Internal and external constraints, including a global pandemic, have stalled the more ambitious long-term and strategic growth objectives of healthcare organizations. In the near term, healthcare providers are re-imagining their positioning with consumers, which includes improvements in operations, patient experience and marketing. Many health systems are now poised for growth. Consumer analytics is a considerable part of catalyzing these transformations, with the potential to positively impact healthcare delivery. 

Using Data to Become Consumer-Centric

The post-pandemic landscape requires greater use of robust and predictive consumer data that can and should be leveraged for a wide range of functions from strategic planning and marketing to daily operations and care delivery. As the pandemic response winds down, leaders are in a position to transition from tactical response to planned initiatives, which should be supported by a better-informed consumer strategy.

The potential of consumer data includes the ability to provide more comprehensive care that engages consumers, improves patient experience and outcomes and helps patients stay in network. Predictive models enable health systems to better identify consumers according to a full range of healthcare needs, offering up services when, where and how consumers need them.

Driving Toward Consumer Value 

Today, it is well recognized that data should be at the forefront of decision-making. However, defining what data should be used and for which use cases is particularly important. Typically, consumer analytics are used to both better understand your existing patient base and the broader needs across your market. 

Consumer data is comprised of the following categories:

• • Internal encounter and clinical data (such as from your electronic health record or EHR)

• • External claims and clinical data  

• • Consumer demographics and descriptive data

• • Social Determinants of Health (SDoH)

Concerning the above categories, it is important to be compliant with all patient health information (PHI) and personal identifiable information (PII) laws and regulations, such as HIPAA. Proper due diligence can help you ensure you are building consumer analytics that are effective, secure and trustworthy.

When done right, predictive consumer analytics has the potential to influence everything from company strategy to how providers interact with customers to improve the health and well-being of patients and whole communities.

Leveraging Different Sources for Predictive Consumer Insights

Developing statistical models to comprehend shifts in healthcare has historically been an inefficient and untimely annual or long-term planning exercise. The pandemic demonstrated that we need better models with more timely results across the market. 

Identifying both internal and external sources of consumer data is an important step that is overlooked by many healthcare organizations. As the healthcare industry embraces consumer-centricity, health systems must be ready to use a broader range of externally-sourced data to assess community needs, respond to social risk and other factors that influence health, and better understand the whole person to provide more effective care.

Additionally, patient and consumer data is often compartmentalized for specific purposes, rather than put together in a holistic manner. For instance, when considering outreach tactics, population health teams might use one source of data while marketing obtains their data from a different asset. Creating an enterprise-wide source of truth for consumer data is the optimal path to predictive consumer insights. 

Scaling Your Data Operations  

As organizations advance in a world driven by data, the significance of data management should not be overlooked. From strategy to clinical teams, decision makers must have access to the right data at the right time.

However, this is not an easy task as the digital ecosystem becomes increasingly complex. The first step is investing in the proper technologies for enterprise data management, which often includes moving to a cloud-based data model that is more scalable and efficient. Healthcare organizations also need to find the right analytics vendors and partners that will work to feed the organization’s data ecosystem, not force the organization to work outside their environment.

Another core component is data governance. In order to build a true consumer master and understand their consumers from a 360-degree perspective, healthcare organizations are required to blend multiple sources of data together in cohesive models. For instance, many organizations are now designing SDoH initiatives that address the influence of social and economic demands on a population. Undertaking this endeavor requires the ability to mesh clinical data, such as the number of persons affected by an illness; SDoH elements such as transportation indicators; and key demographic features, such as number of children in the household. The end result is significant—consumer needs are met dynamically through a transforming care delivery network that anticipates need. 

Targeted implementations of consumer data and analytics will shape the future of healthcare. Leading health systems swiftly integrate data insights at both the strategic and operational levels to provide more equitable, whole-person care that maximizes consumer value, while also fulfilling strategic growth goals.