ramp up its consumer-centric digital strategy”8

Challenges: Data Privacy

CVS Health faced significant challenges in data security, a critical aspect of the big data era. In 2019, it was reported that 1.1 billion CVS Health records of 204GB were exposed due to an unauthorized entry into the unsecured database. The records contain customer email addresses, user IDs, and customer website searches. The database was hosted by a third-party vendor. Although no personal health information was compromised, the event underscored the importance of robust data governance, especially with third-party vendors, to prevent future leakage of important health data.


1. “CVS Health.” Wikipedia, Wikimedia Foundation, 11 Sept. 2023,

2. “Customer Story: CVS Health.” Databricks, Accessed 17 Oct. 2023.

3. “Next-Generation Transform Diabetes Care.” CVS Health Payor Solutions, Accessed 17 Oct. 2023.

4. Mixson, Elizabeth. “Is CVS Health Becoming the Netflix of Healthcare in the Age of Pandemics and Disruption?” AI, Data & Analytics Network, 29 Aug. 2023,

5. “Transform Oncology Care.” CVS Health Payor Solutions,,medical%20cost%20per%201M%20lives. Accessed 17 Oct. 2023.

6. Mixson, Elizabeth. “CVS Health Goes from Digital Transformation to Digital Optimization.” Intelligent Automation Network, 29 Aug. 2023,

7. “CVS Health.” Informatica, Accessed 17 Oct. 2023.

8. Landi, Heather. “CVS Inks Tech Partnership with Microsoft to Accelerate Its ‘digital-First’ Strategy.” Fierce Healthcare, 2 Dec. 2021,


BIG Data in Tesla Inc.


Splunk: Navigating the Digital Landscape with Data-Driven Insights

Student comments on Personalized Care: CVS’s Transformation in Data Analytics

  1. Thank you Serena for this amazing post! I have always thought about how CVS is at a great position in using data to enhance and healthcare and your analysis really helps me understand the specific processes. Everything seems very natural and amazing: CVS works with Microsoft and its big data collection to provide predictive options for diabete, cancer, flu, etc. I also really like your mentioning of the data privacy leaking case at the end, which may be more serious in the context of health information comparing to other fields where data might not be as sensitive. I also would like to stretch other challenges stermed while I reading the post:
    I learned about how messy EHR data could be for machine learning models at HMS. I wonder how well could CVS build models that actually help the population in a proper way (such as low additional financial burdens) that is also unbiased towards demongraphics or psychographicsa. For risk predictions, where the outcomes of the deployment of ML to predict if you are at risk is always better than nothing, it might make sense to trust a more liberal algorithms that minimize false negatives. However, how about the effects of false positives (patients who are not at high risk but predicted by model to be of high risk), which could really add unnecessary financial burdens to patients. Is there an actual moral balance between minimizing false positives vs. false negatives in the context of health vs. finances? Of course this is a question that is almost impossible to be answered but very interesting and crucial to think about.

  2. This is awesome! Healthcare is simultaneously a big data player’s wildest dream and worst nightmare. The pure volume of data available, alongside the mission criticality of its use cases means there is so much opportunity to build rewarding (both intrinsically and financially) products, which is something that CVS appears to have accomplished here. However, the fragmentation of the space in general means data collection and usage is extremely difficult, and the albatross of government regulations hang over every step of the value chain.

    I know many digital health startups have tried making a business out of helping people design custom digital health plans, but customer acquisition was always the hard part, especially since many of the end users were either unused to these technologies, or could not bear the monetary or labor burden of adding another service to their mix. CVS is in a great position to offer this as a value-add service. However, given recent market conditions that has put greater pricing pressures on traditional pharmacies (ex. California recently announced it would not longer use CVS), I do worry that these data-fueled services will get even more fragmented, and undermine their existing (and somewhat tenuous) viability.

Leave a comment