Life Sciences

People are at the Heart of Patient-Level Clinical Data

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Pharmaceutical companies recognize the value of patient-level clinical data, and thanks to a combination of evolving technology and emerging legislation, there’s more data available than ever: Over 86 percent of physicians now use some form of electronic medical record (EMR) or electronic health record (EHR) system, according to the CDC. But the sheer influx of new clinical data also presents unique challenges — like data fragmentation. A recent study found nearly 60 percent of respondents in the health field said fragmented data was their top roadblock to accurately assessing total cost of care.

For pharmaceutical organizations looking to compete in a crowded, competitive marketplace, the problem has another dimension: weak trust in the “big pharma” and health care fields. Just 9 percent of consumers believe pharma and biotech companies put patients over profits, according to a recent Harris Poll. Data holds the key to reversing this perception — but how do you turn that information into actionable insights that help you create compelling experiences if it’s fragmented across too many sources and not easily accessible?

Have Patients, Need People

In a digital-first marketplace where consumers expect real-time responses to concerns and improved product transparency, patient centrality isn’t enough — pharmaceutical manufacturers must adopt a people-centric practice to disrupt the current landscape.

What does that look like? It means a shift from product to service, from delivering treatments to helping consumers better manage their current concerns and prevent potential health issues. Rather than focusing on selling, enterprises need to create a dialogue. That means taking advantage of artificial intelligence to analyze data from a variety of sources, from EHRs to Twitter, to better understand the emotional and physical journeys and trending topics around conditions like breast cancer or diabetes.

These data sources can shed light on some key questions. What influences patients switching from brand prescriptions to generic versions? What factors drive those decisions? What symptoms are patients with a particular diagnosis most concerned with? Those kinds of insights can spark new avenues for research and development, as well as allow companies to use their marketing channels to directly respond to issues that are on consumers’ minds.

The goal here isn’t to sell treatments, but to create a sense of shared community — one that is aligned to the challenges people experience and extends beyond initial contacts to family, friends and even other patients.

Master the Mosaic

The concept sounds simple: Use clinical data to drive people-centric sales and marketing to drive patient loyalty and community. But the sheer amount of patient data available from multiple sources — social media sites, contact forms, partner programs and traditional marketing efforts — can quickly lead to paralysis. Handling this so-called “data mosaic” means adopting three key strategies.

  1. Cultivate Data: All data is valuable. While there’s a growing trend toward weeding out certain data sets to arrive at specific outcomes, pharmaceutical companies are better served by cultivating this data — cleaning and interrogating it for value to develop people-centric initiatives.
  2. Embrace Unstructured Data: The vast majority of patient data is unstructured, but most existing big data tools aren’t designed to amalgamate and process this type of information. This is where cognitive-based systems come in: They can combine public and private patient data to provide an anonymous cross-section of relevant insight, at a scale that just isn’t possible without AI.
  3. Connect Insights and AI When Data Can’t Be Combined: In many cases, data cannot be combined due to HIPAA privacy issues. In order to fully develop the data mosaic, pharma companies must connect analytics and AI at the “insights layer” rather than the data layer. When we can test shared AI techniques across many data sets, true north will reveal itself, and digital and physical commercial experiments can be tested for success in the marketplace.

How can pharmaceutical companies tap into patient clinical data to create a people-centric experience?

An Evolving Prescription

Clinical data has front-end value for the shift to service-based marketing and midstream potential for developing a sense of community among individuals seeking to manage their way through the progression of their disease. But there’s also a case for post-market R&D informed by patient experience and physician reporting. Cognitive-based systems can help pharmaceutical companies repurpose existing treatments for new applications by synthesizing chemical and genetic data with clinical data sets. AI systems such as Watson for Drug Discovery are active in helping pharma companies target new indications in support of brand expansion and drug repurposing. The result? Faster time-to-market and a more agile response to changing market needs.

Companies can’t afford to ignore the commercial insight of big data in treatment marketing and ongoing product development. The keys to harnessing this data-first future? Embrace the shift to people-centric services. Use AI to cultivate unstructured and anonymous data, leverage this information to empower adverse event reporting, and engage actual consumer needs with improved R&D.

Partner, IBM Services, Healthcare & Life Sciences Industry, Cognitive & Commercial Analytics Leader

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