{"id":"W4402412492","doi":"10.2196/46901","title":"User Experiences of Transitioning From a Homegrown Electronic Health Record to a Vendor-Based Product in the Department of Veterans Affairs: Qualitative Findings From a Mixed Methods Evaluation","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Quality Enhancement Research Initiative; Health Services Research and Development; U.S. Department of Veterans Affairs","keywords":"Vendor; Veterans Affairs; Product (mathematics); Electronic health record; Workflow; Formative assessment; Medicine; Medical education; Health care; Nursing; Psychology; Public relations; Business; Marketing; Computer science; Political science; 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":[0.04041029,0.0006480109,0.0007875827,0.001374001,0.008760261,0.006135609,0.003044074,0.001802975,0.002324034],"category_scores_gemma":[0.04243949,0.0007399603,0.0007030168,0.001704197,0.005934661,0.003769054,0.00725717,0.002159455,0.0003509988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007668251,"about_ca_system_score_gemma":0.006960621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008385063,"about_ca_topic_score_gemma":0.01451623,"domain_scores_codex":[0.9609823,0.0330924,0.0008583399,0.001063189,0.001562271,0.002441448],"domain_scores_gemma":[0.9494478,0.03985481,0.001930911,0.001150676,0.003959325,0.003656514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001021224,0.000214074,0.005962846,0.0002295284,0.0000131392,0.0006406453,0.9798725,0.00007044213,0.0009207361,0.0005452487,0.0006289189,0.01079974],"study_design_scores_gemma":[0.0000145472,0.0002989245,0.002431824,0.0002064725,0.00001464505,0.0002352164,0.9910291,0.0001817026,0.0007196168,0.0001847961,0.004664119,0.00001894455],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929879,0.000373005,0.002480208,0.001285225,0.00002926135,0.0003357026,0.000143917,0.00002636722,0.002338507],"genre_scores_gemma":[0.992488,0.000446976,0.003680388,0.0009299801,0.00001636458,0.0006196129,0.00008969339,0.00003974234,0.001689288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04041029,"threshold_uncertainty_score":0.2137126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2095158862250063,"score_gpt":0.615684334869224,"score_spread":0.4061684486442177,"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."}}