{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T20:05:37Z","timestamp":1792267537036,"version":"4.4.0"},"reference-count":32,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T00:00:00Z","timestamp":1779840000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T00:00:00Z","timestamp":1779840000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Paediatrics Child Health"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To evaluate the impact of an artificial intelligence medical scribe (AIMS) on clinical documentation efficiency, document quality, clinician\u2010patient interaction, clinician well\u2010being, consumer perspectives, overtime, and transcription costs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Retrospective\u2010prospective study of AIMS project cohort including medical, allied health and nursing practitioners at a quaternary children's hospital and health service (HHS). Outcome measures included time\u2010to\u2010finalise outpatient correspondence, clinicians' Reflections survey (1\u2009month), document quality survey using modified Physician Documentation Quality Instrument\u20109 tool's domains (3\u2009months), System Usability Scale (SUS) (3\u2009months). Patient\/consumer experience surveys, overtime and cost analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Total 131 participants including 89 medical, 36 allied health and 6 nurse practitioners used AIMS showing significant reduction in median time\u2010to\u2010finalise outpatient letters from 7.9\u2009days (Interquartile range [IQR] 19\u2009days) in pre\u2010AIMS era to 14\u2009min (IQR 6\u2009days) (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). In the Reflections survey participants reported improved: patient engagement (62\/71, 87%), well\u2010being (80%, 57\/71) and work\u2010life balance (66%, 47\/71). The document quality survey showed acceptable document quality with median score 4, in 9 of the 10 survey domains (scale 1\u2010to\u20105,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200977). Mean SUS score was 74 (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200977) suggesting above average usability. Study showed transcription cost savings of 16\u2009903 AUD, but no definitive impact on overtime claims. Patient\/consumer feedback (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009333) was highly positive with over 90% reporting improved clinician\u2010patient interaction and welcoming future use of AIMS.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study showed significantly improved documentation efficiency, acceptable document quality, and reduced transcription costs with significant benefits to clinician well\u2010being and clinician\u2010patient interaction with the use of an ambient AI medical scribe.<\/jats:p>\n                    <jats:p>\n                      <jats:bold>Trial registration:<\/jats:bold>\n                      Australian New Zealand Clinical Trials Registry: ACTRN12625000432415\n                    <\/jats:p>\n                  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