{"id":11017,"date":"2026-08-14T00:30:00","date_gmt":"2026-08-14T08:30:00","guid":{"rendered":"https:\/\/www.osmosis.org\/blog\/?p=11017"},"modified":"2026-08-13T15:15:04","modified_gmt":"2026-08-13T23:15:04","slug":"how-to-use-generative-ai-for-clinical-documentation","status":"publish","type":"post","link":"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation","title":{"rendered":"How to Use Generative AI for Clinical Documentation\u00a0"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_86 ez-toc-wrap-center counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">In This Article<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Why_Clinical_Documentation_Needs_Better_Workflow_Support\" >Why Clinical Documentation Needs Better Workflow Support&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Who_documents_what_in_the_clinical_workflow\" >Who documents what&nbsp;in&nbsp;the clinical workflow?&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#From_Smart_Phrases_to_Source-grounded_AI\" >From Smart Phrases to Source-grounded AI&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Know_Your_AI_Assistants_A_Quick_Glossary\" >Know Your AI Assistants: A Quick Glossary&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#A_Patient_Journey_AI-assisted_Documentation_from_Admission_to_Discharge\" >A Patient Journey: AI-assisted Documentation from Admission to Discharge&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Where_Generative_AI_Helps_Most_in_Clinical_Documentation\" >Where Generative AI Helps Most in Clinical Documentation&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Why_Trusted_Sources_and_Clinician_Review_Matter\" >Why Trusted Sources and Clinician Review Matter&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#The_Risks_of_AI-generated_Clinical_Documentation\" >The Risks of AI-generated Clinical Documentation&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Best_Practices_for_Responsible_AI-assisted_Documentation\" >Best Practices for Responsible AI-assisted Documentation&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Prompts_to_Consider_Matching_Your_Prompt_to_Your_Task_Role_and_Venue\" >Prompts to Consider: Matching Your Prompt to Your Task, Role, and Venue&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#The_Future_of_AI-Assisted_Clinical_Documentation\" >The Future of AI-Assisted Clinical Documentation&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#FAQ_Generative_AI_and_Health_Documentation\" >FAQ: Generative AI and Health Documentation&nbsp;<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#What_is_AI-assisted_clinical_documentation\" >What is AI-assisted clinical documentation?\u00a0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#How_does_generative_AI_help_with_EHR_documentation\" >How does generative AI help with EHR documentation?\u00a0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Can_AI_reduce_clinician_documentation_burden\" >Can AI reduce clinician documentation burden?\u00a0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#What_are_the_risks_of_AI-generated_clinical_notes\" >What are the risks of AI-generated clinical notes?\u00a0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#How_can_healthcare_teams_use_AI_safely_in_documentation\" >How can healthcare teams use AI safely in documentation?\u00a0<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#Key_Takeaways\" >Key Takeaways<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.osmosis.org\/blog\/how-to-use-generative-ai-for-clinical-documentation\/#References\" >References&nbsp;<\/a><\/li><\/ul><\/nav><\/div>\n\n<p class=\"wp-block-paragraph\"><strong>Generative artificial intelligence, or Gen AI, is beginning to show up across electronic health records (EHR)<\/strong> from <strong>ambient scribes<\/strong> in the exam room to <strong>chart summaries<\/strong> at the nurses\u2019 station. So, what does that mean for clinicians and caregivers? <strong>AI-assisted clinical documentation<\/strong> that helps care teams <strong>draft notes, summarize records, organize handoffs, and prepare discharge and patient information.<\/strong> But it works best when healthcare organizations build <strong>trusted sources, patient privacy safeguards, human review, and clear accountability<\/strong> from the start. This article focuses on <strong>AI tools that support creation, organization, review, and communication of clinical documentation, not diagnosis or autonomous clinical decision-making.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Why_Clinical_Documentation_Needs_Better_Workflow_Support\"><\/span><strong>Why Clinical Documentation Needs Better Workflow Support<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Clinical\u00a0<a href=\"https:\/\/www.osmosis.org\/learn\/Standards_and_methods_of_documentation:_Nursing\" target=\"_blank\" rel=\"noreferrer noopener\">documentation<\/a>\u00a0is one of the most important communication tools in healthcare, but it can also create a <strong>heavy administrative burden.<\/strong> The EHR helps clinicians organize patient information, support billing, improve continuity of care, and meet regulatory requirements. At the same time, EHR work can pull clinicians away from direct patient care and add hours of after-hours documentation time. Recent studies of <strong>ambient AI documentation tools<\/strong> suggest that <strong>AI-assisted documentation can reduce time spent in notes, improve documentation efficiency, and ease cognitive load for some clinicians.<\/strong> However, outcomes still depend on careful implementation and oversight. The use of ambient AI tools helps not only improve documentation but also helps clinicians spend more time with patients. Organizations should expect outcomes to vary depending on <strong>workflow design, governance, clinician training, and adoption.<\/strong> AI is most effective when it complements well-designed clinical processes rather than attempting to replace them.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The real opportunity isn&#8217;t just faster note-writing. <strong>It&#8217;s better workflow support: help finding information, organizing the patient story, documenting medical decision-making, communicating across teams, and preparing safe transitions.<\/strong> So far, generative AI&#8217;s biggest impact has been on <strong>workflow and communication, not replacing clinical judgment.<\/strong> It can help with all the above when healthcare organizations pair it with <strong>trusted sources, privacy safeguards, transparent attribution, and human review.<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image alignright size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"379\" height=\"454\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/note-clipboard.png\" alt=\"Osmosisi.org style illustration of a clipboard holding a bulleted document with a red pen resting on top representing patient documentation.\" class=\"wp-image-11036\" style=\"width:297px;height:auto\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/note-clipboard.png 379w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/note-clipboard.png?resize=250,300 250w\" sizes=\"auto, (max-width: 379px) 100vw, 379px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Who_documents_what_in_the_clinical_workflow\"><\/span><strong>Who documents what&nbsp;in&nbsp;the clinical workflow?<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AI-assisted documentation touches more than one kind of clinical note. Clinicians, care managers, social workers, therapists, dietitians, patient educators, learners, and educators all create or use documentation differently. <strong>Defining those roles up front makes it easier to see where AI fits<\/strong>, and it helps to understand the chart itself first. As nurse educator Paige Randall explains in <a href=\"https:\/\/www.osmosis.org\/blog\/the-anatomy-of-a-chart-how-to-read-and-interpret-an-ehr\">The Anatomy of a Chart<\/a>, the EHR is organized into core sections, including demographics, admission notes, results, the medication administration record, assessments, and health maintenance. <strong>Each section helps a different part of the care team understand the patient\u2019s story.<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Prescribers document histories, physical exams, assessments, diagnoses, medical decision-making, orders, prescriptions, medication renewals, referrals, patient messages, procedure notes, discharge summaries, and attestation.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Nurses document assessments, vital signs, medication administration, care plans, patient education, safety checks, escalation concerns, intake and output, discharge readiness, and shift-handoff reports, following\u00a0<a href=\"https:\/\/www.osmosis.org\/learn\/Standards_and_methods_of_documentation:_Nursing\" target=\"_blank\" rel=\"noreferrer noopener\">standardized documentation methods<\/a>\u00a0and using\u00a0<a href=\"https:\/\/www.osmosis.org\/video\/Communication_and_relational_practice:_Nursing\" target=\"_blank\" rel=\"noreferrer noopener\">therapeutic communication<\/a>\u00a0to relay what changed.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Pharmacists document medication reconciliation, drug therapy recommendations,\u00a0<a href=\"https:\/\/www.osmosis.org\/learn\/Safety_in_Medication_Administration\" target=\"_blank\" rel=\"noreferrer noopener\">safety principles in medication administration<\/a>, renal dosing considerations, allergy reviews, formulary substitutions, patient counseling, and discharge medication plans.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Care managers and social workers document discharge barriers, insurance or placement needs, social drivers of health, transportation, home support, follow-up needs, and community resources.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Therapists, dietitians, and patient educators document functional status, nutrition recommendations, mobility goals, patient understanding, education provided, and next steps.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Learners and educators use documentation to understand clinical reasoning, patient safety, communication, care coordination, and professional accountability, a theme we dig into in\u00a0<a href=\"https:\/\/www.osmosis.org\/blog\/embracing-technology-in-nursing-education-innovation-inclusion-and-impact\" target=\"_blank\" rel=\"noreferrer noopener\">Embracing Technology in Nursing Education<\/a>.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"From_Smart_Phrases_to_Source-grounded_AI\"><\/span><strong>From Smart Phrases to Source-grounded AI<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Healthcare documentation has been evolving for decades. <strong>Smart phrases, dot phrases, templates, order sets, flowsheets, and prepopulated fields<\/strong> helped clinicians cut repetition and standardize routine notes. Connected devices and mobile documentation tools made some of that even more automatic, with vital signs flowing straight into the EHR and barcode medication administration syncing to the patient record.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Generative AI extends that progression.<\/strong> Ambient clinical documentation tools, sometimes called <strong>AI-powered medical scribes<\/strong>, can draft encounter notes from a clinical conversation. Enterprise chatbots can help staff retrieve policies or summarize operational information. <strong>Source-grounded AI connects responses to trusted knowledge bases instead of unsupported open-web output.<\/strong> Tools such as <a href=\"https:\/\/www.elsevier.com\/products\/clinicalkey-ai\">ClinicalKey AI<\/a> and <a href=\"https:\/\/www.osmosis.org\/features\/osmosis-ai\">Osmosis AI<\/a> build on <strong>trusted content, citations, and human oversight.<\/strong> That evidence-grounded design makes them different from general-purpose chatbots and easier to verify before the output becomes part of clinical documentation or education. ClinicalKey AI can be embedded directly into the EHR and integrated with ambient documentation tools, bringing <strong>trusted, evidence-based content into clinicians&#8217; workflows at the point of care.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Know_Your_AI_Assistants_A_Quick_Glossary\"><\/span><strong>Know Your AI Assistants: A Quick Glossary<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Not every tool called \u201cAI\u201d in healthcare does the same job.<\/strong> Before the patient journey below,\u00a0here&#8217;s\u00a0a\u00a0plain-language\u00a0look at the categories referenced throughout this piece.\u00a0<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Ambient AI scribes:\u00a0<\/strong>Listen to a clinical encounter and draft a note in real time. <strong>Chart-aware by\u00a0design<\/strong>, since\u00a0they&#8217;re\u00a0built to capture the visit as it happens.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>EHR-embedded AI assistants:\u00a0<\/strong>Live inside the EHR itself.\u00a0<a href=\"https:\/\/www.elsevier.com\/products\/clinicalkey-ai\" target=\"_blank\" rel=\"noreferrer noopener\">ClinicalKey AI<\/a>\u00a0is one example, <strong>surfacing evidence-based answers and supporting inbox drafting, renewals, and handoffs without clinicians leaving the chart.\u00a0<\/strong><\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Source-grounded knowledge and education tools:\u00a0<\/strong>Standalone tools such as\u00a0ClinicalKey\u00a0AI&#8217;s general query mode and\u00a0<a href=\"https:\/\/www.osmosis.org\/features\/osmosis-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Osmosis AI<\/a>\u00a0answer clinical or teaching questions from <strong>cited, vetted content<\/strong>, but without access to a specific patient&#8217;s chart.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Research-grade AI workspaces:\u00a0<\/strong>Elsevier&#8217;s\u00a0<a href=\"https:\/\/www.elsevier.com\/products\/leapspace\" target=\"_blank\" rel=\"noreferrer noopener\">LeapSpace<\/a>\u00a0is built for <strong>literature synthesis, hypothesis generation, and evidence review across millions of peer-reviewed articles<\/strong>.\u00a0It&#8217;s\u00a0a strong fit for teams\u00a0researching\u00a0or\u00a0writing\u00a0documentation policy, but it\u00a0isn&#8217;t\u00a0a chart-facing tool and\u00a0doesn&#8217;t\u00a0belong in a bedside prompt workflow.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>General-purpose public AI chatbots:\u00a0<\/strong>Consumer tools with no patient context and, in most organizations, <strong>no approval to touch protected health information (PHI)<\/strong>. Useful for non-clinical drafting only.\u00a0<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"826\" height=\"184\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/handing-over-discharge-paperwork.png\" alt=\"Illustration of one hand passing an envelope to another outstretched hand.\" class=\"wp-image-11035\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/handing-over-discharge-paperwork.png 826w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/handing-over-discharge-paperwork.png?resize=300,67 300w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/handing-over-discharge-paperwork.png?resize=768,171 768w\" sizes=\"auto, (max-width: 826px) 100vw, 826px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"A_Patient_Journey_AI-assisted_Documentation_from_Admission_to_Discharge\"><\/span><strong>A Patient Journey: AI-assisted Documentation from Admission to Discharge<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A patient journey makes the documentation opportunity easier to see because it shows how information moves from one setting to the next. A patient journey makes the documentation opportunity easier to see because it shows how information moves from one setting to the next. At\u00a0a high level, <strong>AI-assisted clinical documentation follows a repeatable workflow<\/strong>:\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Encounter \u2192 Draft \u2192 Review \u2192 Attest \u2192 Code \u2192 Follow-up<\/strong>&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Encounter:<\/strong>\u00a0Clinical information is captured during patient care.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Draft:<\/strong>\u00a0AI organizes information and drafts documentation from the clinical encounter or other approved sources.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Review:<\/strong>\u00a0The clinician verifies the draft for accuracy, completeness, and clinical context.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Attest:<\/strong>\u00a0The responsible clinician edits the documentation as needed and attests to its accuracy before it becomes part of the medical record.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Code:<\/strong>\u00a0Documentation supports coding, billing, and quality reporting, with human coding oversight.\u00a0<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Follow-up:<\/strong>\u00a0The documentation supports handoffs, discharge planning, remote monitoring, and ongoing care.\u00a0<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The patient journey below illustrates how each step builds on the\u00a0previous\u00a0one. Now\u00a0let\u2019s\u00a0follow a 72-year-old patient who arrives in the emergency department with shortness of breath, fatigue, and leg swelling. The clinician opens the chart and uses <strong>AI-assisted clinical documentation to create a history and physical draft that organizes the patient\u2019s story into a clear timeline<\/strong>: heart failure diagnosed five years ago, diabetes for more than a decade, chronic kidney disease progression over the past two years, two recent medication changes, three missed follow-up appointments, and a new increase in dyspnea over the past week.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The AI-generated timeline is not the final note. The clinician reviews it, corrects missing context, verifies the source material, and turns the draft into a clinically\u00a0accurate\u00a0history and physical<\/strong>. That specificity matters beyond the chart. For example, a note that says \u201c<a href=\"https:\/\/www.osmosis.org\/learn\/Right_heart_failure:_Clinical_sciences\" target=\"_blank\" rel=\"noreferrer noopener\">acute on chronic systolic heart failure<\/a>\u201d gives the coding team more precise information than a note that only\u00a0says\u00a0\u201cheart failure.\u201d The same idea applies to chronic kidney disease, where the stage matters. A chart-aware AI tool can help capture those details as they are documented, so the coding team has clearer information and fewer vague terms to clarify later. During hospitalization, the care team can also use AI to <strong>draft a shift-handoff report in situation, background, assessment, and recommendation or request format<\/strong>, a structured way to communicate what is happening, why it matters, what the assessment shows, and what should happen next [8,9].\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The pharmacist completes a <strong>medication reconciliation<\/strong>, reviewing the home medication list with inpatient orders and flagging medication renewal requests that need prescriber review. The care manager summarizes <strong>barriers to discharge<\/strong>, including transportation, follow-up access, and home support, work that\u00a0builds on\u00a0the nurse&#8217;s discharge-planning role throughout the stay.\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">At discharge, <strong>AI helps the team prepare personalized discharge instructions<\/strong> that reflect the patient&#8217;s health literacy, medication changes, diet recommendations, warning signs, follow-up appointments, and teach-back questions. The prescriber reviews medication renewals and documents the rationale for continuing, stopping, or adjusting therapy. The nurse reinforces the plan with plain-language instructions.\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Behind the scenes, coding runs alongside\u00a0all of\u00a0this rather than waiting until the end. As the prescriber documents heart failure, diabetes, and chronic kidney disease (CKD) progression, the pharmacist documents medication changes, and the care team documents each intervention, <strong>AI can track that running list against the diagnoses and procedures actually addressed during the stay<\/strong>, checking it against\u00a0<a href=\"https:\/\/www.cms.gov\/medicare\/coding-billing\/icd-10-codes\" target=\"_blank\" rel=\"noreferrer noopener\">ICD-10-CM<\/a>\u00a0diagnosis codes and\u00a0<a href=\"https:\/\/www.ama-assn.org\/practice-management\/cpt\" target=\"_blank\" rel=\"noreferrer noopener\">Current Procedural Terminology (CPT)<\/a>\u00a0procedure codes as it goes. Before the encounter closes, CPT flags that a condition was treated but never formally documented, a diagnosis that&#8217;s missing the specificity a payer will need, or a procedure note that doesn&#8217;t yet have a matching code, so the coding and billing team gets an accurate, complete picture instead of chasing clarifications after the patient has already gone home. <strong>A human coder still makes the final call on every code\u00a0submitted<\/strong>, but\u00a0they&#8217;re\u00a0reviewing AI-assembled documentation instead of reconstructing it from scratch.\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the days after discharge, <strong>the documentation trail\u00a0doesn&#8217;t\u00a0stop at the hospital doors<\/strong>. A home health nurse or care coordinator reviews the discharge summary and any connected remote-monitoring data, like a home scale or blood pressure cuff, and uses AI to flag concerning trends. A telephonic follow-up team drafts outreach scripts grounded in that same discharge plan, reviews incoming patient portal messages for early\u00a0warning signs, and summarizes each call back into the chart. If the patient calls in with worsening swelling or shortness of breath, that update joins the same documentation\u00a0trail\u00a0the inpatient team built, so the story\u00a0doesn&#8217;t\u00a0have to be reconstructed from scratch. <strong>That continuity is the real payoff: the home care team\u00a0isn&#8217;t\u00a0starting from a blank page.\u00a0They&#8217;re\u00a0picking up a clearly documented story that AI helped the entire care team keep organized.\u00a0<\/strong>\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Across the full transition, from the emergency department to the hospital floor to the home, <strong>AI helps the care team move from scattered data to organized clinical communication.<\/strong> The final documentation at every step still needs <strong>human review and clinician attestation.<\/strong> But when used responsibly, AI can help create a <strong>clearer, safer, and more connected journey from hospital to home and beyond.<\/strong>\u00a0\u00a0<\/p>\n\n\n\n<figure class=\"wp-block-image alignleft size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"520\" height=\"893\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/nurse-using-computer-and-documenting.png\" alt=\"Osmosis.org illustration of a healthcare professional seated at a mobile computer workstation, typing on a keyboard and reviewing information on a monitor. The image represents electronic health record documentation, digital clinical workflows, or technology use in patient care.\" class=\"wp-image-11034\" style=\"aspect-ratio:0.5823197011780481;width:267px;height:auto\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/nurse-using-computer-and-documenting.png 520w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/nurse-using-computer-and-documenting.png?resize=175,300 175w\" sizes=\"auto, (max-width: 520px) 100vw, 520px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Where_Generative_AI_Helps_Most_in_Clinical_Documentation\"><\/span><strong>Where Generative AI Helps Most in Clinical Documentation<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Across the full transition, from the emergency department to the hospital floor to the home, <strong>AI helps the care team move from scattered data to organized clinical communication.<\/strong> The final documentation at every step still needs <strong>human review and clinician attestation.<\/strong> But when used responsibly, AI can help create a <strong>clearer, safer, and more connected journey from hospital to home and beyond.<\/strong>\u00a0AI can draft H&amp;Ps, progress notes, patient-message responses, discharge instructions, and follow-up outreach scripts.\u00a0It can summarize prior records, recent labs, medication lists, and past medical history. It can also structure content into timelines, SBAR handoffs, discharge plans, documentation-gap lists, and patient education drafts.\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As the patient journey above shows, that same structuring work extends into the administrative layer around documentation, tracking diagnoses and procedures against the codes that\u00a0ultimately support\u00a0billing accuracy and compliance. That said, <strong>code suggestions should never become\u00a0invisible\u00a0automation<\/strong>. Clinicians and organizations need clear governance over what AI can suggest, who reviews the suggestion, how changes are tracked, and how errors get corrected.\u00a0\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Those tasks matter because clinicians often need to act on information before it&#8217;s perfectly organized. <strong>AI can help reduce the friction around searching, copying, rewriting, and reformatting.<\/strong> Studies of ambient AI documentation suggest potential benefits for <strong>documentation burden, documentation efficiency, and clinician experience<\/strong>, though implementation outcomes vary by setting, workflow, training, and adoption patterns.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Why_Trusted_Sources_and_Clinician_Review_Matter\"><\/span><strong>Why Trusted Sources and Clinician Review Matter<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Healthcare\u00a0doesn&#8217;t\u00a0need AI that\u00a0<em>sounds<\/em>\u00a0confident.\u00a0Healthcare\u00a0needs AI\u00a0that&#8217;s\u00a0traceable, clinically useful, privacy-conscious, and reviewed by the humans responsible for care with appropriate guardrails.\u00a0<a href=\"https:\/\/www.elsevier.com\/about\/policies-and-standards\/responsible-ai-principles\" target=\"_blank\" rel=\"noreferrer noopener\">Elsevier&#8217;s Responsible AI Principles<\/a>\u00a0emphasize real-world impact, bias prevention, explainability, human oversight, privacy, and robust data governance.<\/strong>\u00a0<a href=\"https:\/\/www.elsevier.com\/connect\/artificial-intelligence\" target=\"_blank\" rel=\"noreferrer noopener\">Elsevier&#8217;s broader AI approach<\/a>\u00a0also emphasizes governed evidence, clear attribution, and human oversight in AI-enabled workflows.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>That&#8217;s\u00a0why source-grounded AI matters.<\/strong> When AI-generated output is connected to <strong>reliable clinical content, citations, and clinician review<\/strong>, it becomes easier to question and verify. Source-grounded AI platforms, like\u00a0<a href=\"https:\/\/www.elsevier.com\/products\/clinicalkey-ai\" target=\"_blank\" rel=\"noreferrer noopener\">ClinicalKey AI<\/a>\u00a0and\u00a0<a href=\"https:\/\/www.osmosis.org\/blog\/how-to-go-from-question-to-clarity-in-seconds-with-osmosis-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Osmosis AI<\/a>, support clinical and educational workflows because\u00a0they&#8217;re\u00a0built around <strong>trusted Elsevier content and cited responses<\/strong> <strong>rather than unsupported open-web answers.<\/strong> And because content is embedded directly in the EHR rather than accessed through a separate tool, the\u00a0<a href=\"https:\/\/www.osmosis.org\/learn\/Documentation_in_the_Electronic_Health_Record\" target=\"_blank\" rel=\"noreferrer noopener\">chart itself<\/a>\u00a0stays the source of truth, with AI drafting around it rather than replacing it.\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Risks_of_AI-generated_Clinical_Documentation\"><\/span><strong>The Risks of AI-generated Clinical Documentation<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">So what can go wrong when AI helps write clinical documentation? <strong>The risks are real. AI can hallucinate, omit important information, overstate certainty, misread context, or produce polished language that hides clinical gaps.<\/strong> <strong>Automation bias<\/strong> is another concern: if the output looks complete, busy clinicians may trust it too quickly. <strong>Privacy, security, Health Insurance Portability and Accountability Act compliance, bias, documentation integrity, and regulatory expectations<\/strong> all require careful governance, a challenge echoed across the field, including in the\u00a0<a href=\"https:\/\/www.aafp.org\/pubs\/fpm\/issues\/2025\/0500\/ambient-ai-scribes.html\" target=\"_blank\" rel=\"noreferrer noopener\">American Academy of Family Physicians\u2019 review of ambient AI scribes<\/a>.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Clinician accountability also becomes more explicit as AI enters documentation workflows.<\/strong> AI can draft, organize, retrieve, and summarize, but <strong>the clinician remains responsible for the clinical meaning, accuracy, and appropriateness of the documentation. AI-generated content needs review and editing before it becomes part of the clinical record.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Best_Practices_for_Responsible_AI-assisted_Documentation\"><\/span><strong>Best Practices for Responsible AI-assisted Documentation<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The safest AI documentation workflows are source-first and human-reviewed.<\/strong> Healthcare organizations can prioritize tools that use <strong>approved knowledge sources, provide citations or traceability when possible, protect patient data, and fit into existing clinical workflows.<\/strong> Staff need training not only on how to use AI, but also on <strong>how to question its output<\/strong>, an emphasis shared by the\u00a0<a href=\"https:\/\/www.ama-assn.org\/practice-management\/digital\/augmented-intelligence-health-care\" target=\"_blank\" rel=\"noreferrer noopener\">American Medical Association\u2019s guidance on augmented intelligence in health care<\/a>.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Responsible organizations also define what AI cannot do.<\/strong> It cannot autonomously chart without review, generate orders without clinician authority, replace professional assessment, or process protected health information through unapproved public tools. <strong>The safer question isn&#8217;t \u201cCan AI write this?\u201d It&#8217;s \u201cCan AI help a qualified clinician create a clearer, more accurate, better-supported document?\u201d<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">So how can clinicians and learners review AI output without treating it like the final answer? <strong>The AI CARES Model offers a practical checkpoint before AI-generated content is used in a clinical, educational, or patient-facing context.<\/strong> It prompts users to pause and ask whether the output is <strong>accountable, accurate, credible, relevant, ethical, equitable, and safe.<\/strong> In other words, the model keeps AI in the right role: <strong>a support tool for human judgment, not a substitute for it.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Here\u2019s&nbsp;the AI CARES Model and a few questions to get you started evaluating AI output:&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"960\" height=\"1181\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table1.webp\" alt=\"Osmosis from Elsevier educational table presenting the AI CARES framework for evaluating AI-generated content in healthcare and nursing education. It covers authorship and accountability, integrity, credibility and context, application readiness, reliability, ethical and equitable use, and safety, with questions emphasizing human oversight, evidence verification, transparency, privacy, equity, and prevention of harm.\" class=\"wp-image-11018\" style=\"aspect-ratio:0.8133034905014705;width:735px;height:auto\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table1.webp 960w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table1.webp?resize=244,300 244w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table1.webp?resize=768,945 768w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table1.webp?resize=832,1024 832w\" sizes=\"auto, (max-width: 960px) 100vw, 960px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Prompts_to_Consider_Matching_Your_Prompt_to_Your_Task_Role_and_Venue\"><\/span><strong>Prompts to Consider: Matching Your Prompt to Your Task, Role, and Venue<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Not every AI tool knows the same things about a patient, and that changes what a clinician should ask it to do. Before using a prompt, ask two questions: <strong>Does this tool have access to the chart? And is it built on a trusted, cited knowledge base?<\/strong> The table below offers practical examples by task and venue. Always follow your organization\u2019s <strong>approved-tool list and protected health information policies.<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1330\" height=\"4079\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png\" alt=\"Osmosis from Elsevier educational table providing examples of healthcare tasks that can be supported by AI. It pairs clinical roles and AI tools with sample prompts for documentation, handoffs, discharge planning, medication reconciliation, patient education, remote monitoring, evidence lookup, and other healthcare workflows.\" class=\"wp-image-11030\" style=\"aspect-ratio:0.3261733863436241;object-fit:cover;width:741px;height:auto\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png 1330w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png?resize=98,300 98w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png?resize=768,2355 768w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png?resize=334,1024 334w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png?resize=501,1536 501w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2026\/08\/Table2_2026_1330-png.png?resize=668,2048 668w\" sizes=\"auto, (max-width: 1330px) 100vw, 1330px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>General guideline:\u00a0<\/strong>if a tool can\u2019t (or won\u2019t) list sources or tell you where its information comes from, <strong>treat its output as a starting draft, not a citable fact, and never paste identifiable patient information into a tool that is not approved for protected health information.<\/strong>\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Future_of_AI-Assisted_Clinical_Documentation\"><\/span><strong>The Future of AI-Assisted Clinical Documentation<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI-assisted clinical documentation is ultimately about improving clinical communication, not replacing clinical judgment.<\/strong> Across the clinical workflow, generative AI can help clinicians and care teams <strong>draft notes, organize patient timelines, summarize records, support handoffs, prepare discharge information, identify documentation gaps, and communicate more clearly across settings.<\/strong> The greatest value comes when AI helps make complex information easier to <strong>review, verify, and act on<\/strong>, especially during transitions from admission to discharge and follow-up care.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As these tools continue to evolve, healthcare organizations can focus not only on what AI can automate, but also on how it can support more accurate, transparent, patient-centered documentation. <strong>The safest and most effective workflows will use trusted evidence sources, strong governance, privacy safeguards, clinician training, meaningful human oversight, and clear attestation before AI-generated content becomes part of the medical record.<\/strong> In that role, <strong>AI can reduce documentation burden and make clinical documentation more efficient, connected, and reliable across the continuum of care while keeping clinicians accountable for every clinical decision.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"FAQ_Generative_AI_and_Health_Documentation\"><\/span><strong>FAQ: Generative AI and Health Documentation<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_AI-assisted_clinical_documentation\"><\/span>What is AI-assisted clinical documentation?\u00a0<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI-assisted clinical documentation uses generative AI to help clinicians draft, summarize, structure, and verify clinical information in the EHR.\u00a0<\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_does_generative_AI_help_with_EHR_documentation\"><\/span>How does generative AI help with EHR documentation?\u00a0<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Generative AI can summarize prior records, draft clinical notes, organize patient timelines, support patient-message responses,\u00a0identify\u00a0documentation gaps, and prepare discharge information for clinician review.\u00a0<\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Can_AI_reduce_clinician_documentation_burden\"><\/span>Can AI reduce clinician documentation burden?\u00a0<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI can reduce documentation burden when clinical teams use it to organize information, draft routine documentation, reduce duplicate work, and support clinical workflow automation while preserving human review.\u00a0<\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_are_the_risks_of_AI-generated_clinical_notes\"><\/span>What are the risks of AI-generated clinical notes?\u00a0<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Risks include hallucinations, omissions, automation bias, inaccurate summaries, privacy concerns, bias, and overreliance on AI-generated content without clinician verification.\u00a0<\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_can_healthcare_teams_use_AI_safely_in_documentation\"><\/span>How can healthcare teams use AI safely in documentation?\u00a0<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Healthcare teams can use AI safely by choosing source-grounded tools, protecting patient privacy, using approved workflows, training staff, verifying AI-generated output, and requiring clinician attestation before documentation enters the clinical record.\u00a0<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Key_Takeaways\"><\/span>Key Takeaways<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Generative AI can support clinical documentation by drafting, summarizing, and structuring information across the care journey.<\/strong><\/li>\n\n\n\n<li><strong>AI-assisted workflows can support notes, handoffs, discharge planning, patient communication, and other documentation tasks.<\/strong><\/li>\n\n\n\n<li><strong>Source-grounded tools make AI-generated information easier for healthcare professionals to trace and verify.<\/strong><\/li>\n\n\n\n<li><strong>AI-generated clinical documentation carries risks including hallucinations, omissions, automation bias, privacy concerns, and inaccurate summaries.<\/strong><\/li>\n\n\n\n<li><strong>Human review and clinician accountability remain essential before AI-generated content becomes part of the medical record.<\/strong><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"References\"><\/span><strong>References<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Husa, Robyn A., et al. \u201cAmbient Artificial Intelligence Use and Clinician Documentation Burden, Productivity, and Efficiency.\u201d JAMA Network Open, vol. 9, no. 5, 2026, e2615762.\u00a0<\/li>\n\n\n\n<li>Bakken, Suzanne. \u201cClinician, Patient, and Organizational Perspectives on Ambient AI Scribes.\u201d Journal of the American Medical Informatics Association, vol. 33, no. 2, 2026, pp. 253\u2013255.\u00a0<\/li>\n\n\n\n<li>Stults, Cheryl D., et al. \u201cEvaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians.\u201d JAMA Network Open, vol. 8, no. 5, 2025, e258614.\u00a0\u00a0<\/li>\n\n\n\n<li>Elsevier.\u00a0<a href=\"https:\/\/www.elsevier.com\/connect\/artificial-intelligence\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cAI across Elsevier.\u201d<\/a>\u00a0<\/li>\n\n\n\n<li>Elsevier.\u00a0<a href=\"https:\/\/www.elsevier.com\/products\/clinicalkey-ai\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cClinicalKey AI.\u201d<\/a>\u00a0<\/li>\n\n\n\n<li>Elsevier.\u00a0<a href=\"https:\/\/www.elsevier.com\/about\/policies-and-standards\/responsible-ai-principles\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cResponsible AI Principles.\u201d<\/a>\u00a0<\/li>\n\n\n\n<li>Elsevier Support.\u00a0<a href=\"https:\/\/www.osmosis.org\/features\/osmosis-ai\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cWhat Is Osmosis AI?\u201d<\/a>\u00a0Osmosis Support, 3 Mar. 2026.\u00a0<\/li>\n\n\n\n<li>Agency for Healthcare Research and Quality.\u00a0<a href=\"https:\/\/www.ahrq.gov\/teamstepps-program\/curriculum\/communication\/tools\/sbar.html\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cTool: SBAR.\u201d<\/a>\u00a0AHRQ\u00a0TeamSTEPPS.\u00a0<\/li>\n\n\n\n<li>Osmosis.\u00a0<a href=\"https:\/\/www.osmosis.org\/answers\/sbar-handoff-report-acronym\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cSBAR Handoff Report Acronym.\u201d<\/a>\u00a0Osmosis, 4 Mar. 2025.\u00a0<\/li>\n\n\n\n<li>Ng, Joel Jia Wei, et al. \u201cEvaluating the Performance of Artificial Intelligence-Based Speech Recognition for Clinical Documentation: A Systematic Review.\u201d BMC Medical Informatics and Decision Making, 2025.\u00a0<\/li>\n\n\n\n<li>Randall, Paige, MS, RN, CEN, CNE.\u00a0<a href=\"https:\/\/www.osmosis.org\/blog\/the-anatomy-of-a-chart-how-to-read-and-interpret-an-ehr\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cThe Anatomy of a Chart: How to Read and Interpret an EHR.\u201d<\/a>\u00a0Osmosis Blog,\u00a0updated 24 Feb. 2026.\u00a0<\/li>\n\n\n\n<li>Elsevier.\u00a0<a href=\"https:\/\/www.elsevier.com\/products\/leapspace\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cLeapSpace.\u201d<\/a>\u00a0Elsevier Products.\u00a0<\/li>\n\n\n\n<li>Centers for Medicare &amp; Medicaid Services.\u00a0<a href=\"https:\/\/www.cms.gov\/medicare\/coding-billing\/icd-10-codes\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cICD-10-CM\/PCS.\u201d<\/a>\u00a0CMS.gov.\u00a0<\/li>\n\n\n\n<li>American Medical Association.\u00a0<a href=\"https:\/\/www.ama-assn.org\/practice-management\/cpt\" target=\"_blank\" rel=\"noreferrer noopener\">\u201cCPT\u00ae (Current Procedural Terminology).\u201d<\/a>\u00a0AMA.\u00a0 <\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large\"><a href=\"https:\/\/osmosis.org\/plans\"><img loading=\"lazy\" decoding=\"async\" width=\"700\" height=\"250\" src=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2021\/01\/Blog_Display_Ads_GENERAL2_2023.png?w=700\" alt=\"\" class=\"wp-image-4405\" srcset=\"https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2021\/01\/Blog_Display_Ads_GENERAL2_2023.png 700w, https:\/\/www.osmosis.org\/blog\/wp-content\/uploads\/sites\/2\/2021\/01\/Blog_Display_Ads_GENERAL2_2023.png?resize=300,107 300w\" sizes=\"auto, (max-width: 700px) 100vw, 700px\" \/><\/a><\/figure>\n\n\n\n<p class=\"has-text-align-center wp-block-paragraph\"><em><strong>Get<\/strong><\/em><em><strong>&nbsp;your&nbsp;<a href=\"https:\/\/osmosis.org\/plans\" target=\"_blank\" rel=\"noreferrer noopener\">free trial<\/a>&nbsp;now to&nbsp;<\/strong><\/em><em><strong>discover why millions of clinicians and caregivers love learning by Osmosis.<\/strong><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Generative AI is reshaping clinical documentation, from drafting notes to organizing handoffs and discharge information. Explore where AI can support healthcare workflows, and the safeguards needed to use it responsibly.<\/p>\n","protected":false},"author":167,"featured_media":11031,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[27,5,10,21,24,867,30,16,37,32,43],"tags":[3371,3370,748,936,3168,3372,1573,935,937,3367,3369,3368,2745,2394,2971],"class_list":["post-11017","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-medicine","category-clerkships","category-clinical-skills","category-guides","category-imgs","category-lpn","category-np","category-do","category-pa","category-nursing","category-residency","tag-ai-scribes","tag-ambient-ai","tag-clinical-communication","tag-clinical-documentation","tag-clinicalkey-ai","tag-clinician-workflow","tag-digital-health","tag-ehr","tag-electronic-health-records","tag-generative-ai","tag-health-informatics","tag-healthcare-ai","tag-osmosis-ai","tag-patient-privacy","tag-responsible-ai"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.6 - 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