The future of healthcare marketing: Privacy-first personalization in a cookie-less world
Jan 8th, 2025
In recent years, there’s been a big push for stronger privacy protections in healthcare marketing, driven by both consumers and regulators. From HIPAA compliance with protected health information (PHI) to California’s privacy laws around tracking technologies like pixels, and Google’s move to phase out third-party cookies, the trend is clear: privacy is a priority.
For healthcare marketers, this shift means moving away from traditional tactics that have long been used to engage audiences—and rethinking how they approach personalized marketing. In this post, I’ll dive deep into how HIPAA-approved one-to-one marketing can help tackle the challenges of a cookie-less future, allowing healthcare organizations to build more effective, privacy-first marketing strategies that drive long-term value.
For even more insights on this topic, be sure to check out this webinar, where myself and DH Senior Product Marketing Manager, Kevin Dubuc, talk live about all the critical details you need to know.
So what’s the big deal about cookies?
The real concern with third-party cookies lies in the privacy risks they pose. These cookies allow advertisers to track users across various websites, building highly detailed user profiles—sometimes without the user’s knowledge or consent. This capability has raised significant privacy concerns and triggered a wave of regulatory action, including the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the U.S., both of which aim to provide users with more control over their personal data.
Health systems and tech companies are facing lawsuits over tracking technologies
The controversy surrounding tracking technologies has also led to a wave of high-profile lawsuits. In 2024, several healthcare organizations faced legal challenges related to the use of tracking technologies. Atrium Health and Palm Beach Health were both sued over the use of tracking tools like website trackers and Meta’s Pixel, while Kaiser Permanente reported a data breach exposing personal member information to third-party advertisers, including Google, Microsoft and X, the company formerly known as Twitter. These incidents highlight the growing privacy risks for healthcare providers using tracking technologies.
A wake-up call for healthcare marketers
In response to privacy concerns, major browsers like Google Chrome are phasing out third-party cookies in favor of privacy-friendly alternatives. The goal is to limit the ability of companies to track users across the web for ad targeting. This shift will have a significant impact on healthcare advertisers, particularly given that Google Chrome commands 68.4% of global web traffic, as shown below.
Most web traffic is driven by Chrome
Fig 1 Browser market share data for December 2024, as reported by StatCounter, covering global web traffic across all platforms (desktop, mobile, and tablet).
While the removal of third-party cookies presents new challenges, it also offers healthcare marketers an opportunity to adopt privacy-first strategies and engage audiences in new, compliant ways. Originally, Google had planned to phase out third-party cookies by 2024, but this has been pushed back to 2025, giving advertisers additional time to refine their strategies and test privacy-focused alternatives.
Predicting healthcare needs with first-party data
Some healthcare organizations may look to first-party data—such as information collected from electronic health records (EHRs) or patient interactions on their own websites—to predict healthcare needs and personalize marketing. This reflects a more traditional approach to predictive marketing, where organizations relied heavily on their own data to forecast trends and target individuals.
While first-party data offers valuable insights into your own patient population, it does have limitations. For one, it provides an incomplete view of the broader market. You may know your patients well, but without visibility into national trends or wider patient behaviors, your predictive models could lack accuracy and fail to reflect broader patterns. Moreover, EHR interactions and campaign responses tell us only fraction about the consumer, offering limited insights into the full context of the consumer’s story.
Additionally, patient data is not static—it evolves over time as health conditions change, risk factors shift, and patients move between multiple providers. For example, a patient’s risk for colon cancer will change as they age. A model built on a “moment in time” dataset won’t capture these ongoing shifts, which are critical for accurate predictions.
Lastly, privacy and security concerns loom large when working with first-party data. Any healthcare data breach can result in significant financial penalties, lawsuits, and severe damage to your organization’s reputation. Beyond the risk of data breaches, there’s also the potential for inadvertently using patient data in ways they haven’t explicitly consented to, which could lead to privacy violations, as seen in the lawsuits mentioned earlier.
How to prepare for a cookie-less future using third-party data
Given the challenges of relying on cookies or first-party data, healthcare marketers need to rethink their approach to personalization. One solution lies in leveraging third-party, HIPAA-compliant de-identified data, such as claims data or aggregated consumer information from external sources. This data not only allows you to build predictive models that anticipate care needs accurately and compliantly, but also offers a deeper, contextualized understanding of your consumers.
By using third-party data, healthcare marketers can still engage in one-to-one marketing—personalizing messaging and outreach to individual patients—without compromising privacy or violating HIPAA regulations. This de-identified data also allows organizations to create highly relevant marketing efforts based on broader healthcare trends, going beyond the limitations of in-house data that only reflect your own patient base.
The power of de-identified claims data in building predictive models
A key advantage of HIPAA-approved marketing lies in the use of national claims data, which provides comprehensive, de-identified information from across the healthcare ecosystem. From this data, marketers can gain a more holistic understanding of the market, including trends in procedure volumes, referral patterns, and patient behaviors on a national scale. This broader perspective not only enhances the accuracy of market predictions but also supports more targeted, scalable marketing strategies. With a clearer view of healthcare trends and consumer needs, organizations can create more effective, data-driven campaigns.
Unlocking patient insights with de-identified claims data
The process begins with aggregating diagnostic codes and procedure codes related to a specific condition or treatment—say, arrhythmia. By reviewing claims data, you can identify patients who have been diagnosed or treated for arrhythmia. Importantly, this data is de-identified, meaning it doesn’t contain any personally identifiable information (PII). The focus is on understanding patterns of care: What do these patients look like? What demographic factors are common among them?
Creating personas for healthcare-enriched predictive marketing
With this de-identified data, marketers can begin to build consumer personas. For example, in the case of an arrhythmia model, you’ll understand the common demographic attributes of individuals who have received arrhythmia-related care: their age, life stage, gender, and more—but never any specific PHI.
From there, you can build a lookalike audience based on this information. You’re essentially creating a profile of the “ideal patient” for arrhythmia care based on the aggregated characteristics of people who have already sought similar care. Once you have this persona, you can apply it to a much broader consumer dataset, which helps you identify individuals who share similar traits or behaviors to those already receiving care for arrhythmia. This enriched data can also help you understand where to reach these consumers and even their likelihood of having insurance coverage.
Moving beyond retargeting: using data to predict future demand
One of the most powerful aspects of this process is the ability to move beyond simple retargeting and focus on propensity models—predicting who is most likely to need specific treatments, procedures, or services in the future. In traditional cookie-based marketing, retargeting and remarketing are based on users’ past behaviors—what websites they’ve visited, what products they’ve looked at, or what ads they’ve interacted with.
But with healthcare-enriched predictive targeting, you’re able to create personas based on clinical and demographic insights that forecast future healthcare needs and behaviors. This is a more reliable and privacy-respecting way to connect with consumers and patients, particularly in healthcare where the stakes are higher for patient privacy.
Why national data makes a difference when targeting niche populations
National-level data also enables you to address more low-frequency but high-value procedures, such as organ transplants. These are harder to predict using first-party data because the patient population for such services is often smaller and more geographically dispersed. With national claims data, however, you can identify broader trends and patterns across healthcare systems and regions, which improves the accuracy of your models and makes it easier to target smaller patient populations.
The bottom line: privacy and accuracy in healthcare marketing
In a cookie-less world where data privacy concerns are paramount, using HIPAA-approved, de-identified healthcare data allows healthcare marketers to maintain compliance while improving the accuracy and relevance of their marketing efforts. This approach supports:
- Faster time to value with quicker insights and activation
- Higher accuracy in predicting future patient needs
- Stronger targeting capabilities without violating privacy
- More personalized, relevant messaging that aligns with patients based on their real needs
Rather than relying on first-party data or cookies, marketers can use predictive models that are statistically relevant and reflective of longitudinal patient behavior. This isn’t just a shift in technology; it’s a shift toward more responsible, data-driven marketing that protects patient privacy while delivering better results.
Learn more
As cookies are phased out, healthcare organizations can no longer rely on traditional tracking technologies to understand and reach healthcare consumers. Instead, many are turning to third-party data providers to build predictive models that offer more accurate and reliable insights.
To see how our solutions can help you navigate this cookie-less landscape, book a demo of Definitive Healthcare today. And, if you missed our recent webinar, you can watch the replay to learn more about the strategies that will keep you ahead in this evolving environment.
