{"id":"W3147324444","doi":"10.48205/gbr.v17.3","title":"Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System","year":2021,"lang":"en","type":"article","venue":"Gurukul Business Review","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Benchmarking; Data envelopment analysis; Health care; Frontier; Healthcare system; Montenegro; Business; Developing country; China; Economic growth; Economics; Regional science; Geography; Marketing; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004834216,0.0006195956,0.000770066,0.003232802,0.001289917,0.00342984,0.0009056143,0.001115616,0.001923746],"category_scores_gemma":[0.007993286,0.0002888013,0.001765517,0.005646608,0.001609886,0.001332465,0.001935492,0.001140435,0.0001581318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006779306,"about_ca_system_score_gemma":0.003687511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05951845,"about_ca_topic_score_gemma":0.02816063,"domain_scores_codex":[0.9967194,0.001683602,0.0001959667,0.0002201038,0.0006803322,0.0005005736],"domain_scores_gemma":[0.9923412,0.004906325,0.000875226,0.0004934604,0.001130618,0.0002531686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003394781,0.0005425023,0.1218404,0.0006673626,0.0003912598,0.005500809,0.002930117,0.7620196,0.001784444,0.06593428,0.002428832,0.03562091],"study_design_scores_gemma":[0.00008305363,0.0004753446,0.0892547,0.0003424803,0.0002696304,0.00122698,0.01297446,0.8645607,0.002690131,0.02235362,0.005602424,0.0001664629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558714,0.0005674636,0.02376485,0.001210911,0.00002660966,0.0002719753,0.0006512834,0.00006654563,0.01756879],"genre_scores_gemma":[0.9931078,0.0001801652,0.006060302,0.00002443135,0.000004782607,0.00004347529,0.0001184961,0.000009087331,0.0004515716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05951845,"threshold_uncertainty_score":0.1183441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2698042992503173,"score_gpt":0.4028149400066411,"score_spread":0.1330106407563238,"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."}}