How EHRs can enable provider-pharma collaboration

Data in health records offer the opportunity for a partnership that can help direct the pipeline of drugs being developed.


Provider organizations currently have little influence over the strategy of pharmaceutical companies or how these and other life sciences companies develop treatments for their patients. At the same time, pharmaceutical companies have limited access to the wealth of data and clinical information that provider organizations are accumulating in their EHRs.

It may seem daunting or even counterintuitive to envision a formal collaboration between provider and pharma when it comes to either’s clinical strategy. But that was in the old age of healthcare.

Meeting today’s healthcare demands requires all hands on deck to improve care coordination, diagnosis, treatment and therapy adherence. And one tool can help providers and pharmaceutical companies establish the type of partnership to do just that—the EHR.

Providers currently use the EHR to collect large amounts of de-identified patient data to aggregate risk. That data could finally give providers the opportunity to partner with pharmaceutical companies to help them determine their pipeline of drugs for development.

One way is for provider-pharma partners to use EHR data to quickly identify and recruit eligible patients for clinical research trials, which would enable providers to have a more direct impact on drug development and innovation. Additionally, real-time data can generate a larger pool of eligible populations more quickly, helping to fast track a new therapy through the clinical testing stage, saving time, money, and effort for both providers and pharma companies.

On the flip side, rapidly accumulating clinical data in EHRs can be used to help identify new drug development targets — or potential complications and benefits that were not observed in preclinical trials. One of the earliest successful examples of this approach was a 2008 study. The study used aggregated clinical data from 40 hospitals, all of which had the same EHR vendor, to identify persistent hyperglycemia as a better predictor of acute myocardial infarction (AMI) mortality than was admission glucose.

While most of these efforts to date have focused on big-data aggregators—ASCPT has a great overview of the topic—many health systems now possess enough data to start contributing directly to the drug development process.

Some of our most innovative clients are already leading the way on this idea. We were recently contacted by a large pharmaceutical company to optimize its oncology clinical trials by digitizing outreach. Rather than receiving a paper form, eligible patients would instead receive a questionnaire through the patient portal. Results would be aggregated and sent to a care coordinator.

Many health systems still struggle to hardwire evidence-based guidance into their clinical systems. And myriad factors contribute to the challenge, including limited bandwidth of the technical EHR team, difficulties with provider engagement and leadership, and lack of internal infrastructure and coordination. But we have seen organizations make significant progress through partnerships with life science companies.

For example, when a new type of blood thinner that is used to reduce the risk of stroke and blood clots was recently launched, evidence of the potential benefits of that new class of anticoagulants started to mount. Despite proven outcomes, and often fewer bleeding complications, some markets were slow to begin prescribing it. So the pharma company partnered with a large provider organization to create an EHR-enabled, optimized care model for patients with a high risk of stroke.

This optimized care model uses the EHR to identify high-risk patients, and it centers on new decision-support tools and clinical content that was built into the EHR and provider workflows. Additionally, care teams can use the patient portal to reach out to at-risk patients about their treatment options. Now, providers across the organization receive evidence-based guidance for reducing the risk of stroke, both proactively and at the point of care.

This model might sound familiar for provider organizations that are already applying EHR-enabled clinical decision support. However, many provider organizations focus solely on their own domain and miss the opportunity to engage pharma in their process. Pharma companies bring to the table a wealth of knowledge on target patient populations along with medication adherence strategies that can prevent readmissions and improve quality of care. Leaders of provider organizations can use this information to make decisions that will appropriately support clinicians across the system.

While pharma has been more isolated from the growing pains associated with the rapidly changing landscape of health information technology, providers have spent years selecting and implementing EHRs and building the infrastructure to support them. Many are finally in stages where they can move from thinking about go-lives or user adoption, and can begin to explore how to allocate their resources to continue to improve their EHRs in ways that drive clinical and financial improvement.

Providers have sunk millions into their EHRs, and the imperative to make good on the investment has never been stronger. As the EHR continues to evolve and change the way care is delivered to patient populations, provider organizations and pharmaceutical companies alike need to increase collaboration efforts in targeted ways to see the most benefit.

A partnership between the two to optimize their EHRs is a proactive and practical way to achieve shared goals—providing the best possible care to patients and engaging clinicians in that work.

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