Cost Transparency Solutions: The Rise of Real-Time Prescription Benefit Tools
Real-time prescription benefit (RTPB) is a relatively new technology that helps provide transparency around patient-costs in the native order-entry module within the electronic health record (EHR). Real-time benefit tools (also known as Real-Time Prescription Benefit and Real-Time Benefit Check) are transforming the traditional prescribing workflow by proactively providing patient-specific pharmacy benefit coverage information at the point-of-prescribing. This type of information enables providers to view patient out-of-pocket costs, payer recommended alternatives, and coverage restriction information (e.g., prior authorizations, quantity limits) before the prescription is sent to the pharmacy. Transparency of this information also supports cost-conversations with patients and reduces coverage surprises at the pharmacy. RxRevu often describes this type of technology as Prescription Decision Support.
While there are many prescriber and patient benefits with RTPB, this new technology is not without its fallacies.
Real-Time Benefit Challenges
Best practice in healthcare is to provide patient-centered care for every patient, every time. However, the variation in Real-Time Prescription Benefit (RTPB) coverage networks, EHR prescribing fields, and unstandardized data streams increase the likelihood drug pricing will not be seen for every patient and every drug prescribed.
Comprehensive Real-Time Benefit Vendor Networks
While the accuracy of formulary and benefit information is greatly improved with RTPB by providing patient-specific coverage information instead of plan or group level data, no vendor in this space currently has a comprehensive coverage network that includes all payers. This means health systems implementing RTPB need to assess which vendors provide the relevant coverage information for patients seen by providers in their network. In most cases, a decision may be made to include implementing more than one real-time benefit vendor. RxRevu for example, has developed one of the largest payer/PBM networks in the industry, allowing coverage information to be shown for over 150 million patients across the country. However, we do not provide 100% coverage in all markets. We are continuing to pursue payers/PBMs that would increase our coverage footprint, and are actively receiving feedback from health systems as to which payers/PBMs to partner with.
Another challenge is that RTPB tools typically provide coverage information for commercially insured patients. This has resulted in a large gap around providing price transparency for patients with Medicare and Medicaid plans. Legislation is currently in place to narrow this gap with the Centers for Medicare and Medicaid Services requiring Medicare Part D sponsors to implement RTPB capable of integrating with at least one prescriber’s electronic prescribing system or EHR by January 1, 2021. More information about this rule is discussed in our recent blog post: What is a Real-Time Benefit Tool and What Does CMS’s New RTBT Final Rule Mean for the Healthcare Industry?
Variation in Computerized Physician Order Entry (CPOE) – Quantity Units
The EHR has undeniable advantages in structuring documentation and improving the safety and organization of patient care, including prescription ordering.3 Still, with the integration of RTPB tools in the EHR, several challenges have been encountered including a lack of uniformity in units allowed in the ‘Dispense Quantity’ field and unmaintained medication records at the national drug code (NDC) level.
When the claims process is moved forward to the point-of-prescribing, some providers may not be aware of the elements necessary for accurate prescription billing. The National Council for Prescription Drug Programs (NCPDP) has billing unit standards, with three distinct product units (i.e., each, mL, and grams) assigned to a medication.4 The EHR however, supports prescription quantity units outside of these standards, which can result in invalid quantity submissions or inaccurate price estimates. For example, a provider may e-prescribe 1 bottle of ofloxacin 0.3% eye drops, which would result in an invalid quantity error and the absence of pricing in the real-time benefit workflow, since the correct dispense quantity for the prescription would be 5 mL or 10 mL. In a traditional pharmacy claims process outside of RTPB, translation to the correct billing unit would be addressed by pharmacy staff.
RxRevu’s real-time benefit tool, SwiftRx Direct, provides solutioning for this problem by translating prescribed quantities to the appropriate billing unit to avoid invalid quantity errors. This quantity unit of measure conversion not only reduces errors related to incorrect billing units, but also allows providers to continue ordering medications in quantity units they are familiar with.
Product Mismatches and Inaccurate Product Descriptions
All commercially distributed drugs are identified using a three-segment NDC, which allows for identification at the product level. The first segment represents the labeler code (i.e, manufacturer/labeler), the second segment represents the product code (i.e., medication name and strength), and the last segment represents the package code (e.g., bottle).5,6 In RTPB tools, a representative NDC is utilized to reduce the incidence of product mismatches.
In order to solve this issue, the SwiftRx Direct real-time benefit tool provides mapping to a reference NDC to ensure the appropriate translation between the EHR and PBM occurs for accurate pricing information to be presented. This helps reduce the variation seen in the descriptions of drug products as well as reduce the frequency of inactive, repackaged, and unit-dose NDCs that may be sent in the transaction.
Alternative Recommendations: Who Really Benefits?
The role of pharmacy benefit managers (PBMs) and the continued increase in drug costs has been a long debated topic. As the middle-men in the distribution chain for prescription drugs, PBMs have influential roles in determining drug costs for insurers, shaping access to medications through formulary and benefit design, and determining how much pharmacies are paid. A lack of transparency around rebates between PBMs and drug manufacturers as well as payment between PBMs and pharmacies understandably creates skepticism that the surfaced formulary alternatives in RTPB tools truly benefit the patient.
In order to garner the trust of patients and providers, SwiftRx Direct is a real-time data service that surfaces therapy alternatives whenever available and those that are determined by the payer coverage data. Customers of the SwiftRx Direct real-time benefit tool have the ability to configure how many alternatives, if any, are seen in the user-interface as well as alternative sorting order by cost (e.g., lowest cost first), cost thresholds of when an alternative appears (e.g, patient savings compared with the original ordered medication is “$x”), and the ability to suppress alternatives by pharmacy location (e.g., mail order). The ability to customize these settings is contingent upon what EHR vendor a health system may be using, but allows for improved provider utilization of RTPB.
The Cost of Non-Transparent Patient Pricing
Regardless of the attitudes toward payer-PBM partnerships, high drug costs continue to be one of the most well documented factors contributing to non-adherence, medication underuse, prescription abandonment, and higher hospital readmission rates.2, 7-9 While regulatory and legislative efforts continue to be made around rising drug costs, RTPB solutions provide more transparency around patient cost. Further, health systems have the ability to customize various attributes in the user-interface (e.g. alternative surfacing), making the technology more user friendly and effective in the prescribing workflow.
Even though RTPB tools are not always a perfect solution, they are challenging the traditional prescription life cycle, creating more transparency around patient-specific formulary and benefit information, promoting fiscally responsible prescribing practices, and improving patient access to affordable drug therapies. We’ve outlined a few of the considerations that a health system might think about before deploying a RTPB tool, but our hope is that RTPB will soon be a best practice in health care, providing patient-centered care with drug pricing for every patient, every time.
Written by: Megan Holsopple, PharmD, BCPS | Clinical Pharmacy Coordinator, Innovation and Research
- Schumock GT, Stubbings J, Hoffman JM et al. National trends in prescription drug expenditures and projects for 2019. Amer J Syst Pharm. 2019;15(8):560-565. https://academic.oup.com/ajhp/article/76/15/1105/5519176
- Miranda A, Serag-Bolos E, Cooper JB. Cost-related medication underuse: strategies to improve medication adherence at care transitions. Amer J Syst Pharm. 2019;15(8):560-565. https://academic.oup.com/ajhp/article-abstract/76/8/560/5427354?redirectedFrom=fulltext
- Connelly TP and Korvek SJ. Computer Provider Order Entry (CPOE) [Updated 2019 Jul 29]. In: StatPearls [Internet]. Treasure Island (FL): StatsPearls Publishing; 2020 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK470273/
- National Council for Prescription Drug Programs. NCPDP Billing Unit Standard Fact Sheet. https://www.ncpdp.org/NCPDP/media/pdf/BUS_fact_sheet.pdf. Updated April 2018. Accessed February 22, 2020.
- U.S. Food and Drug Administration. National Drug Code Directory. https://www.fda.gov/drugs/drug-approvals-and-databases/national-drug-code-directory. Updated November 2019. Accessed February 22, 2020.
- National Council for Prescription Drug Programs. SCRIPT Implementation Recommendations.https://www.ncpdp.org/NCPDP/media/pdf/SCRIPT-Implementation-Recommendations.pdf. Updated November 2019. Accessed February 22, 2020.
- Frances Yap A, Thirumoorthy T, Heng Kwan Y. Systematic review of the barriers affecting medication adherence in older adults. Geriatr Gerontol Int. 2016;16(10):1093-1101. https://pubmed.ncbi.nlm.nih.gov/26482548-systematic-review-of-the-barriers-affecting-medication-adherence-in-older-adults/
- Krass, Schieback P, Dhippayom. Adherence to diabetes medication: a systematic review. Diabet Med. 2015;32(6):725-37. https://pubmed.ncbi.nlm.nih.gov/25440507-adherence-to-diabetes-medication-a-systematic-review/
- Dunbar-Jacob J and Rohay JM. Predictors of medication adherence: factor or artifact. J Behav Med. 2016; 39(6):957-968. https://pubmed.ncbi.nlm.nih.gov/27306683-predictors-of-medication-adherence-fact-or-artifact/