{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005688313,0.0001376485,0.0007498854,0.0003085033,0.0003799181,0.00001469073,0.0001784201,0.0001369593,0.0000103028],"category_scores_gemma":[0.001186942,0.0001192422,0.00009959757,0.0004624191,0.00004046248,0.0003941221,0.0002817503,0.0006771809,8.79115e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595398,"about_ca_system_score_gemma":0.00258389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008616486,"about_ca_topic_score_gemma":0.001868188,"domain_scores_codex":[0.99399,0.00381636,0.001285297,0.0002694682,0.0002232496,0.000415618],"domain_scores_gemma":[0.9914008,0.004952964,0.002060197,0.0001877639,0.001192006,0.000206301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.02154303,0.004672818,0.1704115,0.02580566,0.009439741,0.0004912163,0.1423884,0.0008402485,0.1523203,0.00583687,0.01843376,0.4478164],"study_design_scores_gemma":[0.01747906,0.00398318,0.01708095,0.0006463872,0.003231013,0.0001609265,0.1510093,0.008533068,0.0006776226,0.00005884609,0.7968393,0.0003003603],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9385906,0.0002200469,0.03106215,0.02622811,0.0007636208,0.002939377,0.00002475773,0.00001030793,0.0001610597],"genre_scores_gemma":[0.9875505,0.0002945804,0.009740002,0.001833607,0.0002114768,0.000141678,0.000004746902,0.00001400039,0.0002094364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7784055,"threshold_uncertainty_score":0.4862558,"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."}}