{"id":"W2123125868","doi":"10.1345/aph.1p314","title":"Medication Reconciliation During Internal Hospital Transfer and Impact of Computerized Prescriber Order Entry","year":2010,"lang":"en","type":"article","venue":"Annals of Pharmacotherapy","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Toronto Western Hospital; University of Toronto; Toronto General Hospital; University Health Network","funders":"","keywords":"Medicine; Computerized physician order entry; Emergency medicine; Order entry; Adverse effect; Multidisciplinary team; Patient safety; Medication Reconciliation; Medical emergency; Health care; Intensive care medicine; Pediatrics; Family medicine; Internal medicine; Pharmacist; Pharmacy; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009014672,0.0001386738,0.0003364525,0.0001132859,0.00010122,0.0000035483,0.0001446009,0.0001533331,0.001200716],"category_scores_gemma":[0.00004481287,0.0001156026,0.00008806644,0.00012452,0.00006117702,0.0001815584,0.00001440849,0.0005341783,0.000007336799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003436938,"about_ca_system_score_gemma":0.0003837658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217722,"about_ca_topic_score_gemma":0.00007047323,"domain_scores_codex":[0.9981036,0.0003390201,0.0007661267,0.000195648,0.0002186342,0.0003769674],"domain_scores_gemma":[0.9987779,0.0002081376,0.0003078317,0.0001746945,0.0003711547,0.0001603119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005483662,0.0001536301,0.06984141,0.0005262417,0.0001986023,5.615459e-7,0.006194911,0.000002734161,0.9033614,0.00008737738,0.003232894,0.01585191],"study_design_scores_gemma":[0.01690179,0.001661286,0.5039546,0.000966601,0.00005092275,0.00001174513,0.0003442786,0.003755764,0.4553739,0.000418817,0.01597724,0.000583065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951077,0.0004048746,0.0006409458,0.001754361,0.0008653417,0.0008314672,0.00003455969,0.00003371609,0.000327105],"genre_scores_gemma":[0.9967809,0.001883678,0.0001638222,0.0004442603,0.0004041464,0.00005646355,0.000009815816,0.00002599563,0.0002309526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4479875,"threshold_uncertainty_score":0.9997123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05541405251740106,"score_gpt":0.4783427704598183,"score_spread":0.4229287179424172,"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."}}