1. A computer hardware-implemented method of matching a current patient to a specific patient readmission cohort, the computer hardware-implemented method comprising: receiving a first set of binary data that describes a specific patient readmission cohort, wherein the first set of binary data describes a shared attribute of patients in the specific patient readmission cohort, wherein the first set of binary data is from a first database, and wherein the first set of binary data describes an historical likelihood of hospital readmission within a predefined post-discharge length of time for members of the specific patient readmission cohort; determining a first cost/speed/probability parameter for a second database that contains a second set of binary data, wherein the first cost/speed/probability parameter defines a first minimum probability that the second database contains data that describes a first current patient attribute for a current patient, wherein the first current patient attribute matches the shared attribute within a predefined level of certainty, and wherein the first cost/speed/probability parameter defines a first maximum cost and a first minimum speed to access the second database; in response to the first cost/speed/probability parameter meeting predefined parameter values, retrieving the second set of binary data from the second database; executing comparison computer instructions to compare the first set of binary data with the second set of binary data in order to determine whether the second database contains data for the current patient that matches the shared attribute of patients in the specific patient readmission cohort within the predefined level of certainty, wherein said comparison computer instructions are executed using said first and second sets of binary data as inputs, and wherein matching the first current patient attribute from the second database to the shared attribute of patients in the specific patient readmission cohort causes the current patient to be placed in the specific patient readmission cohort; in response to execution of said comparison computer instructions, using said first and second sets of binary data as inputs, failing to place the current patient into the specific patient readmission cohort within the predefined level of certainty: retrieving a third set of binary data that further describes the first current patient attribute for the current patient, wherein the third set of binary data is from a third database, wherein the third set of binary data meets a second cost/speed/probability parameter, wherein the second cost/speed/probability parameter defines a second minimum probability that the third database contains data that describes the first current patient attribute for the current patient, and wherein the second cost/speed/probability parameter defines a second maximum cost and a second minimum speed to access the third database, and executing said comparison computer instructions to compare the first set of binary data with the second set of binary data and the third set of binary data, wherein said comparison computer instructions are executed using said first, second and third sets of binary data as inputs; in response to said executing said comparison computer instructions, with said first, second, and third sets of binary data as inputs, matching the first set of binary data to the second and third sets of binary data within the predefined level of certainty, placing the current patient into the specific patient readmission cohort; and recommending an amelioration to reduce a likelihood of hospital readmission of the current patient within the predefined post-discharge length of time.