Reward the Good Soldier: A Dynamic Approach to Consumer Cost-Sharing for Prescription Drugs
Access to, and levels of spending on, prescription drugs has become an important public policy issue. Given the significant individual and population health gains that result from the appropriate use of prescription drugs, as well as the fiscal concerns pertaining to the escalation of health care expenditures, the development and implementation of patient-centered solutions that allow access to medications at an affordable cost are of critical importance.
One common strategy that healthcare purchasers employ to control pharmaceutical spending is to increase consumer cost-sharing. This trend—seen for nearly all drugs across all formulary tiers—has proceeded regardless of the clinical benefit provided by a specific drug, with cost-sharing increasing as rapidly for high-value drugs (eg, included in evidence-based guidelines) as for drugs deemed unnecessary or potentially harmful.1 As consumers are asked to pay a greater proportion of their medication expenses, cost-related nonadherence is an important and growing problem.
A robust body of peerreviewed evidence demonstrates that cost-related non-adherence exists for high-value medical services across the entire episode of clinical care, including clinician visits, diagnostic tests, and especially prescription medications.2,3,4 Nearly 1 in 5 insured adults report going without needed care due to cost.5 Sub-optimal use of evidence-based services results in poor patient-centered outcomes and, in some scenarios, higher expenditures for both the patient and the third-party payer.
An important aim of a multi-tier prescription drug formulary—largely driven by fiscal constraints—is to encourage patients to use effective, lower-cost medications. Such approaches to pharmaceutical management (eg, generic substitution and prior authorization) have been utilized for decades with varying effects on spending. A recommendation that patients are initially prescribed lower cost medication(s) is a reasonable population health strategy, given that a first-line medication will often be effective and, given the relative lower cost, will be considered high-value for that patient and for the payer. However, it is not uncommon that certain patients cannot be prescribed (eg, due to drug allergy or drug-drug interaction), or do not respond to, first-line, lower-cost medications. In these frequent clinical scenarios, an individual will require a substitute or an additional drug to achieve patient-centered clinical outcomes. In these situations, the first-line drug is no longer high-value and a clinically indicated, higher-cost alternative becomes a higher value choice. Therefore, the level of consumer cost-sharing for higher cost medication should be aligned with the clinical value—not solely the price—when lower-cost alternatives do not produce the desired patient-centered outcomes.
The concept of aligning patients’ out-of-pocket costs—such as copayments, co-insurance, and deductibles—with the value of healthcare services is the basic premise of Value-Based Insurance Design (VBID).6 This approach to designing benefit plans recognizes that specific health services have different levels of value. Thus, VBID programs are designed with the tenets of "clinical nuance" in mind, which recognize that 1) medical services differ in the amount of health produced, and 2) the clinical benefit derived from a specific service depends on the consumer using it, as well as when, where, and by whom the service is provided. VBID takes into account that the same pharmaceutical agent can be both high value and low value depending on patient demographics, the disease treated, or the stage of a specific clinical condition.
The ongoing transformation to "precision" preventive care, diagnostics, and therapies provides a clear impetus to include clinical nuance in setting prescription drug cost-sharing levels. To keep pace with the rapid movement toward targeted clinical interventions, the existing "static" drug cost-sharing structure should evolve to a more "dynamic" configuration. Such a transition to a more nuanced approach is supported by several factors, including: 1) an increasing number of evidence-based protocols recommending specific genetic markers, companion diagnostics, or patient-specific factors; and 2) the natural history of many chronic conditions often necessitates the use of multiple evidence-based therapies to achieve desired clinical outcomes. Clinical scenarios often require a patient to take multiple drugs simultaneously and/or cycle through multiple drugs to effectively treat a specific condition.