Executive Summary
Study Overview
AISmartBids by One & Done is an smart Medicare optimization platform that identifies significant inefficiencies in current Medicare plan enrollment. Based on a large-scale simulation of over 1 million realistic enrollee scenarios using data aligned with Centers for Medicare & Medicaid Services (CMS), the platform found that most seniors are enrolled in suboptimal plans, costing them an average of $4,300 annually.
The analysis shows that 77% of enrollees could save over $1,000 per year, while 95% of standalone Prescription Drug Plan (PDP) users would benefit financially and have better coverage by switching to Medicare Advantage Prescription Drug (MAPD) plans.
If applied nationally, optimized plan matching could generate up to $137 billion in annual out-of-pocket beneficiary savings across Medicare Advantage and Part D.
The study highlights a systemic issue: broker-driven plan recommendations are often influenced by commission structures, leading to biased guidance that may not prioritize the consumer's best financial or healthcare outcomes. This problem is intensifying as insurers reduce commissions on more cost-effective plans.
AISmartBids by One & Done addresses this gap by removing sales incentives and delivering unbiased, data-driven recommendations. The platform evaluates plans based on each enrollee's actual and projected healthcare usage, presenting a comprehensive “all-in” cost view, which includes premiums, deductibles, co-pays, and ancillary benefits like dental, vision, and hearing.
Additionally, the platform provides ongoing value through automatic annual re-shopping, ensuring users remain in the most cost-effective and appropriate plan as market conditions evolve.
Methodology Summary
The Medicare test scenario generation methodology models realistic healthcare and insurance situations for 1,170 synthetic users, each assigned 100 unique scenarios—yielding a total of 1,170,000 simulations. Income levels start at a minimum of $10,000, with a low-income bias applied to specific user types (e.g., all D-SNP users and 25% of PDP-only users have incomes below the 2025 Federal Poverty Level threshold of $21,150). Medicare Part A premiums are set to $0 for over 99% of users, while Part B and Part D premiums are determined based on income brackets published by the Centers for Medicare & Medicaid Services (CMS) and adjusted gross income averages from IRS data.
Prescription drug needs are assigned based on usage tiers (low, medium, high) and are randomly selected from a list of 24 of the most common medications for older adults. Medical usage profiles reflect a range of realistic healthcare interactions, including hospitalizations and outpatient care.
Cost estimates for services and premiums incorporate both fixed and randomized components to mirror real-world variation. Scenario logic also introduces weighted preferences for Special Needs Plans (SNP, ~20%), standalone Part D (PDP-only, ~30%), and out-of-network coverage (~20%). These inputs, combined with randomized variation and statistical weighting, ensure a diverse and representative dataset that reflects realistic user behavior and cost outcomes.
The sections below detail the methodology, input assumptions, weighting strategies, and data sources used in this study.