Mining lung cancer patient data to assess healthcare resource utilization

Expert Systems with Applications

Volumn 35, Issue 4, 2008, Pages 1611-1619

  Phillips Wren, Gloria ^a   Sharkey, Phoebe ^a   Dy, Sydney Morss ^b,c  

^a LOYOLA UNIVERSITY MARYLAND   (United States)

^b JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^c JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Data mining; Healthcare utilization; Lung cancer; Medicare claims data; Propensity score

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; BIOLOGICAL ORGANS; CHLORINE COMPOUNDS; DATA MINING; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; DECISION TREES; FINANCE; FOOD PROCESSING; HOSPITAL DATA PROCESSING; INFORMATION MANAGEMENT; INSURANCE; MINING; MINING ENGINEERING; NEURAL NETWORKS; PROBLEM SOLVING; PUBLIC POLICY; SEARCH ENGINES;

ARTIFICIAL NEURAL NETWORKS; DATA MINING METHODS; DATA MINING TECHNIQUES; DEMOGRAPHIC CHARACTERISTICS; GEOGRAPHIC VARIATIONS; HEALTH CARE DELIVERY; HEALTH CARE RESOURCES; HEALTHCARE UTILIZATION; INSURANCE CLAIMS; LUNG CANCER; LUNG CANCERS; MEDICAL DECISION-MAKING; MEDICARE CLAIMS DATA; PATIENT DATA; PREDICTIVE POWER; PROPENSITY SCORE; REGRESSION METHODS; RESOURCE UTILIZATIONS;

HEALTH;

EID: 48949088710     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.08.076     Document Type: Article

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