Originally published in June, 2026, by The Medical Post
Author: Michelle Greiver
I have practiced family medicine in my community for more than 40 years. During that time, I have witnessed substantial changes in the way we gather and record information and conduct visits. Long-term use of electronic medical records followed by the shift to virtual care during the COVID‑19 pandemic prompted me to explore ways to modernize encounters. My goal is to improve patient‑centred care and outcomes, reduce administrative burden and maintain work-life balance.
Traditionally, information was collected during clinic visits. Patients received instructions verbally, sometimes complemented by printed handouts. Over time, I began experimenting with strategies to shift some of this work to before and after the visit, particularly through automated questionnaires, artificial intelligence (AI) tools and emailed follow‑up communication. I also implemented an AI scribe to assist with documentation.
Pre-visit info gathering
Scheduled appointments now trigger automated reminders linked to the patient's information; this approach has been shown to increase completion of patient data in the record. Formatting... Patients receive an initial reminder seven days before their appointment and a second reminder two days prior. The latter includes a visit confirmation request and a set of digital questionnaires tailored to the encounter type. All patients receive a consent form for the AI scribe.
For general visits, patients receive a questionnaire that expands based on their responses. There is evidence that pre‑visit questionnaires improve documentation accuracy and prompt more comprehensive discussions during the visit. If a patient is booked for a diabetes visit, they receive a diabetes‑specific questionnaire; if the visit is preventive, they receive a preventive health questionnaire. An additional field in the schedule indicates a reason for visit using a structured list (e.g., heart failure, COPD, anxiety, depression, asthma); the patient is then also sent condition specific questionnaires.
Patients aged 18–30 automatically receive information about screening for chlamydia and gonorrhea, consistent with current recommendations. This approach ensures that by the time patients arrive, the nurse and I have relevant information that supports a more focused and efficient clinical encounter.
Interprofessional visit workflow
Our medical office assistants take the patient's vitals and enter the data in the EMR; the patient is then shown into an exam room. Many encounters—particularly chronic disease management visits, new patient visits, well baby checks and periodic health exams—are conducted collaboratively: our nurse sees the patient first and then I see them. Before entering the room, we review the vitals and submitted questionnaires to identify concerns. Chart alerts remind us of immunizations and preventive care that may be due. The benefits of workflow optimization and prepared, proactive visits are well documented.
After confirming patient consent, I activate the AI scribe for real‑time documentation. As we know, studies have shown that AI scribes can reduce documentation time and improve physician well‑being. I renew and send prescriptions directly to the pharmacy during the visit.
Patients have told me that they appreciate having their concerns recorded before the visit. This provides them with an additional opportunity to think about what they wish to discuss.
AI-supported documentation and post-visit info
At the end of the encounter, the AI scribe generates a structured visit summary using the SOAP format, which is exported to the chart, and a patient‑friendly summary. I review and update the note for accuracy before finalizing it, as AI can produce errors. I copy the summary outlining actions and securely email it to the patient; this also automatically becomes part of the record.
When clinically appropriate, I use AI decision support tools (OpenEvidence) to assist with differential diagnosis and management. The AI can also generate tailored patient handouts, which are added to the post‑visit email. Patients retain less than half of visit details; effective digital information can improve comprehension, adherence and outcomes.
Impact on workflow and patient care
My clinical time focuses more on paying attention to the patient, shared decision‑making and less on clerical tasks.
A practice audit by my resident found that my median face-to-face encounter time is 11 minutes. The additional time needed to review the pre-visit information, the AI scribe note and email information is manageable: nurse encounters are booked for advertisement half an hour and mine are usually booked at 15-minute intervals; I usually run on time. I may leave some clerical aspects such as finalization of notes and billing to the end of my shift.
Conclusion
Integrating automated pre-visit digital questionnaires, AI‑assisted documentation, collaborative care and a post-visit patient summary into my community practice has modernized my patient encounters without increasing my workload. These tools can indeed enhance patient engagement, support clinical decision‑making and reduce administrative burden. Digital automation and AI can allow more time for the human and relational aspects of care associated with better outcomes in longitudinal family practice.
I believe that these strategies can be gradually adopted and adapted for the needs of other practices. As primary care evolves, thoughtful implementation of technology has the potential to improve care delivery while preserving the relational core of family medicine.