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How data analytics and digital strategies accelerate health equity

Enabling more inclusive health care experiences that improve outcomes and build value

In brief
  • Health organizations must deploy robust data analytics and digital strategies to close health equity gaps, meet consumer expectations and build value.
  • Gaining deeper visibility into patient behaviors, the social drivers of health and other key areas is preferable over taking a one-size-fits-all approach.
  • For life sciences companies, a consumer-centric approach to patient engagement drives commercial excellence.

As the rise of value-based care continues, organizations across the health ecosystem are increasingly focused on understanding the socioeconomic and other factors that impact health equity, especially among underserved groups. But to enable the equitable patient outcomes, access and experience they envision, health companies must first reimagine their operating models and processes to enable better collection and management of patient data. This approach can equip both life sciences and health care organizations with actionable insights into chronic disease progression, barriers to care and a host of other areas related to health equity. Investing in and deploying digital technologies and data analytics capabilities is one of the most effective ways for health companies to gain better visibility into patient population health, but most organizations have significant ground to cover before reaching maturity around health equity data analytics. This gap represents a missed opportunity to enhance both the organization and health outcomes among all its patient populations.

Deeper health equity insights


Leveraging digital technologies and data analytics can provide health organizations with deep insights into both patient population health and the underlying social drivers of health. With this understanding, these companies can develop personalized information and actionable insights to advance more equitable engagement and health care experiences. For example, companies can create composite risk scores around potential patient outcomes, individualized care plans and customer-centric experience strategies that enable frictionless interactions with patients.


By way of further example, having a robust data analytics framework in place can also help health companies identify and sharpen their health equity focus on specific conditions. To that end, we recently teamed with a health data startup to gain deeper insights into chronic kidney disease (CKD), which disproportionately impacts Black Americans. Powered by advanced data analytics tools, our analysis of claims data gathered from 2015 to 2022 on approximately 700,000 patients helped illustrate the drivers and barriers to care around CKD.¹


This analysis revealed that Black CKD patients were more likely to be diagnosed in the later stages of the disease than their White peers, often due to barriers to access that result in delayed engagement with the health care system. Black CKD patients were also more likely to visit an emergency department in the later stages of the disease, resulting in unnecessarily high costs of care and, ultimately, a higher economic burden on the health care system and the US economy. Importantly, we also observed that about 44% of excess risk for CKD among Black Americans is caused by modifiable risk factors around lifestyle, clinical conditions and structural drivers.


As the CKD example demonstrates, organizations have an untapped opportunity to leverage digital and data capabilities to identify and address health inequities. The actionable insights gleaned from these tools can help health care companies tackle similar barriers specific to underserved patient populations and preventable chronic conditions. For life sciences companies, this data can enable more inclusive health care experiences and drive commercial excellence.

A strategic approach to health equity data analytics

For life sciences leaders who seek to utilize data and digital tools to enhance patient engagement and improve both patient experience and outcomes, there are three key actions to get started.

1. Develop a data analytics strategy designed for inclusive health care experiences.

Investing in advanced analytics, and leveraging diverse data sets and AI models, along with automation and other digital capabilities, is an essential part of determining what life sciences patients from underserved communities want and need, creating a more complete view of patients. In addition, insights gleaned from sales representatives’ interactions with health care providers offer deeper visibility into diverse patient behaviors and how companies can best leverage tech to orchestrate the delivery of care-related content based on priority, preference and other metrics. On the whole, this approach drives agility as underserved patients evolve and is essential to create the personalized experiences they now crave and expect.

2. Build sophisticated patient segmentation.

AI-powered, data-driven algorithms can be used to create, optimize and personalize targeting of specific segments of the patient population. For example, scarce patient data containing certain characteristics of interest, such as race or ethnicity, can be “trained” and used to identify other patients of the same race or ethnicity from a larger cohort using AI. In today’s consumer-driven environment, companies must understand and adapt to different patient personas, instead of employing a one-size-fits-all approach. This mindset can help them establish a complete view of specific patient needs, facilitating consumer base expansion and providing a customized, patient-centric offering.

3. Create an omnichannel patient-centric approach that addresses the socioeconomic profiles and population health profiles

Today’s consumers are owning their health care decisions and seeking information across various channels and sources. They also expect simplicity from their health care experiences, which is why reducing complexity and eliminating paper-based and manual processes are essential. Convenience is also paramount — consumer preferences around how and when to be contacted, and in what context, are critical to patient engagement. By leveraging consumer-centric omnichannel transformation strategies, companies can identify provider and patient preferences and needs, and then offer them anticipatory and relevant customer experiences through various channels and content.

Defining success metrics and leveraging automation to help benchmark execution effectiveness against those metrics, company leaders can also gain visibility across campaigns, channels, brands and portfolios into the success of provider and patient journeys and make data-driven adjustments where needed. This approach to continuous improvement against a change agenda is often referred to as a feedback loop. It also helps unite the entire organization around one enterprise goal: enhancing patient engagement. Ultimately, creating an omnichannel patient-centric approach accelerates internal omnichannel capabilities, providing inclusive, dynamic patient experiences that deliver the right content through the right channels.

This article includes contributions from Edwin Reyes, Senior, Business Consulting, Ernst & Young LLP.


Health leaders have an opportunity to utilize digital and data to drive more inclusive health care experiences across the continuum of care through strategic actions that address patients’ needs. Incorporating health equity insights into marketing, medical and market access strategies and execution, as well as early asset planning and commercialization process and strategies, can go a long way toward improving patient outcomes. Further, advancing health equity in the context of commercialization can provide significant value for the pharmaceutical industry through increased market share and improvements in top-line revenue, driving long-term enterprise value and customer excellence.

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