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AI& PILOT PROTOCOL DOC

This pilot is designed to test whether AI& can safely and practically support physicians in selected non-autonomous clinical assistance tasks.

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2–4 Week Controlled Pilot for a Physician-Controlled Clinical Assistance System

Version 0.1

  • March 2026


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1. Purpose of the Pilot

This pilot is designed to test whether AI& can safely and practically support physicians in selected non-autonomous clinical assistance tasks.

The pilot does not aim to prove that AI can replace physicians.

The pilot aims to answer a simpler and more useful question:

Can AI& reduce documentation and communication friction while keeping physicians fully in control?


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2. Pilot Objectives

The pilot has four primary objectives:

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2.1 Efficiency

Evaluate whether AI& reduces time spent on repetitive documentation and communication drafting.

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2.2 Quality

Evaluate whether AI& improves consistency, clarity, and structure of outputs.

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2.3 Safety

Evaluate whether AI& can operate without introducing unacceptable risk, misleading outputs, privacy concerns, or workflow disruption.

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2.4 Trust and Adoption

Evaluate whether participating physicians find AI& useful, acceptable, and worth continuing after the pilot.


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3. Pilot Duration

Recommended duration:

  • minimum: 2 weeks

  • ideal: 3 to 4 weeks

This duration is long enough to observe patterns, but short enough to remain controlled and easy to review.


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4. Pilot Scope

The pilot must remain narrow and highly controlled.

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Recommended First Use Cases

Choose only 1 to 2 use cases for the pilot.

Preferred options:

  1. SOAP note draft generation

  2. Structured visit summary drafting

  3. Patient education draft generation

  4. Follow-up reminder drafting

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Not Included in the Pilot

The pilot must not include:

  • autonomous diagnosis

  • autonomous triage

  • medication recommendation

  • emergency guidance


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5. Pilot Participants

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5.1 Physician Participants

Recommended:

  • 1 primary physician

  • optional: 1 to 3 additional physicians after initial validation

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5.2 Operational Participants

May include:

  • project coordinator

  • technical support person

  • compliance or quality reviewer

  • note-taker for feedback sessions

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5.3 Patients

Patients are not system operators in this pilot.

If patient-linked data is involved, all handling must follow the defined data governance rules.


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6. Entry Criteria Before Pilot Starts

The pilot may begin only if the following conditions are met:

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6.1 Use Case Is Defined

One or two pilot tasks are selected clearly.

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6.2 Workflow Is Agreed

All participants understand:

  • when AI& may be used

  • who reviews outputs

  • what happens if outputs are poor

  • what is logged

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6.3 Safety Boundaries Are Agreed

All participants agree that:

  • physicians remain the final decision-makers

  • no AI output is final without physician review

  • no autonomous patient communication is allowed

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6.4 Templates Are Ready

At least basic templates exist for the selected use cases.

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6.5 Logging Is Ready

The team can record:

  • AI usage events

  • review outcomes

  • corrections

  • incidents


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7. Pilot Workflow

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Step 1 – Select Eligible Case

A participating physician identifies a case appropriate for pilot use.

Examples:

  • routine documentation case

  • follow-up case

  • patient education need

  • non-emergency outpatient interaction

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Step 2 – Enter Structured Input

The physician provides structured input into AI&.

Possible inputs:

  • chief complaint

  • relevant history

  • findings

  • assessment points

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Step 3 – Generate Draft

AI& generates a draft according to the selected workflow.

Examples:

  • SOAP note draft

  • education message draft

  • follow-up summary draft

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Step 4 – Physician Review

The physician must review the draft before any use.

The physician may:

  • approve

  • edit

  • reject

  • regenerate

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Step 5 – Final Use

Only physician-approved output may be used in real workflow.

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Step 6 – Logging

The system or team records:

  • type of task

  • time used

  • degree of correction needed

  • whether output was useful


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8. Case Selection Rules

The pilot should begin with cases that are relatively stable and low-risk.

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Good Early Cases

  • routine follow-up visits

  • straightforward documentation tasks

  • patient education messages for familiar conditions

  • structured note conversion tasks

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Poor Early Cases

  • emergencies

  • highly ambiguous complex cases

  • medico-legal conflict situations

  • emotionally sensitive or crisis communication

The pilot should begin in calm water, not in the storm.


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9. Review Rules

The pilot must define clear review rules.

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Mandatory Review Rule

Every AI-generated output must be reviewed by the responsible physician before use.

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Minimum Review Actions

The physician must check:

  • factual alignment with the encounter

  • clarity of wording

  • completeness

  • safety of advice or explanation

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Rejection Rule

If the output is misleading, incomplete, or confusing, it must not be used.

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Escalation Rule

If the output raises a safety concern, the incident must be logged and reviewed.


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10. Logging Requirements

The pilot should collect both quantitative and qualitative data.

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10.1 Quantitative Log

For each AI-assisted case, record:

  • date

  • physician name or identifier

  • use case type

  • draft generation time

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10.2 Qualitative Log

Record:

  • physician comments

  • moments of trust or distrust

  • unclear phrasing

  • missing information

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10.3 Incident Log

Record separately:

  • misleading clinical wording

  • privacy concern

  • wrong context carryover

  • source issue in evidence summary


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11. Success Metrics

The pilot should define success before it begins.

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11.1 Efficiency Metrics

  • average time saved per task

  • reduction in repetitive writing effort

  • faster preparation of communication drafts

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11.2 Quality Metrics

  • physician rating of clarity

  • physician rating of usefulness

  • consistency of structure

  • completeness of documentation draft

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11.3 Safety Metrics

  • number of rejected outputs

  • number of significant corrections

  • number of incidents or near-misses

  • number of privacy concerns

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11.4 Adoption Metrics

  • percentage of eligible cases where AI& was used

  • repeat voluntary use by physicians

  • willingness to continue after pilot


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12. Simple Scoring Framework

A lightweight scoring framework may be used after each AI-assisted case.

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Per Case Score (1–5)

Physician rates:

  1. usefulness

  2. clarity

  3. time saved

  4. trustworthiness

Optional note:

  • “Would I use this again for a similar case?”


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13. Weekly Review Structure

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End of Week 1

Review:

  • whether the chosen use case was correct

  • whether outputs are generally usable

  • whether templates need adjustment

  • whether workflow is too heavy or too light

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End of Week 2

Review:

  • patterns in editing

  • trust levels

  • repeated weaknesses

  • safety observations

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End of Week 3–4

Review:

  • whether to continue

  • whether to revise scope

  • whether to add one additional use case

  • whether technical deeper build should proceed


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14. Stop / Pause Criteria

The pilot must pause immediately if any of the following occurs:

  • repeated misleading outputs

  • privacy or confidentiality breach

  • unauthorized access issue

  • physician cannot review efficiently

The goal of the pilot is not to force success. The goal is to learn safely.


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15. Fallback Workflow

At any point, the physician must be able to continue manually.

Fallback rule:

If AI& is unavailable, poor, uncertain, or unsafe, normal physician workflow continues without dependence on AI&.

No clinical process should become blocked because AI& failed.


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16. Pilot Deliverables

At the end of the pilot, the team should produce:

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16.1 Pilot Summary

A short narrative of what was tested.

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16.2 Metrics Summary

A simple report of:

  • number of cases

  • use case types

  • efficiency observations

  • quality observations

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16.3 Template Revision Notes

A record of what should be improved.

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16.4 Go / Revise / Stop Recommendation

A final recommendation:

  • Go forward to next phase

  • Revise and repeat pilot

  • Stop due to risk or lack of value


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17. Suggested Pilot Timeline

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Week 0 – Preparation

  • choose use case

  • define workflow

  • finalize review rules

  • prepare templates

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Week 1 – Controlled Initial Use

  • first 5 to 10 cases

  • close observation

  • collect correction patterns

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Week 2 – Adjustment

  • revise templates

  • refine prompts

  • improve review process

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Week 3 – Broader Controlled Use

  • continue with improved workflow

  • observe stability

  • track repeat behavior

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Week 4 – Evaluation

  • summarize findings

  • assess trust, usefulness, and safety

  • decide next step


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18. Recommended First Decision After Pilot

At the end of the pilot, the team should answer one central question:

Did AI& make physician work clearer and lighter without weakening safety, privacy, or control?

If the answer is yes, the team may proceed to:

  • technical architecture detail

  • security architecture detail

  • product requirement specification

  • mock-up / UI-UX design

If the answer is partially yes, the team should revise the pilot design and repeat.

If the answer is no, the project should pause and reconsider scope.


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19. Final Principle

The pilot is successful not when AI looks impressive, but when physicians remain confident, careful, and more present with patients.

That is the standard.


P.S. Other documents related to this document:

  • Document 1 –

  • Document 2 –

  • Document 3 –

  • Document 4 –


P.S.S. Read this document freely for information and guidance. Do not redistribute or restate—no quotes, summaries, paraphrases, or derivatives—without prior written permission from . Sharing the link is allowed. So, share the link, not the text. Do not discuss or re-tell the contents in any form—written, spoken, or recorded—without prior written permission.


Evidence summary for physician review

unsupervised patient messaging

  • direct patient-facing AI interaction

  • unrestricted sharing of patient-linked data across physicians

  • feedback

    plan points

  • communication goals

  • whether any issue occurred

    cases requiring urgent escalation

    appropriateness of tone

    review time

  • whether output was approved, edited, or rejected

  • approximate level of correction required

  • whether output was ultimately used

  • useful outputs

  • workflow friction points

  • unauthorized access concern

  • output that could have caused a near-miss

  • amount of editing needed

    workflow becomes more burdensome than manual work

  • team confidence drops due to unresolved safety concern

  • safety observations

    align pilot participants

    second pilot design

    (this document)
  • Document 5 –

  • Presentation Narrativearrow-up-right
    Strategic Notes and Referencesarrow-up-right
    Product Blueprintarrow-up-right
    Pilot Protocolarrow-up-right
    Prof. NOTAarrow-up-right
    Discussion Logarrow-up-right