{"id":"W4406854628","doi":"10.1007/s41666-025-00187-8","title":"Integrating the Patient Perspective into Healthcare and Real-World Evidence: The Multi-site, Cross-Disease, Patient-Centered Outcomes Research Project in the Medical Informatics Initiative (PCOR-MII)","year":2025,"lang":"en","type":"article","venue":"Journal of Healthcare Informatics Research","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Charité – Universitätsmedizin Berlin; Bundesministerium für Bildung und Forschung","keywords":"Perspective (graphical); Patient-centered outcomes; Informatics; Health care; Health informatics; Medicine; Outcomes research; Nursing; Political science; Computer science; Alternative medicine; Public health; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.02109273,0.0003352097,0.0005951491,0.002056598,0.001882584,0.0007955751,0.001886316,0.0002289708,0.00003579583],"category_scores_gemma":[0.01055757,0.0001670297,0.0002543206,0.003527912,0.001533345,0.001266656,0.001049363,0.006370336,0.00003324967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002340973,"about_ca_system_score_gemma":0.004807332,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01771639,"about_ca_topic_score_gemma":0.02773974,"domain_scores_codex":[0.9831276,0.006382589,0.004224218,0.0002455641,0.004586663,0.001433365],"domain_scores_gemma":[0.9816189,0.01049021,0.001192032,0.0009861789,0.005215284,0.0004973931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001605079,0.001133361,0.162603,0.00280042,0.0002284174,0.0001538329,0.6840503,0.000009895475,2.31009e-7,0.04817684,0.01461352,0.08462518],"study_design_scores_gemma":[0.001556339,0.003084474,0.1090938,0.007107733,0.00001706738,0.0001245822,0.8645251,0.002130402,0.000004742721,0.008193799,0.003958794,0.0002031287],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7914436,0.006582126,0.000129484,0.1846638,0.001751704,0.006967087,0.0002084356,0.00003603586,0.008217758],"genre_scores_gemma":[0.9930606,0.0007156606,0.000573674,0.004855905,0.00008517757,0.0004689666,0.00001285132,0.00002427391,0.0002029122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.201617,"threshold_uncertainty_score":0.9994168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.285989016265896,"score_gpt":0.6053786241674862,"score_spread":0.3193896079015902,"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."}}