An important step for employers looking to revitalize their approach is to recalibrate health risk strategies and medical cost strategies. Strategies that reduce population health risks reap long term benefits but are not the most direct way to lower next year's medical costs.
3% of an employer plan's members drive in excess of 56% of the cost of the plan.
For a plan of 10,000 members costing the employer sponsor $50 million: 300 people account for $28 million.
Understanding who is high cost this year, and who will be high cost next year will help shape critical medical cost strategies.
Members with diabetes need solutions for diabetics. Members with cancer need cancer-specific strategies. Likewise for orthopedic surgeries, intensive neonatal care and severe behavioral health conditions. Solutions that can be carved out for the small number of high risk and high cost claimants is becoming increasingly important to a successful plan year.
What's covered and for what clinical indications is integral to many of the high-profile decisions for your plan. What should you cover depends on how rich your plan is, and what your competition covers in the marketplace. Making sure that you and your members are getting the covered services that you've agreed to, requires careful clinical guidance
More employers are relying on expert surveillance of medical and pharmaceutical new technology pipelines. This can help shape next year's medical benefits plan design, and cost forecasts. Along with the Specialty Medicine juggernaut, we are anticipating cost waves in medical devices, cancer treatment, vaccines, surgical procedures and behavioral health modalities that will require careful scrutiny.
Strategies in population health need to reflect employer business goals and operational realities. Understanding an employer's business, marketplace, workforce and employee turnover are the first step in prioritizing goals. This requires a comparison of risk stratification, cost stratification, key conditions prevalence utilization, cost per service against appropriate benchmark populations.