A Qualitative Evaluation of the Use of Facial Recognition Technology for Opioid Substitution Treatment in Community Pharmacies

Abstract

ABSTRACT Introduction: Opioids are used as analgesics and are available as prescription opioids, over-the-counter opioids or illicitly as heroin. Increasingly opioid addiction has become prevalent. Opioid addiction or dependence results in the addicts indulging in harmful or dangerous behaviour including unsafe opioid injecting. To address this issue, approved opioid substitution therapy (OST) has been introduced in Australia. It has been identified informally that community pharmacies have issues in dispensing OST because of less than robust patient verification processes. This has led to input errors, misidentification of patients, and refusal to dispense when the patient is not recognised in the records. Facial Recognition Technology (FRT), a form of artificial intelligence, has been used to recognise patients, dispense, and confirm medication ingestion. Some pharmacies in Victoria have commenced using FRT to address the mis-identification issues and help with better record keeping and auditing. Methods: A study to evaluate the pharmacy stakeholders’ (pharmacists, pharmacy assistants and pharmacy owners) experience of using FRT to dispense OST was conducted over 2019–2020. To evaluate the stakeholder’s views, an innovative evaluation approach termed ‘integrated model of evaluation (IMoE)’ was used. The stakeholders (pharmacies) views about use of FRT for OST and its impact on business practice (medication dispensing process and record keeping) improvement was evaluated. Semi-structured questionnaires were used to conduct interviews with individual stakeholders. To obtain a well-rounded perspective about the experiences with FRT, 11 key participants including three pharmacy owners, six pharmacists and two pharmacy assistants were interviewed. Interviews were transcribed and analysed using thematic analysis. Analysis compared and contrasted experiences and perspectives of OST dispensing prior to and after introduction of FRT. Results: The data was collated and analysed as per the IMoE framework. The framework focuses on five components including context, intervention, change, outcomes, and emergent program theory. As per the IMoE framework, the data is analysed inductively and used to formulate a theory explaining the changes because of the OST. As per this assessment process, the findings indicate a positive perception of the utility of FRT in OST program in specific and the pharmacy context in general. The employment of FRT was seen to be conducive to reducing time to pharmacy dispensing and time saving. Where there were issues, it was because of unfamiliarity with the technology or integration problems. Improvement in integration and scaling up of FRT in more pharmacies will yield efficiencies and economies of scale. Conclusions: This study presents an important view about the concerns and opportunities pharmacy stakeholders have in the use of FRT. This will help stakeholders better understand the way to implement facial recognition in the pharmacy sector and in what way they should disseminate information to better inform the public of its pros and cons.