AI medical scribe: how to conduct a safe pilot in a practice

The benefit is not in producing a note more quickly on screen, but in reducing total documentation work through signature. In practice, compare the typing time that disappears with the time spent reading, correcting, supplementing, and handling exceptions that the draft now requires. If the physician needs to rewrite the entire note, the scribe has merely shifted the work to another stage.

Start with a narrow use case: one specialty, one note template, and a small group of physicians. Define in advance what will count as success, which errors are critical, and the situations in which use will be stopped. The baseline should include time to the signed note, after-hours work, the number of corrections, and perceived documentation burden.

Do not compare only before-and-after averages. Results may vary by specialty, language, visit duration, noise, number of participants, and the physician's familiarity with the medical record. A pragmatic randomized trial involving 238 outpatient physicians from 14 specialties compared two tools with usual care; its design reinforces the need to evaluate the tool, context, and workflow instead of promising a single effect for every practice. (pubmed.ncbi.nlm.nih.gov)

Names vary among vendors, but the operational distinction matters: which data go in, which result comes out, how much context the system interprets, and who needs to review it.

• Medical voice dictation: the physician speaks the content they want to record. The tool converts speech to text, usually under direct command. The physician has better control over the input but remains responsible for organizing the information and checking the result.

• Literal transcription: the system converts a recording into text that is close to the original speech and may identify participants. The primary product is a transcript, not a structured clinical note. A transcription may be faithful to the words and still be of little use for the medical record.

• Ambient scribe: the tool captures the clinical conversation and produces a summary or structured note. It must interpret context, attribute speech, separate the patient's report from the physician's decision, and handle negations, temporality, and medical terms.

• AI medical scribe: this is the broader term for a documentation-support workflow. It may use ambient audio, dictation, or other data to generate a draft. The commercial label alone does not indicate whether there is continuous recording, an intermediate transcript, training with the data, or automatic entry into the medical record. These functions must be confirmed in the actual workflow.

Before clinical use, technical leadership should confirm with qualified professionals which rules and guidance are in force for the workflow, specialty, and context. Until that validation is complete, use clear patient information, complete physician review, auditing, monitoring, and the ability to stop use as minimum safeguards.

For an initial pilot, the output should be a draft that the physician can open, compare with the visit, edit, and discard. The system should not diagnose, prescribe, determine the course of care, invent findings, fill gaps based on plausibility, or sign the note automatically. The safest integration is one in which information reaches the medical record only after review and an explicit action by the professional.

Before clinical use, technical leadership should confirm with qualified professionals which rules and guidance are in force for the workflow, specialty, and context. Until that validation is complete, use clear patient information, complete physician review, auditing, monitoring, and the ability to stop use as minimum safeguards.

The map must track every artifact, not only the initial audio. List raw audio, buffers or temporary segments, transcripts, instructions and context sent to the model, drafts, final notes, access logs, version records, integrations with the medical record, backups, support tickets, and any exports.

For each item, record its purpose, the system where it is stored, its location, the people with access, the retention period, the method of disposal, backup copies, subprocessors, processing outside Brazil, and the procedure in the event of an incident. Also ask whether the data may be used to train or improve models. If the answer depends on a contractual exception or a vague policy, the pilot is not ready.

ANPD recommends administrative and technical security measures, including contract management, access control, protection of stored data, communications security, and vulnerability management. The guide for small processing agents is useful for smaller practices, but it should not be interpreted as an automatic exemption from obligations or as proof that the processing is appropriate for the specific case. (gov.br)

Minimum responsibility matrix:

• Technical leadership: approves the use case, sets the boundaries of clinical risk, defines suspension criteria, and monitors relevant incidents.
• Participating physician: informs the patient in accordance with the protocol, uses the system within scope, reviews the entire draft, corrects discrepancies, and signs only the final version.
• IT and integration: controls identity, permissions, availability, integration with the medical record, technical logs, and the plan for returning to the manual workflow.
• Security and privacy: assesses threats, retention, disposal, encryption, access, subprocessors, transfers, and incident response.
• Data protection officer: coordinates communications about data protection, provides guidance on responding to data subjects, and participates in governance; the officer should not be treated as solely responsible for every decision made by the practice.
• Vendor: documents how the system works, its limitations, versions, access levels, subcontracting arrangements, incidents, significant changes, and data disposal in accordance with applicable instructions and obligations.

Phase 1 — Baseline. Measure the current workflow without the tool. Observe time to the signed note, minutes spent in the medical record after the encounter, after-hours work, the number of corrections, rework, and perceived burden. Use a comparable sample and also record interruptions, long visits, and encounters with multiple participants.

Phase 2 — Simulated cases. Test with synthetic or appropriately de-identified cases before involving patients. Include rapid speech, accents, noise, overlapping voices, medication names, doses, allergies, negations, dates, symptom timing, absent findings, and ambiguous phrases. Compare the draft with a reference reviewed by professionals, not only with the quality of the audio transcription.

Phase 3 — Restricted clinical use. Start with a few physicians and a relatively low-risk workflow. Maintain complete human review, with no automatic signature and no silent entry into the medical record. Give the physician a simple way to deactivate the system during the visit, and record failures, corrections, and near misses. The team must know when to return immediately to the manual process.

Phase 4 — Scale decision. Hold a go/no-go meeting with technical leadership, participating physicians, IT, security, the data protection officer, and the vendor. Decide whether to scale, adjust and repeat the pilot, or stop. The decision must be based on criteria defined in advance, not merely on the impression that the tool appears modern or pleasant to use.

Combine objective and subjective metrics. Evaluate time to signature, after-hours work, the proportion of drafts used, review time, corrections per note, critical clinical omissions, additions not supported by the visit, incidents, downtime, satisfaction, cognitive burden, and patient comfort. A 60-day study involving 40 professionals found an improvement in perceived burden without a significant change in objective documentation minutes; that difference is exactly why both dimensions should be measured. (pubmed.ncbi.nlm.nih.gov)

Validation must also be local. A study of a bilingual Arabic-English scribe showed that language, context, and clinical setting are factors in performance. Its results do not demonstrate performance in Brazilian Portuguese, across all specialties, or in noisy environments. (pubmed.ncbi.nlm.nih.gov)

Review should not depend solely on the physician's memory. Use a short, repeatable sequence: confirm the patient and encounter date; check the complaint, history, and timing; review medications, doses, allergies, and negations; verify the physical examination and results; check the assessment and plan; remove any fact that was not stated or is not supported; confirm referrals, follow-up, and instructions; then sign.

The greatest risk is not an isolated mistranscribed word, but a plausible note that mixes up speakers, turns uncertainty into certainty, or adds a finding that did not occur. During the pilot, classify errors by severity and track cases in which the physician corrected something that could change management, follow-up, medication safety, or communication with another professional.

At a minimum, a go requires mandatory physician review, acceptable quality in the tested language and specialty, a demonstrated reduction in net work, no meaningful increase in critical errors, a complete data map, contractually established responsibilities, logs, support, training, and a plan for stopping use. A no-go applies when review becomes a second complete documentation effort, the vendor does not explain retention or subprocessors, automatic writing occurs without confirmation, the model changes without traceability, or the team cannot investigate a discrepancy.

Scaling does not mean removing oversight. It means expanding a process that has already proved controllable, measurable, and useful for that practice. The goal is to return time to care without shifting the work to endless review or turning a probabilistic output into clinical truth.