by Gautam Char
Change is always occurring, and lately it is happening at a faster and faster pace. As you embark on adding intelligent technology to your revenue cycle, it is important to be purposeful in selecting technology that identifies and resolves your business problems. Before due diligence starts, it is wise to ask some key questions as your analytics platform strategy is under construction. Look inward – at yourself and your organization – and you will discover gaps in knowledge, technical gaps, and questions that need to be addressed.
Performing a gap analysis of your current RCM and Operations technology stack is the first step. Consider current strengths and areas where functionality is missing or lacking around automation and insight. Then, identifying what is needed to create a comprehensive solution. This assessment will help you evaluate how well existing vendors and home-grown, manual solutions address your needs. Armed with self-knowledge, you will be well positioned to begin due diligence.
Integration
Most healthcare organizations have grown through acquisition. This trend has been escalated in recent years due to the pandemic. Now even larger, integrated health systems are left trying to integrate everything that has been acquired. It is important to take a full inventory of the systems that contribute to the revenue cycle. What electronic health record systems do you have: Epic, Cerner, Meditech, multiple systems, other? Which practice management system(s) will go forward and which will be rationalized? What ERP and finance systems do you have? How will you manage that transition and its effect on the revenue cycle, operations, and your data governance? What other systems contribute to your revenue and profitability management? Also consider whether the vendors you are pursuing have experience integrating with the systems you have on hand as well as new proposed solutions.
Not only is it important that your analytics platform ingests data from disparate source systems, but is must also process and manage that data to create a uniform health dataset before AI and machine learning can be applied to drive business intelligence and continual learning from your data. Be sure to consider how the platforms you are considering will help build organization alignment through data.
Most RCM and operational analytics platforms create a purpose-built health dataset. However, it is not always the case with data rendering tools like Tableau. Consider the following questions in your due diligence efforts.
Many analytics platforms are not purpose-built for healthcare, or even for the revenue cycle. Rather, they tend to be toolkits that contain functional building blocks that technicians can be assemble into infinite configurations. In this scenario, you will need technical support to build queries and format report specific to your revenue cycle and operational workstreams. But first, data scientists will need to spend time creating your own normalized database. Keep in mind that since you are a revenue cycle and operational expert, there will also be a learning curve as you begin to write requirements for the reports needed to run your own business.
Platforms that have been created specific to the revenue cycle and operational needs of healthcare organizations are more apt to have essential functionality right out of the box. At WhiteSpace Health, we are RCM, HIM, operations, and healthcare IT experts. It is all we do, and we have built a platform that answers the questions we had while we were running RCM and Healthcare Operations as you do now. We believe data, insight, and knowledge needed to resolve and prioritization are essential for good management.
Security of data and PHI are core to any analytics platform. It is also important to ensure the right subset of the date are available for various roles that use the analytics platform. Aside from verifying SOC2+ certification which ensures compliance with technical security best practices, you need to set up enhanced security with role-based permissions. It is important that your team has access to everything essential to do their jobs while also staying focused on key areas of responsibility.
Be sure to ask for a generic project plan for the analytics platform you are considering. This should apply to both off the shelf analytics platforms and home-grown solutions. Historically, analytics implementations were quite long and take a lot of effort from experienced resources. Loss of project momentum and executive support is a risk as the project drags on. If you are only getting a data rendering toolkit that contains building blocks that still must be assembled into meaningful reports, it is likely to take a lot longer to achieve the value you need. Other questions to ask include:
Be sure to budget the correct amount of FTE time so you project receives the focus needed to succeed while also ensuring that day-to-day tasks do not suffer.
When you get all of your questions answered right “out of the box” at go-live, there is less to do to fine tune your new platform. Questions to help you discern what else might be needed include:
Once your new platform is set up and ready to go, consider how long will it take for our team to become proficient users – and how they will become proficient.
Success criteria can look different at each organization and measures of success need to be carefully considered before your buying decision is made and implementation begins. Achievement of these goals should serve a guidepost as decisions are being made during the implementation process.
Most leaders need to demonstrate a compelling ROI on their investment. To ensure you have an advantageous position to do this, be sure to collect “before” benchmark data from your processes so you can compare it to the post go-live performance. Be sure to estimate the time you are currently spending to manually calculate daily, weekly, and monthly operational KPIs and analyzing your data to uncover problems. Take note other key metrics such as denial volume and average time to resolve. Compare the velocity of cash before and after implementation – at 30 days, 60 days, 90 days, and year over year to monitor improvement. Most importantly, are the improved levels of performance sustainable? All these factors, and more, will contribute to the value you receive from your investment.
About Gautam Char
Gautam Char is the president and CEO of WhiteSpace Health. He has a wealth of experience bringing products to market and rapidly growing companies. Known for building high performance teams that create valuable products and solutions for customers, Char’s talent for collaboration and his industry knowledge will position WhiteSpace Health for growth and excellence.
Contact: gautam.char@whitespacehealth.com
2424 North Federal Highway, Suite 205
Boca Raton, FL 33431
