OBJECTIVES:  To assess the accuracy of the Affordable Care Act’s (ACA) Risk Adjustment Program, which will include additional adjustment for prescription drugs for select diseases in the 2018 plan year, in predicting costs for patients with diseases that have significant cost variance due to non-uniform use of specialty therapeutics. METHODS:  This study compares actual patient costs, as reported by 2015 claims data in the Truven Marketscan database, to estimated disease-related costs as predicted by the ACA Risk Adjustment Program’s revised 2018 methodology, which incorporates additional adjustment for prescription drug users. Errors in estimated costs for specialty therapeutic users and non-specialty therapeutic users (including non-drug users) were determined for Rheumatoid Arthritis (RA), Multiple Sclerosis (MS), and Inflammatory Bowel Disease (IBD). Monte Carlo simulation was used to calculate errors in estimated costs for five plan sizes (1250, 3750, 7500, 37500, 100000). RESULTS:  Using the 2018 algorithm, the median error among RA patients with adjustment for prescription drugs is $30,835 and $8,158 for those without adjustment. For IBD, the median error for patients with and without adjustment is $23,880 and $7,587 respectively. Among MS patients taking prescription drugs, the median error is $7,855.24 compared to $13,251.32 for patients without adjustment. At the plan level, these errors translate to an absolute dollar error ranging from $163,429.03 (1,250 covered lives) to $12,212,832.30 (100,000 covered lives) for RA. The average absolute dollar error per plan for IBD and MS range from $60,170.65 to $3,552,171.29 and $23,249.45 to $1,154,468.70 respectively. CONCLUSIONS:  The Risk Adjustment Program’s revised methodology does not take into account differing cost structures for drugs, which may result in the substantial over-estimation of costs for patients taking less expensive therapies. This significant difference in predicted risk could lead to harmful incentives for payers, including limiting access to specialty therapeutics and engaging in adverse selection practices.