Healthcare and Medical Plan Costs Projected to Rise in 2023

January 18, 2023

Based on data collected from corporate/single employers, public employers/government entities, and multiemployer benefit funds, and then reported by the International Foundation of Employee Benefit Plans (IFEBP), healthcare costs including medical plan costs are expected to increase in 2023.

Money on a white table surrounded by face masks

The IFEBP projected the median increase on medical plans to be 7%. This projected increase is based on the responses from the corporate/single employers, public employers/government entities, and multiemployer benefit funds who were asked to select one primary reason for their cost increases. Here’s the breakdown of those reasons:

  • Catastrophic claims: 17%
  • Medical provider costs: 14%
  • Utilization due to chronic health conditions: 13%
  • Utilization due to delayed preventive/elective care during the pandemic: 12%
  • Specialty/costly prescription drugs: 10%
  • Stop-loss insurance premiums: 6%
  • Utilization due to demographics: 5%
  • Covered lives due to increase in staffing levels: 2%
  • Utilization due to unhealthy lifestyles: 2%
  • Utilization of high-cost medical technology: 1%
  • None of the above: 9%
  • Not sure: 9%

The IFEBP also cited those initiatives that plan sponsors were anticipating would have the greatest impact on costs in 2023. Here’s what they said:

  • Purchasing/provider initiatives such as telemedicine, price transparency tools, centers of excellence, health care navigators/advocates, coalitions, and quality initiatives: 24%
  • Cost-sharing initiatives (e.g., deductibles, coinsure copays, premium contributions): 21%
  • Utilization control initiatives (e.g., prior authorization, case management, disease management, nurse advice lines): 13%
  • Plan design initiatives (e.g., dependent eligibility audits, high-deductible health plans, wellness initiatives, spousal surcharges/carve-outs): 11%
  • Administration/data analysis initiatives (e.g., claims audits, utilization analysis, data warehouse, predictive modeling): 9%
  • None of the above: 12%
  • Not sure: 10%

The breakdown of the respondents was as follows:

  • 70%: corporations/single employers
  • 15%: each of public employers/government entities and multiemployer benefit funds

Respondent breakdown regionally:

  • 31%: Midwest (IA, IL, IN, KS, MI, MN, MO, ND, NE, OH, SD, WI)
  • 22%: South (AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, TX, VA, WV)
  • 20%: Northeast (CT, DC, DE, MA, MD, ME, NH, NJ, NY, PA, RI, VT)
  • 19%: West (AK, AZ, CA, CO, HI, ID, MT, NM, NV, OR, UT, WA, WY)
  • 8%: noted “other”