{"id":"W2986075423","doi":"10.3386/w26455","title":"How do Hospitals Respond to Payment Incentives?","year":2019,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Reimbursement; Incentive; Payment; Revenue; Actuarial science; Coding (social sciences); Business; Medical diagnosis; Medical record; Medical classification; Diagnosis code; Medical costs; Prospective payment system; Finance; Medicine; Economics; Nursing; Health care; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01173666,0.0004107821,0.0006738385,0.00197313,0.001231151,0.006496478,0.001211126,0.003876534,0.009077687],"category_scores_gemma":[0.09962691,0.0004806403,0.0007277081,0.0024616,0.001355359,0.005165388,0.003060312,0.003011481,0.001156001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004567616,"about_ca_system_score_gemma":0.004947061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006549691,"about_ca_topic_score_gemma":0.007005215,"domain_scores_codex":[0.9851949,0.006651305,0.0008362494,0.0008607558,0.002218682,0.00423826],"domain_scores_gemma":[0.9217007,0.02856276,0.03170699,0.002292411,0.007146401,0.008590767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000628021,0.0007869778,0.6745247,0.0005332156,0.0005245226,0.0003834652,0.002277456,0.007281153,0.0006576888,0.05423403,0.09514317,0.1630256],"study_design_scores_gemma":[0.0004764908,0.0007417981,0.7686594,0.001036979,0.0002129643,0.0006171278,0.01551525,0.009456933,0.001096151,0.1022171,0.09971011,0.0002595857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5028446,0.007857384,0.005305265,0.4258446,0.001688714,0.0002615988,0.002475204,0.0002117526,0.05351086],"genre_scores_gemma":[0.972656,0.001445418,0.0008214731,0.02188133,0.0007203319,0.00007874463,0.0003565301,0.00003821783,0.00200197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01173666,"threshold_uncertainty_score":0.06207013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4299712649442424,"score_gpt":0.5120134682861768,"score_spread":0.0820422033419344,"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."}}