{"id":"W2778817261","doi":"10.5430/jha.v7n1p1","title":"Impact of Computerized Provider Order Entry Systems on hospital staff pharmacist workflow productivity: A three site comparative analysis based on level of CPOE implementation","year":2017,"lang":"en","type":"article","venue":"Journal of Hospital Administration","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Order entry; Medicine; Pharmacist; Workflow; Computerized physician order entry; Post-hoc analysis; Observational study; Clinical pharmacy; Health care; Medical emergency; Nursing; Pharmacy; Computer science; Internal medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002821331,0.0002247281,0.0003138994,0.001107287,0.0003350897,0.0008404776,0.0003583777,0.000301853,0.001787891],"category_scores_gemma":[0.01037772,0.0002033926,0.0006757468,0.000903693,0.0004522777,0.0008101688,0.0008361692,0.0002750008,0.0002120958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009111514,"about_ca_system_score_gemma":0.0008459718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002675334,"about_ca_topic_score_gemma":0.002952113,"domain_scores_codex":[0.9964515,0.001441651,0.0003802433,0.0003569747,0.0008901735,0.0004794392],"domain_scores_gemma":[0.9829696,0.007362206,0.005419056,0.0005375081,0.001865532,0.00184611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002638636,0.0009096317,0.9799967,0.00007011698,0.0001570806,0.00009218181,0.001557304,0.0002358583,0.001715944,0.00002141022,0.00007422744,0.01253105],"study_design_scores_gemma":[0.00002622281,0.003065376,0.9951193,0.00000599214,0.00002804385,0.00003529257,0.001117664,0.000252231,0.0002787019,0.000006983169,0.00005600658,0.000008130446],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998122,0.00001493661,0.00005819112,0.00000495095,8.050741e-7,0.000009466801,0.00002949711,0.000001431185,0.00006847873],"genre_scores_gemma":[0.9996976,0.00001452884,0.0001187342,0.00000441125,0.000002268764,0.00001900744,0.00006971428,0.000001485956,0.0000723429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002821331,"threshold_uncertainty_score":0.01492077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1448768261959249,"score_gpt":0.4961279371696454,"score_spread":0.3512511109737205,"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."}}