By Sou Chon Young, Hayes Management Consulting
Twitter: @HayesManagement
Rapidly changing payment methods. Shift from fee-for-service to value-based care. Declining insurance reimbursements. Increased government regulations.
Sound familiar? The litany of changes impacting the healthcare industry appears to grow longer every day. Taken together, they add up to one thing: more stress on your revenue cycle. Organizations need to adapt to this new reality to survive the upheaval.
There is a way for you to not only address these issues, but also to thrive in the turbulent times ahead. The key to solving the dilemma is close at hand: the data that resides in your EHR and other IT systems and applications. Harnessing this treasure trove of information and converting it into actionable data can help you meet the growing demands you face. But to access this big data, you need to develop a comprehensive data analytics program.
Why data analytics?
How important is collecting, analyzing, and acting on the vast amounts of data that exist within your organization? McKinsey researchers believe big data analysis can potentially save the US healthcare industry more than $300 billion annually¹. Thanks to rapid advances in software technology and expanded network bandwidth, healthcare organizations now have the ability to analyze a wide variety of data to drive improvements, better understand your patients’ needs and care histories, and make informed decisions.
The migration to Electronic Health Records (EHR) and adoption of standard transaction code sets provides you with data that has historically been difficult to aggregate and examine. Analyzing and applying this data is a key factor in helping you identify improvement opportunities. According to one survey, 60% of healthcare IT professionals plan to increase investment in technology to help them expand their ability to handle complex analytics². As a result, institutions today are better positioned than ever to use data to positively impact their operations.
Obtaining and analyzing available data can make a rapid positive impact on your revenue cycle in many ways including:
- Reducing bad debt and write-offs
- Clearly defining patient financial responsibility
- Improving denials management
- Quickly providing actionable billing and collection information to staff
- Establishing targeting and segmentation models to develop effective marketing programs to increase revenue
An effective data analytics program can also help you address the ongoing challenges presented by changes occurring in the healthcare industry including:
- Shift to quality-based reimbursement models such as pay-for-performance
- Increase in bundled payments where organizations need to disperse funds appropriately and negotiate contract terms
- Move to consumer-driven healthcare where patients shop for providers based on price and quality
- Growth of Accountable Care Organizations that drive a need for data and data points to monitor care, cost, and reimbursement
Getting started
Just possessing the data somewhere in your system isn’t enough. For you to aggregate and evaluate this information and turn it into actionable opportunities requires developing an organization-wide plan. Designing and implementing a comprehensive plan is critical to making data analytics an integral part of your decision making process. An effective plan begins with support from senior executives and cascades throughout the organization.
The first step is to establish a core group that understands the data and the importance of using it to drive business initiatives. Typically, departments within organizations work in silos; the clinical and financial teams don’t typically share data or work on integrated, cross-functional reporting to find opportunities. Your data analytics team must have representatives from all of these groups to break down the walls and share information across all departments.
Empower this cross-functional team to review data and plan for future needs, all the while aligning with executive organizational goals. They should define the key metrics for every initiative since that’s the only way to appropriately manage improvement.
It’s crucial to involve operations when developing your data analytics plan. Ask business users what they need to better manage their departments and have them participate in setting up appropriate new reports and designing real time analytics dashboards. Schedule periodic meetings with operations/business owners and the IT group to review progress, discuss future goals, and establish plans to achieve them.
A key step to an effective data analytics program is establishing a strong data governance protocol. Create a data management team of business owners and IT staff to govern the process. Include analysts with in-depth knowledge of the business and the data, as well as strong analytical and research skills.
The data governance plan determines who is responsible for maintaining data, who has access, which data is to be integrated, and how it will be accomplished. Institute a process that enables constant QA of your data and conduct audits and user surveys to ensure the selected data is meeting end user requirements.
Working with IT to discover opportunities
It’s difficult for senior management and the IT group to keep up with the vast amount of detailed data that is available. The IT staff is familiar with the data but might not have the analytics experience to leverage it into relevant action items. The process for senior management to request reports traditionally has not been real-time so by the time they receive requested information it’s either not what they had in mind, it prompts a request for an additional report once they review, or the data is simply too dated to be useful. From a systems standpoint, not all meaningful and useful data is available electronically and even when it is, it may not be in a standardized format so is difficult to share.
Resolving these issues and uncovering valuable insights from your data requires a close working relationship among your managers, analysts, and IT Ops personnel. The IT team has the system knowledge to help gather and organize the information you need to guide you in making meaningful decisions. These steps provide a path to an effective collaboration between operations and IT to optimize your data analytics program:
- Establish consensus on the goals and initiatives of the program
- Determine top priority organizational goals and determine what data sources are required to help drive decisions
- Ensure your data is standardized and design an appropriate repository to house it
- Outline an inventory of current reports and determine which ones are still being used. Suspend existing reports not currently used (but do not eliminate in case they may be needed later).
- Establish regular reporting schedules
Using this collaborative approach will not only help identify opportunities but will also expedite the process of fulfilling business needs.
Finally, to truly leverage your data requires strong business intelligence tools and knowledgeable analysts that not only understand the business and the data that drives it, but also know how to use the tools to identify opportunities and communicate those effectively to the rest of the organization.
Growing economic pressures clearly dictates that you focus more closely on business realities. This means adopting business rules, tools, and technology to operate more efficiently and productively. As revenues decline and margins shrink, you should use every tool at your disposal to maintain viability and thrive in a difficult economy. Leveraging big data can play a huge part in helping your reach those goals.
¹Big Data: The next frontier for innovation, competition, and productivity. McKinsey & Company. May 2011. Web. April 2014.
²Big Data Driving Analytics Investments, Healthcare IT News, March 2013
This article was originally published on Hayes Management Consulting and is republished here with permission.