{"id":"W3213957885","doi":"10.1177/10781552211053253","title":"Application of the Failure Mode and Effects Analysis (FMEA) to identify vulnerabilities and opportunities for improvement prior to implementing a computerized prescription order entry (CPOE) system in a university hospital oncology clinic","year":2021,"lang":"en","type":"article","venue":"Journal of Oncology Pharmacy Practice","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Eli Lilly Canada; Amgen Canada; Novartis Pharmaceuticals Canada; Astellas Pharma Canada; Merck Canada; AstraZeneca Canada; F. Hoffmann-La Roche; Takeda Pharmaceuticals North America; Celgene; Bristol-Myers Squibb Canada; Seattle Genetics; Gilead Sciences","keywords":"Medicine; Medical prescription; Order entry; Computerized physician order entry; Failure mode and effects analysis; Medical emergency; Emergency medicine; Intensive care medicine; Nursing; Health care; Reliability engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01720692,0.001008304,0.0007130346,0.005943074,0.0007493151,0.001129961,0.000663212,0.0007202712,0.002110423],"category_scores_gemma":[0.04292984,0.0003534241,0.002014576,0.001590038,0.0005650166,0.001062953,0.0009383614,0.0006946966,0.0001344255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001972511,"about_ca_system_score_gemma":0.003109922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005774708,"about_ca_topic_score_gemma":0.005248039,"domain_scores_codex":[0.9917352,0.00513362,0.0005185271,0.000714723,0.001659745,0.0002381378],"domain_scores_gemma":[0.917762,0.07092824,0.005658234,0.001758245,0.003439458,0.0004537931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001657281,0.001615516,0.6677501,0.001150015,0.00147786,0.0005749526,0.005243442,0.02060746,0.006655008,0.002029849,0.001076924,0.2901616],"study_design_scores_gemma":[0.000203143,0.009294786,0.8097653,0.0005915237,0.001058809,0.0008128273,0.003779305,0.1599098,0.008129988,0.003933502,0.002326299,0.0001946981],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9024923,0.0003528941,0.09166195,0.0003092396,0.00003507964,0.001528287,0.0005510012,0.0004174502,0.002651808],"genre_scores_gemma":[0.9292204,0.0001014378,0.06952348,0.00006026569,0.00001125741,0.0005934865,0.0001606713,0.00002199699,0.0003069735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01720692,"threshold_uncertainty_score":0.09099996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07289850436393183,"score_gpt":0.4934987644334726,"score_spread":0.4206002600695408,"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."}}