METHOD AND APPARATUS FOR DETERMINING HIGH SERVICE UTILIZATION PATIENTS
First Claim
1. A method of identifying patients likely to have future high use of medical services, comprising the steps of:
- collecting patient claims data in electronic form on a population of patients as records for each patient, each patient record including at least claim elements identifying the patient, a disease or condition and prior utilization of medical services;
creating a model for predicting which patients will require a disproportionately high use of medical services based on the patient claims data by performing regression analysis on each of the claims elements to select one or more high relevance claims elements and their relative power or weight in predicting high use, said model being expressed as a probability equation in the form of the sum of each of the high relevance claims variables multiplied by its weighing coefficient; and
applying the claims data for at least one of the patient records to the probability equation to assign a score to the patient record based the result of the probability equation, said score being a prediction of the relative likelihood that the patient will use a disproportionately high amount of medical services.
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Abstract
An automated method and system for predicting the likelihood that a patient will acquire high medical service utilization characteristics, thereby becoming a high-cost patient to a managed care organization or the like, relative to other patients includes selecting a predictive subset of variables from a larger set of variables corresponding to patient claims data based on the results of multivariate statistical modeling, such as logistical regression analysis. Predetermined weighing coefficients derived from the statistical modeling are applied to each of the claims variables of the predictive subset and a probability equation is developed based upon the weighing coefficients and claims variables of the predictive set. The probability equation is applied to patient claims data to determine a probability value indicative of the likelihood that the given patient will have a high utilization of health care resources in a given period of time, and thereby become a higher-cost patient relative to other patients. Once identified, high-use patients can be targeted for preventative medical interventions.
99 Citations
24 Claims
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1. A method of identifying patients likely to have future high use of medical services, comprising the steps of:
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collecting patient claims data in electronic form on a population of patients as records for each patient, each patient record including at least claim elements identifying the patient, a disease or condition and prior utilization of medical services;
creating a model for predicting which patients will require a disproportionately high use of medical services based on the patient claims data by performing regression analysis on each of the claims elements to select one or more high relevance claims elements and their relative power or weight in predicting high use, said model being expressed as a probability equation in the form of the sum of each of the high relevance claims variables multiplied by its weighing coefficient; and
applying the claims data for at least one of the patient records to the probability equation to assign a score to the patient record based the result of the probability equation, said score being a prediction of the relative likelihood that the patient will use a disproportionately high amount of medical services. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of identifying patients who are likely to have future high utilization of medical services, comprising the steps of:
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collecting patient claims data in electronic form on a population of patients as records for each patient, each patient record including at least an identification of the patient and claims data associated with a predetermined group of high relevance claims variables;
applying a probability equation to the claims data for at least one of the patient records based on the sum of each of the predetermined high relevance claims variables multiplied by a predetermined weighing coefficient;
assigning a score to the patient record based the result of the probability equation, said score being a prediction of the relative likelihood that the patient will incur high use of medical services; and
intervening with the patient having a score indicating an above average probability that the patient will incur high use of medical services. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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20. Apparatus for identifying patients who are likely to have high utilization of medical services, comprising:
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at least one data processing terminal through which patient claims data is collected on patients in electronic form, said terminal collecting the data in the form of records for each patient, each patient record including variable elements of data providing at least an identification of the patient and the utilization of medical services by the patient;
a database in the form of an organized memory in which the patient records are stored;
a predictive computing system including a processor, a processor memory and a device for accessing patient records in said database, said processor memory storing a regression analysis program which operates in said processor on the various elements of data in the patient record in regard to selecting a group of one or more high relevance claim variables to create a model for predicting which patients will incur high medical service utilization, said model being stored in the processor memory.
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21. Apparatus for identifying patients who are likely to have high use of medical services, comprising:
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at least one data processing terminal through which patient claims data is collected on patients in electronic form, said terminal collecting the data in the form of records for each patient, each patient record including variable elements of data providing at least an identification of the patient and the utilization by the patient of medical services;
a database in the form of an organized memory in which the patient records are stored;
a predictive computing system including a processor, a processor memory and a device for accessing patient records in said database;
said program memory storing a model as a probability equation predicting which patients will incur high utilization of medical services, said processor further assigning a score to each patient record based on the model, the score being a prediction of the relative likelihood that the patient will incur high use of medical services; and
an output device for indicating the score. - View Dependent Claims (22, 23, 24)
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Specification