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How Healthcare Organizations are Using AI to Address Medication Non-Adherence

April 25, 2023

Medication non-adherence is a significant challenge that impacts patients, healthcare providers, and payers. According to the World Health Organization, medication non-adherence accounts for about 50% of treatment failures, 125,000 deaths, and up to $100 billion in avoidable healthcare costs. However, the rise of AI-powered population health solutions offers a glimmer of hope in addressing this critical issue. 

Why Patients Struggle with Medication Non-Adherence 

Medication non-adherence is caused by various factors, such as:

- Forgetfulness
- Cost
- Adverse effects
- Complexity of medication regimens

Patients with chronic diseases, such as diabetes or hypertension, may have to take multiple medications at different times of the day, making it challenging to stay on track. In addition, patients may not fully understand the importance of taking their medications as prescribed, or they may be reluctant to take medications due to concerns about side effects or other issues. 

How Clinicians Struggle to Understand Why

Identifying patients at risk of medication non-adherence can be challenging for healthcare providers for various reasons. One common factor is that it is difficult for providers to understand the complexity and many barriers to medication adherence in the limited time they have during a typical office visit.

Additionally, medication non-adherence is often an issue that develops over time, rather than one that presents itself immediately. A patient may begin taking a new medication as prescribed but gradually become less adherent months or years later for reasons that may not be immediately apparent to their provider. This slow progression can make it challenging for providers to identify non-adherence early on and intervene with support and resources.

Another obstacle to identifying patients at risk of medication non-adherence is the lack of comprehensive data available to providers. In many cases, providers may not have access to a patient's complete medication history, or socioeconomic information, which can make it difficult to identify patterns of non-adherence or potential risk factors. 

This is where AI-powered population health solutions can play a valuable role in improving medication adherence rates and patient outcomes.

Can AI Help Improve Adherence Now and in the Future?

The benefits of utilizing an AI-powered population health solution, such as Diagnostic Robotics, are numerous. Our solution uses data analytics and machine learning algorithms to identify patients at risk of non-adherence and provide personalized interventions to improve adherence rates.

To help providers create a comprehensive picture of patients' medication adherence behaviors, the solution collects data such as:

- Medical claims
- Pharmacy records
- Social Determinants of Health (SDoH)
- Patient-generated surveys
- Historical program information

It then uses AI algorithms to analyze the data, identify patterns, and predict which patients are at high risk of non-adherence. Once high-risk patients are identified, our solution provides personalized interventions to improve adherence rates. 

These interventions can include reminders, education, and outreach to healthcare providers to adjust medications or provide additional support. AI algorithms can also monitor patient responses to these interventions to identify the most effective approaches and adjust the interventions accordingly.

By automating the process of identifying high-risk patients and providing personalized interventions, healthcare providers can focus their attention on patients who require the most assistance. This leads to more efficient and effective care and lower cost of care.

In conclusion, medication non-adherence is a critical healthcare challenge that requires innovative solutions to improve patient outcomes. AI-powered population health solutions like Diagnostic Robotics offer promising approaches to addressing this problem. By using data analytics and machine learning algorithms to identify high-risk patients and provide personalized interventions, healthcare providers can improve medication adherence rates, streamline workflows, and improve patient outcomes. As AI technology continues to advance, solutions like Diagnostic Robotics are likely to become increasingly important tools for improving medication adherence and patient outcomes.

Find out more about our solutions here: https://www.diagnosticrobotics.com/ai-powered-population-health-management 

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