{"id":"W3005410934","doi":"10.2196/16502","title":"The Impact of Electronic Health Records on the Duration of Patients’ Visits: Time and Motion Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Jazan University","keywords":"Medicine; Observational study; Metropolitan area; Descriptive statistics; Family medicine; Duration (music); Medical emergency; Electronic health record; Workflow; Patient satisfaction; Health care; Nursing","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":[0.003124531,0.0002687474,0.0004247781,0.00146766,0.0005351227,0.0006923021,0.000622407,0.000493013,0.002615881],"category_scores_gemma":[0.01514086,0.0002384678,0.001453673,0.002256622,0.0003899569,0.0008871132,0.000961469,0.0006788921,0.0003341897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001030324,"about_ca_system_score_gemma":0.0009873667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005206625,"about_ca_topic_score_gemma":0.006062557,"domain_scores_codex":[0.9970443,0.001402064,0.0004600601,0.0002702514,0.0005408259,0.0002825843],"domain_scores_gemma":[0.9742913,0.008588951,0.01296287,0.0008606995,0.001451813,0.001844396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001732507,0.0006861295,0.9885412,0.0001128576,0.0002573419,0.00006167952,0.0009360617,0.0001451905,0.0002176327,0.00003306751,0.000149628,0.007126641],"study_design_scores_gemma":[0.0000317783,0.001186265,0.9972637,0.00001447888,0.00007205846,0.00006734193,0.0007957499,0.000217006,0.00007230986,0.00001154115,0.0002550695,0.00001261693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986644,0.0001908946,0.0001562407,0.00004636935,0.000005407472,0.00005974795,0.0005193775,0.00000234808,0.0003552345],"genre_scores_gemma":[0.9986838,0.0001174344,0.000276058,0.00003418887,0.00001664961,0.0001422161,0.0005297442,0.000002986877,0.0001970723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005206625,"threshold_uncertainty_score":0.01652431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03342077467692022,"score_gpt":0.4163143529026551,"score_spread":0.3828935782257349,"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."}}