Webinar – The Upside of the Claims Talent Crisis – A Roadmap Forward
Workers’ compensation claims organizations are facing a crisis — an aging talent pool and a mass exodus of Baby Boomers that will impact virtually every facet of claims operations. From core competencies, to technology, to development and retention strategies — the industry must undertake a holistic evaluation of the far-reaching risks and repercussions that the coming crisis poses. And while this crossroads represents a challenge, it also provides the opportunity to draw a roadmap forward, from uncertainty to upside.
Results from the Workers’ Compensation Benchmarking Study, a national multi-year study of more than 700 claims leaders, has quantified the state of claims management today as well as captured executives’ visions for the future through this year’s focus group research.
In 2015, we find claims leaders centering on the talent gap, as well as how to empower a new generation so that they are creators of value through better outcomes management. As revealed by study results, far too few organizations are investing in developing talent, a business risk with grave consequences.
This webinar seeks to redefine the talent crisis as an opportunity to ask this question — how do we align the industry’s emerging claims talent with achieving better results: getting injured employees healthier and productive faster, while lowering costs.
Expert panelists involved in the study will discuss:
- Attracting and retaining the new generation of talent — Millennials. Ambitious, technology-friendly, and keen on achieving a sense of higher purpose in their work, this new generation has enormous potential — if that potential can be tapped, developed and deployed effectively.
- Restructuring strategies to aim for success in outcomes management, not just process and compliance improvement, with a much greater emphasis on empowering claims professionals with the data, tools and training needed to achieve mastery in claims management.
- Making the perfect match: Marrying talent strategies with technology strategies and pairing the tech-driven Millennials with advanced analytics that enhance complex decision-making.
- Defining new career paths that will allow Millennials and other professionals to fly faster and farther and achieve their ambitions while providing a high degree of job satisfaction.
- Developing solid mentoring opportunities and senior training to ensure a culture of formalized knowledge transfer programs.
- Elevating the socially-conscious aspects of the claims profession, understanding the importance of purposeful employment for today’s talent.
Webinar attendees will receive a complimentary copy of the Benchmarking Study’s 2015 Insights Report, which will be released in the coming weeks.
Space is limited, so register today!
Date: Wednesday, October 21st, 2015, 1:00 – 2:00pm EST
Webinar – Value-Based Purchasing in WC: An Idea Whose Time is Here
Getting excellent medical results for injured workers at a price that is both predictable and reasonable doesn’t seem like too much to ask. So why is it that the workers’ comp industry and its vendors can’t get this one right?
This webinar’s expert panel is going to show us the way forward. We’ll hear from a California-based medical provider who is contracting with carriers to produce high quality results with spinal injuries, one of workers’ compensation’s toughest and most expensive challenges.
We’ll also talk to the executive director of one of the largest state funds, which has launched a pilot program to use value-based medical provider compensation in managing hundreds of worker knee injuries.
Lastly, we’ll hear from a workers’ comp company that has successfully launched a value-based program for bundled orthopedic surgical procedures.
Furthermore, the expert panel will discuss:
- The impact of healthcare reform and the creation of accountable care organizations; and the need for workers’ comp to recognize that it must inevitably follow the trend away from the flawed fee-for-service model.
- How improved modeling is giving payers and providers much better transparency into their risk portfolios of injured workers, and how those analytics can be acted on.
- That although frequency is down, workers’ comp costs continue to rise. Merely watching this trend and doing nothing is not an option.
- The challenges of bundled or value-based purchasing, presenting a holistic view of this topic.
- The recommended steps workers’ comp can take today to implement value-based models, moving the industry towards walking the walk not just talking the talk.
6 Truths about Predictive Analytics
Predictive data analytics is coming out of the shadows to change the course of claims management.
But along with the real benefits of this new technology comes a lot of hype and misinformation.
A new approach, ACE 4D, provides the tools and expertise to capture, analyze and leverage both structured and unstructured claims data. The former is what the industry is used to – the traditional line-item views of claims as they progress. The latter, comprises the vital information that does not fit neatly into the rows and columns of a traditional spreadsheet or database, such as claim adjuster notes.
ACE’s recently published whitepaper, “ACE 4D: Power of Predictive Analytics” provides an in-depth perspective on how to leverage predictive analytics to improve claims outcomes.
Below are 6 key insights that are highlighted in the paper:
1) Why is predictive analytics important to claims management?
Because it finds relationships in data that achieve a more complete picture of a claim, guiding better decisions around its management.
The typical workers’ compensation claim involves an enormous volume of disparate data that accumulates as the claim progresses. Making sense of it all for decision-making purposes can be extremely challenging, given the sheer complexity of the data that includes incident descriptions, doctor visits, medications, personal information, medical records, etc.
Predictive analytics alters this paradigm, offering the means to distill and assess all the aforementioned claims information. Such analytical tools can, for instance, identify previously unrecognized potential claims severity and the relevant contributing factors. Having this information in hand early in the claims process, a claims professional can take deliberate actions to more effectively manage the claim and potentially reduce or mitigate the claim exposures.
2) Unstructured data is vital
The industry has long relied on structured data to make business decisions. But, unstructured data like claim adjuster notes can be an equally important source of claims intelligence. The difficulty in the past has been the preparation and analysis of this fast-growing source of information.
Often buried within a claim adjuster’s notes are nuggets of information that can guide better treatment of the claimant or suggest actions that might lower associated claim costs. Adjusters routinely compile these notes from the initial investigation of the claim through subsequent medical reports, legal notifications, and conversations with the employer and claimant. This unstructured data, for example, may indicate that a claimant continually comments about a high level of pain.
With ACE 4D, the model determines the relationship between the number of times the word appears and the likely severity of the claim. Similarly, the notes may disclose a claimant’s diabetic condition (or other health-related issue), unknown at the time of the claim filing but voluntarily disclosed by the claimant in conversation with the adjuster. These insights are vital to evolving management strategies and improving a claim’s outcome.
3) Insights come from careful analysis
Predictive analytics will help identify claim characteristics that drive exposure. These characteristics coupled with claims handling experience create the opportunity to change the course of a claim.
To test the efficacy of the actions implemented, a before-after impact assessment serves as a measurement tool. Otherwise, how else can program stakeholders be sure that the actions that were taken actually achieved the desired effects?
Say certain claim management interventions are proposed to reduce the duration of a particular claim. One way to test this hypothesis is to go back in time and evaluate the interventions against previous claim experience. In other words, how does the intervention group of claims compare to the claims that would have been intervened on in the past had the model been in place?
An analogy to this past-present analysis is the insight that a pharmaceutical trial captures through the use of a placebo and an actual drug, but instead of the two approaches running at the same time, the placebo group is based on historical experience.
4) Making data actionable
Information is everything in business. But, unless it is given to applicable decision-makers on a timely basis for purposeful actions, information becomes stale and of little utility. Even worse, it may direct bad decisions.
For claims data to have value as actionable information, it must be accessible to prompt dialogue among those involved in the claims process. Although a model may capture reams of structured and unstructured data, these intricate data sets must be distilled into a comprehensible collection of usable information.
To simplify client understanding, ACE 4D produces a model score illustrating the relative severity of a claim, a percentage chance of a claim breaching a certain financial threshold or retention level depending on the model and program. The tool then documents the top factors feeding into these scores.
5) Balancing action with metrics
The capacity to mine, process, and analyze both structured and unstructured data together enhances the predictability of a model. But, there is risk in not carefully weighing the value and import of each type of data. Overdependence on text, for instance, or undervaluing such structured information as the type of injury or the claimant’s age, can result in inferior deductions.
A major modeling pitfall is measurement as an afterthought. Frequently this is caused by a rush to implement the model, which results in a failure to record relevant data concerning the actions that were taken over time to affect outcomes.
For modeling to be effective, actions must be translated into metrics and then monitored to ensure their consistent application. Prior to implementing the model, insurers need to establish clear processes and metrics as part of planning. Otherwise, they are flying blind, hoping their deliberate actions achieve the desired outcomes.
6) The bottom line
While the science of data analytics continues to improve, predictive modeling is not a replacement for experience. Seasoned claims professionals and risk managers will always be relied upon to evaluate the mathematical conclusions produced by the models, and base their actions on this guidance and their seasoned knowledge.
The reason is – like people – predictive models cannot know everything. There will always be nuances, subtle shifts in direction, or data that has not been captured in the model requiring careful consideration and judgment. People must take the science of predictive data analytics and apply their intellect and imagination to make more informed decisions.
Please download the whitepaper, “ACE 4D: Power of Predictive Analytics” to learn more about how predictive analytics can help you reduce costs and increase efficiencies.
This article was produced by the R&I Brand Studio, a unit of the advertising department of Risk & Insurance, in collaboration with ACE Group. The editorial staff of Risk & Insurance had no role in its preparation.