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Slide 1Slide 2Slide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19
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2026-08-23T02:45:08Z
2026-08-23T02:45:08Z
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AI IN DAILY MEDICAL PRACTICEModule 2AI for Clinical Documentation & Administrative EfficiencySelf-paced · ~3 hrs totalAI in Daily Medical Practice — a curriculum for practicing physiciansPK
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BEFORE YOU STARTHow this self-paced module works1Preview Quiz5 min, ungraded. Orients you before reading.→2Handout / SlidesIncludes a worked exercise — do it actively.→3Post-Test12 questions, scored. 80% pass, retake anytime.→4Module 3Opens once Module 2 is evaluated.2PK
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BY THE END OF THIS MODULEYou will be able to1Use an AI documentation/scribing tool safely and effectively within a real clinical encounter.2Apply verification habits that catch errors in an AI-drafted note before they reach the chart.3Evaluate which documentation tools are practical given your own connectivity, language, and data-privacy constraints.3PK
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ASECTION AWhy Documentation IsWhere This Course StartsKNOW4PK
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SECTION A · FRAMINGKeyboard liberationAcross the sources behind this curriculum, one theme was more consistent than any other: physicians spend a disproportionate share of clinic time charting rather than treating. Exact figures vary — the direction and the frustration don't.“Ambient documentation” listens to — or reads a transcript of — an encounter and drafts a structured note, so the physician stays with the patient instead of the keyboard. That's the goal “keyboard liberation” describes.Why this module comes before diagnostic AI (Module 3): lower relative risk, and a fast, visible win that builds trust before higher-stakes applications.5PK
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BSECTION BHow AI ScribesActually WorkKNOW6PK
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SECTION B · THE BASIC PIPELINEFour steps, every time1Audio ortranscript captured→2Speech convertedto text (if audio)→3LLM structures itinto a note format→4Draft handed to youfor reviewThe draft is a starting point, never a finished note — that's the entire subject of Section C.7PK
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SECTION B · FAILURE MODES (1/2)The same risks, now inside a noteHallucinationA detail appears that was never actually said — a symptom, a value, a plan.MisattributionSomething the patient said gets written as the physician's assessment, or vice versa.Silent omissionThe model drops a detail it judged “unimportant” — especially dangerous for allergies mentioned once.8PK
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SECTION B · FAILURE MODES (2/2)...continuedPlausible-value fillingWhen information was genuinely missing, the model may still generate a realistic-sounding value rather than a blank.MishearingA spoken number is transcribed wrong — “20 mg” heard as “200 mg” — then carried through with full confidence.9PK
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CSECTION CEditing, Verifying,and Signing OffTHINK10PK
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SECTION C · WORKED EXERCISE — STEP 1Read this transcript firstFollow-up visit, known hypertensionPhysician: How have you been since we adjusted your blood pressure medication last month?Patient: Better. Less of that morning headache. Taking the lisinopril, 10 milligrams, every morning like you said.Physician: Good. Any dizziness, ankle swelling, cough?Patient: No cough. Ankles were a little swollen last week but that's better now.Physician: Your blood pressure today is 138 over 86 — improved. Same dose, back in two months. I saw a penicillin allergy in your file — still accurate?Patient: Yes, still allergic. Breaks me out in hives.11PK
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SECTION C · WORKED EXERCISE — STEP 2Now the AI-drafted noteBefore you turn the page: what's wrong with it? (highlighted phrases are the planted errors)Subjective: Improvement since medication adjustment. Taking lisinopril 20 mg daily. Denies headache, cough, and ankle swelling. Objective: BP 128/82 today, improved from prior visit. Assessment: Hypertension, well-controlled on current regimen. Plan: Continue current dose. Follow up in 2 months. No known drug allergies.12PK
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SECTION C · WORKED EXERCISE — ANSWER KEYFour errors were planted1Dosage errorPatient said 10 mg; draft says 20 mg — a mishearing error with real clinical consequence.2Symptom reversedPatient described improving ankle swelling; draft states swelling was denied entirely.3Value driftTranscript: 138/86. Draft: 128/82 — a fabricated but plausible-sounding number.4Dangerous omissionPatient confirmed a penicillin allergy; draft says “no known drug allergies.” The most dangerous error here.Caught three or four on your own? Good instinct. Fewer? That's exactly why this exercise exists.13PK
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SECTION C · A CHECKLIST YOU CAN ACTUALLY USEBefore you signChief complaint and history match what was actually saidEvery medication name, dose, and frequency checked against what was statedAllergies confirmed present and accurate — never assume “none” by defaultVital signs and numeric values cross-checked against the sourcePlan and follow-up instructions match what was actually agreedNo detail appears that you don't remember being said14PK
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DSECTION DData Quality and theDocumentation Feedback LoopKNOW15PK
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SECTION DYour notes may train the next versionMany documentation tools use clinician-reviewed notes to improve future versions of the model — subject to each vendor's own data and consent policies. A sloppy or uncorrected note doesn't just sit wrong in one chart.PRACTICAL HABITTreat every note you sign as if it might teach the next version of the software — because for some products, it may do exactly that.16PK
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SECTION E · FIND / THINKTools That Work in Your SettingA self-directed worksheet in the handout, same format as Module 1. Work through it before you actually select a tool.1Does the tool need to work with intermittent or no internet during a consultation?2What language(s) do your encounters happen in — and does it draft notes accurately, not just transcribe?3Where is the audio or transcript data stored, for how long, and who can access it?4What does it cost on an ongoing basis — sustainable, not just affordable once?5Does it need to integrate with an existing record system, or work standalone?17PK
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BEFORE YOU MOVE ONModule 2 summaryKNOWWhat ambient documentation tools do, the capture-to-draft pipeline, five documentation-specific failure modes, and the documentation feedback loop.THINKA trained verification habit, practiced on a worked example, plus a reusable pre-signing checklist.FINDA first pass at judging documentation-tool fit — connectivity, language, data storage, cost, integration.18PK
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NEXT STEPSTake the Post-Test12 scored questions, 80% pass mark. Once Module 2 is evaluated, Module 3 — AI-Supported Clinical Decision Making — opens next.Module 2 of 6 — AI for Clinical Documentation & Administrative Efficiency19PK
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7/23/19Click to edit Master text stylesSecond levelThird levelFourth levelFifth level‹#›PK
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