Better together: Why primary care wins when physicians, payers and pharma share data

If you’re a primary care physician in the United States, you likely spend too much time navigating administrative complexity and too little time delivering care. Between prior authorizations, fragmented records and incomplete medication histories, your clinical decisions are often made without the whole picture. But what if that picture could be filled in, not just by hospitals or electronic health records (EHRs), but by the very stakeholders that sit on the other side of the care equation: insurers and life sciences organizations?

This is not about burdening you with more systems. It’s about more innovative collaboration, powered by real-time, governed data sharing between physicians and other clinicians (like you), payers (insurers) and life sciences companies (pharmaceutical and medical technology). When done right, this health care trifecta can be a game changer for primary care.

A missed opportunity hiding in plain sight

But instead of working in sync, each member of the trifecta often operates in a silo, guarding data as proprietary or too sensitive to share.

This lack of collaboration creates inefficiencies that fall squarely on your shoulders. Consider the following:

• Prior authorizations that are delayed due to a lack of claims or diagnosis history
• Incomplete medication records when patients use outside pharmacies
• Duplicated diagnostics because lab or imaging results are not shared across networks
• Unclear risk factors because social determinants or genomic data are inaccessible

Meanwhile, each stakeholder holds one part of the answer. Payers know which treatments are being reimbursed and where outcomes vary. Pharmaceutical companies monitor real-world effectiveness and adverse events. However, you, the clinician, sit at the intersection of it all, tasked with pulling these threads together.

Rewriting the playbook with shared, governed data

What if we treated this data landscape not as a collection of siloed systems but as a shared resource, governed properly, accessed securely and used responsibly?

That’s exactly what technologies like logical data management do, combined with what health care platforms like Epic aim to achieve. Rather than physically moving or duplicating data, logical data management capabilities deliver secure, policy-controlled views of information in real time, from claims databases to EHRs to pharmaceutical trials and beyond.

This means the following:

• You get access to relevant payer data (e.g., approved treatments, formulary alignment, care gaps).
• You can view relevant life sciences insights (e.g., trial outcomes, drug effectiveness, adverse events).
• You have access to these all while staying compliant with privacy laws and minimizing IT overhead.

It’s not just about integration: It’s about creating artificial intelligence (AI)-ready, clinician-usable data products that surface insights at the point of care.

Real-world examples in primary care

Imagine primary care physicians accessing a shared medication adherence dashboard updated in real time by both the dispensing pharmacy and the prescribing specialist.

Or internists using a referral optimization tool that considers payer approvals, clinical urgency and provider availability, all in one interface.

Or pediatricians and OB-GYNs with proactive alerts about at-risk patients based on social determinants of health factors and care gaps, before symptoms escalate.

These are examples of smart data products, but they only work powered by clean, governed, real-time data flowing between provider systems, payer claims and pharmaceutical registries. Semantic query engines, which interpret context across fragmented records, can help data to flow meaningfully, enabling more confident and accurate decisions at the point of care.

Consider a few more examples:

• A medication adherence dashboard populated with pharmacy refill data (payers), prescribing trends (life sciences) and patient encounters (EHRs)
• A referral optimization tool that shows which specialists deliver the best outcomes for covered patients, saving time and increasing the number of patients treated
• A risk scoring model that combines social determinants, claims and genetic markers to flag at-risk patients before complications arise

These are not hypotheticals — they are already being piloted in health systems using secure logical data management platforms.

Breaking the logjam on data sharing

“But pharmaceutical data are proprietary,” you might say. Or “insurance data aren’t clinical.” Those are valid concerns. But they’re also solvable.

With the right architecture, the following can occur:

• Pharmaceutical insights can be shared as deidentified aggregates.
• Payer data can be accessed via secure APIs with role-based permissions.
• All parties retain control over what’s shared, with auditability and compliance baked in.

Don’t think of this as giving away data but as getting the tools to see the whole patient story.

What the United States can learn from the world

Interestingly, other nations have shown glimpses of what’s possible. In the U.K., for instance, the National Health Service is piloting federated data platforms to bring together disparate records. In Singapore, multistakeholder data exchanges support real-time pandemic tracking. And in Denmark, patient-centric data sharing is enabling preventive care programs.

In the United States, we have the stakeholders. We have the data. Now, we need the will, and the right platforms, to bridge the gaps.

The call to action: Let’s not waste the trifecta

You, as a primary care physician, shouldn’t bear the weight of a fractured system. The promise of AI, personalized medicine and value-based care can only be realized if the correct data flow to the right hands at the right time.

That starts with collaboration and a new approach to data.

Instead of building more data warehouses or waiting for that one system that will “own it all,” we need logical data management: a way to access and unify data from different sources — EHRs, payer systems, clinical trials, even social determinants, without having to move or duplicate it. This means clinicians get governed, real-time access to the data they need, when they need it, with privacy and control built in from the start.

Beyond data integration, logical data management is geared toward the seamless creation of AI-ready data products, such as risk dashboards, care coordination trackers or treatment optimization insights, that support you at the point of care rather than adding to your workflow.

The bottom line

The health care trifecta is our greatest strength. Suppose payers, life sciences and care providers can securely align around shared data principles. If so, we can finally address many of the challenges that face U.S. health care today: administrative burden, inconsistent outcomes, high costs and clinician burnout.

With the proper foundation of governed, context-aware, real-time data, primary care can become more proactive, personalized and assertive. And you, the clinician, can spend more time with patients and less time chasing the whole picture.

Let’s stop waiting for the system to fix itself. Let’s put the data to work for everyone.

Errol Rodericks is a vertical product marketing director at Denodo, helping health care and life sciences organizations unlock secure, trusted and real-time insights from data. He collaborates with clinicians, system integrators and platform partners to deliver pragmatic, governed data solutions that support AI, compliance and patient-centered care.