The debate over prior authorization is particularly important in oncology, where rising drug costs and daily advances in research and emerging therapies make it difficult for health plans to ensure their members are getting the right treatment at the right time.
Pros and Cons of Various Prior Authorization Approaches for Oncology
Is Prior Authorization the Best Approach for Oncology? explores the following:
- An overview of the challenges that are unique to oncology prior authorization, which impact health plans, providers and patients
- Approaches to prior authorization that address the unique needs of all stakeholders and provide an opportunity to better manage costs, provider abrasion and patient outcomes
Content Summary
Introduction
Prior Authorization’s Impact on Oncology
Traditional Prior Authorization
e-Prior Authorization
e-Prior Authorization with Data Science and Analytics
Summary of Results
Introduction
Prior authorization (PA) is a process to obtain health plan approval for the provision of specific healthcare services to a patient covered by the health plan. Health plans have used PA to manage the utilization of healthcare resources, improve the quality of care and control healthcare spending. The goal of PA in oncology drug utilization is to optimize patient outcomes by ensuring that they receive the most appropriate medication while reducing waste, error and unnecessary prescription drug use and cost.
The debate over PA is particularly important in oncology, where the wrong treatment approach may mean the difference between life and death. With a myriad of treatment approaches, breakthrough therapies coming to market at a brisk pace, and the high toxicity of some cancer drugs, getting it right is critical. In the United States, cancer is one of the costliest conditions to treat. With a larger proportion of costs for health services shifting to employees and consumers through higher co-pays, larger deductibles, and narrow physician networks, it is vital that health plans, in partnership with treating providers, ensure that patients receive the safest, most accurate care at the best possible price and outcome.
The purpose of this article is to provide an understanding of the prior authorization challenges that health plans, providers, and patients face in oncology; and offer insights into approaches that may offer better options to these stakeholders.
Prior Authorization’s Impact on Oncology
PA was devised to help insurers control costs by requiring providers to obtain approvals before performing services. This process is not without controversy. PA, as commonly used today, faces opposition from some providers and their lobbying groups, as they believe it slows down and complicates their abilities to care for their patients. Most recently, the American Medical Association (AMA) called it “overused, costly, inefficient, opaque and responsible for patient care delays.”
While these objections may have merit in some situations, different medical conditions require different levels of prior authorization. For example, treatment for a patient’s cancer diagnosis is much more complex than treatment for a torn rotator cuff. Therefore, prior authorization cannot be viewed as a one size fits all approach, nor would removing it from the care delivery process be a viable solution.
Without question, oncology presents unique challenges for prior authorization to be effective. One such example is access to current, evidence-based data and research to make the correct treatment recommendation. As cancer care continues to evolve, the growing number of treatment options, combinations, and additional lines of therapy significantly increases the decision-making complexity for oncologists. It has been estimated that oncologists would need 29 hours a day1 to keep up with the research and findings that enter the market daily.
The common sentiment for opponents of PA is that it increases both administrative time and delays in treatment; however, on the flip side, there is the cost of “getting it wrong.” When treatments are incorrectly or improperly prescribed, the patient’s condition won’t improve, which can ultimately cost health plans and patients more money and lead to worse outcomes. Interestingly, physicians may not be aware of the severity of the problem, as while a majority of surveyed physicians (60%) in a National Coalition on Health Care/Best Doctors study estimated the cancer misdiagnosis rate to be 10% or less, the BMJ Quality and Safety journal reported the actual misdiagnosis rate to be 28%.
The following is a common example where a lack of information or oversight can lead to an expensive, ineffective, and potentially dangerous treatment recommendation.
Bevacizumab is a drug used to treat many different types of cancer, including breast cancer. Even though bevacizumab has been available for many years, providers continue to use this agent improperly. Almost a decade ago, the FDA indication for bevacizumab in combination with paclitaxel in the first-line management of HER2 (Human Epidermal Growth Factor Receptor-2)-negative, metastatic breast cancer was withdrawn due to the risk of life-threatening side effects without any proof of benefit. Multiple options exist for the first-line management of metastatic HER2-negative breast cancer that has far more efficacy than the bevacizumab-based regimen, yet prior authorization requests continue to be received for this regimen with extreme regularity.
Realistically, there is no going back to a system without at least some components for PA. In oncology, this is particularly important, for the complexity of a cancer diagnosis necessitates that some form of PA to be adhered to. But which form?
We will now examine the pros and cons of various PA approaches for oncology:
- Traditional PA
- e-Prior Authorization
- e-Prior Authorization with Data Science and Analytics
Traditional Prior Authorization
Traditional PA is typically a manual process, where providers (or their staff) submit treatment requests by phone and/or fax. According to the AMA, the top reasons doctors oppose PA include delayed patient treatment; the fact that a practitioner’s medical judgment is questioned; and that the process is both manual and time-consuming for both providers and health plans, requiring resources that could otherwise be spent on clinical care.
From an oncology perspective, traditional PA is also more likely to have gaps when it comes to ensuring that patients receive the right treatment. For example, in 2018, almost five novel drugs per month were approved by the FDA’s Center for Drug Evaluation and Research, a new record. Additionally, a huge body of research is published yearly, revealing new insights into existing drugs. According to the National Institute for Health, in 2017 more than 800,000 medical source citations were added to MEDLINE®. As such, the amount of critical research and information coming out is outpacing oncologists’ abilities to keep up with it on their own, making the “review” in the PA process that much more critical.
If a health plan has entrusted the review process to physicians who are not oncologists, the likelihood increases that they will not be familiar with all current evidence-based guidelines, effective off-label uses of medications or understand the longer-term savings of a treatment that may be more costly initially but offers longer-term savings and a better outcome for the patient.
The manual, time-consuming nature of traditional PA, coupled with its lack of consistency and quality in the review process, makes it a risky approach to adopt for oncology.
e-Prior Authorization
The e-prior authorization (e-PA) approach was devised as an electronic means of shortening the approval time in the care delivery process. According to the AMA, the use of e-PA transactions saves patients, providers, and health plans significant time and resources.
The AMA’s stated principles say that e-PA “promotes safe, timely, and affordable access to evidence-based care for patients enhances efficiency, and reduces administrative burdens.” The AMA also recommends that healthcare providers, health systems, health plans, and pharmacy benefit managers accelerate the use of national standard transactions for e-PA.
There is strong momentum toward e-PA adoption. According to the AMA, 96% of health plans said they were committed to an e-PA solution, and some 79% of EHR vendors said they were implementing e-PA. The biggest impediment may come from the stakeholder most opposed to the current PA system: physicians. The provider adoption of this technology is very slow. Only 51% of surveyed physicians were even aware of e-PA technology.
e-PA for oncology faces additional challenges. For example, while expediting decisions, e-PA does not impact the quality of the decision. In this area, e-PA has the same exposure as traditional PA, whereby if an oncologist sends a proposed treatment electronically, the decision is only as good as the physician approving or declining the request at the other end. Many times, the prior authorization request is not reviewed by an oncologist, as this requires the health plan to make a large investment in retaining full-time oncology expertise, which can be cost-prohibitive. Unfortunately, this means that physicians with limited or no oncology experience often make these critical treatment decisions.
Further, there is a lack of transparency of PA requirements in EHRs for physicians. Only 21% of physicians surveyed by the AMA said their EHR system offers e-PAs for prescriptions. This is important since physicians are typically behind the technology curve, with responders reporting phone and fax as the most commonly used ways they currently complete PAs.
It’s not that e-PA is the wrong approach for oncology; it’s just that it may not go far enough. A problem that consistently presents itself in e-PA is a lack of comprehensiveness concerning a patient’s medical information, which is needed to ensure an evidence-based treatment decision. The lack of standards surrounding attachments of medical documents exacerbates the problem. In an era where consumers can easily send money to each other with a simple smartphone application, it is deflating to think that today’s smartphone equivalent for medical information exchange is a fax machine. Yet, even if authorization comes faster with e-PA, there is always the concern that the decision is based solely on the cost of treatment.
e-Prior Authorization with Data Science and Analytics
In the early days of the 20th century, department store magnate John Wanamaker famously said, “I know that half of my advertising doesn’t work. The problem is that I don’t know which half.” Effective use of data science holds great promise if health plans can collect enough data about medical treatments and use that data effectively. The use of real-world data in the prior authorization review and decision-making process should be able to predict more accurately, which treatments will be effective for a specific patient, and which treatments won’t.
For example, a long-held belief among providers was that tamoxifen was roughly 80% effective for breast cancer patients. But now, through the use of real-world data and analytics, we know much more: we know that it’s 100% effective in 70% to 80% of patients2 and ineffective in the rest. Therefore, if e-PA is consistently combined with data science, health plans and providers should be able to more quickly determine the right therapy, sequenced at the right time with predictable outcomes.
At the heart of the e-PA with data science and analytics, the approach is the marriage of data, analytics, and clinical expertise, which addresses the two biggest challenges for prior authorization in oncology: speed and evidence. This approach requires that patient cases reviewed by health plans are handled only by board-certified oncologists and oncology pharmacists to ensure that patients receive the “right” care, not just “quick” care.
While e-PA with data science and analytics demands health plans to make a larger investment in clinical expertise, the approach will provide the same fast turnaround time benefits of e-PA, while simultaneously improving the quality of patient treatment recommendations, which is especially important for cases with a complex or rare diagnosis. In this scenario, oncologist-to-oncologist collaboration is key so that that treatment recommendations can be optimized to the individual patient and decisions involving off-label uses or novel, more costly therapies are handled properly.
One of the reasons for the effectiveness of e-PA with data science and analytics is that it focuses on treatments with better outcomes. Consider this example of patients being prescribed therapies that were not in their best interest.
In 2012, the American Society of Clinical Oncology (ASCO) published it’s Choosing Wisely initiatives, which are designed to promote conversations between physicians and patients to choose care that is supported by evidence, not duplicative of other tests or procedures already received, truly necessary, and are free from harm. As one of its first five recommendations, ASCO stated, “Don’t use white cell stimulating factors for primary prevention of febrile neutropenia for patients with less than 20% risk for this complication.” While white blood cell growth factors like pegfilgrastim are generally considered safe, all drugs have potential adverse reactions. Pegfilgrastim may cause splenomegaly, splenic rupture, severe bone pain, death, and its use in some populations has been associated with an increased risk of acute myeloid leukemia.
Despite the clear Choosing Wisely recommendations, between August 1, 2018, and Aug 1, 2019, Oncology Analytics received 2,340 requests for pegfilgrastim as primary prophylaxis for patients receiving chemotherapy associated with a low risk of febrile neutropenia (FN), a life-threatening complication of cancer chemotherapy.
Out of a pool of 3,301physicians, 870 (26%) requested pegfilgrastim outside of the guidelines, with no support even after taking FN-risk and patient-specific factors into consideration. This is but one example of off-guideline therapy seen and corrected by an effective e-PA with analytics approach.
Summary of Results
Insights into cancer treatment are so fast-moving, complex and overwhelming in the volume that prior authorization approaches such as traditional PA or even e-PA cannot scale to address individual patient needs. There are simply too many cancer-related discoveries and updates for providers and payers to monitor without assistance. According to a presentation at the 2019 Asembia Specialty Pharmacy Summit, there are more than 700 late-stage oncology drugs in development3. While providers want to get their treatments right, they don’t always have access to needed resources or are unable to assimilate all available information. Beyond this, providers may see patients with a range of cancers, making it even more difficult to track the latest developments in specific ones. As such, even with the best of intentions, patients don’t always get the best care.
While traditional PA offers some limited benefits to healthcare stakeholders, the burden to the health system is clear. An e-PA approach addresses the time to treatment for all patients, but, doesn’t improve treatment decisions or all cost issues. But, when e-PA is combined with the right data science and analytics approach, it delivers the same time advantages of e-PA with additional savings and better patient outcomes because the integrity of the process ensures that an evidence-based treatment recommendation was employed.
Source: Oncology Analytics
