{"id":"W2131585986","doi":"10.2196/humanfactors.3524","title":"Applying Human Factors Principles to Mitigate Usability Issues Related to Embedded Assumptions in Health Information Technology Design","year":2014,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usability; Workflow; Health information technology; Usability engineering; Health care; Patient safety; User-centered design; Computer science; Heuristic evaluation; Health equity; Web usability; Harm; Design science; Risk analysis (engineering); Knowledge management; Medicine; Human–computer interaction; Psychology; Public health; Nursing","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":[0.1440593,0.002767097,0.001441044,0.009680995,0.00570637,0.01355964,0.004279101,0.004312775,0.003555549],"category_scores_gemma":[0.1763884,0.002115972,0.002986518,0.003755977,0.01654479,0.007498598,0.008821639,0.007609822,0.0008765302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01377475,"about_ca_system_score_gemma":0.03334142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007731206,"about_ca_topic_score_gemma":0.01297726,"domain_scores_codex":[0.7899753,0.153852,0.01318765,0.006460089,0.0342724,0.00225256],"domain_scores_gemma":[0.6201652,0.3078707,0.01511867,0.01482404,0.0403306,0.001690933],"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":[0.0002150825,0.0008041107,0.01490997,0.02197688,0.0007434972,0.001430732,0.175157,0.01756134,0.008357622,0.2103714,0.01339101,0.5350812],"study_design_scores_gemma":[0.0006823729,0.002427504,0.01754246,0.03436642,0.001374925,0.002437456,0.07950719,0.04601884,0.01744954,0.4730168,0.3244758,0.0007007649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02631414,0.005820129,0.9061463,0.01875994,0.0005601622,0.00892039,0.0001656837,0.000519179,0.03279408],"genre_scores_gemma":[0.1486121,0.002659134,0.836648,0.002497446,0.0001361047,0.007086187,0.0001158964,0.0001257166,0.002119408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1440593,"threshold_uncertainty_score":0.7618673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.105457781777454,"score_gpt":0.4595712322343141,"score_spread":0.3541134504568602,"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."}}