The Connected Data Helping to Reach HCPs and Lift Treatment Barriers

It can take up to five years to diagnose a rare disease, if it occurs at all. Only then do efforts begin to find and understand the people and entities prepared to support the patient. Increasingly complex therapies for smaller patient populations make connecting with essential healthcare professionals (HCPs) harder. The work simply can’t be done the traditional way, especially when trying to reach geographically dispersed or traditionally underserved patients. Integrated data offers a path forward and hope for the HCPs and the patients they treat.

“The goal is to give physicians the information they need to make a difference in treating patients to improve outcomes,” says the director and lead data scientist at a global biopharma. “We can use data to get a sense of what content engages healthcare professionals (HCPs) and, based on that, what the next best action would be.”

According to Veeva Pulse data, 30% of the most sought-after specialties — oncology, neurology, and internal medicine — meet with only one biopharma. As a result, field teams need support in the form of connected data and tools to reach HCPs in their moment of need. The correct foundational data that pulls from historically siloed sources is essential to their engagement strategy.

Integrating customer, patient, and key opinion leader (KOL) data allows sales, marketing, and medical teams to work together to address challenges traditionally tackled in isolation. For example, reps craft a better message when they access information about common patient treatment barriers for a disease and know a target HCP’s communication preferences.

You can bring greater efficiency and precision to clinical and commercial operations by connecting reference, deep, and transaction data. Each of these data sets gives you a unique way to prioritize outreach:

1. Using HCP/healthcare organization (HCO) affiliation and reference data promotes the ability to support field teams with precise data, which is especially important in new regions and for small patient populations.
2. Analyzing KOL and account information — including deep data (e.g., clinical participation, scientific expertise, and social media behavior) — before a product launch correlates to a measurable increase in treatment adoption.
3. Accessing longitudinal patient data, including social determinants of health (SDOH) and projected prescriptions and procedures data, shows where potential new patients are and promotes patient centricity.
4. Applying aggregated and anonymized field trends data helps teams respond to HCPs with on-demand education and resources as communication preferences change.

Business objectives that require integrated data

Think of data integration as a vehicle to deliver better data. It connects the information necessary for all stakeholders in a commercial initiative and offers a superior customer experience. For example, a rep conducting research can look at one source to find stakeholders across their area. Or, teams can accelerate early market access work in countries before launch.

A test for success in better-managing data is to ask whether clinical and commercial teams can use your current technology and processes to:

• Understand how patients move within and between healthcare systems for your therapy(ies).
• Develop a unified list of critical physicians based on treatment potential, referral patterns, diagnosis, and KOL status.
• Prioritize the field force’s time with priority HCPs to impact more patients.
• Capitalize on digital and AI initiatives to find and communicate with medical leaders.

Biopharma use cases show that AI and digital initiatives, in particular, require accurate and connected data to function correctly.

Companies with integrated analytics in action

Patient-level data, medical claims, specialty pharmacy, and consumer data can combine to broaden access to the right HCPs and KOLs and speed up patient treatment.

Following are examples of companies that have successfully harmonized reference, deep, and transaction data to achieve their patient activation and retention goals.

Matching patient longitudinal data with HCP insights

When launching its first rare disease therapeutic, ANI Pharmaceuticals sought to fully understand the patient journey, potential prescribers, treatment patterns, and the overall market landscape. ANI pulled through information locating eligible patients and their HCPs, getting the resulting insights:

• The company’s prescriber base
• Patient location
• HCP location
• The complete patient journey and experience

“We’ve been able to leverage insights from Veeva Compass Patient Data immediately after getting access to it,” says Bob Acropolis, senior director of operations and analytics at ANI, citing its speed and accessibility as key to understanding different patient populations.

Combining field trends and patient data

Across the industry, manufacturers are adapting their tactics, promotions, and channel deployments to meet individual customers’ personal needs. The director and lead data scientist at a global biopharma says that the ability to connect data in the cloud is exciting because it enables access to an unconstrained universe of information without defining a market first.

He adds, “Seeing that entire data universe opens up business questions that aren’t possible in the traditional data model. The ability to pull across the experience of all the manufacturers in the industry, using Pulse Field Trends data, ‘supercharges’ the team’s ability to solve a problem and effectively deliver information to our customers.”

Advanced analytics depend on connected data

Companies that can define the marketplace for their products, identify impacted patients and associate HCPs, and move faster than the competition will succeed. Clean, connected data with a common architecture across customers, patients, KOLs, and business operations will be necessary to get there.

Learn how a top pharma leveraged connected data to develop a unified HCP target list for launch.