Showing prescribers a medication's cost could help them save patients money
Key takeaways:
- Showing clinicians the prices their patients would have to pay for medications led to changes in one of eight medication orders.
- When the potential cost-saving was $20 or more, one in six orders changed.
Seeing how much a medication would cost a patient helped some physicians make decisions when prescribing, according to the results of research published in JAMA Internal Medicine.
“Many Americans struggle with the affordability of their prescription drugs, and we need interventions that can help people find lower cost medications to help people be able to afford their needed medications,” Anna Doar Sinaiko, PhD, MPP, an assistant professor of health economics and policy at the Harvard T.H. Chan School of Public Health, told Healio.
A potential solution comes in the form of Real-Time Benefit Tools (RTBTs), which Sinaiko said “provide more meaningful information about patient drug prices in clinical settings than has previously been available.” RTBTs can provide estimates of the out-of-pocket (OOP) price for specific patients, accounting for their individual health plans, “as opposed to symbols or colors indicating drugs that are more or less expensive, which has been the status quo.”
“Medicare policy has promoted adoption of RTBTs by health systems and health plans, which made this study of interest,” she said. “We wanted to know whether showing clinicians their patients’ medication price at the time of ordering would change the medications that they ordered for patients.”
So, Sinaiko and colleagues conducted a cross-sectional study examining an RTBT at the University of Colorado Health, which had alerts that appeared if an alternative was available at an onsite pharmacy or if an alternative that costs at least $0.15 per prescription less than the prescriber’s first-choice medication existed. The alternative medications, the researchers wrote, could differ from the prescriber’s first choice in pharmacy, strength, formulation, etc.
They ultimately included 889 clinicians, 53.2% of whom were women, and 1,877,649 medication orders, 9.7% of which included an RTBT price estimate.
Higher savings led to more changes
Sinaiko and colleagues found that, when clinicians viewed RTBT price estimates, 12.3% of medication orders changed. When the potential cost savings were $5 or more, 14% changed. Adjusted analyses also revealed that clinicians tended to change medications more frequently for some drug classes — cardiovascular, asthma and chronic obstructive pulmonary disease medications and antihyperglycemic agents — and if the potential savings were $20 or more. They were less likely to change their orders for psychotherapeutic medications.
“Medication orders were changed more often when the potential cost savings for patients were larger,” Sinaiko said. “This suggests to me that clinicians were taking medication OOP cost into account when it was most salient for the patient.”
Notably, no sociodemographic characteristics were linked to changing medication orders, a finding that “suggests this intervention affects medication changes across patients equally,” Sinaiko said.
The overall role that cost plays into prescription decisions varies for each patient-physician relationship, she said, and “there is still a lot to understand about how and when alerts with price information affect medication orders, and in the cases when a clinician doesn’t switch options when it could save a patient money, why that is.”
Letting price information guide, not dictate, decisions
“There are many reasons — for example, due to alert fatigue — clinicians may ignore the alerts,” Sinaiko said. “I’d like to know if clinicians discount or ignore the price estimates because they don’t know where it comes from or whether it is accurate. It’s also possible that clinicians discuss the option to change a medication order with their patient, and for reasons other than cost they decide to keep the original selection. This suggests that clinicians might be using price information to guide — not dictate — their clinical decisions and could make medication choices more consistent with patient preferences.”
In some cases, like when prescribing drugs a physician knows have high OOP costs like antihyperglycemics, “the patient cost can be a big factor in decisions about which specific medication to prescribe.”
“Some clinicians consider patient costs in their medication choices only after they’ve heard from their patient, a pharmacist, or someone else in the office that a prescribed drug is expensive,” she said. “Thus, the extent that patient cost can affect clinician prescribing decisions depends on whether the clinician learns what a patient’s cost is, and this doesn’t always happen. Providing this form of patient-specific medication price information is thus critical to efforts to make medications less of a financial burden.”
Reference:
Perspective
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I feel this was a good abstract and good study. It shows how difficult it is to change the current situation when you factor the present electronic medical records and drug prescribing data. There did seem to be a threshold of $20 — that over that amount may cause some behavioral changes for the prescriber. Other motivators to have prescriptions changed to less costly therapeutic options may be considered with certain classes of drugs. Examples like antipsychotics seem to have much more of an impact for financial benefit as opposed to the drugs that affect body weight, which tend to be thought of as more patient specific. Further studies should look at point-of-service screens and having providers assess efficacy for more costly therapy.
Perspective
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The advent of RTBTs has the potential to revolutionize the way we provide patient-centered care, especially in primary care. Primary care clinicians are on the front lines of health care, ensuring that patients have access to affordable medications by exploring every option available with the information we have in front of us. As a family physician, this can be a very difficult and time-consuming task, given that we frequently have to search many external resources and cross-reference with a vast array of formularies that differ depending on what insurance the patient has. As an Epic medical records user, I have experienced the value of the RTBTs firsthand, and to me, this is a game changer for patient care. As the authors point out, over 99% of price estimates are displayed via an alert in the medical record as we are actively writing the prescription, which is very helpful because you can discuss the prices of medications with patients before they leave the exam room. Patients are finally able to anticipate the cost of their prescriptions before they leave their doctor's office. This is one alert that I find timely, effective and necessary in my daily workflow with patient care. I do not agree with the authors' suggestion that clinicians do not seek price information when prescribing drugs based on primarily using alerts. There are a multitude of other price-estimating tools available outside of the EMR that clinicians may use that are not captured in this study. Some specialty clinicians may recommend only certain medications to patients because that is the evidence-based medication the patient needs, despite cost (ie, certain blood thinners, inhalers, heart failure medications, etc.). Therefore, I think it would be beneficial for this study to show their data broken down by primary care clinicians and specialty clinicians to see if any further conclusions could be made on the effectiveness of RTBTs specifically in the primary care setting.
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