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Building on the Rockwood frailty index and an EHR-derived frailty index (eFI), the team developed an eFI in the Wake Forest University School of Medicine EHR from data gathered during standard clinical care. Using 54 age-associated deficits and eFI cut-points for Fit and Pre-Frail, findings across 22+ articles link eFI to adverse outcomes, including mortality, utilization, falls, readmissions, and hospitalization, and support ongoing pathway testing to improve quality of life.",{"@graph":69,"@context":123},[70,84,106],{"@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/gerontologizing-the-learning-health-system-the-electronic-frailty-index-as-a-passive-digital-marker-for-frailty/428332/",{"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/gerontologizing-the-learning-health-system-the-electronic-frailty-index-as-a-passive-digital-marker-for-frailty/428332.png","ImageObject",300,407,{"name":92,"@type":93},"Mabel","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-04","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",13,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the electronic frailty index (eFI) in this work?","Question",{"text":113,"@type":114},"The eFI is an EHR-derived measure of frailty built from personalized data collected during routine clinical care and computed using 54 age-associated deficits.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How are frailty categories determined using eFI scores?",{"text":118,"@type":114},"eFI scores are reported as a proportion with cut-points labeled “Fit” (eFI≤0.10) and “Pre-Frail” (0.10–0.21), with higher scores indicating frailty.",{"name":120,"@type":111,"acceptedAnswer":121},"Which adverse outcomes are associated with higher eFI scores?",{"text":122,"@type":114},"Higher eFI is associated with adverse outcomes such as increased mortality, acute utilization and emergency department visits, injurious falls, higher hazards of six-month mortality, greater odds of 30-day readmissions, and increased hospitalization in older adults with solid tumors undergoing chemotherapy.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},428332,1790718214,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":14,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":24,"preview_page_count":4},7971474920318,"https://ap-avatar.wpscdn.com/avatar/74000ee537e6b0ca360?x-image-process=image/resize,m_fixed,w_180,h_180&k=1788430171632181674","376 Innovation in Aging, 2025, Vol. 9, No. S2  \nAbstract citation ID: igaf122.1279  \nGERONTOLOGIZING THE LEARNING HEALTH SYSTEM – THE ELECTRONIC FRAILTY INDEX ASA PASSIVE DIGITAL MARKER FOR FRAILTY  \nKathryn Callahan, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States  \nWhether defined as a phenotype (Fried et al.) or through a frailty index (Rockwood et al., age-associated deficit accumulation), frailty metrics capture a unique description of an individual’s, or population’s, health in aging. Frailty has been slow to  \nInnovation in Aging, 2025, Vol. 9, No. S2 377  \nimplement in healthcare systems, likely due to burdensome assessments. Building upon the Rockwood frailty index and the Clegg et al. electronic health record (EHR) based frailty index (eFI) in England, our team developed and implemented an eFI within the Wake Forest University School of Medicine (WFUSM) EHR, derived from personalized data collected during routine clinical care. Consistent with established methods, we compiled  \n54 age-associated deficits. eFI scores are reported as a simple proportion, with cut-points denoted as “Fit” (eFI≤0.10),“Pre-Frail”(0.100.21). Across 22+ published articles in multiple healthcare domains, eFI scores are consistently associated with adverse health outcomes for older adults. In primary care, the c-statistics for frailty include (adjusted for age, sex, race/ethnicity, past utilization) 0.79 for mortality, 0.74 for acute utilization, 0.79 for emergency department visits, 0.74 for injurious falls. Post-operative frail (eFI>0.21) older adults experienced an elevated hazard of six-month mortality (HR 2.86, 1.84-4.44), and elevated odds of 30-day readmissions (OR 2.46, 1.72-3.52) and post-acute services (OR 1.68, 1.36-2.08). Frail older adults with solid tumors undergoing chemotherapy experienced greater hazard of hospitalization (HR 3.23, 2.23-4.69) and lower mean overall survival (19m in frail vs 54m in fit) . We are testing care pathways to improve quality of life and health outcomes in frailty.","cbCaipDhFAOCETxi","https://ap.wps.com/l/cbCaipDhFAOCETxi","pdf",717680,"English","# Background\n## eFI Development in Wake Forest EHR\n## Deficits, Scoring, and Cut-Points\n## Associations With Health Outcomes\n## Ongoing Care Pathway Testing","[{\"question\":\"What is the electronic frailty index (eFI) in this work?\",\"answer\":\"The eFI is an EHR-derived measure of frailty built from personalized data collected during routine clinical care and computed using 54 age-associated deficits.\"},{\"question\":\"How are frailty categories determined using eFI scores?\",\"answer\":\"eFI scores are reported as a proportion with cut-points labeled “Fit” (eFI≤0.10) and “Pre-Frail” (0.10–0.21), with higher scores indicating frailty.\"},{\"question\":\"Which adverse outcomes are associated with higher eFI scores?\",\"answer\":\"Higher eFI is associated with adverse outcomes such as increased mortality, acute utilization and emergency department visits, injurious falls, higher hazards of six-month mortality, greater odds of 30-day readmissions, and increased hospitalization in older adults with solid tumors undergoing chemotherapy.\"}]","GERONTOLOGIZING THE LEARNING HEALTH SYSTEM - THE ELECTRONIC FRAILTY INDEX AS A PASSIVE DIGITAL MARKER FOR FRAILTY | PDF",1790646426]