New BD Software Helps Tackle Hospital Drug Diversion

BD (Becton, Dickinson and Company) announced the launch of a new software application designed to help hospitals and health systems identify drug diversion at the 2018 American Society of Health-System Pharmacists (ASHP) Midyear Meeting.
 
Addiction to prescription narcotics in the United States has reached epidemic proportions, contributing to the opioid crisis and becoming a major driver of drug diversion within healthcare settings^1,2,3. Diversion of drugs, for personal use or illegal distribution, can cause significant financial loss⁴ and potentially impact care to patients and staff safety⁵.
 
As part of the BD HealthSight platform that is designed to support enterprise-wide medication management, the new BD HealthSight diversion management application is the next step in the company’s efforts to address drug diversion through integrated solutions and analytics. The solution leverages data from existing BD products, including the BD Pyxis ES system, and the Electronic Medical Record (EMR) to provide actionable insights to assist with a hospital or health system’s diversion investigations.
 
“Medication diversion is a growing and complex challenge for hospitals and health systems. We believe that to best address this challenge, a holistic approach to medication management that includes a combination of connected technologies and robust analytics is required,” said Ranjeet Banerjee, worldwide president of Medication Management Solutions for BD. “Specific cases of diversion can be difficult to detect, and the impact can be devastating from a patient and healthcare worker safety standpoint. The new BD HealthSight diversion management application is designed to address the unique challenges associated with diversion by tracking patterns and risky behavior to help identify diverters as early as possible.”
 
BD HealthSight diversion management is a hosted, cloud-based application that assists with drug diversion investigations by creating an investigation workflow to monitor, triage and assign potential diversion cases to specific investigators. Compared to traditional, statistically-based analytical tools that only look at amounts dispensed to identify potential diversion, BD utilizes machine learning algorithms and multiple dispensing behaviors—such as overrides, canceled transactions, delays in dispensing, administering and wasting medications—to surface clinicians whose behavior indicates higher risk for diversion. BD has partnered with Microsoft, who brings industry-leading expertise in artificial intelligence (AI) and data science methodologies, to support development of these machine-learning based algorithms. Importantly, the application also aggregates EMR and dispensing cabinet data to automate a normally time-consuming and tedious manual review process to reconcile and automatically flag anomalous dispense, administration and waste transactions.
 
References
¹ Cicero TJ, Ellis MS. The prescription opioid epidemic: a review of qualitative studies on the progression from initial use to abuse. Dialogues Clin Neurosci. 2017;19(3):259-269.
² Opioid addiction 2016 Facts and Figures https://www.asam.org/docs/default-source/advocacy/opioid-addiction-disease-facts-figures.pdf   Accessed October 30, 2018
³ Burger G, Burger M. Drug Diversion: New Approaches to an Old Problem. Am J Pharm Benefits. 2016;8(1):30-33.
⁴ UM pays $4.3M to settle federal charges for stolen drugs, but criminal charges possible https://www.detroitnews.com/story/news/local/michigan/2018/08/30/university-michigan-3-million-settle-federal-drug-diversion-lawsuit/1145373002/; Accessed October 30, 2018
⁵ Hospital tech who spread hepatitis C through drug use sentenced to 39 years https://www.cbsnews.com/news/lab-tech-hepatitis-c-kwiatkowski-sentenced-39-years/ Accessed October 30, 2018