Medication adherence is one of healthcare most significant challenges. Non-adherence to prescribed treatments can lead to poor health outcomes, increased hospitalizations, and rising healthcare costs. For healthcare providers, ensuring patients follow their prescribed medication regimens is key to achieving optimal treatment outcomes.

Fortunately, advancements in technology have led to the development of powerful tools aimed at improving medication adherence. One such tool is the H2H Digital Rx’s AI-powered Medical Adherence Prediction Module, integrated into the H2H Digital Rx platform. This cutting-edge feature provides real-time insights into patient medication adherence, empowering healthcare providers to make data-driven decisions and offer personalized support to patients.

The Challenge of Medication Adherence

Studies have shown that a significant number of patients struggle with adhering to their prescribed medications. This can be due to a variety of factors, such as forgetfulness, misunderstandings about the medication’s importance, side effects, or even the complexity of the treatment regimen. These factors can lead to negative health outcomes, including disease progression, avoidable hospitalizations, and increased healthcare spending.

For healthcare providers, the challenge lies in identifying and addressing the root causes of non-adherence. While the reasons behind missed doses or delayed refills are varied, understanding these factors and acting on them in a timely manner can improve patient outcomes.

Introducing the Medical Adherence Prediction Module

The AI-powered Medical Adherence Prediction Module, developed by H2H Solutions, enhances the H2H Digital Rx platform by providing healthcare providers with real-time insights into patients’ medication adherence. Using over nine factors from a patient’s 365-day view, the module predicts the likelihood of a patient adhering to their prescribed regimen, allowing providers to act early to improve adherence.

Here’s how it works:

1. Real-Time Data Analysis: The AI-powered Medical Adherence Prediction Module analyzes medication history, refill requests, and prescription completion times to calculate an adherence percentage.
2. Actionable Insights: Based on this data, the module generates insights into why a patient may not be adhering to their medication regimen and offers actionable suggestions for providers to address these issues.
3. Tailored Support: Providers can use these insights to offer personalized counseling or recommend adjustments to the treatment plan, addressing factors like side effects or the complexity of the regimen that may be causing non-adherence.
4. Medication Reminders: To further improve adherence, the module sends automated medication reminders to patients, helping them stay on track with their prescribed treatments.

Key Benefits for Healthcare Providers

The Medical Adherence Prediction Module offers several benefits that enhance both patient care and provider decision-making:

• Patient Insights: Providers gain detailed insights into a patient’s likelihood of adhering to their medication, allowing for more informed decisions.
• Improved Patient Care: By offering actionable suggestions and reminders, providers can intervene early and offer additional support, ultimately improving patient outcomes.
• Factors & Suggestions: The module highlights factors affecting adherence—such as missed refills or late prescription completions—and offers tailored recommendations for providers to address these barriers.
• Medication Reminders: By sending timely medication reminders to patients, the module helps reduce the risk of non-adherence and ensures that treatment is followed as prescribed.

How the Medical Adherence Prediction Module Works

The AI-powered Medical Adherence Prediction Module leverages over nine factors from a patient’s 365-day view, including past adherence, medication history, and refill request timing. The AI model analyzes this data to identify factors contributing to non-adherence, calculating an overall adherence percentage for each patient.

Providers can view the adherence percentage on each drug prescription pane, categorized into three levels:

• High Adherence: The patient has a strong likelihood of adhering to their medication regimen.
• Moderate Adherence: The patient is somewhat adherent, but there may be room for improvement.
• Low Adherence: The patient is at significant risk of not adhering to their treatment.

By clicking the hyperlink next to the adherence percentage, providers can access detailed insights into the patient’s adherence, reasons for non-adherence, and suggested actions to improve the situation.

Enhancing Provider-Patient Communication

The Medical Adherence Prediction Module fosters better communication between providers and patients. If a provider notices low adherence, the system offers suggestions for additional support, such as counseling, to reinforce the importance of staying on track with treatment.

Moreover, the system allows providers to adjust prescriptions or recommend alternative medications if the patient experiences side effects or challenges with the current regimen. This flexibility enables providers to tailor treatment to individual patient needs.

Continuous Improvement with Provider Feedback

The AI-powered Medical Adherence Prediction Module also encourages continuous improvement through feedback from providers. By using the ‘Agree’ or ‘Disagree’ buttons, providers can offer feedback on the AI’s predictions. This feedback loop helps refine the system over time, enhancing its future predictions.

AI and Provider Responsibility

It’s important to note that the medication adherence score displayed by the Medical Adherence Module is generated by an AI model. While the module provides valuable insights, it is ultimately the prescriber’s responsibility to make informed decisions when modifying medications or offering recommendations. The AI serves as a tool to support providers, not replace their clinical judgment.

Improving medication adherence is crucial for better health outcomes, reduced hospitalizations, and lower healthcare costs. The Medical Adherence Prediction Module integrated into H2H Digital Rx provides healthcare providers with the tools needed to gain real-time insights into patient adherence and make data-driven decisions. By harnessing the power of AI, providers can offer more personalized care, address barriers to adherence, and help their patients stay on track with their treatment plans.

With this module, providers are empowered to take a proactive role in improving patient outcomes, leading to healthier, more satisfied patients.

Surescripts plans to include veterinary medications within its e-prescribing service. Surescripts E-Prescribing for Veterinary Medications, which is the name of the new feature, will improve care for pets by improving medication adherence & reducing time spent by veterinarians on administrative tasks. These tasks include reducing the need for handwritten prescriptions, as well as phone calls or faxes between pharmacies and prescribers.

This new service will use the newest NCPDP SCRIPT Standard (Version 2023011), which was finalized in June 2024 by the Centers for Medicare and Medicaid Services.

A study backed by Surescripts found that more pharmacists are electronically prescribing medications as they assist doctors in helping patients with chronic illnesses, which shows an interesting evolution in the ecosystem of primary care. Surescripts reported a 12.1% increase per year between 2018 and 2022 in prescribers outside of traditional primary care providers, while the number of clinicians who provide primary care grew by less than 1%.

As concerns about the gaps in primary care access rise, particularly in rural areas, this data shows a growing trend in the field where pharmacists have been lessening the burdens of physicians in a move towards more team-based care for patients. This change is welcomed by prescribers and pharmacists alike: Not only can help lessen physician burnout as they can focus on providing critical care, but this benefits patients who visit their pharmacists more often than their doctors.

Dr. Wendy Crouse, a Texas-based independent house call veterinarian is the first veterinarian who is testing e-prescribing software that is pharmacy-agnostic. This move is bridging the gap between pet and human doctors in terms of being able to prescribe medications without needing to phone pharmacies and manually calling in every prescription they write. A process that usually takes 30 to 45 minutes, and can require staff to hand write prescriptions that are then delivered by patients with days of delays, now takes 5 minutes or less with e-prescribing software.

This transition also allows Dr. Crouse to honor patient’s pharmacy requests more easily, whether it be a mom-and-pop shop or a larger pharmacy in a different area. An expanded pharmacy selection also makes medication pick-up easier for patients by being more forgiving to working schedules and distances. While e-prescribing for veterinarians does not include controlled substances like it does for human doctors right now, it is expected to be developed soon.