It took 18 months to implement an Electronic Health Record (EHR). Your staff is documenting demographics, medications, assessments, state-mandated outcome tools, service notes, etc. Your entire organization is connected now, from your front desk staff through your billing team, with data flowing across every business unit. You feel pretty good about the technology supporting your organization.
Then you sit down with your executive team to do strategic planning. Someone asks the question, “what is the average cost of treating a consumer with Schizophrenia?” Silence. “Did our PHQ-9 scores improve for consumers with a major depressive disorder?” Uncomfortable looks. “What was our diversion rate for our high-risk population?” You get the point.
Behavioral health organizations are swimming in data from the electronic systems supporting their clinical, financial, and administrative business units. However, most teams are barely leveraging this data. Reports are created. Reports are viewed (sometimes). Rarely does this lead to any real insights that improve clinical or financial performance. This is a prevalent theme within healthcare, but one that needs to be fixed so providers can thrive in a competitive landscape. Below are some steps that can help simplify the path to becoming a data-driven organization.
There is so much data being collected and stored about consumers that special tools are needed to make sense of it all. The static reports from an EHR just aren’t going to cut it. This is where a data warehouse comes into the picture. Going without a data warehouse is like asking the Coast Guard to patrol in sailboats – it is technically possible, but it is going to take a lot longer, and there is a lot they would miss. With a warehouse, you can cover much more ground in a shorter period.
Data warehouses create a central repository where people can come to investigate the data associated with consumer populations. Why did hospitalizations spike last month? Which programs need more support to get their productivity up? Who are the high-risk consumers? Warehouses empower staff because it provides them a tool to slice and dice organizational data without needing programming skills. For organizations that are trying to improve their clinical and financial performance, this becomes extremely powerful.
As is the case with most technology, a data warehouse and analytics platform is not going to make its intended impact without a strong infrastructure to support it. The key is creating a culture around data and ensuring that the right resources and processes are in place.
It is essential to develop a governance team to make decisions about the technology, and also to set the goals, objectives, and strategic direction related to the warehouse. With governance in place, the next phase is creating a “data swat team.” This will be the group responsible for operationalizing the warehouse. Their charge will be ensuring that data turns into insights, which then turns into meaningful change.
There are a few distinct roles that make up this team. The first is a “technical” resource that understands the data and the warehouse framework. The second is a subject matter expert that deeply understands specific parts of your business. Lock these two people in a room, and they will ask the questions and churn through data to identify issues, outliers, and opportunities for improvement. Depending on the problems you want to solve, the subject matter expert will likely vary but can include resources from the medical, clinical, financial, and administrative teams.
Finally, once you have identified an issue or opportunity, it’s time to implement the solution. The final role within the data team is a person charged with process re-design and change management. This person will embed themselves into different teams throughout your organization, helping them to define and implement solutions to the issues identified. To succeed, they will need to be part project manager, part process engineer, and part change management specialist.
With all the roles aligned, a fluid data governance process, and a robust technical platform, an organization will have the framework to turn data into action. At that point, it is all about working the process and continuing to develop the culture of data-driven decision making throughout your organization.
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