Cut Polypharmacy Risks by 30% with Data-Driven Med Management

As older adults increasingly find themselves managing 10 to 15 medications—spanning prescriptions, over-the-counter drugs, and supplements—the urgency to refine medication management has never been greater. Over the last two decades, the average number of prescriptions for individuals 65 and older has doubled, driven by a mix of longer life expectancy, chronic disease management, symptom-based prescribing, and the common practice of layering additional medications to counteract side effects.

This growing reliance on multiple medications—known as polypharmacy—poses significant risks, particularly for older patients with multiple chronic conditions. According to the National Council on Aging (NCOA), nearly 95% of adults over 60 have at least one chronic disease, while 80% manage two or more. Common conditions such as hypertension, diabetes, arthritis, and depression require different treatment approaches, yet the challenge lies in ensuring these medications work together rather than introducing unintended harm. With aging bodies metabolizing drugs at a slower, often unpredictable rate, the risk of adverse reactions, cognitive decline, and serious complications such as falls or hospitalizations increases significantly.

Beyond Deprescribing: A Need for Smarter Medication ManagementDeprescribing—the careful reduction or discontinuation of certain medications—is emerging as a crucial strategy to reduce these risks. While deprescribing can enhance quality of life, it should be viewed as one component of a broader, proactive medication management strategy rather than a reactive solution to problematic prescribing.

Take the case of Renée (a pseudonym), an 80-year-old retired school administrator who had always been an energetic leader in her community. Over time, however, she became increasingly withdrawn, avoiding social activities and struggling with persistent fatigue and cognitive fog. A review of her medication regimen revealed a complex web of prescriptions, including antipsychotics, antidepressants, anti-Parkinson’s drugs, and benzodiazepines—many prescribed to treat symptoms that never had a clear underlying cause.

With a comprehensive medication review, Renée’s healthcare team worked closely with her and her family to strategically reduce her medications while carefully monitoring for withdrawal effects and changes in symptoms. The results were dramatic—within weeks, her energy and cognitive function improved, allowing her to reengage with hobbies, household activities, and eventually cognitive behavioral therapy to address lingering anxiety. What had initially been diagnosed as depression and neurological decline turned out to be a severe case of medication-induced side effects.

Technology as a Catalyst for Smarter PrescribingStories like Renée’s illustrate the need for a more structured, technology-enabled approach to medication management. Currently, clinicians are expected to navigate a labor-intensive reconciliation process, which involves:

Gathering a complete, often fragmented medication history across multiple providers

Evaluating drug indications, drug-drug interactions, drug-disease interactions, duplications, and dosing errors

Monitoring for side effects, functional decline, or worsening of underlying conditions

However, these tasks are time-consuming and prone to human error, leading many providers to focus narrowly on adherence and drug interactions rather than taking a whole-person approach to medication planning. Technology-driven solutions can change that.Today, advanced platforms increasingly use AI and predictive analytics to support clinical decision-making, helping providers make sense of complex patient data and anticipate and mitigate risks. By integrating real-time data on, for example, patient age, kidney function, liver metabolism, and disease progression, these systems can help providers:

Predict potential medication complications before they arise

Proactively adjust dosages to reflect changes in metabolic function over time

Identify which medications are no longer necessary based on clinical trends and patient response

In a value-based care landscape, where reimbursement increasingly depends on preventing hospitalizations and adverse events, technology can provide actionable insights that help providers optimize prescribing decisions, improve outcomes, and enhance patient safety.

A Future of Personalized, Data-Driven Medication ManagementAdopting a personalized, data-driven approach to medication management can ensure that medications work in harmony with a patient’s overall health rather than simply adding layers of treatment to manage isolated symptoms.

To accomplish this, healthcare leaders must:

Integrate advanced decision-support tools to help providers assess medication risk-benefit ratios

Encourage a shift from symptom-based prescribing to functional and outcomes-based medication management

Foster cross-specialty collaboration between primary care physicians, pharmacists, and geriatric specialists to create holistic care teams and medication strategies

By moving beyond reactive deprescribing efforts and embracing a technology-driven, patient-centric approach, which leverages AI and predictive analytics, providers can make a meaningful impact on patient well-being, reduce healthcare costs, and ultimately, redefine what safe and effective medication management looks like in an aging population.