{"id":"W4389134535","doi":"10.2196/52524","title":"Value of Electronic Health Records Measured Using Financial and Clinical Outcomes: Quantitative Study","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health records; Electronic health record; Value (mathematics); Actuarial science; Medicine; Business; Computer science; Health care; Economics","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":[0.02088956,0.0003718226,0.0005653859,0.00290416,0.0009631881,0.001712085,0.0008190263,0.0006379183,0.002358967],"category_scores_gemma":[0.06928279,0.0002950981,0.001141723,0.004352944,0.001441442,0.00244081,0.00195102,0.001184696,0.0002440629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001929933,"about_ca_system_score_gemma":0.002140087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794321,"about_ca_topic_score_gemma":0.001971663,"domain_scores_codex":[0.9817604,0.01122904,0.00140614,0.001102224,0.003538823,0.0009633826],"domain_scores_gemma":[0.8796329,0.073447,0.03119957,0.003209431,0.01000835,0.00250271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002014606,0.0009379899,0.9789762,0.0001490062,0.000190169,0.00006309548,0.004615836,0.0002521467,0.0001604693,0.0003828331,0.0003583542,0.0137124],"study_design_scores_gemma":[0.00003622526,0.0009968671,0.9843668,0.00009746266,0.00008223631,0.0001064506,0.01094136,0.001801635,0.0003451446,0.0003814751,0.0008053939,0.00003897017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998052,0.00006357497,0.0006280133,0.0001241333,0.000004837015,0.0001391487,0.000464481,0.000004612137,0.0005192424],"genre_scores_gemma":[0.998055,0.00005281615,0.0009737507,0.00005356492,0.0000102735,0.0003851415,0.0003194116,0.000003798837,0.0001463729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02088956,"threshold_uncertainty_score":0.1104758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1828222788635362,"score_gpt":0.5546759858673469,"score_spread":0.3718537070038107,"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."}}