By Steven Albert, Chief Product Officer, Cloudmed
More data than ever before exists for revenue cycle management (RCM) teams at hospitals and health systems. But despite the quantity of available information, significant barriers to accessing and analyzing data for strategic insights cause many teams to miss inaccuracies that hinder revenue collection.
Each hospital functions like an independent city, with multiple departmental “neighborhoods” collecting and tracking datapoints differently, plus a web of specialists, labs, and other external “suburbs” feeding information into the system. Not only do these disparate data points make it challenging to collect data into a cohesive system, but they also hinder efforts to draw actionable insights. In the rapidly changing reimbursement landscape, many hospital administrators lack the time and proper resources for this effort.
Predictive analytics can determine opportunities to correct errors, so teams can focus on high-value work and potentially leave less revenue on the table. Here are a few key considerations RCM leaders should keep in mind when seeking to leverage their own data for strategic efficiency and financial health.
1. Use historical trends to illuminate the next best step.
Perhaps more important than pinpointing past trends, data can – and should – inform solutions to a staff’s daily problems. Skilled data experts can analyze and cleanse large data sets to assess trends in workflow and operations, with the goal of tweaking day-to-day processes and improving efficiency. When fully optimized, these data sets and numerical information can prescribe the next best step so software can take automatic action.
For example, when a patient visit is coded for a certain procedure, reports can reflect past usages of the code across various hospital units and departments. But a record of historical visits and the associated codes can also identify common inaccuracies, such as misusage of a code. Predictive models can leverage trends to queue up actions based on error potential. Team members can then prioritize tasks that most need attention – in the long run, this will streamline processes by reducing errors and focusing team effort.
2. Numbers alone aren’t enough – RCM teams thrive when supported by experts.
To reach their full potential, RCM teams need more than access to the right numbers. They also need experts to organize and interpret them.
For most health systems, it’s not realistic to expect in-house RCM staff to possess the depth of specialization or breadth of resources needed to maximize information. Hospitals need two types of experts – technical analysts who extract, normalize, and organize data for analysis and insights, as well as content experts who can correctly interpret data and information in the nuanced healthcare RCM space. These skills have become critical across healthcare, with hospitals facing workforce burnout and competing with non-healthcare companies for tech talent.
Fortunately, a third-party partner can offer technical and analytical experts with the ability to contribute specific skillsets that are so needed but otherwise hard to come by. A partner can also offer highly experienced collaboration for RCM employees, from cleaning and updating databases, to providing insight on the nuances of ongoing regulatory changes. This translates to continuous improvements at every stage of the cycle, more efficient staffing and workflows, and, ultimately, more agile teams.
3. A broad view can help identify hidden trends and patterns.
At its best, internal data can predict the next step. But a single provider organization might not have the scale to build its own “big picture” informational models, which can mean a short-sighted view of payer behavior and uncover inefficiencies hiding beneath the surface. Seeing what’s ahead is best done with a broad lens of industry-wide trends – beyond what the average hospital can assess from its limited sample size.
A third-party partner can provide data from multiple independent hospitals to identify otherwise imperceptible patterns. Each hospital can better understand common coding errors, payer trends, and effectiveness of certain claims adjustments outside of what typically happens inside its own practice. This level of insight can help each system see beyond its own relationship to payers and procedures and opportunities to understand network-wide patterns.
For example, when examining broader trends, a hospital can benchmark its reimbursement trends against those at other hospitals. Based on the areas where its payment falls short, that RCM team can then identify payers or categories of codes where inaccuracies may be limiting potential opportunities – slip-ups that intra-system trends can’t show.
The whole cycle can benefit from an agile workforce with a solid understanding of payer behavior and industry trends, so staff can double down on high-value cases.
Supporting High Performance
Data can help provide a revenue safety net while also helping RCM teams operate at peak efficiency – but by themselves, numbers and datapoints aren’t enough. Employees need the ability to see the next best step, tap into specialized expertise, and work from a broad point of view to make the most of the data at hand. Staff armed with the most up-to-date knowledge of trends, especially those happening outside an individual health system or hospital, can better navigate the perpetual changes inherent to RCM.
Steven Albert is the Chief Product Officer for Cloudmed, bringing over two decades of leadership experience in new market development and product innovation for enterprise-scale data management and analytics organizations. Steve leads Cloudmed’s product vision and roadmap, drives product innovation, and helps grow the company through expansion into new markets.
Prior to joining Cloudmed, Steve has held product and market development leadership roles at 1010data, Mastercard, Equifax, and most recently at GeoPhy. He has extensive experience leading and scaling go-to-market, product, and data science teams that delivered product-led revenue growth. Steve has an MBA from The Wharton School, University of Pennsylvania.
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