Opioid abuse and misuse in the US has reached epidemic proportions, spurring a host of new technologies and solutions. While many of these solutions are focused on identifying and treating patients who are already known clinically as being dependent, the key to combating the epidemic requires the earliest possible identification and intervention. 

Conventional Prescription Drug Monitoring Programs (PDMP) and Clinical Decision Support (CDS) tools provide a limited view of a patient’s future risk of opioid dependency. These rules-based systems identify suspected opioid abuse and risk of overdose. By the time a patient is flagged by these systems, they are likely already dependent and their downhill clinical course may be hard to mitigate. PDMP and CDS tools fall short in catching patients at risk for future opioid dependency during their initial opioid prescribing events.

Also supporting the need to intervene as soon as possible is the time and cost of treating opioid dependence. In 2018, the total cost of the opioid epidemic was estimated to be nearly $180 billion, which included healthcare costs, lost productivity, and education assistance. Identifying at-risk patients and empowering clinicians to adjust opioid therapy before a patient becomes dependent can dramatically reduce these costs and improve the quality of patients’ lives. 

Adopting AI-Based Tools for Early Identification of Risk

Intelligent technology solutions, like the one from MedAware, integrate with any existing health system infrastructure to identify patients who may be at an increased risk of becoming opioid-dependent from the moment the first opioid prescription is written. These systems work by leveraging AI (Artificial Intelligence) to provide a highly personalized notification to the prescribing clinician based on a host of factors, including the patient’s longitudinal medication and medical history. These solutions go deep into the patient chart, analyzing all historical data to provide insights often missed by legacy systems that are not built to continuously analyze large-scale data, constantly on the search for outliers and other evolving dangerous situations. 

With relevant opioid dependency risk directly in front of clinicians, they are better equipped to decide on whether to initiate opioid therapy, how soon to follow up, and consider non-opioid treatment alternatives which allow for improved patient experiences and outcomes. 

The Future of Opioid Prescribing

The future of opioid prescribing is here. Artificial intelligence solutions allow for more informed decision making based on early risk identification. Imagine how leveraging these tools could improve the quality of life for patients and their families, as well as reduce the strain on healthcare resources. Now is the time to integrate AI with existing health data systems to harness the full power of data and reduce opioid dependency.

Contact us for more information about MedAware’s AI-based Opioid Risk Application and learn how it can integrate with your healthcare technology stack.

Additional reading you may be interested in:

• E-Prescribing: New Opportunities, New Patient Safety Risks
• Identifying Patients with Undiagnosed Opioid Use Disorder
• Personalized Medication Risk Mitigation