AI-Enabled Pharmacist Assistant and Patient Concierge
Streamlining the pharmacist and patient journey across clinical services.
Project Overview
The Problem
The world is facing an unprecedented global shortage within the healthcare workforce, exacerbated by an aging population and a rise in prevalence of chronic health conditions. Canada’s senior population has tripled in size in the last 40 years¹ and prevalence of chronic disease increased by 11.0% over the last 10 years, impacting one in three Canadians², while more than one in five Canadians lack a dedicated healthcare provider they see regularly³.
In response, recent legislation has expanded the scope of pharmacist practice, enabling them to deliver a wider range of clinical services. However, there exist significant barriers to pharmacists practicing to the full breadth of their scope and expertise, such as high level of administrative burden leading to burnout and lack of pharmacy-specific tools that enable efficient service delivery. Integration of artificial intelligence (AI) into pharmacy operations is an emerging field that has not yet achieved widespread global adoption, with immense opportunity for a Canadian-based solution that can transform delivery of clinical services into an effective and efficient experience for both pharmacists and patients.
How We Are Solving It
This project will introduce an AI Pharmacist Assistant and Patient Concierge to MedMe Health’s existing clinical services management tool, currently used by over 3,500 pharmacies. In collaboration with Shoppers Drug Mart for initial commercialization testing in select pharmacies nationwide, the University of Waterloo School of Pharmacy, and Asepha, this solution aims to streamline both the pharmacist and patient journeys across a diverse set of clinical services ranging from acute to chronic and preventative to longitudinal, such as vaccinations, minor ailment assessment and prescribing medication reviews, and chronic disease management. The AI-based solution will enhance four critical stages of their respective journeys:
- Pre-consultation to collect patient information, triage patient concerns, and book appointments when appropriate to reduce pharmacist time spent on manual patient intake, eligibility assessment, and appointment management.
- In-consultation to automatically transcribe the conversation, produce a summary, and extract relevant clinical information to populate data fields in pre-determined formats that meet clinical and billing requirements, thereby reducing pharmacist time spent on manual documentation.
- Post-consultation for a machine learning (ML) model to suggest clinically appropriate treatments and follow-up tasks such as prescriptions, additional appointments and monitoring, or periodic clinical questionnaires based on latest drug monographs and clinical evidence to provide decision support for pharmacists. Examples of usage include:
- During medication review appointments, an AI-powered agent to identify gaps in patient care and issues with medication regimens prior to the appointment visit.
- During travel health appointments, an AI-powered agent can produce vaccine recommendations and provide associated dosing, eligibility requirements, and safety considerations based on patient medical history, travel plans, and guideline recommendations.
- After appointments that require prescriptions, an AI-powered agent can create a personalized handout that considers prescription information as well as patient-specific factors.
4. Continuous Monitoring to identify any potential risks or needs for intervention by using data from patient monitoring device integrations.
Supported by these AI-driven tools, the pharmacist remains the clinical care decision maker and makes all final patient care decisions.
Notifications and two-way messaging supported by AI-facilitated draft responses will help facilitate interactive and personalized patient-pharmacist communication while minimizing administrative burden on pharmacists throughout the journey.
These solutions streamline pharmacist workflows and elevate the patient experience, leading to improved patient outcomes and adherence to treatment plans. Optimized workflows empower pharmacists in conducting proactive care planning, facilitating personalized, longitudinal care delivery. Additionally, AI-enabled clinical decision support based on comprehensive, accurate documentation can enhance patient safety by reducing the rate of medication errors and adverse clinical events. Ultimately, this project will empower pharmacists to practice at the full breadth of their scope and expertise to mitigate the strain on the broader healthcare system both in Canada and globally.
