how healthcare providers should think about data

What’s the deal with data

In a prior blog post, Andrew Sawyer, MPH, extolled the virtues of building a robust bridge between the CMO and the CIO. As those pylons begin to be poured… a new question arises… what data matters for these new engagement initiatives and how do health systems organize it?

Let’s start by dividing data into two major categories: transactional data and engagement data.

In most enterprise organizations, there is a vast amount of structured legacy transactional data that supports myriad activities — supply chain, finance, HR, etc. On the other end of the spectrum is less structured engagement data, which spans from basic customer demographic information to purchasing or usage preferences and advanced web behavior.

If we adjust our view to focus specifically on health systems — in addition to the above, they also have a vast amount of clinical and industry specific information regarding their patients, providers, and payers stored in the EMR and Claims applications. This data set squarely falls into the structured transactional category (albeit there may be some slight overlap, i.e. demographics). Despite this mass of information, health systems do not often have mechanisms to manage and organize engagement data; technologies like CRM, Marketing Automation, CDP, DMP, etc.

This point is foundational because in the modern digital era, we, as consumers, are accustomed to our retail, travel, e-commerce, and banking providers using engagement data to serve us better; creating a “persona” that amalgamates our preferences and behaviors. That persona is further used to serve us with information, communication, and content that is personalized and individually relevant. The manifestation of this can be as simple as seeing your city skyline when you log into your banking app, to being able to serve up specific program offers, like a mortgage discount, based on your usage of Zillow. This allows these organizations to meet the consumer in the right place, at the right time, and be extremely strategic in how they acquire new customers or market additional services.

Inarguably, this notion of abstraction and personalization is not yet in the working vocabulary of many health systems. Certainly many organizations are moving in this direction by beginning large digital transformations that include solutions to help house this “new” dataset. Nevertheless, this process goes far beyond buying the latest technologies and applications.

With more data, comes more responsibility… and that responsibility begins with understanding how to organize and master said data.

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How to start adjusting your expectations

Ever since there has been data, there has been a desire to put it all in one place (warehouse, lake, insert latest big data buzzword here). However, this methodology can create inefficiencies and introduce security vulnerabilities; more importantly, it is nearly impossible to keep that dataset clean and up-to-date. Imagine a single locked room full of file folders which are full of information for each individual, regardless of type; you can see that they may not be easy to keep straight in the long term as more and more files are added to each folder.

Now imagine individual locked file cabinets in that room that house information by type (demographics, preferences, past visits, etc.) and contain labeled folders for each individual. You can see how it would be much easier to find and collate the necessary data on a single entity, as needed, rather than having to get ALL the data on that entity and then filter out what is unnecessary. Fear not, as modern integration technologies allow enterprises to master data “in-place” and ensure data can be joined when needed for any number of use cases.

Ultimately, data organization, mastery, and mobility are paramount to create a successful transformation towards successfully adopting modern digital technologies. No matter how great the CRM or marketing platform is, it alone, cannot solve the complex issues with data or provide strategies to manage it over time. In fact, they can often introduce even more disparate and disorganized datasets.

For all these reasons, many of our conversations at Cured begin and end with data. We strongly believe that without an effective and long-term data management strategy, health systems (and others) who are just entering the digital engagement realm will not be successful.

You may be asking yourself: that seems ideal, but where do we start? We continually stress that the first step in this process is gaining an extremely intimate and deep understanding of the first party data (the EMR!) available to you… and without question that is you should begin.

There is much more to come on this topic over the coming months as we dive deeper into the data sphere and discuss successful methods we and our clients have used to deploy these strategies.