“Healthcare Practice Management System And Method Thereof” in Patent Application Approval Process (USPTO 20210210199)

2021 JUL 23 (NewsRx) -- By a News Reporter-Staff News Editor at Computer Business Daily -- A patent application by the inventors LIROV, Erez (Morganville, NJ, US); LIROV, Yuval (Clearwater Beach, FL, US), filed on March 22, 2021, was made available online on July 8, 2021, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application has not been assigned to a company or institution.

The following quote was obtained by the news editors from the background information supplied by the inventors: “Healthcare institutions struggle to receive payments for their services from insurance companies and Payors of medical services. There is a constant battle between healthcare service providers (“Payees”) and insurance companies, such as Blue Cross Blue Shield and governmental organizations, such as Medicare and Medicaid, (“Payors”) to process claims and transmit payment for services provided.

“Payees work diligently process claims so as to timely collect payment from Payors. Delays, however, are often present in transmitting and collecting insurance premiums from Payors that transmit payment. Payors, such as insurance companies, do not pay out all the money they collect right away. Rather, an insurance company will collect money in the form of premiums from its clients, invest that money, and then pay out claims as needed at some future date. The difference between premiums collected and claims paid out is insurance float or float. Float is, in essence, a loan to the Payors, or debt owed by the Payors to the Payees. System float (or total system float) refers to an entire amount of float (or money) owed to a single Payee, by one or more Payors.

“In practice, healthcare institutions have large numbers of clients and submit thousands of claims to various Payors. Tracking the claims and payments and having payments processed is extraordinarily complex, as insurance companies have a built-in incentives not to pay legally valid claims under their contractual obligations and to maximize float, as it gives maximum amounts of time to invest money from clients. Furthermore, insurance companies intentionally fail to make payments or make underpayments in order to increase float and have additional time in which to invest float funds. Insurance companies also make the rules for submitting claims intentionally complex and dispute claims for the most trivial and minor of reasons. In short, it is the Payor’s financial best interest to not timely pay any claim. Furthermore, it is to be noted that all or substantially all Payors require electronic communications, i.e., all claims must be submitted electronically. It is often the case that substantially all or all of the information regarding service provided by a healthcare service provider is entered and maintained electronically. Most patients are given a tablet when first visiting a healthcare service provider the first time to enter all their relevant contact, insurance, and medical history information to be processed by the healthcare service provider. The doctor(s) or nurse(s) or physician’s assistants that provide the care also enter and store treatment information electronically. Even x-ray images are taken and stored in electronic format. All of this electronic processing is done to minimize human interaction with the data and to more efficiently process the treatment, record keeping, and submissions of claims to Payors.

“For healthcare institutions, there is an incentive to minimize insurance float. However, tackling this task is difficult as it is often difficult to determine which insurance claims to target and to follow up on to have paid. The total number of decision possibilities in a typical healthcare institution practice is comparable to the number of possibilities in a chess game. A typical healthcare practice owner and/or practice management staff do not have the mental wherewithal to manage such complexities daily, and it is often impossible to choose the proper claim to work on during the day in order to have it paid so to reduce overall Payor float owed to the healthcare institution.

“For example, a healthcare institution might have a patient roster of 500 patients. Each patient has their own Payor which has its own set of rules and complicated processes. In this example, complexity exists as processing the order of claims is often extremely laborious and time consuming.

“For a larger practice, say 10 offices each containing 500 patients; complexity reaches thousands of decision points and it is often impossible to target the claims to focus on to reduce Payor float; as workflow reaches astronomical hyper-complexity.

“Ideally, staff in healthcare institutions need to choose their best actions and perform each quickly, accurately, timely, and pressing the envelope of their own limitations and to target the claims to reduce Payor float. Given the astronomical number of potential complex choices, it is mentally impossible to ensure an optimal decision for each one.

“This growing complexity negatively affects a practice in multiple ways. It exacerbates practice management challenges by inviting more errors which domino into errors causing more delays which adds to overall complexity and thus creating a vicious downward productivity cycle.

“As staff make more mistakes in processing claims, often Payor float increases as Payor float delay payment in order to maximize profits.

“Current methods and systems are not designed with the goal to minimize Payor float and with the aspects of complexity and Payor adversity in mind. As a result, practice owners and managers must analyze reports, consider action alternatives, and make the best management decisions based on their personal experience and mental ability to compare the alternatives in mind, rather than taking a systematic and approach to reducing insurance float.

“The only alternative is memory-management which is humanly impossible; hence very few practice owners thrive in healthcare and healthcare insurance business.

“Accordingly, it is an object of the present invention to provide systems and methods to solve the problems set forth above.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “It is an object of the embodiments to provide systems and methods to reduce insurance float.

“It is an object of the embodiments to provide systems, methods and non-transitory computer readable medium that execute instructions to reduce insurance float. In certain embodiments, the instructions are stored on a memory and are executed by a computer processor.

“It is an object of the embodiments to provide systems, methods and non-transitory computer readable medium that execute instructions to provide workflow management and a task list so that staff are able to effectively allocate their resources to process claims and reduce insurance float.

“According to a first aspect of the embodiments, a computer-implemented health insurance billing system is provided, comprising: a memory comprising computer executable instructions; and a processor coupled to the memory and configured by the computer executable instructions, the processor configured to:

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“(1) Access at least one database having patient claim data;

“(2) Rank the patient claim data to create a ranked list of patient claim data; and

“(3) Generate a list of action items based upon the ranked list of patient claim data, wherein the list of action items are sorted according to Payor float of each of the patient claim data items, wherein steps (2)-(3) are completed on the processor.

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“In certain embodiments, the computer-implemented health insurance billing system minimizes overall Payor float.

“In certain embodiments, the patient claim data is sorted by Payor float of each of the patient claim data items.

“In certain embodiments, the Payor float is normalized by a float factor.

“In certain embodiments, the float factor includes Payor information, the Payor information sorted by Payor difficulty in making payments and payment delay.

“In certain embodiments, the float factor is at least partially sorted by an amount of each of the unpaid patient claim data items.

“In certain embodiments, the float factor includes a weighting factor generated by a weighting system, such that the weighting factor can be adjusted based upon Payor data.

“In certain embodiments, the system includes heuristic learning, wherein the system is configured to adjust the weighting factor based upon heuristic learning.

“In certain embodiments, the float factor is adjusted based upon batch processing such that patient claim data items are sorted into groups and combinations of groups contribute to Payor float.

“In certain embodiments, the float factor is configured based upon specific rules, and the rules are followed to create the ranked list of patient claim data.

“In certain embodiments, the float factor is adjusted based upon Current Procedural Terminology (CPT) codes and in-network reimbursement fees.

“In certain embodiments, the computer-implemented health insurance billing system provides a workflow of action items for each day.

“In certain embodiments, the workflow of action items for each day minimizes overall Payor float.

“In certain embodiments, the system automatically provides a list of top 10 action items to work on for each day.

“In certain embodiments, the system automatically provides a list of action items to work on for each day and delegates them to individual staff at a healthcare institution

“In certain embodiments, the system automatically generates a task list on a work bench for multiple users.

“In certain embodiments, the at least one database is selected from a group consisting of patients, providers, practice management staff, claims, claim validation rules, tasks, process description, or a combination thereof.

“In certain embodiments, the system is in communication with the Payor in order to send claims, appeals, notifications and receive notifications and payments.

“Other aspects of the embodiments are achieved by providing a computer-implemented method for minimizes overall Payor float in a health insurance billing system, the method comprising:

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“(1) Accessing at least one database having patient claim data;

“(2) Ranking the patient claim data to create a ranked list of patient claim data; and

“(3) Generating a list of action items based upon the ranked list of patient claim data, wherein the list of action items are sorted according to Payor float of each of the patient claim data items, wherein steps (2) and (3) are completed on a processor.

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“In certain embodiments, step (2) includes a custom software/algorithm based on game theory.

“Other aspects of the embodiments are achieved by providing a non-transitory computer readable storage medium storing a computer program product for minimizing Payor float in a healthcare insurance billing system, the non-transitory computer readable storage medium comprising: computer executable instructions and data, the computer executable instructions able to execute a computer program that are able to:

“

“(1) Access at least one database having patient claim data;

“(2) Rank the patient claim data to create a ranked list of patient claim data; and

“(3) Generate a list of action items based upon the ranked list of patient claim data, wherein the list of action items are sorted according to Payor float of each of the patient claim data items, wherein steps (2)-(3) are performed on a processor.

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“Other aspects of the invention are directed to a float reduction system comprising: at least one processor communicatively couple to at least one database server; a memory operatively connected to the at least one processor, wherein the memory stores computer executable instructions that, when executed by the at least one processor, causes the at least one processor to execute a method that comprises: accessing the at least one database that includes a plurality of patient claim data items for a healthcare service provider (payee); determining a weighting factor for each of a plurality of patient claim data items for each of a plurality of healthcare insurance providers (payors) to determine a potential float reduction (PFR), wherein the weighting factor takes into account respective payor difficulty in making payments to the payee and heuristic learning of previous attempts to collect payments from each respective payor to the payee, wherein the determined weighting factor is substantially continuously determined; applying the determined weighting factor to each of a plurality of patient claim data items for respective payors to generate a normalized list of patient claim data items; generating a list of action items based upon the normalized list of patient claim data items; sorting the list of action items based on the normalized patient claim data, such that normalized patient claim data is sorted by PFR from highest to lowest; and performing further processing of claims based on the sorted list of action items such that those with the highest PFR are processed soonest, thereby reducing float owed to the payee.

“In certain embodiments, the method further involves adjusting the weighting factor based upon batch processing such that patient claim data items are sorted into groups and combinations of groups contribute to payor float.

“In certain embodiments, the method further involves configuring the weighting factor based upon specific rules, the rules being followed to create the ranked list of patient claim data.

“In certain embodiments, the method further involves adjusting the weighting factor based upon current procedural terminology (CPT) codes and in-network reimbursement fees.

“In certain embodiments, the method further involves providing a workflow of action items for each day.

“In certain embodiments, the workflow of action items for each day substantially minimizes overall payor float.

“In certain embodiments, the method further involves providing a list of action items to work on for each day; and delegating them to individual staff at a healthcare institution.

“In certain embodiments, the method further involves generating a task list on a work bench for multiple users.

“In certain embodiments, said at least one database is selected from a group consisting of patients, providers, practice management staff, claims, claim validation rules, tasks, process description, or a combination thereof.

“In certain embodiments, the method further involves communicating via electronic communication systems with the payor in order to send claims, appeals, notifications and receive notifications and payments.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1. A float reduction system comprising: at least one processor communicatively couple to at least one database server; a memory operatively connected to the at least one processor, wherein the memory stores computer executable instructions that, when executed by the at least one processor, causes the at least one processor to execute a method that comprises: accessing the at least one database that includes a plurality of patient claim data items for a healthcare service provider (payee); determining a weighting factor for each of a plurality of patient claim data items for each of a plurality of healthcare insurance providers (payors) to determine a potential float reduction (PFR), wherein the weighting factor takes into account respective payor difficulty in making payments to the payee and heuristic learning of previous attempts to collect payments from each respective payor to the payee, wherein the determined weighting factor is substantially continuously determined; applying the determined weighting factor to each of a plurality of patient claim data items for respective payors to generate a normalized list of patient claim data items; generating a list of action items based upon the normalized list of patient claim data items; sorting the list of action items based on the normalized patient claim data, such that normalized patient claim data is sorted by PFR from highest to lowest; and performing further processing of claims based on the sorted list of action items such that those with the highest PFR are processed soonest, thereby reducing float owed to the payee.

“2. The float reduction system according to claim 1, wherein method that is executed by the at least one processor further comprises: adjusting the weighting factor based upon batch processing such that patient claim data items are sorted into groups and combinations of groups contribute to payor float.

“3. The float reduction system according to claim 1, wherein method that is executed by the at least one processor further comprises: configuring the weighting factor based upon specific rules, the rules being followed to create the ranked list of patient claim data.

“4. The float reduction system according to claim 1, wherein method that is executed by the at least one processor further comprises: adjusting the weighting factor based upon current procedural terminology (CPT) codes and in-network reimbursement fees.

“5. The float reduction system according to claim 1, wherein the method that is executed by the at least one processor further comprises: providing a workflow of action items for each day.

“6. The float reduction system according to claim 5, wherein the workflow of action items for each day substantially minimizes overall payor float.

“7. The float reduction system according to claim 1, wherein the method that is executed by the at least one processor further comprises: providing a list of action items to work on for each day; and delegating them to individual staff at a healthcare institution.

“8. The float reduction system according to claim 1, wherein the method that is executed by the at least one processor further comprises: generating a task list on a work bench for multiple users.

“9. The float reduction system according to claim 1, wherein said at least one database is selected from a group consisting of patients, providers, practice management staff, claims, claim validation rules, tasks, process description, or a combination thereof.

“10. The float reduction system according to claim 1, wherein the method that is executed by the at least one processor further comprises: communicating via electronic communication systems with the payor in order to send claims, appeals, notifications and receive notifications and payments.

“11. A method for minimizing overall payor float in a health insurance billing system, the method comprising: accessing at least one database that includes a plurality of patient claim data items for a healthcare service provider (payee), wherein the at least one database is stored in a memory operatively connected to at least one processor, wherein the memory stores computer executable instructions that, when executed by the at least one processor, causes the at least one processor to execute the method, and wherein the at least one database and at least processor comprise the health insurance billing system (system); determining a weighting factor for each of a plurality of patient claim data items for each of a plurality of healthcare insurance providers (payors) to determine a potential float reduction (PFR), wherein the weighting factor takes into account respective payor difficulty in making payments to the payee and heuristic learning of previous attempts to collect payments from each respective payor to the payee, wherein the determined weighting factor is substantially continuously determined; applying the determined weighting factor to each of a plurality of patient claim data items for respective payors to generate a normalized list of patient claim data items; generating a list of action items based upon the normalized list of patient claim data items; sorting the list of action items based on the normalized patient claim data, such that normalized patient claim data is sorted by PFR from highest to lowest; and performing further processing of claims based on the sorted list of action items such that those with the highest PFR are processed soonest, thereby reducing float owed to the payee.

“12. The method according to claim 11, further comprising: adjusting the weighting factor based upon batch processing such that patient claim data items are sorted into groups and combinations of groups contribute to payor float.

“13. The method according to claim 11, further comprising: configuring the weighting factor based upon specific rules, the rules being followed to create the ranked list of patient claim data.

“14. The method according to claim 11, wherein further comprising: adjusting the weighting factor based upon current procedural terminology (CPT) codes and in-network reimbursement fees.

“15. The method according to claim 11, wherein further comprising: providing a workflow of action items for each day.

“16. The method according to claim 15, wherein the workflow of action items for each day minimizes overall payor float.

“17. The method according to claim 11, further comprising: providing a list of action items to work on for each day; and delegating the list of action items to individual staff at a healthcare institution.

“18. The method according to claim 11, further comprising: generating a task list on a work bench for multiple users.

“19. The method according to claim 11, wherein the at least one database is selected from a group consisting of patients, providers, practice management staff, claims, claim validation rules, tasks, process description, or a combination thereof.

“20. The method according to claim 11, further comprising: communicating with the payor via an electronic communications system to send claims, appeals, notifications and receive notifications and payments.

“21. A non-transitory computer readable storage medium storing a computer program product for minimizing payor float in a healthcare insurance billing system, the non-transitory computer readable storage medium comprising computer executable instructions and data, the computer executable instructions able to execute a computer program able to: determine a weighting factor for each of a plurality of patient claim data items for each of a plurality of healthcare insurance providers (payors) to determine a potential float reduction (PFR), wherein the weighting factor takes into account respective payor difficulty in making payments to the payee and heuristic learning of previous attempts to collect payments from each respective payor to the payee, wherein the determined weighting factor is substantially continuously determined; apply the determined weighting factor to each of a plurality of patient claim data items for respective payors to generate a normalized list of patient claim data items; generate a list of action items based upon the normalized list of patient claim data items; sort the list of action items based on the normalized patient claim data items, such that normalized patient claim data is sorted by PFR from highest to lowest; and perform further processing of claims based on the sorted list of action items such that those with the highest PFR are processed soonest, thereby reducing float owed to the payee.”

URL and more information on this patent application, see: LIROV, Erez; LIROV, Yuval. Healthcare Practice Management System And Method Thereof. Filed March 22, 2021 and posted July 8, 2021. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220210210199%22.PGNR.&OS=DN/20210210199&RS=DN/20210210199

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