[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-425536-105":59,"doc-detail-425536-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","artificial-intelligence-applications-in-advance-care-planning-issue-2-poster-policy","ARTIFICIAL INTELLIGENCE APPLICATIONS IN ADVANCE CARE PLANNING - Issue 2 - Poster policy","","This scoping review examines artificial intelligence (AI) applications in advance care planning (ACP), synthesizing evidence from PubMed, Web of Science, and Scopus (2019-2024) across ten articles using PRISMA guidance. It evaluates AI tools for ACP documentation, decision-making support, and workflow optimization, excluding studies without clinical validation or patient-centered outcomes. Results highlight predictive models, NLP to reduce documentation review time, and chatbots improving ACP literacy while pointing to persistent disparities. Major challenges include algorithmic bias, clinician resistance, limited caregiver/surrogate coverage, and evidence gaps on e-planning cost-effectiveness, standardized metrics, and ethical over-reliance.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/artificial-intelligence-applications-in-advance-care-planning-issue-2-poster-policy/425536/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/artificial-intelligence-applications-in-advance-care-planning-issue-2-poster-policy/425536.png","ImageObject",300,407,{"name":92,"@type":93},"Genevieve","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the scope and method of the review?","Question",{"text":112,"@type":113},"The review is a scoping review of AI applications in advance care planning, synthesizing evidence from PubMed, Web of Science, and Scopus for 2019–2024 across ten articles using PRISMA guidance.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which AI approaches were identified as promising for ACP?",{"text":117,"@type":113},"The review highlights predictive models for identifying high-risk patients and prompting earlier ACP discussions, NLP to reduce documentation review time, and chatbots that increase ACP literacy among older adults.",{"name":119,"@type":110,"acceptedAnswer":120},"What challenges and research gaps limit current AI use in ACP?",{"text":121,"@type":113},"The review points to algorithmic bias from non-diverse datasets, clinician resistance related to liability and EHR interoperability, limited tool coverage for caregiver burden and surrogate needs, and gaps in cost-effectiveness evidence, standardized evaluation metrics, and ethical risk research.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},425536,1790766272,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":81,"preview_page_count":4},1374391974585,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Innovation in Aging, 2025, Vol. 9, No. S2 1005  \nSESSION 7515 (POSTER)  POLICY  \nAbstract citation ID: igaf122.3389  \nARTIFICIAL INTELLIGENCE APPLICATIONS IN  \nADVANCE CARE PLANNING  \nGirish Hemrajani, and Debra Dobbs, University of South Florida, Tampa, Florida, United States  \nThis scoping review examines artificial intelligence (AI) applications in advance care planning (ACP), synthesizing evidence from databases like PubMed, Web of Science, and Scopus (2019-2024), ten articles, using PRISMA guidelines. The review focused on AI tools for ACP documentation, decision-making, and workflow optimization, excluding studies lacking clinical validation or patient-centered outcomes. Findings reveal promising AI applications in ACP: predictive models, like Stanford’s EHR-based mortality predictor, improved high-risk patient identification, triggering earlier ACP discussions. Natural Language Processing reduced ACP documentation review time significantly. AI-powered chatbots increased ACP literacy among older adults by 40%, addressing health disparities. Challenges like algorithmic bias from non-diverse datasets exacerbates inequities inACP access persist. Clinician resistance stems from unclear liability frameworks and poor EHR interoperability. Only 25% of tools address caregiver burden or surrogate decision-maker needs. Research gaps include limited evidence on AI-driven e-planning tools’ cost-effectiveness, lack of standardized metrics for evaluating AI’s impact on patient autonomy and understudied ethical risks of over-reliance on AI for sensitive end-of-life conversations. Future directions focus on equity-driven design, the integration of e-planning into electronic medical records, and the assessment of AI’s capacity to alleviate caregiver burden and enhance preparedness of surrogate decision-makers. This research emphasizes the necessity to transformACPfrom a documentation-oriented process to a communication-centered continuum, utilizing AI to democratize access and tackle systemic inequalities. It highlights the potential of AI to transform ACP, while emphasizing the importance of ethical implementation and patient-centered outcomes.: Keywords: Artificial intelligence, advance care planning, health equity, predictive analytics, natural language processing.","cbCaijWzoRdADJt3","https://ap.wps.com/l/cbCaijWzoRdADJt3","pdf",53924,"English","# Abstract\n## Review scope and methods\n## Key findings\n## Challenges and research gaps\n## Future directions","[{\"question\":\"What is the scope and method of the review?\",\"answer\":\"The review is a scoping review of AI applications in advance care planning, synthesizing evidence from PubMed, Web of Science, and Scopus for 2019–2024 across ten articles using PRISMA guidance.\"},{\"question\":\"Which AI approaches were identified as promising for ACP?\",\"answer\":\"The review highlights predictive models for identifying high-risk patients and prompting earlier ACP discussions, NLP to reduce documentation review time, and chatbots that increase ACP literacy among older adults.\"},{\"question\":\"What challenges and research gaps limit current AI use in ACP?\",\"answer\":\"The review points to algorithmic bias from non-diverse datasets, clinician resistance related to liability and EHR interoperability, limited tool coverage for caregiver burden and surrogate needs, and gaps in cost-effectiveness evidence, standardized evaluation metrics, and ethical risk research.\"}]","ARTIFICIAL INTELLIGENCE APPLICATIONS IN ADVANCE CARE PLANNING - Issue 2 - Poster policy | PDF",1790637585]