Health Care Systems Need to Better Understand Patients as Consumers

The data is clear: Patients in the United States aren’t loyal customers. They split their care across an average of four to five different provider networks each year. Given the increasing number of options for where and how consumers can seek care — from new virtual and primary care providers to retail entrants and urgent care centers — who can blame them?

To remain competitive, health systems and traditional provider organizations must seek to better understand patients as health care consumers: how they make decisions, what motivates them, and how, where, and why they are engaging with the broader health care system. They must also understand how the forces of demand and supply shape the markets in which they operate.

And compete they must. While 44% of Americans have an active Amazon Prime membership — giving Amazon even more consumer data to use in its ongoing health care expansion and targeting strategies — the nation’s largest health system, HCA Healthcare, only engages with 1% of Americans through its care delivery system.

Hospitals and health systems must take a page from Amazon and other big tech companies’ consumer strategy handbooks. The entire $4.3 trillion health economy will benefit the more that health systems can understand, design for, and meet consumer preferences and needs, and this process must start by leveraging the right data and establishing the right metrics.

Two Challenges

One challenge health systems face when trying to incorporate consumer-focused metrics into strategic planning is the very limited nature of information being tracked in this category. Another is that health systems often use the few traditional consumer/patient satisfaction measures that do exist such as Net Promoter Score (NPS) and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores, to project what patients may do in the future (e.g., the likelihood a patient will return to the same system for care).

But a patient’s self-reported perception of how satisfied they were with their hospital experience doesn’t dictate whether that patient will return. In reality, hospital NPS and HCAHPS scores are not reliable indicators of what patients will do in the future. For example, someone may plan to work out five times a week but only make it to the gym once; that person’s consumer profile would be very different from someone who actually did work out five times that week.

Health system leaders shouldn’t rely on patient satisfaction measures to project and account for future patient behaviors. Instead, they need to look at what patients actually do and incorporate that information into strategic planning accordingly.

To put their organizations in the strongest position to compete for a shrinking number of patients, health systems must have clearly defined measures and metrics to better meet consumer needs — at the individual, organizational, and market levels. Two of the most important categories of metrics that health systems should be tracking for this purpose are the following:

1. Consumer Preferences and Proclivities

Leading retailers such as Amazon and Walmart have been using data to better understand different customer segments for years and employ those insights to decide on the way in which consumers are served. Amazon’s recommendation engine, for example, engages with shoppers by sending tailored messages about products they bought previously and new ones that may interest them.

Americans also see this kind of personalization every election cycle, where political campaigns engage with likely voters by sending messages about specific issues that resonate with those voters, as opposed to messaging about every issue in a party platform. And consumer packaged goods companies such as Procter & Gamble have long relied on psychographic data (i.e., looking at what motivates different consumer segments to make certain decisions) to better understand consumers and inform their business strategies.

Health systems, and the health economy at large, are woefully behind in adopting such data-driven practices, but they must embrace them to compete for patients in the long run. For example, is a patient not returning to a health system because there aren’t appointments available early enough or because the patient prefers another provider organization? While some questions will be harder to answer than others, by building a more comprehensive technology infrastructure, health system leaders can devote data-engineering resources to connect patient-health-care-utilization patterns to behavioral profiles at scale.

Are there more no-shows or cancellations during certain hours, or does integrating consumer behavior data uncover new insights about how certain patient demographics behave at different times of day? Can psychographic profiles better explain what’s already happening within an organization’s four walls or point to why a health system may be losing market share for a specific specialty? These are the kinds of real-time takeaways that become clearer by jointly leveraging health care and patient behavior data and other like resources that already exist across the health care ecosystem. By understanding what motivates consumer behaviors and drives their decisions, health systems can take more targeted steps to reach, engage, and serve health care consumers with their preferences and needs in mind.

2. Share of Care

Consumer-facing organizations in industries other than health care do everything possible to understand the economic factors affecting their businesses, including knowing their total addressable market, market share for certain products or services, market value, and how to acquire market share from the competition. Health systems should be doing the same.

Health systems need to look beyond revenue targets and seek to understand their “share of care” in the markets they serve. For example, of the patients that a given health system treats, what percent of all of those patients’ care interactions were not with that health system?

To better grasp this kind of information, health system leaders can look to both internal data (e.g., internal patient journey data across care settings and individual electronic medical records) and external data (e.g., local U.S. Census data, benchmarks, and leakage indications from each of their health plans). Claims clearinghouses can be particularly rich sources of raw data across payers and provider types, and while they lack context without layering on consumer data, applying machine-learning algorithms on top of aggregated claims data can help a health system determine its share of care and network integrity.

Understanding the total addressable market and applying patient behavior metrics are also essential for health systems to make strategic investment decisions. Many health systems have invested in specific access points, such as telehealth and urgent care, with the notion that these will be a “front door” to care — getting patients into a health system’s network and keeping them there for future procedures and care needs. Data on the longitudinal patient journey, however, show this is not always true, and knowing this could have a tremendous impact on the service line and investment decisions health systems are making.

Unfortunately, data fragmentation and lagging interoperability initiatives also mean health systems don’t have easy access to this kind of information. Electronic medical records data can be informative but tend to be blind to patient interactions outside of a health system’s organizational walls. However, when health care consumers have more care options than ever before (e.g., new entrants like CVS and Amazon), knowledge (through longitudinal data) is truly the greatest power that health systems have at their disposal.

Health care delivery will only become more competitive, and to position themselves for growth, health systems must not only be data-driven but be aligned to measures specific to the health care consumer. Only with consumer-focused information can health systems be prepared to compete for patient share of care in a health economy where supply exceeds current demand for services.


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