Linda Lane: Workers’ Comp Data Tells a Story: What Does It Say About the Providers Treating Your Injured Workers?
Posted on 10.08.18
Many workers’ compensation (WC) programs use provider networks to leverage economical rates among those providers who agree to participate in them. Traditionally, WC programs wanted networks that were broad and deep to ensure appropriate scope and access to care.
However, provider listings have arguably grown too large, allowing almost any licensed physician to join, with essentially no barriers to entry. Providers simply confirm their license is up-to-date and accept agreed-upon rates when they sign the contract. There may be a few additional quality-control hoops to jump through to become credentialed, but traditionally, networks have had an open-door policy. Another disadvantage is it’s virtually impossible for providers with superior results to stand out; they are buried among all the others.
When workplace accidents occur, payers consult their provider directories and refer injured workers for care. Quality criteria which is typically subjective in nature may be applied to some degree but decisions, for the most part, are based on location. If we were to bottom line the story within this data strategy, it would be: we’re going to send you to a nearby doctor, but we’re unclear how this provider will perform in caring for your injury or getting you back to work. And we can’t say if this is the best physician out of all choices available, or simply the closest.
Today, analytics can improve this story and empower claims professionals to make better informed decisions. In this article, we’ll examine how organizations can more thoroughly screen and evaluate providers using their existing data, and in the end, achieve better results – not to mention enhance their care management story.
Overcoming the Data Hurdles
The premise of an outcomes-based strategy is simple. If injured workers begin treatment with high-performing physicians, those claims will likely experience enhanced outcomes, and the benefits are reproduced across an entire book of business. Over time, this strategy can have a significant impact, helping to reduce medical and indemnity costs, and avoid or mitigate litigation.
However, there are a couple hurdles. First, data must be cleansed before the analysis occurs. Payers often have several different records for a single provider – on the order of 15 to 17 different versions with slightly differing names, addresses, and associations with different medical groups.
It’s quite common for individual provider networks to have “unclean” data, meaning the listing has duplicates and inaccuracies. Imagine these issues multiplied across many networks, which can happen when organizations engage network mosaics. Ultimately, organizations need to get down to a single accurate record for each individual physician and unique practice – across all networks. And they need to be able to collapse all information about a single physician into a working set of data. This is the critical first step in the process.
This data-cleansing process is critical and often underestimated. It is the foundation by which organizations can arrive at a single master record for each physician, which is then matched to all relevant cases. If cleansing does not occur, the data will be jumbled and incoherent, and the resulting analysis will be inherently flawed.
A sophisticated analytics firm will offer a comprehensive master data management process that uses AI (artificial intelligence) to sort through the files and accelerate decisions around provider records based on prior information and decisions.
Identifying Top Performing Doctors
To perform an objective analysis, an analytics firm needs to receive multiple data sources from which it can begin to develop an accurate story. The data can be derived from claims systems, provider networks, billing and payment platforms. Data points are extracted from the various sources and run through carefully crafted and statistically viable algorithms. With this analysis, organizations can begin to assess performance in key areas, such as lost time, disability, and litigation.
The model will evaluate a particular provider specialty, and performance is assessed in comparison to a group of peers in that same geographic region. Factors considered in the ranking can include cost of treatment, claim duration, and recidivism. The model should also contemplate case mix as well as comorbidities to ensure the comparisons are level set.
The Story in the Data
For a particular specialty, a physician might outperform others in a given geographic area. Let’s consider two spine surgeons. With all factors being equal, the data may reveal that one spine surgeon has vastly better results than the second one. The first surgeon might have taken a more aggressive approach to care early on, which may seem counter-intuitive to saving costs, but looking at the data the first surgeon on average is able to get injured workers back to health and back on the job sooner, saving overall occurrence costs.
The analytics discern a difference in outcomes, which may be attributed to a difference in approach. But these types of findings may not be immediately evident from traditional reports. Sophisticated analytics bring them to light. Without these tools, a payer, when faced with a different treatment approach, might simply deny authorization. But this decision would not be based on a complete picture. Instead, it might be based on ODG or ACOEM guidelines alone.
Another story found in the data is comorbidities significantly drive up treatment costs and claims duration. But if organizations dig further, they may find that certain physicians have better outcomes across claimants with comorbidities. Perhaps these physicians are able to better integrate care for injured workers with other existing medical conditions, such as diabetes and obesity.
Another story the data tells is that different physicians deal with different severity levels in cases, referred to as case mix. For example, organizations might see one orthopedic surgeon who is absolutely superior when treating catastrophic injuries, while another orthopedic surgeon is better at handling minor sprains and strains. If they’re not taking case mix into account, the analysis may become skewed.
Continually Enhancing the Story
Payers can’t just implement a provider network and say, end of the story – our medical management challenge is solved. Instead, they need to leverage data to continually improve outcomes and refine their panel of providers.
By using analytics, organizations can identify physicians who produces better results. From there, they can direct injured workers to those high-performing physicians for the benefit of their programs – but also for the benefit of the injured workers, who are the ultimate recipient of the better care and outcomes that these physicians achieve.
With this approach, organizations have been able to cut overall claims costs by nearly 20% and indemnity-related costs by nearly one-third, when compared to WC programs not using these strategies.
These results are achieved because injured workers aren’t seeing just any provider in a broad network. Instead, the story becomes – we’re sending our injured workers to physicians we know are leaders in their respective fields; they have track records of good results in treating similar injuries and in returning injured workers back to their jobs.
About Linda Lane
Linda Lane is President of Harbor Health Systems, a company that is revolutionizing workers’ compensation by identifying the best performing physicians for better outcomes at lower overall costs. Linda also leads strategic initiatives with customers, improving both access to care and overall medical outcomes. Her career in workers’ compensation spans more than 20 years of innovation, helping move the industry from a focus on cost containment and transactions to one which brings true medical management. Linda is also one of the founders of a leadership training program for women, founder and chair of the Business Insurance Women to Watch Foundation, and a graduate of Radford University. She can be reached at email@example.com.
About Harbor Health Systems
Harbor Health Systems, a One Call company based in Newport Beach, Calif., leads a revolution in medical networks that allows customers to build and manage a medical system based on quality performance of providers rather than the “lowest bidder medicine” that is typical of PPOs and HMOs. Harbor Health builds and manages outcomes-based medical networks, and supplies the tools, software and services to help their customers build, implement and optimize custom networks. With Harbor Health Systems, companies can identify physicians and other medical professionals who have exceptional skills in clinical, patient care and business management. By working with these healthcare professionals, payers and self-insured employers can greatly reduce the cost of care, complications, and time away from work. For more information, visit www.harborhealthsystems.com.
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This is not a paid placement.