Underutilized first-party patient data could be costing you.

As marketers, there was a time not that long ago when we were the consumers of data, not producers. Our colleagues in IT and Finance provided information to us and it was our job to interpret and advise how that data related to marketing. Things have changed. Data has become larger than we can even fathom. Audience data and marketing analytics now make up a substantial part of the 1,200 petabytes of data stored by Google, Facebook, Amazon and Microsoft. Don’t worry, it’s ok if you needed to Google what a petabyte equates to… We’re going to get there.

By now, most health systems are pretty used to dealing with tremendous amounts of patient information. According to a 2018 study by DVmobile, over 1 Terabyte of data was produced by a cancer patient every day. These numbers are only going up.

Here’s a simpler way to think about this:

1 Terabyte (TB) of data is the equivalent of 140 HD movies that are 2 hours in length. And 1 Gigabyte (GB) of data = 399 Instagram photos or 285 songs or 1 movie.

Clearly, we live in an era where data is everywhere. As marketing leaders, there is no shortage of marketing data to sift through either. However, the power insight isn’t in the raw data itself — the power is in how you decide to use that data. That’s what “Business Intelligence” does.

Business Intelligence, or the study of applying data to actionable information, is a growing force within all industries, including healthcare.

According to a 2019 Health Leaders Media article, less than 50 percent of health systems are using Business Intelligence to tie financial outcomes to clinical outcomes. And less than 10 percent have connected clinical, financial, and patient acquisition to marketing. It is more important than ever to build new relationships within the C-suite to bring together financial intelligence, clinical insights and marketing analytics. Of course, this is no small feat. Finance, data, and marketing departments within health systems do not speak the same language. In our over 40 years of partnering with healthcare industry marketing leaders, that communication barrier has been one of the biggest hurdles we have seen healthcare departments go up against.

Fortunately, there are simple ways you can inch your way towards speaking the same language across departments. Start by turning your acquaintances in the finance department into your friends and partners.

Building New Relationships Between People-and Data-in Your C-Suite

You need to know where your organization makes the most money in order to decide which marketing investment will translate into the most value. Whether we’re talking about healthcare or direct-to-consumer markets — which are becoming increasingly similar — there are certain “products” and services that are chosen more by consumers (for a litany of reasons) and make more money. Even within the model of nonprofits and the healthcare sector, understanding what drives the needed margin to fulfill your mission is critical.

As marketers, you’re responsible for patient acquisition. Understanding the types of services and patient needs that are necessary to drive margin, as well as understanding the patients and services that are dependent on that margin to fulfill your mission, go hand-in-hand. That means you’ll need to be willing to dig into the nitty-gritty financial details around the services being sold by your health system, hospital, or practice in order to have provable ROI for your marketing dollars spent. The only real way to accomplish that mission is by forging new relationships with the CIO and the CFO — and the data they manage — so that you and your teams can be as effective as possible. A great way to think about this data is by categorizing and developing it into a comprehensive four-pronged model. Here’s an example:

Understanding the power of building a patient-centric data model (similar to the customer-centric data model) is no easy task. But we promise you, combining patient claims information and financial information, along with demographic and behavioral data will help you prove the value of marketing dollars spent. The first step is to get your hands on your patient claims data.

Using Patient Claims Data to Deliver Marketing Results

We recently helped a client work through the basics of utilizing their patient data. They have many primary care locations throughout the region, but they need more patients coming into those locations. Here’s how we got them started.

Step 1. We requested the data they had available on the new patients they’d acquired within the last 6 months.

Step 2. Our business intelligence team combed through that data to determine what needs brought those patients into the office — their ages, genders, where they live, etc. It turned out that they’d assumed their patients were older than they actually were, and we were able to determine the top conditions bringing them in.

Step 3. Our channel engagement team ensured advertising targeting was capturing the largest groups of demographics already represented in their new patient base — to capture more "look-alike" patient leads. Then, our content team referenced those top patient profiles and reasons for visits as they picked who to depict in images and what topics to highlight in messaging.

Turning Insights into Action with Patient Data

Rather than trying to blanketly reach everyone in your community, using first-party data, you can target the patients who are mathematically the most likely to choose your hospital or health system. You can also learn who is the least likely to choose you for their health concerns, and in turn, develop a long-term strategy to build trust with those people. Either way, you get to prioritize your marketing efforts based on the true opportunities in front of you rather than just guessing.

Customer propensity modeling in particular has proven to be extremely effective for creating ROI in patient acquisition investments. Members of our Business Intelligence department have successfully used this method to identify a top-10 market for key patients who were the most likely to choose the health system. That data also revealed that the health system could focus in on half the market to gain market share in high priority service lines, which saved significantly inpatient acquisition investments. Here’s how the propensity model works.

Using Data Science with the Patient-Centered Data Model

What exactly is propensity modeling? At its core, propensity modeling is about using data to understand the choices your patients make. It applies machine learning to determine which patients — and which characteristics — are most important to your current customer base, and where they are seeking care outside of your system, so you can reach them more effectively. The best models understand that people are complex, with many demographic dynamics, social determinants, spending habits, lifestyle factors, and preferences that shape their judgment and behavior. It can be expensive to try to market to everyone in your target market all the time.

Understanding who is likely to choose you for patient care, why they are choosing you, and for which services — as well as understanding who is choosing your competitor — can help you create a plan to grow the services that are most vital to your organizational strengths and wellbeing.

This not only allows you to be more efficient with your marketing outreach to existing customers, but it lets you better understand what resonates with them. It’s targeted marketing with all the power of data science leading the way.

Lewis Business Intelligence has used this type of approach with large retail clients and Academic Medical Centers to help position them for growth — not only in understanding who prefers them today but in figuring out why and how to reach those who refer patients to you, as well as understanding who prefers your competitor today. Propensity modeling applies machine learning to define retrospective analysis — what occurred with customer engagements in the past — and then makes predictions about the future. Lastly, and most importantly, it provides a prescription for how to apply that data to business decisions. It takes a skilled team to effectively mine and apply the data to achieve strategic outcomes.

Unfortunately, 47% of healthcare organizations lack the business intelligence staff to implement this model. It’s cited as their number one barrier to applying business intelligence data. A business intelligence department is not simple to develop without experienced, high-level talent to lead it. Especially in the healthcare field.

Applying the Patient-Centered Data Model

If first-party data is the future of healthcare marketing and growth — and we think it is — every organization should now be implementing the necessary steps to mine data for either their own or their agency partners’ business intelligence teams to transform into valuable prescriptions for their business needs.

If you’re not ready for artificial intelligence, there are still great opportunities to apply the patient-centered data model to understand who your patients are, why, and when they are choosing you, as well as how to reach them effectively. In working with a health system client recently, we were able to analyze recent patient demographic data and reasons for patient visits to inform their primary care advertisements and media approach. The results were high ad engagement, and subsequently, immediate new patient visit increases of 19%.

Above anything else, patients respond to messaging where they feel heard, seen, and special. There is no “one size fits all” approach to your messaging, nor to building the right model to create collaborative growth. But the right data can be a pivotal element in helping you reach the right patients and families at the time when they need you the most.

Contact us to learn about how our BI team can help you get there.