How hyper-targeting patient communications can improve medication adherence
April 05, 2019
By Robert Oscar
It causes more deaths than Alzheimer’s disease. It causes more deaths than diabetes. It causes more deaths than the flu/pneumonia, kidney disease, and suicide. It even causes more deaths than gun violence and motor vehicle accidents combined.
What is this dreaded scourge plaguing the nation? Medication non-adherence. The simple act of not taking prescribed medications is responsible for roughly 125,000 deaths in the U.S. each year – not to mention 10 percent of hospitalizations. It’s also estimated to cost the already-struggling U.S. health system between $100 billion and $289 billion annually.
As bad as that news is, however, here’s the saddest part: every single one of those deaths from medication non-adherence – along with scores of hospital stays and emergency department (ED) visits – was preventable. Every. Single. One.
There are many reasons for members not taking their medications as-prescribed. Some revolve around social determinants of health (SDoH) such as cost. If a member must choose between filling their prescription (or taking the full recommended dosage) and paying the rent or buying food, the medication is going to lose. Other typical challenges include a lack of transportation to a pharmacy, or apartment dwellers being unable to receive mail-order medications in bulk due to mailbox size.
Sometimes there are behavioral or other comorbid conditions, such as a member with depression who has trouble functioning, or someone with Alzheimer’s disease who forgets to take their medication. Sometimes members simply choose not to, without an apparent reason.
Whatever the cause, it’s clear that improving medication adherence can have a profound effect on member health (and mortality/morbidity) as well as the cost of care. Of course, that’s like saying if we could get everyone to stop fighting the world would be a happier place. The statement is true, but how do you make it happen?
Replacing generic messages with hyper-targeting
Many health payers understand the value of communicating with members to encourage them to take their medications as prescribed. They send out messages explaining the health (and financial) benefits of doing so, as well as the health and financial cost of failing to do it.
The problem with most of these messages is they are too general. Telling a member with high blood pressure they should take their “medication” isn’t nearly as effective as saying they should ingest one 160 mg dose of Valsartan each morning with their breakfast. It’s the specificity that helps.
Yet even this effort may largely be wasted because it’s still too general. It doesn’t take into account, for example, all the members who are already following this routine. Receiving a reminder to do something they’re already doing is an annoyance and a distraction that is likely to make them less receptive to future messages from the health payer.
A better approach would be to hyper-target members whose claims and/or medical records indicate they are not filling their prescriptions or taking their medications as prescribed, and deliver meaningful messages to help convince them to change their behavior. This is where sophisticated analytics and business intelligence can be invaluable in turning the tide.
Sorting the cohort
The first step is to identify members who have adherence levels that fall below a user-defined threshold for non-adherence. For these purposes we will use the industry standard, which is 80 percent, and look across three classes of maintenance drugs: anti-hypertensive medications (ACE/ARB), oral diabetes medications, and statin medications for lowering cholesterol. To run the numbers we will use the records of a health plan with 250,000 total members, and only include members who are 18 years of age or older who have not opted out of receiving communications.
Using predictive analytics we discover a baseline noncompliance rate of 22 percent for the hypertension medication, 30.9 percent for diabetes and 25.6 percent for statins. This is our target audience, and the only ones who will receive communication.
Delivering the message
To begin changing behaviors, we can use technology to generate and deliver hyper-targeted messages to a total of 13,240 members using their preferred messaging channels (email, SMS/text, print, etc.). The technology also tracks open and bounce rates where possible to help continually refine the program.
Based on the health plan’s prior data, the predictive analytics are able to calculate the program’s impact on adherence, as well as the average medical savings generated for each conversion from non-adherence to adherence. The results are impressive.
In the hypertension category, hyper-targeting messages is able to convert 736 members (more than 15 percent) from noncompliant to compliant. This results in a total savings of $158 per conversion for a total savings of $116,308.
In the diabetes category, 523 members are converted (also more than 15 percent), resulting in a savings of $625 per conversion and $327,113 total.
The statins category sees 674 conversions (more than 13 percent) for a savings of $214 per conversion and $144,333 total.
Together, these three interventions result in annual savings to the health plan of $587,754, which, measured across the entire member population, comes to $2.35 per member per year, or $0.20 per member per month.
Obviously, it also results in healthier members who are far more likely to be satisfied with their health plans (and provider network) – and who will continue paying premiums. Members whose non-adherence results in death, of course, pay nothing. Add in the expected financial returns as result of increased STAR rating scores and the value to the health plan is even greater.
Preventing the preventable
Medication non-adherence is a huge issue in the U.S., exacting a tremendous cost in both money and lives. But it is completely preventable – if payers are willing to make it the priority it should be.
By using analytics to identify non-adherent members, then hyper-targeting them with communications that address their specific conditions and needs, health payers can help members understand the value of taking their medications as prescribed, and convert the reluctant into willing, enthusiastic participants in their own care.
About the author: Robert Oscar is the CEO of RxEOB
It causes more deaths than Alzheimer’s disease. It causes more deaths than diabetes. It causes more deaths than the flu/pneumonia, kidney disease, and suicide. It even causes more deaths than gun violence and motor vehicle accidents combined.
What is this dreaded scourge plaguing the nation? Medication non-adherence. The simple act of not taking prescribed medications is responsible for roughly 125,000 deaths in the U.S. each year – not to mention 10 percent of hospitalizations. It’s also estimated to cost the already-struggling U.S. health system between $100 billion and $289 billion annually.
As bad as that news is, however, here’s the saddest part: every single one of those deaths from medication non-adherence – along with scores of hospital stays and emergency department (ED) visits – was preventable. Every. Single. One.
There are many reasons for members not taking their medications as-prescribed. Some revolve around social determinants of health (SDoH) such as cost. If a member must choose between filling their prescription (or taking the full recommended dosage) and paying the rent or buying food, the medication is going to lose. Other typical challenges include a lack of transportation to a pharmacy, or apartment dwellers being unable to receive mail-order medications in bulk due to mailbox size.
Sometimes there are behavioral or other comorbid conditions, such as a member with depression who has trouble functioning, or someone with Alzheimer’s disease who forgets to take their medication. Sometimes members simply choose not to, without an apparent reason.
Whatever the cause, it’s clear that improving medication adherence can have a profound effect on member health (and mortality/morbidity) as well as the cost of care. Of course, that’s like saying if we could get everyone to stop fighting the world would be a happier place. The statement is true, but how do you make it happen?
Replacing generic messages with hyper-targeting
Many health payers understand the value of communicating with members to encourage them to take their medications as prescribed. They send out messages explaining the health (and financial) benefits of doing so, as well as the health and financial cost of failing to do it.
The problem with most of these messages is they are too general. Telling a member with high blood pressure they should take their “medication” isn’t nearly as effective as saying they should ingest one 160 mg dose of Valsartan each morning with their breakfast. It’s the specificity that helps.
Yet even this effort may largely be wasted because it’s still too general. It doesn’t take into account, for example, all the members who are already following this routine. Receiving a reminder to do something they’re already doing is an annoyance and a distraction that is likely to make them less receptive to future messages from the health payer.
A better approach would be to hyper-target members whose claims and/or medical records indicate they are not filling their prescriptions or taking their medications as prescribed, and deliver meaningful messages to help convince them to change their behavior. This is where sophisticated analytics and business intelligence can be invaluable in turning the tide.
Sorting the cohort
The first step is to identify members who have adherence levels that fall below a user-defined threshold for non-adherence. For these purposes we will use the industry standard, which is 80 percent, and look across three classes of maintenance drugs: anti-hypertensive medications (ACE/ARB), oral diabetes medications, and statin medications for lowering cholesterol. To run the numbers we will use the records of a health plan with 250,000 total members, and only include members who are 18 years of age or older who have not opted out of receiving communications.
Using predictive analytics we discover a baseline noncompliance rate of 22 percent for the hypertension medication, 30.9 percent for diabetes and 25.6 percent for statins. This is our target audience, and the only ones who will receive communication.
Delivering the message
To begin changing behaviors, we can use technology to generate and deliver hyper-targeted messages to a total of 13,240 members using their preferred messaging channels (email, SMS/text, print, etc.). The technology also tracks open and bounce rates where possible to help continually refine the program.
Based on the health plan’s prior data, the predictive analytics are able to calculate the program’s impact on adherence, as well as the average medical savings generated for each conversion from non-adherence to adherence. The results are impressive.
In the hypertension category, hyper-targeting messages is able to convert 736 members (more than 15 percent) from noncompliant to compliant. This results in a total savings of $158 per conversion for a total savings of $116,308.
In the diabetes category, 523 members are converted (also more than 15 percent), resulting in a savings of $625 per conversion and $327,113 total.
The statins category sees 674 conversions (more than 13 percent) for a savings of $214 per conversion and $144,333 total.
Together, these three interventions result in annual savings to the health plan of $587,754, which, measured across the entire member population, comes to $2.35 per member per year, or $0.20 per member per month.
Obviously, it also results in healthier members who are far more likely to be satisfied with their health plans (and provider network) – and who will continue paying premiums. Members whose non-adherence results in death, of course, pay nothing. Add in the expected financial returns as result of increased STAR rating scores and the value to the health plan is even greater.
Preventing the preventable
Medication non-adherence is a huge issue in the U.S., exacting a tremendous cost in both money and lives. But it is completely preventable – if payers are willing to make it the priority it should be.
By using analytics to identify non-adherent members, then hyper-targeting them with communications that address their specific conditions and needs, health payers can help members understand the value of taking their medications as prescribed, and convert the reluctant into willing, enthusiastic participants in their own care.
About the author: Robert Oscar is the CEO of RxEOB