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The United States Federal Government operates one of the worldslargest medical insurance programs, Medicare, to ensure payment for clinicalservices for the elderly, illegal aliens and those without the ability to payfor their care directly. This paper evaluates the Medicare 2011 TransactionData Set which details the transfer of funds from Medicare to private andpublic clinical care facilities for specific clinical services for theoperational year 2011. Methods: Data mining was conducted to establish therelationships between reported and computed transaction values in the data setto better understand the drivers of Medicare transactions at a programmaticlevel. Results: The models averaged 88 for average model accuracy and 38 foraverage Kappa during training. Some reported classes are highly independentfrom the available data as their predictability remains stable regardless ofredaction of supporting and contradictory evidence. DRG or procedure typeappears to be unpredictable from the available financial transaction values.Conclusions: Overlay hypotheses such as charges being driven by the volumeserved or DRG being related to charges or payments is readily false in thisanalysis despite 28 million Americans being billed through Medicare in 2011 andthe program distributing over 70 billion in this transaction set alone. It maybe impossible to predict the dependencies and data structures the payer of lastresort without data from payers of first and second resort. Political concernsabout Medicare would be better served focusing on these first and second orderpayer systems as what Medicare costs is not dependent on Medicare itself.

Conclusions from a NAIVE Bayes Operator Predicting the Medicare 2011 Transaction Data Set