Increasing Naloxone Access and Prescribing for Patients on High-Dose Opioids From a Managed Care Pharmacy Health Plan Perspective.
Jodi P HansgenMegan L RobertsonEllen M VerzinoLindsay M ManningPublished in: Journal of pharmacy practice (2024)
Background: Opioid overdoses decrease when communities have access to naloxone. Clinicians play a key role in offering naloxone to high-risk chronic opioid patients. Managed care pharmacists within our health plan noted disproportionate processing for claims of opioid utilizers compared to claims of naloxone prescriptions. Objective: To increase naloxone access and prescribing to members who classify at a dosage with a higher risk for opioid overdose, defined as over 90 morphine milligram equivalents (MME). Methods: Multiple system-wide initiatives were implemented to improve naloxone access. A claims file was pulled monthly to identify members on opioids meeting MME criteria >90 MME per day excluding members with cancer, sickle cell disease, or on hospice. A separate report was then matched to naloxone claims and prescribing percentages calculated. Results: 12 444 utilizing members on opioids were identified from June 2019 prescription claims data. Of these, 131 were on opioids exceeding 90 MME per day, or 1.05% of utilizers, and the percentage of members exceeding 90 MME per day prescribed naloxone was 6.87%. By May 2023, the percentage of opioid utilizers exceeding 90 MME per day decreased to 0.58%. Naloxone prescribing increased to 41.18%. Conclusion: A multi-pronged approach to improve access to naloxone and continued educational efforts by our health plan increased naloxone prescribing in members on opioids exceeding 90 MME per day.
Keyphrases
- pain management
- chronic pain
- healthcare
- primary care
- health insurance
- palliative care
- end stage renal disease
- public health
- high dose
- sickle cell disease
- newly diagnosed
- mental health
- chronic kidney disease
- quality improvement
- health information
- adverse drug
- electronic health record
- prognostic factors
- social media
- risk assessment
- machine learning
- artificial intelligence
- patient reported outcomes
- deep learning
- stem cell transplantation
- big data
- squamous cell