Donald Gainsborough, a seasoned political savant and the leader of Government Curated, stands at the intersection of legislative policy and the digital frontier. With a career dedicated to streamlining how residents interact with state services, he brings a unique perspective on the delicate balance between high-level data governance and the granular technicalities of web tracking. As Connecticut moves toward a more integrated public health model, Gainsborough’s expertise in navigating the complexities of privacy regulations like the CCPA while ensuring robust site performance is more critical than ever. In this conversation, we explore how data-sharing frameworks can bridge disparities, the technical realities of cross-device tracking, and the future of personalized public health delivery.
How does cross-sector data-sharing specifically address Connecticut’s public health disparities? Please walk through the process of integrating data from diverse sources and explain how this collaboration improves health outcomes compared to siloed efforts.
When we look at the landscape of public health in Connecticut, the biggest enemy is often the isolation of information. By integrating first-party cookies—those small text files we set directly to remember a user’s language preferences or login details—with broader datasets, we create a more cohesive journey for the resident. In the past, a person might have to re-identify their needs every time they moved between different agency platforms, which creates a frustrating barrier for those already facing health disparities. By using these data points to maintain a consistent state of “being known” by the system, we can ensure that a resident’s specific needs, like language accessibility, are met the moment they arrive. This collaborative approach allows us to see the “full picture” of site performance across different sectors, rather than just looking at one isolated portal, which ultimately helps us direct resources to the communities that need them most.
How do you distinguish between strictly necessary data for site performance and data used for marketing? What specific protocols ensure that “sale of data” protections are maintained while still allowing agencies to monitor site traffic and improve public health outreach?
The distinction between strictly necessary data and marketing data is the foundation of our trust with the public. We define strictly necessary cookies as those essential for the basic functioning of the website, such as prompting the initial privacy banner or remembering your specific privacy choices so we don’t ask you twice. These protocols are designed to be CCPA-compliant, meaning they do not constitute a “sale” of personal information; they are functional tools, not commodities. For marketing and advertising efforts, we use third-party cookies from domains other than our own, but we provide a clear, accessible toggle switch for residents to opt out of this specific use. It is a rigorous balancing act where we protect the resident’s right to privacy while still collecting the vital traffic metrics needed to understand if our outreach campaigns are actually reaching the intended neighborhoods.
How do functional and performance cookies enhance a resident’s experience on public health platforms? What challenges arise when users opt out of tracking, and how do you ensure vital health information remains accessible despite these privacy choices?
Functional and performance cookies are the silent workhorses that make a digital health platform feel intuitive rather than an obstacle course. They allow the site to remember that a user prefers a specific language or a certain layout, which is deeply important when someone is stressed and looking for urgent health information. The challenge arises when a user decides to block these cookies through their browser settings—perhaps by visiting sites like allaboutcookies.org to learn how to lock down their preferences—which can cause some parts of the site to stop working as intended. To mitigate this, we ensure that while the “personalized” experience might be diminished, the core, vital health information remains accessible to everyone. We want the technology to be an enhancer, but we never let the lack of a cookie prevent a resident from finding the care or data they require.
Tracking users across different devices and browsers presents significant technical hurdles for data-sharing initiatives. What specific metrics or technologies are used to monitor cross-sector engagement, and how do you maintain data accuracy when individual user selections apply only to specific devices?
The technical reality is that our current infrastructure does not track users across different devices, browsers, or various properties. If you opt out of certain tracking on your laptop, that choice stays on that specific device and browser, which means if you pick up your phone, the system treats you as a new visitor. This creates a hurdle for data accuracy because it can lead to “double-counting” traffic or missing the continuity of a resident’s search for health services. To manage this, we rely heavily on the metrics gathered from those who do choose to stay opted-in, using that data as a representative sample to monitor site traffic and performance. It requires a high level of transparency, as we must constantly remind users that their privacy selections are localized to their current hardware to avoid confusion.
What steps are taken to personalize content for health initiatives without infringing on privacy? Could you share a scenario where site performance data or traffic monitoring directly led to a specific improvement in how public health services are delivered to residents?
Personalization is about relevance—ensuring that a resident in an urban center sees information about local clinics rather than services three towns away. We use targeting and social media cookies to determine what content is most relevant to a visitor, but we always place the power back in the resident’s hands via that toggle switch for the “sale” of personal data. A concrete example of improvement occurs when our performance monitoring shows a high “drop-off” rate on a specific mobile browser; we can then see that a vital health form isn’t loading correctly, allowing us to fix the technical glitch in real-time. By watching these traffic patterns, we recently identified a surge in interest for a specific health initiative and were able to move that information to the front page, ensuring that thousands of residents found what they were looking for without having to dig through menus.
What is your forecast for Improving Connecticut’s public health through cross-sector data-sharing?
I believe we are moving toward a future where the “digital front door” of Connecticut’s public health system will be more responsive and intuitive than ever before. As we refine how we use first-party data to bridge the gaps between different agencies, we will see a significant reduction in the “administrative burden” placed on our most vulnerable residents. My forecast is that within the next few years, our ability to monitor site performance and traffic will allow for hyper-localized health alerts that can be delivered with surgical precision, all while maintaining the gold standard of privacy protection. We will prove that you don’t have to sacrifice a resident’s anonymity to provide them with a world-class, personalized public health experience.
