Next-Generation Medication Therapy Management Saves Money
January 21, 2016
We have recently posted about the difficulty seniors face maintaining their prescription drug adherence. Failure can lead to enormous negative consequences in health outcomes and costs to the system. Hospital readmissions can be the most costly results of mismanaged prescriptions. New data-driven and algorithmic approaches in Medication Therapy Management (MTM) have emerged that leverage technology to ensure lower costs and prevent inefficient prescribing. By enhancing traditional MTM programs with cost-saving algorithmic applications that seek out inefficiencies, these new data-driven approaches save payers millions. Writing for Forbes magazine, Rob Szczerba defines traditional MTM in a column published this month:
“In [traditional] Medication Therapy Management, a pharmacist evaluates a patient’s prescriptions and how the patient is feeling to identify and resolve issues including: untreated conditions, drug interactions, adverse drug reactions, inappropriate drugs or doses, and whether a patient is taking the medications as prescribed.”
One of the most compelling conclusions that can be drawn from these efforts is how rooted in common sense they sound. That someone would follow up with an ailing senior about their multiple medications feels like an obvious common sense idea. The benefits of these programs save lives, while reducing health complications and costs that burden systems and fail patients. MTM programs do not reduce patient access or cause rationing. It is an investment in common sense that emphasizes improved outcomes and lower costs. The result is an improvement in care for everyone.
“When extrapolated to the entire Medicare population (minus expenses incurred to deliver MTM services) it’s reasonable to estimate net savings approaching $3 billion.”
These savings are based on the MTM program that prevent dangerous drug interactions and complications caused by failure in prescription drug adherence. MTM reduces readmission and saves the system money. But new advances in algorithmic cost-optimization promise to dramatically reduce costs further.
Traditional MTM programs rely on humans to identify and correct all of the inefficient prescribing. But with thousands of medications, each with their own dosing, and therapeutic alternatives, you can quickly lose sight of potential savings. Even still, MTM programs deliver results, but imagine what happens when you arm MTM programs with modern, comprehensive, cost-optimization algorithms. With the click of the mouse, all savings opportunities can be presented to physicians, pharmacists and care team members.
The SwiftRx platform, by RxREVU, dramatically enhances MTM programs by offering non-binding cost-driven reviews of prescriptions that emphasize outcomes and savings at the same time. Imagine an army of pharmacists and care team members catching flaws in overlapping prescriptions with a fluency in equal value low-cost generic alternatives. It’s a highly effective and scalable front-line advance that corrects against inefficiencies and battles skyrocketing drug costs.
There is no argument that suggests seniors should be given less help managing their healthcare decisions. It is good business to aid seniors, and all patients, with resources helping them make the best decisions that promote the best outcomes. The number of hospital readmissions after implementing next generation MTM programs are dramatically improved.
“One of the key findings was that risk-level 1 patients in the MTM group experienced an 86% reduction in readmissions compared to the control group. To put it another way, the group receiving MTM was three times more likely to remain out of the hospital after 60 days.”
The health and outcome improvements are stellar. So what if you enhanced your MTM program to emphasize value based treatments and improved outcomes with cost controls and direct oversight in high-cost patient groups? What if your MTM program consistently emphasized lower cost generic alternatives before being giving expensive name brand drug, so that prescriptions were optimized for cost as well as effectiveness? This isn’t about limiting options as much as it is finding savings where a lack of data causes failure and inefficiency. If implemented correctly, a transparent and highly optimized, algorithmic MTM service that is knowledgeable about health outcomes as well as costs saves payers millions and saves patients related out-of-pocket costs on expensive copays.