Medicare Part D Claims Rejections for Nursing Home Residents, 2006 to 2010

The US government relies on private plans to administer the Medicare Part D prescription drug benefit, including the establishment of premiums, pharmacy networks, and formulary design. Within limits, Part D plans (PDPs) have flexibility to shape enrollees’ drug use through levers such as coverage, cost-sharing, and utilization management techniques including prior authorization, step therapy, and quantity limits. The underlying expectation of this approach is that informed consumers will choose the plan that best suits their needs and that price competition across plans will optimize government payments for drugs.¹

Although Part D includes special protections for nursing home residents, the program’s administrative reliance on private plans and the emphasis on consumer choice is similar across institutional and community settings. In addition to nursing home residents having relatively high levels of medication use and physical and cognitive frailty as compared with other Medicare beneficiaries, a key difference in the nursing home setting is that almost two-thirds of long-stay residents are dually eligible for Medicare and Medicaid.² Part D’s implementation shifted medication coverage for duals from Medicaid to Medicare and randomly assigned these individuals to plans with premiums at or below regional benchmark rates set by the Centers for Medicare & Medicaid Services (CMS). Under Part D, nursing homes and the pharmacies with which they contract no longer function under a state’s Medicaid policies for dually eligible residents but instead work across multiple plans, each of which may have different formulary designs and administrative procedures.³ The transition to Part D in the nursing home sector has not always been smooth, with early concerns about coverage adequacy and administrative burdens expressed by physicians, pharmacists, and administrators working in nursing homes.^4,5

Little has been written about the extent of claims rejections or their clinical and administrative implications. One previous study using data on claims in rejected status at the end of 2006 found considerable variation in the reasons for rejection across medications and in the relative rejection rates across PDPs.⁶ However, no published information exists about the overall rate at which Part D claims are rejected; whether these rates differ across plans, drugs, and medication classes; and how these rejection rates and reasons have evolved over time. To address these questions, we examined data on paid and rejected Part D claims submitted by 1 large national long-term care pharmacy (LTCP) over the initial 5 years of Medicare Part D.

METHODS

We obtained data on all paid and rejected Part D claims from Omnicare, Inc (Covington, Kentucky), the nation’s largest long-term care pharmacy, operating in 47 states and serving approximately half of US nursing home residents. A claim is defined as a demand of payment for a particular drug, for a particular individual, on a particular date. Data include Part D claims for nursing home and assisted living residents, although more than 8 in 10 claims are estimated to be for nursing home residents. Data capture all claims filed in the month of March for each of 5 study years (2006-2010) (although we purposely avoided using data from January because of potential transition challenges at the beginning of the year, the choice of March was somewhat arbitrary. March 2010 also was the latest month available when the study began). All observations include the claim date; unique identifiers for residents and facilities; the National Drug Code (NDC) of the product; the plan to which the claim was submitted; and up to 3 reasons for denial of rejected claims. For ease of presentation, we group rejections into 3 broad categories (see eAppendix A, available at www.ajmc.com): 1) Product not covered—capturing instances where the product is not covered; 2) utilization management techniques—capturing instances where coverage applies only after plans approve necessary documentation from pharmacies and clinicians (prior authorization), where less expensive medications must first be tried and failed before more expensive medications are dispensed (step therapy), and instances where plans limit the number (or amount) of drugs covered within a certain time period (quantity limits and refill too soon); and 3) administrative rejections—including instances where claims have non-matched pharmacy or member identification numbers and missing/invalid information about the prescriber, patient, or prescription itself. Importantly, administrative rejections can stem directly from coverage restrictions (eg, missing or inadequate justification for a “dispense as written” prescription order is the second-most prominent code in this category).

We define the total number of claims as the sum of paid claims and the subset of rejected claims that remain unpaid at the end of the month. We are able to flag claims that were rejected multiple times (around 1 in 4 rejected claims) and claims that were rejected and then paid during the 1-month windows of the 5 study years. We count these flagged claims only once. We define the total number of rejections to include all rejected claims, regardless of whether the claim was paid subsequently. If a claim was rejected multiple times for the same reason(s), we count these as 1 rejection. If a claim was rejected multiple times for different reasons, we count each unique set of reasons separately. We are unable to observe the life cycle of claims outside our 1-month windows (eg, if a claim was rejected in March and paid in a subsequent month, we have no record of the later payment). To calculate the rejection rate, we divide the total number of rejections by the total number of submitted claims. We present the rejection rate by year, PDP, and product. We consider generic and brand formulations of the same molecule as distinct products for our analyses; similarly, we treat different formulations of the same molecule (eg, tablets, solutions, and extendedrelease formulations) separately. We exclude 248,026 rejections (7% of all rejections) that were rejected due to problems transmitting claims electronically, such as “host processing error” or “system unavailable.” Based on conversations with the data provider, these rejections typically are resubmitted automatically, either to be resolved or rejected for another reason. We also exclude from our analyses the small number of claims that could not be matched to a drug name (1.6% of rejected claims; 0.1% of paid claims) and that were missing a rejection reason (0.02%).

RESULTS