{"id":"W3129341320","doi":"10.2196/18534","title":"Using a Clinical Workflow Analysis to Enhance eHealth Implementation Planning: Tutorial and Case Study","year":2021,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"eHealth; Workflow; Computer science; mHealth; Process management; Knowledge management; Data science; Health care; Psychological intervention; Medicine; Nursing; Engineering; Database","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.007937914,0.0003985194,0.001499696,0.0005204975,0.002558202,0.00005104069,0.0001284348,0.0003766984,0.0001071417],"category_scores_gemma":[0.0002947381,0.0003930554,0.0001101386,0.002042738,0.00005515944,0.00018158,0.0002065502,0.001577141,0.00002048183],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009352373,"about_ca_system_score_gemma":0.007042462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0169582,"about_ca_topic_score_gemma":0.03061139,"domain_scores_codex":[0.9876163,0.005266296,0.003150629,0.001359459,0.0005447612,0.002062536],"domain_scores_gemma":[0.9939581,0.001456652,0.001039353,0.000710898,0.0004053006,0.002429731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003807735,0.0004100738,0.9187635,0.002029339,0.0002501287,0.0006934751,0.0261425,0.00001600203,0.000007401288,0.0001296969,0.001703302,0.04947386],"study_design_scores_gemma":[0.009623098,0.005988928,0.7608299,0.0007768947,0.002265161,0.001059738,0.1897831,0.00348339,0.000005785075,0.0002653741,0.02452776,0.001390813],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867809,0.002195894,0.001569297,0.002487066,0.002235166,0.004449019,0.00004879242,0.0001294191,0.0001044734],"genre_scores_gemma":[0.9883668,0.0005555901,0.002819811,0.005017226,0.002479415,0.0004916877,0.00003409501,0.00005893641,0.0001764194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1636406,"threshold_uncertainty_score":0.9998521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2876407653634799,"score_gpt":0.6494225993116508,"score_spread":0.3617818339481709,"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."}}