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Blog
Supercharge Brand Growth With AI Driven HCP Alerts
How artificial intelligence can help improve physician outreach and patient care.
Cindy Weber, Principal Real World Analytics and Artificial Intelligence (RWA&AI) IQVIA
Mar 21, 2022
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  • Supercharge Brand Growth With AI Driven HCP Alerts

Imagine knowing exactly when a physician or healthcare professional (HCP) is likely to see a patient who could benefit from your treatment? This kind of prescient knowledge was impossible in the past. But when life sciences companies leverage data, analytics, and the power of artificial intelligence and machine learning (AI/ML), they can capture proactive insights about the patient journey and shape their outreach accordingly.

In the current life sciences landscape, this level of detail and timing can be key to having a successful brand.

Targeted therapies and precise patient populations are increasingly the norm

Today’s market growth is increasingly driven by high-value targeted therapies that are only used by small patient populations; and overall, treatment regimens have become increasingly complex and diverse. For example, an HCP may only treat a handful of patients with a specific rare disease in their career; or an HCP may treat one patient with a biologic but not another patient, even though both patients present with similar disease symptoms. So, outreach needs to find the right patient; find the right HCP of that patient; and find the patient and HCP at the right time to be effective – before a treatment decision is made.

That level of precision isn’t easy, particularly for diseases and treatments where the data makes it difficult to precisely and comprehensively identify the patients of interest. For example, ICD-10 codes may not be specific enough or utilized consistently by the HCPs; and it may take patients months or years to be correctly diagnosed as having a condition.

AI can help find patients

However, it is possible to cut through this complexity and find the right patients by utilizing AI-powered analytical models. The most successful life sciences organizations use predictive models to identify patients who will benefit from their treatments; and identify the HCPs those patients are seeing.

This predictive approach is consistently more precise and comprehensive than common data-driven rules-based approaches, which tend to be overly noisy and reactive. The resulting AI-driven Alerts are applied to identify the predicted patients and their HCPs on an ongoing basis (for example, identifying the HCPs each week or each month who are likely be seeing a patient of interest during a defined timeframe). By using ongoing Alerts, the AI model is effectively turned into outreach actions.

How does it work

As a simplified explanation -- using real world data and clinical expertise, the patient population to be identified is carefully defined. The AI and machine learning algorithms then use the rich medical history of those patients to “train” the model to find other patients who “look like” those patients of interest, but who have not yet been diagnosed or treated. The result is a “scored” set of predicted patients and the HCPs associated to those patients.

However, it’s important to measure the results of the AI model qualitatively and quantitatively, ensure the data being used is appropriate and wisely applied, and use the insights derived to inform outreach planning and messaging. An AI model is powerful and precise when done well, but the results can be despairingly fuzzy when done poorly – so, it’s important to develop AI modeling expertise over time, and lean on the expertise of others while learning.

The right data drives results

With the right datasets, technology, and clinical expertise, these AI solutions can find even the most difficult to locate patients.

For example, IQVIA recently worked with a pharma manufacturer that had a treatment for an ultra-rare genetic disease that was very difficult to diagnose. Using rules-based models, this company had been unable to find any patients with this condition in the prior year. But when they deployed the AI model, the team was able to successfully identify 10 new patients in three months.

The insights helped sales reps and medical science liaisons proactively engage with physicians who were seeing these patients, helping the physicians to appropriately diagnose and treat the patients.

By using AI-driven Alerts, sales and marketing teams can engage HCPs at the right time with educational material and treatment information relevant to the patient and where that patient is in their medical journey. Alerts can be scheduled to go out on a regular basis or produced on an as-needed basis if the sales and marketing teams have an immediate outreach tactic or message planned. Teams can also monitor whether the AI-driven Alerts achieve the results expected.

Early adopters can get ahead

These AI-driven Alerts can transform sales and marketing team effectiveness, and powerfully improve HCP outreach and patient care.

However, according to the survey conducted at a recent IQVIA webinar, 62% of the professionals responding reported that they aren’t using any type of alerts to inform their sales and marketing (neither using AI-driven nor data-driven rules-based approaches); and only 18% said they are using AI-driven Alerts at all.

So, early adopters of AI models have an opportunity to gain a significant competitive advantage – identify the right patient, the right HCP, at the right time. It’s a powerful value proposition that can positively impact a patient, while delivering better business results.

To learn more about how AI driven alerts can transform your sales cycle, check out our recent webinar, Supercharge Your Brand Growth: Leverage AI to drive precise and timely HCP Alerts, or click the Contact Us button in the right hand corner to speak to an expert.

 

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Fact Sheet
IQVIA HCP Alerts

Supercharge your brand growth by leveraging AI to drive precise and timely HCP alerts
Webinar
Supercharge Your Brand Growth

Leverage AI to drive precise and timely HCP Alerts

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