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Medicare Part D Claims Rejections for Nursing Home Residents, 2006 to 2010
David G. Stevenson, PhD; Laura M. Keohane, MS; Susan L. Mitchell, MD, MPH; Barbara J. Zarowitz, PharmD, FCCP, BCPS, CGP, FASCP; and Haiden A. Huskamp, PhD
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Medicare Part D Claims Rejections for Nursing Home Residents, 2006 to 2010

David G. Stevenson, PhD; Laura M. Keohane, MS; Susan L. Mitchell, MD, MPH; Barbara J. Zarowitz, PharmD, FCCP, BCPS, CGP, FASCP; and Haiden A. Huskamp, PhD
This study presents data on paid and rejected claims submitted by 1 large long-term care pharmacy over the initial 5 years of Medicare Part D.
Over the initial 5 years of Medicare Part D, nearly 1 in 6 drug claims for beneficiaries living in nursing homes and other long-term care settings was rejected. Although one might have expected the rejection rate to decline over time after the initial transition to the program and as pharmacies and clinicians grew more accustomed to working across private plans, this has not occurred. After an initial decline, the rejection rate has increased slightly each year. At the same time, reasons for denials have evolved considerably. Lack of coverage has become less of a factor in claims rejections than it was initially; increasingly, other formulary tools such as drug utilization review, quantity-related coverage limits, and prior authorization are used to deny claims. Although these results are consistent with broader trends concerning PDP formularies, somewhat more surprising is the persistence of administrative claims rejections throughout the study period, a feature that likely reflects the complexity of working across multiple plans and policies in a given year, as well as changes in coverage policies over time.

Not surprisingly, rejection rates and reasons varied considerably across products. Medications most commonly used by nursing home residents generally have below average denial rates (around 1 in 7 claims), with coverage issues rarely noted. Given the relatively low cost of many of these drugs (9 out of 10 most commonly used drugs are generics), these features are unsurprising. Among drugs with the highest rejection rates, explanations for denials are complex and vary across products, which include generics, brand drugs with generic alternatives, and brand drugs without generic alternatives.

Among the most rejected generics, half of the denials for pantoprazole sodium extended release tablet (a proton pump inhibitor for conditions such as gastroesophageal reflux disease) were due to the product not being covered. The primary reason for rejections of fluticasone propionate nasal spray (for asthma and allergy symptoms) stemmed from claims having missing/invalid information about days-supply, a problem also affecting other solutions and inhalation products. Three-fourths of rejections for potassium chloride solution (for nutritional deficiencies) were due to non-coverage, a feature likely reflecting a CMS ruling that the formulation did not meet Part D coverage requirements and the subsequent shift by PDPs to reimburse only non-liquid formulations of the drug.

Denials for brand name drugs with generic equivalents likely reflect PDPs’ efforts to promote use of cheaper generic alternatives. The high rejection rate for Flomax (tamsulosin) (for symptoms of an enlarged prostate) largely stemmed from claims having missing/invalid “dispense as written” information, an issue that presumably arose following the availability of generic tamsulosin in early 2010. Among the handful of brand drugs without generic equivalents, an example worth highlighting is Procrit (epoetin alfa), an expensive blood modifier used to treat anemia due to chronic renal failure and other select conditions. More than three-fourths of Procrit’s rejections were due to prior authorization issues, something not unexpected given the drug’s high cost and potentially harmful side effects.7

A striking feature of our product-level findings is that 6 out of 20 medications with the highest rejection rates in 2010 are used to treat pain (oxycodone/acetaminophen, oxycodone hydrochloride, morphine sulfate extended release, fentanyl patch, propoxyphene napsylate/acetaminophen, and Lidoderm (lidocaine). With the exception of propoxyphene napsylate/acetaminophen (an opioid combination of questionable effectiveness and safety in older adults8,9) and Lidoderm (an expensive topical anesthetic patch used to treat pain from shingles and other sources of neuropathic pain), denials for pain medications arise primarily from administrative rejections and utilization management techniques. An illustrative example is that nearly 1 in 3 claims was denied for the fentanyl patch in 2010—a rate nearly double its 2006 level; and administrative rejections and utilization management accounted for almost all of these rejections. Although rejection rates for pain medications could reflect their considerable abuse and diversion potential, concerns must be weighed against the need for timely access to effective medications for individuals living with chronic pain.10,11

Rejection rates and reasons also vary considerably across PDPs. In the context of a facility’s residents being enrolled in multiple plans, this variation presents administrative challenges for facility and pharmacy staff and may undermine the predictability of coverage across residents with similar conditions. Although it is difficult to convey a clear, concise story in the context of the PDP rejection rates, plans’ higher administrative rejection rates generally imply higher rejection rates overall. Further context for administrative rejections relates to continuing challenges that providers and pharmacies face in updating residents’ Medicaid eligibility status, delays which can result in enrollment gaps and incorrectly collected copayments.5 Nonetheless, the cross-plan variation in the extent to which these issues lead to rejected claims implies that there may be room for improvement at plans with especially high administrative rejection rates.

It is unclear what the optimal or expected rejection rate should be in Part D generally or in the long-term care setting specifically. Besides administrative errors that must be corrected before payment, plans have legitimate reasons to deny claims; and the optimal rejection rate is not zero. Prior  authorization, for instance, could add valuable safeguards when prescribing is of questionable efficacy or appropriateness (eg, in the historically problematic area of psychotropic drug use among elderly nursing home residents12-14). Similarly, step therapy edits could push clinicians to prescribe less costly medications that are clinically similar or, in the case of brand-to-generic comparisons, equivalent. Nonetheless, use of these strategies creates a tension between the push to lower costs and the importance of ensuring access to needed medications.

The clinical impact of claims rejections on long-term care residents is unclear. We do not have information about beneficiaries’ diagnoses or health outcomes and are unable to assess the potential impact of denials on individuals’ health or on the overall appropriateness of prescribing. Similarly, we do not have information about the absolute or relative administrative burden or costs associated with rejected claims. It is likely that some denials are rectified relatively easily, while others require more coordinated effort. Because of the limited time frame (1 month each year) for which we have data, we are unable to estimate the extent to which individuals switch or discontinue medications because of claims denials (or, conversely, obtain their needed medication in the end). Prescribing behavior also may adjust to PDPs’ formularies and administrative practices (eg, if clinicians reduce prescribing a particular medication because it is difficult to obtain), something we are unable to observe. Important context for these points is that regulations require that nursing homes adhere to residents’ clinical care plans regardless of financial coverage, meaning that clinicians must either work within plans’ extant formulary constraints or leave facilities and/or pharmacies to shoulder the financial cost of medications. Finally, although the same PDPs serve individuals across institutional and community-based settings, our data are from individuals living in long-term care settings and come from a single (albeit very large) LTCP. Thus, generalizing our findings to the Part D program as a whole or even to the entire long-term care sector should be done with caution.

Nonetheless, our results have several implications for policy. Our findings suggest that medication-specific and planwide rejection rates could be useful information for policy makers, beneficiaries, and clinicians. Policy makers could monitor and possibly report rejection rates across plans to identify potential access problems for Medicare beneficiaries, to inform the Part D appeals process, and even to make adjustments to regulatory guidance if necessary. Given uncertainty about the optimal or appropriate rejection rate in Part D, related oversight likely would focus on identifying outliers at the plan, product, or class levels for further investigation. For example, CMS currently requires that plans cover at least 1 formulation of all medications in selected medication classes.15 CMS could consider rejection rates in decisions about whether to incorporate special protections around formulary coverage or the use of utilization management for these or other drugs. Although beneficiaries could use rejection rates in evaluating plans (eg, to compare plans with comparable coverage on drugs of interest), previous research suggests consumers already are overwhelmed by available information and could benefit from having fewer, more targeted data points.16 More specific to the nursing home population, policy makers could consider using rejection rates in decisions about plan assignment of dually eligible residents (eg, not assigning individuals to plans where medication access looks especially problematic) or even about which plans are eligible to serve dually eligible individuals altogether. Similarly, providers and the pharmacies they work with could monitor rejection data in establishing formularies and prescribing practices more generally.

Throughout the brief history of the Medicare Part D program, comparing generosity of coverage across private PDPs has been a key point of interest for consumers, policy makers, and researchers.17 Claims rejections have been an unobserved feature of these comparisons to date. Our research shows that examining rejection rates across plans and medications can provide important supplemental information to assess plans’ generosity of coverage and to identify potential areas of concern. Going forward, information about claims rejections should be more systematically monitored and analyzed for oversight purposes, not only to identify administrative challenges that arise in the Part D marketplace but also to ensure the program is working well for Medicare beneficiaries as a whole.

Author Affiliations: From Department of Health Care Policy (DGS, HAH), Harvard Medical School, Boston, MA: Department of Health Services, Policy, and Practice (LK), Alpert Medical School of Brown University, Providence, RI; Hebrew SeniorLife (SLM), Institute for Aging Research, Boston, MA; Omnicare, Inc (BJZ), Livonia, MI.

Funding Source: This work was supported by a grant from the National Institute on Aging (NIA), grant number R01 AG034085. Dr Stevenson also was supported by an NIA Career Development Award (K01 AG038481). Dr Huskamp also was supported by a Robert Wood Johnson Foundation Investigator Award in Health Policy Research. Dr Mitchell was supported by NIA grant number K24AG033640.

Author Disclosures: Dr Zarowitz reports receiving consultancies from the Health Technology Assessment Council and sanofi-aventis, as well as employment and stock ownership in Omnicare, Inc. The other authors (DGS, LK, SLM, HAH) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (DGS, LK, SLM, BJZ, HAH); acquisition of data (DGS, LK, BJZ, HAH); analysis and interpretation of data (DGS. LK, SLM, HAH); drafting of the manuscript (DGS, LK, SLM); critical revision of the manuscript for important intellectual content (DGS. LK, SLM, BJZ, HAH); statistical analysis (DGS, LK, HAH); provision of study materials or patients (BJZ); obtaining funding (DGS, HAH); administrative, technical, or logistic support (DGS, LK, BJZ, HAH); and supervision (DGS, HAH).

Address correspondence to: David G. Stevenson, PhD, Associate Professor, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115. E-mail:
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17. Gruber J. Choosing a Medicare Part D Plan: Are Medicare Beneficiaries Choosing Low-Cost Plans? Washington, DC: Kaiser Family Foundation; March 2009.
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