The Road To Better Data Governance In Healthcare Begins With a Strong Data Foundation

John Walton

By John Walton, solution architect, CTG

When it comes to formulating and operationalizing a data management strategy, the healthcare industry as a whole is not where it should be. As integrated delivery networks continue to acquire more healthcare companies — and even other integrated delivery networks — organizations are dealing with a confusing assortment of different electronic health record systems and analytics solutions. Each system ends up acting as a silo with its own proprietary data and key performance indicators.

These KPIs are meant to help businesses succeed in their three- or five-year plans, but many in the industry either fail to tie these metrics to specific strategies or find themselves with competing KPIs from other sections of the company. The result is a mess of data that many organizations decide to dump into a data lake, hoping data scientists will step in and solve the problem. Unsurprisingly, this doesn’t often produce ideal results.

Why Healthcare Data Management Has to Improve

This lack of proper data management in healthcare leads to several problems. For one, it makes it virtually impossible to stay compliant in areas such as value-based care contracts and population health management. As healthcare organizations strive to provide analytics at the point of care, a lack of integration between payer and provider data can also become a nearly insurmountable obstacle.

To effectively take advantage of the data they’re acquiring, healthcare organizations need to work from a solid data foundation. With a proper blueprint, organizations can better see how to prioritize analytics at an enterprise level. Even more important, the dimensions of analysis in a data blueprint will provide healthcare companies with the core requirements necessary to implement a viable data governance strategy.

4 Steps to Building a Strong Data Foundation

For healthcare organizations dealing with a quagmire of data in various silos, building a foundation might sound easier said than done. Fortunately, any CIO in the industry can take a few steps to get their data in order and get on the right path to excellent healthcare data management and effective data governance:

  1. Analyze current dashboards and reports.

IT teams should start by developing a KPI inventory across all existing dashboards. These KPIs should match an organization’s strategic plans and include all contributing metrics to get a full picture of performance. For example, if an organization aims to improve patient satisfaction by 90% over three years, the KPI inventory should include metrics such as ER wait times and readmission rates.

CIOs should also ensure their organization can perform drill-down analytics on performance metrics. Drill-down analytics provide a deeper view into data’s details and origins, making troubleshooting and management much more straightforward.

  1. Perform a gap analysis with stakeholders.

After developing an inventory of current KPIs, CIOs should interview information stakeholders, such as department managers and VP-level executives, to determine what other KPIs and metrics to add. These stakeholders have a good grasp of the metrics required to run their departments, so they can help develop a data foundation that better mirrors the company’s overall strategy.

Stakeholders should be asked about vital departmental metrics and how they roll up to KPIs. These lower levels of data aggregation will be important when it comes to developing a strong data management strategy.

  1. Create a first draft of your data blueprint.

With a complete inventory of healthcare KPIs and metrics, CIOs can begin to draft an initial data blueprint. The most straightforward method is to map it out in a series of bubble diagrams.

The central bubble on each diagram should be a fact table containing important numerical metrics such as gross and net revenue. The surrounding bubbles are the dimensions of analysis that provide context; in the case of revenue numbers, for example, the surrounding dimensions would show different ways the organization wants to analyze these metrics, such as by sales opportunity, geographic location, and salesperson. Essentially, each bubble diagram should depict a data mart that stakeholders can easily understand and adjust.

  1. Perform a review session with stakeholders.

With an easily digestible model in hand, CIOs should bring stakeholders back in and work with them to make any necessary final changes. The end goal should be to create something that takes into account every relevant metric for each KPI and aligns with the organization’s long-term strategic goals. Additionally, it is very important to note that the dimensions of analysis common to all diagrams developed in step three are candidate master data domains that will be managed by the data governance program.

Proper data governance in healthcare is an increasingly important part of any successful healthcare practice. By creating a data blueprint that all stakeholders can understand, CIOs can better position their organizations to implement an enterprise analytics framework that can increase revenue and improve patient outcomes.


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