The opportunity is here for behavioral health organizations to leverage their data to increase clinical, operational, and financial performance. Our guide will help explain the benefits to data driven decision making, along with some of basic ways that organizations need to shift their processes to better leverage data in the future.
An Introduction to Data Driven Decision Making in Behavioral Health
Optimization Opportunities in Behavioral Health
Behavioral health organizations work in an incredibly difficult environment. The reimbursement of services and modes of funding are constantly changing and never up-to-par with that of physical healthcare services. Regulations are controlled state-by-state, and sometimes county-by-county, and they change on what feels like a weekly basis. At the same time, these organizations are serving the most difficult population of healthcare consumers in this country.
Because of the environment in which they work, it’s very important for behavioral health organizations to concentrate on optimizing their financial, clinical, and operational processes. This entails trying to maximize revenue, all the while decreasing costs and providing the most effective services for their consumers. While this isn’t an easy ask, most behavioral health organizations at least have the opportunity now to use data to identify opportunities for improvement and drive innovation within their own agency. This is the future for the industry, and if done well can help lead to opportunities for growth and expansion within the marketplace.
At this point, most behavioral health organizations are very familiar with the importance of data capture, reporting, and even data warehousing. The buzz words of data analytics, business intelligence, and machine learning can be heard in ever corner of healthcare. The reality, though, is that most organizations (and its executives) really don’t understand the power of analytics compared to the static reports that they’ve worked in for decades. Today’s organizations are capturing enormous amounts of data in every part of their workflow. Using this data, creating a structure to identify insights, and then driving change from those insights is how optimization comes about effectively.
The power of data analytics for healthcare is that it allows staff ranging from direct providers to executives access to data that will help them improve in real-time. Instead of the endless cycle of developing reports, opening reports, exporting the data, and then using Excel to filter, a properly created data warehouse and analytics tool will allow staff to filter and dig into data in a matter of seconds. This creates more powerful information sources, and also creates a much faster feedback loop that will help to drive and sustain innovation.
It’s important, though, to keep in mind that dashboards and business intelligence tools are only the beginning. Getting outcomes from your data requires a shift in culture and leadership to help support the process improvement and change management efforts. There must be people that are accountable to help drive change in the organization, and it’s important to create a structured plan and governance team to keep initiatives on track. Much like any major internal initiative, becoming a data driven organization will take time and energy, but by doing so you’ll better position your organization for the future of healthcare.
Over the past few years, Afia has had the opportunity to team with behavioral health organizations across the country to improve their clinical, financial, and operational performance. This has ranged from ensuring the successful development of integrated health models to the improvement in revenue cycle best practices. We’ve seen the power that data creates to validate issues that an organization feels like they are experiencing, and also to identify the path to improvement.
Clinical Example – Hospitalizations
One of the most common requests that we’ve received, that is also a industry-wide initiative, is to decrease unnecessary hospitalizations. This is a great example of an initiative where data can be leveraged to understand the underlying reasons why this is potentially occurring, and also to help identify changes in workflow or process to improve the situation. An example of this was a Community Mental Health organization in Michigan where we identified through their data that their rate of admission was much higher in the early evening hours than it was earlier in the day. After brief conversations with their team, we identified that their crisis staff worked until 5, and would start transferring calls to the hospital-based team at 3pm. And to no surprise, that team had a 98% admission rate. After updating their schedules and workflow, over the next 6 months they reduced their overall hospitalizations by 17% and children’s hospitalizations by 38%.
Financial Example – Revenue Cycle Optimization
Another area where data can be a very powerful tool for optimization is in revenue cycle operations. Since there are great financial best practice metrics to compare against, organizations have the ability to identify points of leakage or revenue loss within their organization pretty easily. Once an area of weakness is identified from data comparison, the implementation of streamlined workflows and monitoring tools can help the organization get back to a strong baseline and maintain their performance into the future.
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