Rating system, process and predictive algorithmic based medium for treatment of medical conditions and including workman compensation and general rehabilitation modules for optimizing care provider efficiencies and expedited treatment for achieving higher patient functional outcomes and lower cost

• US 10,417,381 B2
• Filed: 06/09/2016
• Issued: 09/17/2019
• Est. Priority Date: 09/26/2013
• Status: Active Grant

• Current Assignee: Ali Alhimiri
• Original Assignee: Ali Alhimiri
• Inventors: Alhimiri, Ali
• Primary Examiner(s): Tomaszewski, Michael
• Assistant Examiner(s): Patel, Jay M.
• Application Number:
  US15/177,903
• Publication Number:
  US 20160292371A1
• Time in Patent Office: 1,195 Days
• Field of Search: None
• CPC Class Codes: B01F 23/191 characterised by the construction of the controlling means
• CPC Class Codes: B01F 25/3141 with additional mixing means other than injector mixers
• CPC Class Codes: B01F 25/4336 Mixers with a diverging cross-section
• CPC Class Codes: B01F 35/2113 Pressure
• CPC Class Codes: B01F 35/2211 Amount of delivered fluid during a period
• CPC Class Codes: B01F 35/715 Feeding the components in several steps, e.g. successive steps
• CPC Class Codes: B01F 35/833 Flow control by valves, e.g. opening intermittently
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0217 involving input on products or services in exchange for incentives or rewards
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• 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 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 70/20 relating to practices or guidelines

Abstract

The present invention discloses a system, method and non-transitory software based computer writeable medium usable with a processor driven device for optimizing the diagnosis, treatment and resolution of worker injury events, such as associated with a workman compensation claim, and which improves upon the existing paper based module by synthesizing, in a digital environment, symptom, treatment and progress variables in a multi-party available format. A further related rehabilitation module, such as not limited to a worker injury event but also including any injury event associated with a typical accountable care organization (insurer/other payor/etc.) in a general health application is provided for establishing and tracking a patient'"'"'s functional independent (FEM) measurement score. As with the workman compensation module, the rehabilitation module integrates the establishment of current conditions, achievable goals, and time based tracking of the patient treatment (including time elapsed changes in response to flat line response indicating a non-effective treatment plan) in order to define a patient goal outcome and to optimize real time treatment and progress tracking to that goal.

Claims

1. A non-transitory software based algorithmic medium usable with a processor driven device for use in the treatment of an injured worker by a care provider through a graphical user interface, the injured worker further being involved in a workman compensation claim with an employer or payer, comprising:

a first subroutine for assembling a provider network incorporating a best practices model in a database interfacing with the processor device and which presents series of treatment options associated with a given type of service, along with a fee schedule incentivizing the care provider in an achievement of a best functional outcome;

a second subroutine, configured to be executed after the first subroutine, for training a plurality of the care providers in one or more of a series of medical related diagnosis and treatment programs consistent with objectives of the first subroutine, said second subroutine further including establishing one or more management pathways which are customizable by the provider network and through establishing a questioning protocol for modifying or customizing a base algorithm for any one or more of a variety of treatment sub-species;

a third subroutine, configured to be executed after the second subroutine, for use by a supervisor designated by the employer/payer and which, upon occurrence of an injury event, provides input of both worker biographical and detail of injury;

a fourth subroutine, configured to be executed after the third subroutine, for assignment, by the provider network, of the care provider;

a fifth subroutine, configured to be executed after the fourth subroutine, which, upon an initial visit of the injured worker with the care provider, provides for confirmation by the injured worker of details previously provided by the supervisor and for;

inputting of additional information, details surrounding the injury event, or both;

a sixth subroutine, configured to be executed after the fifth subroutine, for establishing, by the injured worker, an electronic initial injury detail chart including a pictorial representation of a human form and inputs for symptoms relating to the injury event including type and intensity of pain;

a seventh subroutine, configured to be executed after the sixth subroutine, for synthesizing all of the preceding subroutines in the establishment of a symptoms and treatment catalog over a duration of time extending from the injury event to an eventually determined end event corresponding to a recovery by the injured worker of a level of ability and function necessary for triggering a return to work event; and

an eighth subroutine, configured to be executed after the seventh subroutine, for iteratively treating the injured worker and updating the symptoms and treatment catalog, such occurring at determined time intervals following the injury event until the eventually determined end event.

2. The non-transitory software based algorithmic medium of claim 1, further comprising a ninth subroutine for determining, between the care provider, worker and employer/payer, a set of goals for achievement by the injured worker in triggering the return to work event.

3. The non-transitory software based algorithmic medium of claim 2, said sixth subroutine further comprising front and back pictorial depictions of a human form, said symptom inputs further comprising listing of any of an aching pain, stabbing pain, burning pain or a numbness/tingling, along with either of a color or numerical intensity code.

4. The non-transitory software based algorithmic medium of claim 1, further comprising a tenth worker ability input subroutine, occurring between the fifth and seventh subroutines, and listing a number of typical duties associated with a job of the injured worker, and for which the injured worker provides a current ability input.

5. The non-transitory software based algorithmic medium of claim 4, said current ability input of the tenth subroutine further comprising listing a point score for each duty as tied to any one of a minimum effort, moderate effort, severe effort, extreme effort and unable to perform, an accumulation of the points totaling the injured worker'"'"'s current ability.

6. The non-transitory software based algorithmic medium of claim 5, said eighth subroutine further comprising a time interval comparison of said current ability and goals and corresponding to both treatment and changes in treatment derived from the first and second subroutines.

7. The non-transitory software based algorithmic medium of claim 6, further comprising synthesizing said injured worker ability input subroutine with said seventh and eighth subroutines in order to create an eleventh subroutine for determining, for each time interval, a range between injured worker inputted current ability and goal ability for each identified job duty.

8. The non-transitory software based algorithmic medium of claim 7, further comprising a twelfth subroutine for graphing a succession of time interval data points, each corresponding to an average of a current injured worker ability for the identified job duties, the care provider comparing an angle of inclination of the graph with the treatment protocols provided in the best practices model of the first subroutine and the management pathways of the second subroutine in continued treatment of the injured worker according to the eighth subroutine.

14. The non-transitory software based algorithmic medium of claim 3, wherein the front and back pictorial depictions of a human form further comprise displayed physiological location indicators based upon input received from the injured worker at a symptoms input graphical user interface.

9. A non-transitory software based algorithmic medium usable with a processor driven device utilizing a graphical user interface for use in the treatment and rehabilitation of a patient covered by a provider network, comprising:

a first subroutine for assembling a provider network incorporating a best practices model in a database interfacing with the processor device and which presents series of treatment options associated with a given type of service, along with a fee schedule incentivizing the care provider in the achievement of a best functional outcome;

a second subroutine, configured to be executed after the first subroutine, for training a plurality of the care providers in one or more of a series of medical related diagnosis and treatment programs consistent with objectives of the first subroutine, said second subroutine further including establishing one or more management pathways which are customizable by the provider network and through establishing a questioning protocol for modifying or customizing a base algorithm for any one or more of a variety of treatment sub-species;

a third subroutine, configured to be executed after the second subroutine, for entering or synthesizing patient information including biographical and nature/type of condition associated with an event date;

a fourth subroutine, configured to be executed after the third subroutine, for assignment, by the provider network, of a care provider for the treatment of the patient;

a fifth rehabilitation setting input subroutine, configured to be executed after the fourth subroutine, for establishing, by the patient with or without assistance of the care provider, a listing of scaled efforts ranging independent to total physical assist and associated with a listing of patient ADL functions, such determinative of a present or future rehabilitative setting as recommended to the provider network;

a sixth subroutine, configured to be executed after the fifth rehabilitation setting input subroutine, for synthesizing all of the preceding subroutines in establishing a treatment and rehabilitation catalog over a duration of time extending from the event date to an eventually determined end event corresponding to an eventual final degree of recovery by the patient of a level of ability and function associated with an end rehabilitation setting; and

a seventh subroutine, configured to be executed after the sixth subroutine, for iteratively treating the patient and updating the symptoms and treatment catalog, such occurring at determined time intervals following the event date until an eventually determined end date.

10. The non-transitory software based algorithmic medium of claim 9, further comprising an eighth rehabilitation subroutine for determining, between the care provider, patient and provider network, a set of goals for achievement by the patient in satisfying an established criteria for a given rehabilitation setting ranging from inpatient, subacute, home care, outpatient or none.

11. The non-transitory software based algorithmic medium of claim 10, said seventh subroutine further comprising a time interval comparison of said current ability and goals and corresponding to both treatment and changes in treatment derived from the first and second subroutines.

12. The non-transitory software based algorithmic medium of claim 11, further comprising synthesizing said rehabilitation setting input subroutine with said sixth and seventh subroutines in order to create a ninth rehab setting subroutine for determining, for each time interval, a range between patient inputted prior function, current function and goal function for each identified ADL function.

13. The non-transitory software based algorithmic medium of claim 12, further comprising an eighth subroutine for graphing a succession of time interval data points, each corresponding to an average of a patient ability for the identified ADL functions, the care provider comparing an angle of inclination of the graph with the treatment protocols provided in the best practices model of the first subroutine and the management pathways of the second subroutine in continued treatment of the patient according to the seventh subroutine.