Health data processing system

• US 5,778,345 A
• Filed: 01/16/1996
• Issued: 07/07/1998
• Est. Priority Date: 01/16/1996
• Status: Expired due to Term

• Current Assignee: Medisolv, Inc.
• Original Assignee: Mccartney Consultants Ltd.
• Inventors: McCartney, Michael J.
• Primary Examiner(s): Weinhardt, Robert A.
• Assistant Examiner(s): Poinvil, Frantzy
• Application Number:
  US08/586,246
• Time in Patent Office: 903 Days
• Field of Search: 395/201, 395/202, 395/203, 705/1-3, 283/54, 283/55, 364/468.05
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• 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 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Abstract

A method and system for evaluating health care provider performance, forecasting health care resource consumption on a macroeconomic scale, and optimizing the allocation of health care resource. The method includes the steps of a) providing patient discharge data which includes an address field indicating one of a plurality of micro-geographical areas (MGAs) wherein a patient resides, b) establishing a referral population for a subject health care provider based upon the market share it has for each cohort in each MGA, c) calculating occurrence rates of medical service demand for the referral population, d) providing and applying population growth factors to the referral population thereby projecting it to a future time, e) applying the occurrence rates to the projected referral population thereby forecasting the consumption of health resources, and f) allocating health care resources in accordance with the forecast. The invention can also factor into the forecast the expected caseload demand from undeveloped or proposed communities. In addition, the invention optionally computes repatriatable caseload volume, i.e. medical service demand which has gone to another health care provider but could be handled by the subject health care provider, and adds this volume to the forecast. Finally, the invention provides for a method for efficiently allocating health resources amongst neighbouring health care providers, based on either current or forecasted medical service demand data.

Claims

1. A computer-implemented method of optimizing the allocation of health resources for at least one subject health care provider, comprising the steps of:

providing census data and patient discharge records for substantially all of the patient populations of the subject health care provider and other major health care providers within a boundary region, said patient discharge records including an address field indicating one of a plurality of micro-geographical areas (MGAs) where a patient resides, the MGAs for logically apportioning the boundary region into sub-areas having roughly equal population sizes;

establishing a referral population;

calculating occurrence rates of medical services for the referral population;

providing and applying population growth factors to the referral population thereby projecting it to a future time;

applying said occurrence rates to the projected referral population thereby forecasting the consumption of health resources for the subject health care provider; and

altering the composition of the health care provider'"'"'s resources in accordance with said forecast.

2. A method according to claim 1 wherein the step of establishing a referral population comprises the steps of:

determining a market share of the subject health care provider in the boundary region; and

selecting portions of the population of the boundary region generally in accordance with said market share thereby establishing the referral population.

3. A method according to claim 2 including the steps of:

providing housing development planning data for a proposed community;

establishing the demographics of the proposed community in accordance with historical data in respect of past housing developments which occurred in an MGA wherein the proposed community is situated;

estimating the number of occurrences of medical services for the proposed community population in accordance with occurrence rates for a general population; and

incorporating the estimated number of medical service occurrences with the amount of medical services occurrences calculated for the MGA the proposed community is located in.

4. A method according to claim 2 further including the step of computing a financial budget for the subject health care provider.

5. A method according to claim 2 including the steps of:

determining a population size per cohort from said census data, the cohorts being pre-selected; and

computing said market share per cohort.

6. A method according to claim 5 wherein said market share is computed substantially per each unique MGA present in said patient discharge records.

7. A method according to claim 6 including the steps of:

determining a current population size, S⁰_coh,mga, per cohort, per MGA, from said census data;

determining a number, N_coh,mga, of people attending any health care provider, per cohort, per MGA;

determining a number, H_coh,mga, of people attending the subject health care provider, per cohort, per MGA; and

setting the referral population size for a given cohort and a given MGA, R⁰_coh,mga, such that R⁰_coh,mga =S⁰_coh,mga * (H_coh,mga /N_coh,mga).

8. A method according to claim 7 wherein said population growth factors are computed for a given MGA by employing published growth figures for a political jurisdiction associated with the given MGA and varying the published figure generally in accordance with the number of housing units planned for the given MGA.

9. A method according to claim 7 wherein said population growth factor for a given MGA is derived from a regression analysis of historical population growth for the given MGA.

10. A method according to claim 8 wherein said determination of said population growth factor for a given MGA includes the steps of:

determining a first variation in an amount of recently constructed housing units from a recent mean amount of housing units constructed for MGAs composing the jurisdiction;

determining a second variation in historical population growth rate for the given MGA from a historical published jurisdictional growth rate based on birth, date and migration rates;

correlating said first and second variations;

determining a third variation in the present planned number of housing units from a mean amount of planned housing units for MGAs composing the jurisdiction;

applying the correlation to the third variation to thereby compute a variation in the present published jurisdictional growth rate; and

varying the published jurisdiction growth rate by the fourth variation to thereby compute said population growth factor.

11. A method according to claim 8 wherein said step of projecting said referral population includes the steps of:

computing a projected population size, S^t_coh mga, per cohort, per MGA, by applying said growth factor per MGA to S⁰_coh,mga, and

computing a projected referral population size, R^t_coh mga, per cohort, per MGA, where R^t_coh,mga =S^t_coh,mga * (H_coh,mga /N_coh,mga).

12. A method according to claim 2 wherein said occurrence rates are static.

13. A method according to claim 2 wherein said occurrence rates are equations derived from historical patient discharge data.

14. A method according to claim 13 including the steps of:

determining, per category of medical service, a plurality of static occurrence rates for a plurality of generally contiguous years;

computing, per category of medical service, a best curve equation for the occurrence rate plurality.

15. A method according to claim 3 wherein the step of determining demographics for said proposed community includes the steps of:

determining the number of housing units planned for said proposed community and the price ranges thereof from the housing development data;

determining, from historical housing development and census data, a breakdown of cohort proportion for each range of housing prices;

multiplying the cohort breakdown against the planned number of housing units to thereby compute the demographics of said proposed community.

16. A method according to claim 15 including the step of determining, from historical housing development and census data, an ethnic breakdown for each cohort per each range of housing price, and wherein said step of computing occurrence rates from the general population comprises the steps of computing occurrence rates for substantially each ethnicity in the ethnic breakdown per cohort by limiting said general population to the respective ethnic group and thereafter combining the occurrence rates computed per ethnic group to thereby compute the total occurrence rate per cohort.

17. A method according to claim 4 wherein said budget calculating step includes the step of calculating a budget based on a prospective payment system.

18. A method according to claim 4 wherein said budget calculating step includes the step of calculating a budget based on a projection of current cost.

19. A method according to claim 2 including the step of computing a catchment area for the subject health provider and thereby allocating health care resources associated with the subject health care provider in accordance with the geographic scope of the catchment area and the density of service therein.

20. A method according to claim 19 wherein the step of computing a catchment area comprises the steps of:

determining, for each MGA in the boundary region, the proportion of usage of the given health care provider'"'"'s resources by the population thereof;

ranking said MGAs by proportion of usage;

selecting a subset of said MGAs, the subset consisting of the MGA having the highest proportion of usage quantum and including additional MGAS, in descending order of quantum, until the subset of MGAs collectively represent a specified cumulative proportion of usage, thereby determining a Pareto efficient distribution of the given health care provider'"'"'s patient population.

21. A computer-implemented process for optimizing the consumption of health resources of at least one subject health care provider, comprising the steps of:

providing i) a master disease and medical services classification database (MCD), ii) a patient record composite file (PRCF) having patient records for substantially all of the subject health care provider'"'"'s patient population and other major health care providers within a boundary region, said patient record including an address field indicating one of a plurality of micro-geographical areas (MGAs) wherein the patient resides, the MGAs for logically apportioning the boundary region into subareas having roughly equal population sizes, iii) a census data file for at least the boundary region, and iv) population growth factors for the boundary region;

determining, from the census data file, a population per each unique MGA present in the address field of the PRCF;

compiling, from the PRCF, a breakdown of the usage of all health care providers by the residents of each MGA;

computing, from the breakdown and the population size, a market share quantum for the subject health care provider per MGA;

selecting portions of the total population of each MGA in accordance with the market share of the subject health care provider therein, thereby determining a referral population per MGA;

determining, with respect to the MCD, occurrence rates of medical service for the referral population per MGA;

applying the population growth factors to the referral population per MGA thereby projecting it to a future time;

applying said occurrence rates to the projected referral population per MGA thereby forecasting the consumption of health resources for the subject health care provider; and

altering the composition of the health care provider'"'"'s resources in accordance with the forecast.

22. A process according to claim 21 further including the steps of:

providing housing development planning data for a proposed community and providing historical planning data for the MGA(s) the proposed community is located in;

determining a population for the proposed community in accordance with the historical planning data;

estimating the number of occurrences of medical services for the proposed community population in accordance with occurrence rates for a general population; and

incorporating the estimated number of medical service occurrences with an actual amount of medical services occurrences for the referral population of the MGA the proposed community is located in.

23. A process according to claim 21 including the step of computing a financial budget for the subject health care provider based upon the forecasted health resource demand.

24. A process according to claim 21 wherein said market share per MGA is additionally determined per cohort and said referral population per MGA is additionally determined per cohort.

25. A process according to claim 21 wherein said occurrence rates are static and based upon data for a latest period in the PRCF.

26. A process according to claim 21 wherein said occurrence rates are equations derived from historical patient discharge data composing the PRCF.

27. A process according to claim 21 including the step of computing a catchment area for the subject health provider and thereby allocating health care resources associated with the subject health care provider in accordance with the geographic scope of the catchment area and the density of service therein.

28. A computer-implemented process for optimizing the allocation of health care resources amongst a plurality of health care providers situated within a boundary region, comprising the steps of:

providing a patient record composite file (PRCF) having patient records for substantially all of the subject health care provider'"'"'s patient population and other major health care providers within the boundary region, said patient record including an address field indicating one of a plurality micro-geographical areas (MGAs) wherein the patient resides, the MGAs for logically apportioning the boundary region into sub-areas having roughly equal population sizes;

establishing a catchment area for each health care provider;

comparing the geographic scope of the catchment areas;

computing a patient/physician ratio for at least one category of medical service for each health care provider; and

redistributing or altering the health resources associated with the health care providers in accordance with said ratios providing the catchment areas at least partially overlap.

29. A process according to claim 28 wherein the step of establishing a catchment area comprises the steps of:

determining, from the patient records in the PRCF, the number of patient discharges per unique MGA, per health care provider; and

selecting, for each health care provider, a subset of MGAs having the highest levels of patient discharges such that the subset composes a Pareto efficient geographic distribution of the health care provider'"'"'s patient population, thereby identifying the catchment area for each health care provider.

30. A process according to claim 29 wherein the step of defining a catchment area for a given health care provider includes the steps of:

determining, for a plurality of MGAs in the boundary region, the proportion of usage of the given health care provider'"'"'s resources by the populace of each MGA;

ranking said MGA plurality by proportion of usage;

selecting a subset of said MGA plurality, the subset consisting of the MGA having the highest proportion of usage quantum and including additional MGAs, in descending order of quantum, until the subset of MGAs collectively represent a specified cumulative proportion of usage, thereby determining said Pareto efficient distribution of the given health care provider'"'"'s patient population.

31. A computer-implemented process for optimizing the allocation of health care resources of at least one subject health care provider, comprising the steps of

providing a patient record composite file (PRCF) having patient records for substantially all of the subject health care provider'"'"'s patient population and other major health care providers within the boundary region, said patient record including an address field indicating one of a plurality micro-geographical areas (MGAS) wherein the patient resides, the MGAs for logically apportioning a boundary region into sub-areas having roughly equal population sizes;

establishing a catchment area for the subject health provider;

selecting, from the PRCF, patient records in respect of patients seeking health services outside of the catchment area, thereby forming a set;

calculating an isarythmic boundary for the subject health care provider;

excluding from the set patient records in respect of patients living external to the isarythmic boundary;

excluding from the set patient records in respect of complex cases transferred to specified health care providers; and

altering the composition of health resources for the subject health care provider in accordance with categories and amounts of medical service listed in the set.

32. A process according to claim 31 wherein the step of establishing the catchment area comprises the steps of:

determining, from the patient records in the PRCF, the number of patient discharges per unique MGA;

selecting a subset of MGAs having the highest levels of patient discharges such that the subset composes a Pareto efficient geographic distribution of the health care provider'"'"'s patient population, thereby establishing the catchment area.