In behavioral health, EHR optimization can take many forms. Your organization may be selecting a new system, improving an existing EHR that is not working as well as it should, or adapting established workflows to support a new program, grant, or service. Whatever prompts the change, the technology itself is only part of the equation.
During our recent webinar on configuring your EHR to optimize quality data, Product Manager Niya Branham explained how these initiatives often succeed or fail based on decisions made long before anyone writes a single configuration requirement. Keep reading about eight considerations that can help your organization plan the change, support adoption, and build a stronger foundation for quality data.
Why Data Quality Matters for Behavioral Health Organizations
Before diving into the eight considerations, it’s worth taking a step back to look at why the planning process matters in the first place: It creates the foundation for quality data your organization can use.
The value of EHR data depends on more than how much information you collect. That information also needs to be accurate, consistent, and structured in a way that makes it useful.
When those pieces are in place, EHR data can provide a timely view of what is happening across your organization. Leaders can monitor quality measures, identify documentation issues, and understand service activity without relying solely on delayed claims data or end-of-quarter reports. Reliable data can also help teams catch errors earlier, respond to questions with greater confidence, and support continuous quality improvement.
Achieving that kind of data quality requires more than changing fields, forms, or screens. It depends on the goals you set, the workflows you design, the people you involve, and how well you support and evaluate the change.
The following eight considerations can help your organization address those factors before configuration begins.
1Define the goal and the problem you are solving.
Start by getting specific about what the optimization needs to accomplish. Are you trying to close a reporting gap, improve quality measures, or make a process more efficient?
One way to clarify the goal is to begin with the story you want to tell at the end. Think about six months, nine months, or a year from now. What do you want to be able to say to your board, staff, community, or other stakeholders? Once you know, you can work backward to determine what data you need to tell the story reliably.
For example, if you want to explain how the organization reduced no-shows, you need a consistent and accurate way to capture no-show data. If you want to measure how long clients remain in a program, you need to identify the data points necessary to calculate that length of time. The desired outcome should guide the way information is collected, rather than trying to build a story around whatever data happens to be available.
2Identify your data requirements.
Prioritize workstreams across access and crisis services, workforce and training, care coordination, documentation and reporting, and financial readiness. Not everything has to happen at once, but each workstream should have clear ownership, success criteria, and milestones. This is also the stage where organizations should determine whether technology modernization will happen before, during, or after certification.
3Be realistic about timing and resources.
Optimization almost always takes longer than expected, not necessarily because anything goes wrong, but because behavioral health organizations operate in the real world.
Staffing changes, IT availability, competing initiatives, and unexpected program issues can all interrupt the work. A project plan that looks reasonable on paper may become difficult to sustain when the people responsible for it are also supporting clients and managing day-to-day operations.
You also need to think about burnout and how much time individuals can realistically devote to an initiative that may extend over many months. The same cross-functional team may manage the full initiative, or responsibility may shift as the project progresses. The right approach depends on the organization and who is involved.
4Establish governance and leadership.
The subject-matter experts who understand your workflows are not always the same people who can approve a change.
Before the optimization begins, establish who owns decisions, who can resolve competing priorities, and who has final approval. If two stakeholders disagree, the project needs a clear path for reaching a decision. Without that structure, the conversation can stall because no one knows who has the authority to move it forward.
Clear governance can also prevent late-stage surprises. A project team may work effectively for months, only to present its recommendation to an approver who raises significant questions or concerns. Identifying required decision-makers earlier gives them an opportunity to shape the work before the team reaches the final stage.
5Map workflows before configuring the EHR.
EHR design should reflect how people actually work, not how leaders assume they work or how a process was intended to work years ago.
A “day in the life” exercise can help uncover that reality. Ask staff to walk through the forms they use, the information they need, and the steps required to move their work forward. Along the way, look for tasks that no longer add value, continue simply because they’ve always been done that way, or duplicate information someone else is already collecting.
Keep in mind that different programs may follow different paths. As the number of services, locations, and populations grows, workflows are likely to become more varied. That makes it even more important to lay out those differences and understand how they come together within one EHR.
6Plan for training and change management.
Training and change management are related, but they are not the same.
Technical training helps staff understand how to use the system. Even when the organization keeps the same EHR, a redesigned screen, relocated button, or unfamiliar icon can disrupt a task that once felt automatic. Staff need practical guidance on what has changed and how to complete their work in the new configuration.
Change management addresses the human side of the transition. Some people may resist change because they’re used to doing things a certain way. Others may not understand or support the reason for it. How you prepare for that resistance can make the difference between staff adopting a new process and finding ways to work around it.
Even well-designed changes fail without clear communication, appropriate training, and active support throughout the transition. Explain not only what is changing, but why it is changing and how the new approach supports staff, clients, and organizational goals.
7Build a practical go-live and rollout plan.
Training and change management are related, but they are not the same.
Technical training helps staff understand how to use the system. Even when the organization keeps the same EHR, a redesigned screen, relocated button, or unfamiliar icon can disrupt a task that once felt automatic. Staff need practical guidance on what has changed and how to complete their work in the new configuration.
Change management addresses the human side of the transition. Some people may resist change because they’re used to doing things a certain way. Others may not understand or support the reason for it. How you prepare for that resistance can make the difference between staff adopting a new process and finding ways to work around it.
Even well-designed changes fail without clear communication, appropriate training, and active support throughout the transition. Explain not only what is changing, but why it is changing and how the new approach supports staff, clients, and organizational goals.
8Define how you will evaluate change.
Go-live is not the end of an optimization. Your organization also needs a structured way to determine whether the change produces the intended results.
Improved clinical outcomes are of course part of that evaluation, but data quality and user adoption matter as well. Increased EHR usage does not represent success if your staff are completing forms incorrectly, producing more errors, or entering inaccurate information.
Determine before go-live you’ll measure success, then establish a formal review point, such as 60 or 90 days after implementation. Assess whether quality data is entering the system and whether staff are using the new workflows as intended.
Evaluation should connect directly to the original goal. Return to the story you wanted to tell. Do you now have the data needed to tell it accurately and reliably? If not, the review should help the team identify what needs to change.
Conclusion: Plan the Change Before Configuring the System
These eight considerations are distinct, but they influence one another.
Goals shape data requirements, data requirements inform workflows, and workflows affect training and adoption. Governance keeps decisions moving, while realistic timelines and rollout plans make the work more manageable. Evaluation closes the loop by showing whether the change delivered the intended result.
The strongest optimization efforts begin with a clear problem, an honest understanding of how work happens today, and a shared plan for helping people move through the change. Before configuring the system, take the time to define the story you want your data to tell. Then build the workflows, responsibilities, and measures needed to tell that story with confidence.
Watch the full webinar, Configuring Your EHR to Optimize Data Quality: Building the Foundation for Better Insights, for more practical guidance on EHR optimization, including common obstacles to anticipate. You’ll also hear real-world examples from The Village Network that demonstrate the power of thinking ahead in system design.