{"id":"W2343571725","doi":"10.2196/humanfactors.4537","title":"Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned","year":2015,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Usability; Clinical decision support system; Workflow; Documentation; Decision support system; Emergency department; Health information technology; Health informatics; Test (biology); Medical emergency; Computer science; Medicine; Health care; Nursing; Human–computer interaction; Public health; Database; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07583771,0.001820654,0.001291982,0.001625674,0.001707264,0.003256807,0.003598951,0.002209851,0.001156222],"category_scores_gemma":[0.1154189,0.0008047394,0.001313244,0.001036814,0.002280618,0.004563667,0.002690512,0.002482343,0.00041704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003289258,"about_ca_system_score_gemma":0.005809614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004854224,"about_ca_topic_score_gemma":0.007732787,"domain_scores_codex":[0.9411324,0.04250776,0.003876037,0.002684691,0.007710972,0.002088174],"domain_scores_gemma":[0.8317469,0.11536,0.003005753,0.006881982,0.03836856,0.004636716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001249304,0.02840356,0.0884562,0.004182355,0.0004533477,0.002680359,0.07960432,0.005680501,0.01770206,0.001044719,0.009957855,0.7605854],"study_design_scores_gemma":[0.003936154,0.1564271,0.3783259,0.01162122,0.001387599,0.007730768,0.2127081,0.08396279,0.06708285,0.01153171,0.06347555,0.001810367],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9188489,0.001026048,0.06083584,0.005802088,0.0003285576,0.008263406,0.0001124132,0.0005673718,0.00421526],"genre_scores_gemma":[0.8105639,0.001296766,0.1796677,0.002093172,0.0002075912,0.004218039,0.0002262615,0.0001668222,0.001559892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07583771,"threshold_uncertainty_score":0.4010729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5794027548146631,"score_gpt":0.5980208998969563,"score_spread":0.0186181450822932,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}