Medical resource estimation and simulation system

• US 20070055543A1
• Filed: 02/17/2006
• Published: 03/08/2007
• Est. Priority Date: 02/17/2005
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Knapp, Robert
• Granted Patent: US 8,762,171 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/20 relating to practices or guidelines
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A healthcare decision support system simulates effects of a change in a number of patients. A repository includes patient specific clinical and non-clinical data, comprising multiple medical record attributes of multiple patients. A simulation processor receives data representing multiple factors for adjusting a value representing number of patients in corresponding multiple associated subsets of the multiple patients. An individual subset comprises patients having a particular medical record attribute of a particular type. A calculation processor identifies patients common to different particular subsets, and calculates a change in a value representing number of patients common to the different particular subsets by calculating a product of factors associated with the different particular subsets.

Claims

1. A healthcare decision support system for simulating effects of a change in a number of patients, comprising:

at least one repository including patient specific clinical and non-clinical data comprising a plurality of medical record attributes of a plurality of patients;

a simulation processor for receiving data representing a plurality of factors for adjusting a value representing number of patients in a corresponding plurality of associated subsets of said plurality of patients, an individual subset comprising patients having a particular medical record attribute of a particular type; and

a calculation processor for identifying patients common to different particular subsets and for calculating a change in a value representing number of patients common to said different particular subsets by calculating a product of factors associated with said different particular subsets.

2. A system according to claim 1, wherein

said medical record attribute comprises a clinical or non-clinical attribute and a clinical attribute comprises at least one of, (a) a diagnostic code, (b) a DRG (Diagnosis Related Group) code, (c) a treatment identifier, (d) a procedure identifier, (e) a medical condition identifier (f) healthcare provider visit type and

said non-clinical attribute comprises at least one of, (i) age, (ii) gender, (iii) weight, (iv) geographical area identifier, (v) healthcare provider, (vi) physician, (vii) medical insurance company and (viii) number of healthcare provider visits.

3. A system according to claim 1, wherein

said corresponding plurality of associated subsets of said plurality of patients are within a set of said plurality of patients determined by said simulation processor in response to user command.

4. A system according to claim 1, wherein

said simulation processor receives said data in response to user data entry.

5. A healthcare decision support system for simulating effects of a change in a number of patients, comprising:

at least one repository including patient specific clinical and non-clinical data comprising a plurality of medical record attributes of a plurality of patients;

a simulation processor for receiving data comprising,

a first factor for adjusting a value representing a number of patients in a corresponding first subset of said plurality of patients having a first medical record attribute of a first type,

a second factor for adjusting a value representing a number of patients in a corresponding second subset of said plurality of patients having a first medical record attribute of a different second type,

a third factor for adjusting a value representing a number of patients in a corresponding third subset of said plurality of patients having a second medical record attribute of a first type and

a fourth factor for adjusting a value representing a number of patients in a corresponding fourth subset of said plurality of patients having a second medical record attribute of a different second type; and

a calculation processor for identifying patients common to different particular subsets and for calculating a change in a value representing a number of patients common to said different particular subsets by calculating a product of factors associated with said different particular subsets.

6. A system according to claim 5, wherein

said calculation processor identifies patients common to two different particular subsets and calculates a cumulative change in number of patients common to said two different particular subsets by calculating a product of factors associated with said two different particular subsets.

7. A method for simulating effects of a change in a number of patients, comprising the steps of:

receiving patient specific clinical and non-clinical data, including medical record attributes of multiple patients;

applying one or more simulations to one or more individual subsets of the patient specific clinical and non-clinical data to generate corresponding adjustment factors; and

calculating a change in value, representing a number of patients common to the different particular individual subsets, by calculating a product of adjustment factors associated with the different particular individual subsets.

8. A method, according to claim 7, further comprising the steps of:

receiving data, representing a change in patient data;

generating simulation rules responsive to receiving the patient change data; and

generating the one or more simulations responsive to receiving the simulation rules.

9. A method, according to claim 7, further comprising the step of:

applying the product of the adjustment factors to the different particular individual subsets of the patient specific clinical and non-clinical data to generate forecast patient data.

10. A method, according to claim 7, further comprising the step of:

selecting by a user the one or more simulations and the one or more individual subsets of the patient specific clinical and non-clinical data.

11. A method for simulating effects of a change in a number of patients, comprising the steps of:

receiving data, representing a change in patient data;

generating simulation rules responsive to receiving the patient change data;

generating one or more simulations responsive to receiving the simulation rules;

receiving patient specific clinical and non-clinical data, including medical record attributes of multiple patients;

applying the one or more simulations to one or more individual subsets of the patient specific clinical and non-clinical data to generate corresponding adjustment factors; and

calculating a change in value, representing a number of patients common to the different particular individual subsets, by calculating a product of adjustment factors associated with the different particular individual subsets.

12. A method, according to claim 11, further comprising the step of:

applying the product of the adjustment factors to the different particular individual subsets of the patient specific clinical and non-clinical data to generate forecast patient data.

13. A method, according to claim 12, further comprising the step of:

selecting by a user the one or more simulations and the one or more individual subsets of the patient specific clinical and non-clinical data.

14. A method, according to claim 11, further comprising the step of:

selecting by a user the one or more simulations and the one or more individual subsets of the patient specific clinical and non-clinical data.

15. A user interface system permitting a user to simulate effects of a change in a number of patients, comprising:

a data input device permitting a user to select one or more simulations and one or more individual subsets of patient specific clinical and non-clinical data, wherein the one or more simulations are applied to the one or more individual subsets of the patient specific clinical and non-clinical data to generate corresponding adjustment factors; and

a data output device permitting a user to determine a change in value, representing a number of patients common to the different particular individual subsets by determining a product of adjustment factors associated with the different particular individual subsets.

16. A user interface system, according to claim 15, wherein the data output device permits a user to determine forecast patient data by applying the product of the adjustment factors to the different particular individual subsets of the patient specific clinical and non-clinical data.

17. A user interface system, according to claim 15, wherein the data input device is a keyboard, and herein the data output device is a display.

18. A method of using a user interface system by a user to permit the user to simulate effects of a change in a number of patients, comprising the steps of:

receiving, from a user, one or more commands to select one or more simulations and one or more individual subsets of patient specific clinical and non-clinical data, wherein the one or more simulations are applied to the one or more individual subsets of the patient specific clinical and non-clinical data to generate corresponding adjustment factors; and

determining, by the user, a change in value, representing a number of patients common to the different particular individual subsets by determining a product of adjustment factors associated with the different particular individual subsets.

19. A method, according to claim 18, further comprising the step of:

determining, by the user, forecast patient data by applying the product of the adjustment factors to the different particular individual subsets of the patient specific clinical and non-clinical data.