A new study analyzing prior authorization rejections and subsequent actions reveals a burgeoning access to care issue for patients with prescriptions for brand-name drugs.
The study, published in JAMA Health Forum, analyzed nearly 206,000 medication dispensations rejected due to prior authorization (PA), representing 3% of total branded drug transactions.
Of prescriptions initially rejected, only 11% were resolved and approved on the same day as the patient's first attempt to fill the prescription. For the rest, the study found that 44% were approved after a median of six days and 45% were eventually denied.
"This empirical evidence demonstrated the frequent treatment delays and denials caused by PA, adding to a growing body of literature on the impact of PA on curbing treatment access," the study's authors wrote.
The results indicate that most patients who face PAs for their prescriptions experience friction at the pharmacy, especially female patients and those with multiple disease conditions, who the study found have lower ultimate approval rates.
The study also showed that Medicaid patients had higher same-day adjudication rates but lower approval rates than those in Medicare and commercial plans. Clinicians affiliated with corporate entities also experienced higher approval rates.
Breaking down PA results
PAs led to frequent treatment delays and denials. However, the study identified characteristics associated with longer wait times and lower approval rates.
First, prescription fill transactions with multiple rounds of PA reviews were the most delayed. The study's authors explained that this claim adjudication complexity contributed to decision delays, although these cases may have reflected complex treatment decisions.
Still, payers could consider streamlining the review process to expedite it, given that these claims tend to experience the longest delays, they said.
Additionally, the study found that additional rejection reasons and refills were associated with higher approval rates despite longer processing times.
These cases with a high probability of eventual approval can inform a payer's PA strategy. For example, reducing prior authorization requirements in these cases can significantly improve patients' access to treatment while also relieving the administrative and financial burden on payers.
Clinicians should also learn from PA results to streamline the process. For example, the study linked lower final approval rates to prescriptions with longer days of supply. There were also varying processing times and approval rates for different molecules under the same drug class.
Notably, the study found that some GLP-1 prescriptions were more likely to be approved or processed more quickly. Overall, same-day adjudication was most common for ubrogepant (40%) and least common for evolocumab (29%), while approval rates were highest for evolocumab (66%) and lowest for tirzepatide (49%).
Half of the ten most popular drugs in the study were GLP-1 agonists.
The role of technology with prior authorizations
Very few brand-name prescriptions with a PA were approved on the same day patients went to fill them. However, technology may be helping to streamline the process for at least some patients.
The study authors suggested that the growing adoption of algorithms and AI for real-time claim adjudication contributed to the 11% of prescriptions initially rejected by prior authorization receiving same-day resolution. However, the study did not specifically analyze the use of such technology for PAs.
Technology adoption may also contribute to the variation in clinician approval rates. For example, clinicians affiliated with larger corporate entities likely have better access to resources that help them navigate prior authorization requirements and support prescribing decisions, the study authors stated. Those resources include advanced data software that makes a patient's formulary information or approval rates readily available.
The healthcare industry is betting on AI to smooth the notoriously burdensome PA process. CMS recently launched the Wasteful and Inappropriate Service Reduction (WISeR) Model, an initiative that uses AI to conduct prior authorizations for high-risk Medicare services in six states.
However, the model garnered heavy criticism from key industry stakeholders, including several lawmakers who sought to repeal it and a technology nonprofit that recently sued CMS over the vendors selected to operationalize AI-driven PAs.
A recent report from the Peterson Health Technology Institute also raised concerns that AI is exacerbating core issues with the PA process, which has yet to be smoothed out by payers and providers.
The JAMA Health Forum study did not explore AI's use, but the area warrants additional research, the study's authors said.
Jacqueline LaPointe is a graduate of Brandeis University and King's College London. She has been writing about healthcare finance and revenue cycle management since 2016.
