| 摘要 |
Computer-based methods and systems are presented for determining an illness complexity score, which can be used to predict the likelihood of high-cost hospitalization and/or to predict the patient's healthcare reimbursement costs. The methods comprise the steps of measuring a plurality of factors of a population of individuals, determining an effect on the healthcare costs of the individuals and a weighting coefficient for each factor, identifying significant factors as complexity variables, and computing illness complexity scores for the population of individuals using the weighting coefficients and complexity variables. The population data may then be used to predict the healthcare costs of a patient by calculating the illness complexity score of the individual.
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