The single most unappreciated asset in the design and management of employer-sponsored health benefits plans is transactional-level claims data. In addition to the more obvious benefit of optimizing the financial performance of the plan, the less intuitive value of accessing and utilizing transactional-level claims data is its utility as a strategic planning tool and measuring return on investment (ROI). What makes the set of transactional-level claims data even more exciting in 2013 is the ability to more easily integrate drug claims (by far the most numerous and robust from a data perspective), with short-term disability (STD) and long-term disability (LTD) data sets.
While transactional-level data is still the most underutilized and underappreciated asset in group benefits, it’s exciting to see the awareness among carriers, health service providers and plan advisors of the need for meaningful solutions that are data-driven. It’s one thing to be able to isolate and quantify an issue, but without solutions to actually address the priority issues, and then measure the benefit of those solutions, plans are no further ahead. There’s some great leadership being exhibited in the areas of solutions, and the opportunities that exist for plan sponsors in 2013 are very different from what existed even five years ago. Plans that are not leveraging their own data are missing the boat. We can no longer suggest that the solutions do not exist (they do). What’s needed is isolation, quantification and prioritization of issues within a plan before anything can happen.
Let’s consider the case of depression in the workplace. Thankfully, in 2013, nobody is going to dispute this is a major health issue for Canadians and a leading cause of absence and disability. It’s nice to see that the stigma attached with depression and other forms of mental illness is beginning to materially recede. In Canada, efforts like the Global Business and Economic Roundtable on Addiction and Mental Health that were driven by the efforts of the legendary Bill Wilkerson deserve a great deal of the credit in paving the way for awareness and the need for action. It’s inspiring to see the efforts of many large corporations (for example, Bell Canada’s Let’s Talk initiative) in helping to bring awareness of the impact of suboptimal mental health, in addition to funding and supporting important programs and treatment infrastructures for Canadians.
What many plan sponsors haven’t considered is where some of their biggest challenges exist in the area of depression within their workplace and how they can establish baseline measures, institute solutions and measure tangible ROI metrics (to ensure sustainable win-win investment) in a way that completely protects the privacy of members. However, plan data can change all of that. It simply needs to be harnessed.
Consider the following case of a plan sponsor that has an average prevalence of depression within its plan in Canada: one out of seven claimants within the prescription drug plan benefit is actively treating depression. This figure does not consider members who have stopped pharmacological treatment for depression, those people who are being managed solely with non-pharmacological measures such as psychotherapy or those who have not yet sought treatment. Here’s what the plan is seeing.
- More than 40% of claimants actively treating depression are not adhering to their treatment. If members are not properly adhering to treatment, what chance do they have of effectively treating their condition? Is there a role here for external counselling or a case management type of intervention for members continuing down a path of non-adherence that can be done in a way that protects the privacy of members?
- More than 10% of all claimants actively treating depression in this plan appear to be treating treatment-resistant depression (TRD). Wouldn’t it make sense to prioritize case management for these individuals who have very serious cases of major depressive disorder? You can measure the ROI of this kind of initiative by looking at integrated disability data, as well as utilization and spending on co-morbid conditions.
- One out of every eight claimants within depression is a dependent child. Would targeting dependent children through case management and/or assisting in the provision of needed psychotherapy and other appropriate supportive measures not provide tangible ROI to the employer? What is the impact of impaired productivity, increased absenteeism and/or suboptimal health for the employee dealing with a significant mental health challenge with a child? Do we even know if this is an issue?
Some other questions that can be answered with integrated sets of analytics include the following:
- What are the leading indicators of STD and LTD within a given disease state within a specific plan? How can that insight be used proactively, rather than reactively, to positively impact disability and absence experiences? Is there a case to target specific members through case management in order to mitigate disability claims in the first place (in a way that protects privacy of the member)?
- Are members on STD or LTD leaves still adherent to, or still even taking, medications needed to treat primary and/or secondary diagnoses?
- What impact is better management of an underlying condition having on utilization and spending for co-morbid conditions? What impact is that having on the plan?
- What impact has a given initiative had on reducing frequency and/or average duration of a disability claim? How has that benefited the plan members and plan sponsor?
- What is the total burden of illness of a specific disease state on a given plan? Does total burden of illness impact priorities as it relates to health and wellness initiatives?
If plans aren’t leveraging their own data to assess where specific problem issues exist and establish baseline measures, and then measuring the impacts of solutions that are implemented to determine an ROI, how do they expect to address key issues within the plan? Just throwing money blindly into benefits plans and hoping for better outcomes is not likely a sustainable endeavour, nor is it even reality for Canadian plan sponsors that do not have the ability to keep opening up their wallets with no questions asked.
In addition to needed financial plan performance assessment, that same set of integrated data can be used to identify, quantify, prioritize and address key health-related issues affecting the plan. With sophistication around the measurement, and the ability to calculate a return, plans can extract more value for the money they are investing into health benefits.
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