SBIR-STTR Award

Drug diversion, defined as “the transfer of a controlled substance from a lawful to an unlawful channel of distribution or use,” is a challenging issue in today's healthcare systems. Based on an analysis, the volume of dosage lost due to diversion increased from 21 million in 2017 to 47 million in 2018, a 126% increase. This resulted in over $450M loss to healthcare systems due to drug diversion, a 50% increase compared to 2017. Hospitals and medical centers constitute the single largest category affected by drug diversion accounting for 33% of all cases and 94% of drug diversion incidents involved opioids. Addressing the drug diversion problem is a multi-faceted problem involving many components ranging from provider training to implementation of hardware and software systems to manage access to controlled substances. However, despite recent improvements in controlling and monitoring access to controlled substances, the process of identifying drug diversion is complicated and time consuming. In this Phase I project, we propose to build on our earlier work in machine learning and automated technologies in healthcare and consensus in a distributed and decentralized architecture to develop a technology based on blockchains to track and document transportation and administration of controlled substances in a hospital environment. The proposed system involves using a smartphone app to scan uniquely generated barcodes for vials of controlled substances during the transport process, digitally sign medication transfers between staff using secure digital certificates to eliminate current paper-based systems, and finally document administration of a controlled substance to the patient by scanning the unique barcode assigned to the vial and recording an after administration picture of the empty vial. Specific Aims: 1) Developing and validating an in silico model of drug transport/diversion in the hospital; we will develop a stochastic model of controlled substance vial movement in the hospital between a series of locations at the hospital. The vials are exchanged between these locations by agents that represent clinical staff. 2) Developing a blockchain-based framework to track medications; we will use the Hyperledger Fabric, an open-source blockchain framework geared towards enterprise applications to design and implement a blockchain framework. We will develop a software interface to record data in and retrieve data from the blockchain (and in a potential Phase II, retrieve data from EMRs and automated dispensing cabinets) for further processing. Finally, we will use the in silico model to quantify the computational power and storage requirements for the blockchain framework discussed above; and 3) Development of an algorithm to identify diversion, the goal of this specific aim is to develop a computational engine that uses data (recorded in the blockchain) to detect drug diversion. We propose to use a framework based on machine learning to detect anomalies in data (i.e., drug diversion). !

Public Health Relevance Statement:
Addressing the drug diversion problem is a multi-faceted problem involving many components ranging from provider training to implementation of hardware and software systems to manage access to controlled substances. However, despite recent improvements in controlling and monitoring access to controlled substances, the process of identifying drug diversion and ensuring compliance is complicated and time consuming. A system is proposed that uses a smartphone app to scan uniquely generated barcodes for vials of controlled substances during the transport process, digitally sign medication transfers between staff using secure digital certificates to eliminate current paper-based systems, and document administration of a controlled substance, while a computation engine uses the rich data generated through the process to identify drug diversion.!

Project Terms:
Accounting; Address; Affect; algorithm development; Algorithmic Analysis; Algorithms; Architecture; Bar Codes; base; blockchain; Categories; Certification; Clinical; Computer software; Computerized Medical Record; Consensus; Consumption; Coupled; Data; Data Management Resources; Data Set; Decentralization; design; Detection; digital; distributed ledger; dosage; Drug Modelings; Drug Transport; Ensure; Environment; Event; Goals; Healthcare; Healthcare Systems; Hospitals; in silico; Individual; Infrastructure; intelligent algorithm; Life; Link; Location; Machine Learning; Medical center; Medication Management; Modeling; Monitor; Movement; open source; Opioid; Paper; Patients; Pharmaceutical Preparations; Phase; prevent; Process; Provider; Scanning; Secure; Sensitivity and Specificity; Series; simulation; smartphone Application; software systems; statistics; System; Technology; Textiles; Time; Training; Transport Process; Transportation; Vial device; Work

Based on an analysis, the volume of dosage lost due to diversion increased from 21 million in 2017 to 47million in 2018, a 126% increase. Addressing the drug diversion problem is a multi-faceted problem involvingmany components ranging from provider training to implementation of hardware and software systems tomanage access to controlled substances. However, despite recent improvements in controlling and monitoringaccess to controlled substances, the process of identifying drug diversion and ensuring compliance iscomplicated and time consuming. Our overall goal is to further develop a technology based on blockchainsto track and document transportation and administration of controlled substances in a hospital environmentand detect drug diversion. The feasibility of the technology and the associated machine learning-based dataanalysis engine was established in the Phase I project. Our specific aims are: 1. Further Development of acloud-based software platform to leverage smartphones to capture drug transactions in clinic. We willfurther develop the cloud-based software platform and its associated smartphone app and web-baseddashboard developed in the Phase I project. The software platform, which uses blockchains to create animmutable audit trail, will be further developed to capture the "cradle-to-grave" documentation of controlledsubstance use and location within an ambulatory surgical center. Prior to deployment, the platform will betested by simulation testing using the in silico model developed in our Phase I project, which is capable ofgenerating realistic transaction data by using a multi-agent simulation framework. 2. Deploying the softwareplatform at the collaborating health system. We will perform a two-stage rollout of our software platform,where in the first stage (the focus of this Specific Aim), we plan to perform a pilot test of our smartphone appand the associated administrator web-based dashboard to ultimately replace the paper logs. The goal of thisstage of the rollout is to understand and address challenges of deploying a new system and potential impactson the workflow and its adoption. Data related to adoption, adherence to protocols, and impact on clinicalworkflow will be measured and any challenges will be addressed by fine-tuning of the software platform. 3.Further development and deployment of an analysis engine to detect drug diversion. The goal of thisspecific aim is to further develop and fine-tune the analysis engine that uses data (recorded on the blockchain)to detect drug diversion. This effort involves two main tasks. Real data (collected as part of Specific Aim 2) willbe analyzed offline by the framework developed in Phase I. Through collaboration with our collaborating healthsystem, we will investigate the generated red flags and use the results of such investigation to fine-tune theparameters of our model. Next, we will integrate the updated analysis engine and rollout the drug diversiondetection capability to the pilot in collaboration with the partner health system in the second stage of the rollout.

Public Health Relevance Statement:
Addressing the drug diversion problem is a multi-faceted problem involving many components ranging from provider training to implementation of hardware and software systems to manage access to controlled substances. However, despite recent improvements in controlling and monitoring access to controlled substances, the process of identifying drug diversion and ensuring compliance is complicated and time consuming. Our overall goal is to further develop a technology based on blockchains to track and document transportation and administration of controlled substances in a hospital environment and detect drug diversion.

Project Terms: