The Value of Health Care Analytics in Reducing

Employer Health Care Expenditure

Benefits consultants of today are responsible for ensuring their clients have innovative means of reducing risk or costs related to the employer’s health care expense.  There is a wealth of information existing within an employer’s historical and present-day health expense data.  This data may help guide future risk management strategies.

To reap the true benefits of this data, the data analysis needs to result in actionable steps. Many times, expertise in various disciplines (i.e., epidemiology, wellness, insurance, etc.) are necessary to identify these actionable steps.

The contribution of the benefits consultant may be enhanced through an understanding of risk for health care expense with solutions that can reduce this risk.  To have a clear understanding of health expense data, two questions guide the potential solutions: “What are the cost or risk drivers?” and then” What can be done about it to reduce cost or risk?”


An example of annual health expense data for 2015 (Table 1) is shown below in order to better demonstrate the expense to the employer and how it relates to the enrolled population.  The annual health expenditure is stratified by deciles.  Approximately 60% of the enrolled population had an annual health expenditure less than $1,000 which accounted for approximately 4% of the total annual health expenditure for the employer.  On the other end of the spectrum, only about 1% of the total enrolled population accounted for annual expenditure of greater than or equal to $50,000.  This portion of the population was responsible for approximately 34% of the total annual health expenditure for the employer.  Most of the covered population (approximately 80%) had an annual health expenditure of less than $4,000.


An obvious question follows from this data analysis on cost, what diseases are the main contributors for the high cost individuals.  Based on a 2018 Milken Institute report, hypertension had the highest total health cost in millions of US dollars (direct + indirect) of $1,042,923 in 2016.1 This same publication found that adult diabetes was the second highest total health cost driver ($526,574) and chronic back pain came in as the third highest total health cost driver ($440,315).  The disease prevalence (how many individuals have the disease) in 2016 from this same report does not completely map with the health cost driver information just indicated.  Dyslipidemia has the highest prevalence, followed be hypertension then osteoarthritis.

Many times, an individual may have more than one condition contributes to increased health expenditure.  Using the same population as Table 1, Table 2 provides a breakdown of the average number of comorbidities per person by each annual expenditure decile.  As expected, the population having an annual health expenditure of less than $1,000 had no comorbidities or at most one comorbidity equating to less than half average number of comorbidities per person.  The highest annual health expenditure group (>=$50,000) had approximately two comorbidities per person.  Our data demonstrates a positive relationship between number of comorbidities and annual health expenditure (i.e. as the number of comorbidities increase, the annual health expenditure also increases).  Diseases like diabetes are more likely to be prevalent with others chronic diseases such as hypertension, CHF and dyslipidemia. 2 When a patient has at least one comorbid condition then treatment needs to address all the conditions which results in increased costs as demonstrated by our data in Table 2.


Treating patients with chronic conditions and comorbidities could help reduce sequelae, thereby reducing future health expenses. The capability of an employer to identify these individuals at risk for potential disease sequelae and then direct them to treatment may mitigate future health expense (direct and indirect costs).  Claims analytics for both medical and pharmacy health expense data could serve as a tool to identify these individuals with chronic diseases and provide the necessary assistance to prevent any complications due to their existing disease.  Assistance can range from medication adherence programs to behavior modification programs for nutrition, weight or tobacco cessation. As our results have shown, a small segment of the eligible population was responsible for more than a quarter of the highest decile in annual health expenditure.  On the other hand, for those individuals without chronic disease, the goal is to prevent disease from occurring. The scientific evidence is quite consistent in their findings that sedentary behavior and physical inactivity increases the risk of many chronic diseases.3 Early intervention with these individuals through behavior modification and potential medication use can reduce the likelihood of chronic disease development.

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In order to prevent disease or adequately manage existing diseases, evidence-based rules (e.g. NCQA HEDIS measures, US Preventive Task Force guidelines, etc.) have been developed that serve as a standard of care for these chronic conditions.  These evidence-based rules integrate clinical expertise with collection of systematic clinical evidence.  They can also serve as a road map for appropriate chronic disease treatment and management.  Using evidence-based rules in conjunction with data from claims analytics provides a foundation for actionable items by the employer to reduce health risk for their employees and potential cost-savings for the company.

Finding a wellness company that can effectively partner with an employer to identify their unique population health management issues and implement a wellness program that keeps healthy employees on track while directing high cost individuals to more cost-effective means of care is key.  Look for a company that has proven outcomes for similar clients and who knows how to mine health care claims data to create the best roadmap specific for your population to drive results.  Finally, it is critical that wellness companies today have an extensive ecosystem of integrated partners that can deliver custom tailored solutions to individual members based on their individual chronic conditions and specific needs.

Article by Orthus Health, Rethinking Traditional Wellness


  1. Water H, Graf M.  The Cost of Chronic Disease in the U.S. Executive Summary. Milken Institute. May 2018
  2. Pantalone KMHobbs TMWells BJKong SXKattan MWBouchard JYu CSakurada BMilinovich AWeng WBauman JMZimmerman RS. Clinical characteristics, complications, comorbidities and treatment patterns among patients with type 2 diabetes mellitus in a large integrated health system. BMJ Open Diabetes Research and Care 2015;
  3. Ozemek CLavie CJRognmo Ø. Global physical activity levels – Need for intervention. Prog Cardiovasc Dis. 2019 Mar – Apr;62(2):102-107

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