U.S. patent application number 10/439423 was filed with the patent office on 2003-12-11 for systems and methods for identifying fraud and abuse in prescription claims.
Invention is credited to Eidex, Brian H., Rowe, James Couser III.
Application Number | 20030229519 10/439423 |
Document ID | / |
Family ID | 29550116 |
Filed Date | 2003-12-11 |
United States Patent
Application |
20030229519 |
Kind Code |
A1 |
Eidex, Brian H. ; et
al. |
December 11, 2003 |
Systems and methods for identifying fraud and abuse in prescription
claims
Abstract
Systems and methods permit the identification of fraud and abuse
in electronic prescription transactions by intercepting and
analyzing prescription claims to determine the likelihood that a
claim is fraudulent. A fraud scoring engine utilizes a compilation
of expert rules and profiling engine methodologies to determine the
likelihood that a transaction is the result of fraudulent or
abusive behavior. The fraud scoring engine assigns a fraud score to
rate the probability that a transaction is fraudulent in nature.
The fraud score is compared against payer-defined business rules to
determine if a claim is rejected as fraudulent. A fraud management
interface enables payers to view a rejected claim and the reasons
why a claim is rejected so that the reasons can be explained to a
pharmacist, should the pharmacist contact the payer.
Inventors: |
Eidex, Brian H.;
(Stockbridge, GA) ; Rowe, James Couser III; (Sugar
Hill, GA) |
Correspondence
Address: |
William R. Silverio
SUTHERLAND ASBILL & BRENNAN LLP
999 Peachtree Street, NE
Atlanta
GA
30309-3996
US
|
Family ID: |
29550116 |
Appl. No.: |
10/439423 |
Filed: |
May 16, 2003 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60381395 |
May 16, 2002 |
|
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Current U.S.
Class: |
705/2 |
Current CPC
Class: |
G06Q 40/08 20130101;
G16H 20/10 20180101; G06Q 20/4016 20130101; G16Z 99/00 20190201;
G16H 50/20 20180101; G06Q 10/10 20130101 |
Class at
Publication: |
705/2 |
International
Class: |
G06F 017/60 |
Claims
That which is claimed:
1. A method for identifying fraudulent prescription claims,
comprising: receiving a prescription claim, said prescription claim
identifying a drug product and the pharmacy submitting said
prescription claim; analyzing the prescription claim to generate a
fraud score, said fraud score based upon the likelihood that the
prescription claim is fraudulent; comparing said fraud score to
business rules generated at least in part by a payer, wherein said
business rules define a threshold value; and rejecting said
prescription claim as fraudulent where said fraud score exceeds
said threshold value.
2. A computer-readable medium having stored thereon
computer-executable instructions for performing the method of claim
1.
3. The method of claim 1, further comprising the step of processing
said prescription claim where said fraud score fails to exceed said
threshold value.
4. The method of claim 1, wherein said step of rejecting further
comprises providing said pharmacy at least one reason code for
rejecting said prescription claim.
5. The method of claim 1, wherein said step of rejecting further
comprises providing said payer at least one reason code for
rejecting said prescription claim.
6. The method of claim 1, wherein said step of analyzing comprises
the step of analyzing the prescription claim to generate a fraud
score, wherein said fraud score is based at least in part upon
statistical information.
7. The method of claim 1, wherein said step of analyzing comprises
the step of analyzing the prescription claim to generate a fraud
score, wherein said fraud score is based at least in part upon
expert rules established by the payer.
8. The method of claim 1, further comprising the step of forwarding
said prescription claim to said payer where said fraud score fails
to exceed said threshold value.
9. A system for identifying fraudulent prescription claims,
comprising: means for receiving a prescription claim, said
prescription claim identifying a drug product and the pharmacy
submitting said prescription claim; and a processor functionally
coupled to said means for receiving a prescription claim and
configured for executing computer-executable instructions for:
analyzing the prescription claim to generate a fraud score, said
fraud score based upon the likelihood that the prescription claim
is fraudulent; comparing said fraud score to business rules
generated at least in part by a payer, wherein said business rules
define a threshold value; and rejecting said prescription claim as
fraudulent where said fraud score exceeds said threshold value.
10. The system of claim 9, wherein said processor further includes
computer-executable instructions for processing said prescription
claim where said fraud score fails to exceed said threshold
value.
11. The system of claim 9, wherein said processor further includes
computer-executable instructions for providing said pharmacy at
least one reason code for rejecting said prescription claim.
12. The system of claim 9, wherein said processor further includes
computer-executable instructions for assigning at least one reason
code to said prescription claim, wherein said at least one reason
code indicates a reason for the generated fraud score.
13. The method of claim 9, wherein said processor further includes
computer-executable instructions for analyzing the prescription
claim to generate a fraud score, wherein said fraud score is based
at least in part upon comparing said prescription claim to at least
one statistical model.
14. The method of claim 9, wherein said processor further includes
computer-executable instructions for analyzing the prescription
claim to generate a fraud score, wherein said fraud score is based
at least in part upon expert rules established by the payer.
15. The method of claim 9, wherein said processor further includes
computer-executable instructions for forwarding said prescription
claim to said payer where said fraud score fails to exceed said
threshold value.
16. A system for identifying fraudulent prescription claims,
comprising: at least one pharmacy point-of-sale (POS) device; and a
host sever, in communication with said at least one pharmacy POS
device via a network connection, wherein said host server comprises
a fraud and abuse module, said fraud and abuse module comprising:
means for analyzing a prescription claim transmitted to said host
server from said at least one pharmacy POS device, wherein said
means for analyzing are operable to generate a fraud score
corresponding to said prescription claim; means for comparing said
fraud score to at least one threshold value generated at least in
part by a payer; and means for rejecting said prescription claim as
fraudulent where said fraud score exceeds said threshold value.
17. The system of claim 16, wherein said fraud and abuse module
further comprises means for forwarding said prescription claim to
said payer where said fraud score fails to exceed said threshold
value.
18. The system of claim 16, wherein said means for analyzing
comprises means for analyzing operable to generate at least one
reason code associated with the prescription claim, wherein said at
least one reason code indicates at least one reason for the
generated fraud score.
19. The system of claim 18, wherein said fraud and abuse module
fraud and abuse module further comprises means for forwarding said
at least one reason code to the payer or the at least one pharmacy
point-of-sale (POS) device.
20. The system of claim 16, wherein said means for analyzing
comprise means for analyzing operable to generate a fraud score
based at least in part upon a comparison of said prescription claim
to at least one statistical model.
Description
RELATED APPLICATION DATA
[0001] The present application claims the benefit of U.S.
Provisional Patent Application Serial No. 60/381,395, filed May 16,
2002, titled "Systems and Methods for Verifying Electronically
Transmitted Claim Content", which is hereby incorporated by
reference as if set forth fully herein.
FIELD OF THE INVENTION
[0002] The present invention relates generally to identifying fraud
during the processing of electronic claims. More particularly, the
present invention relates to systems and methods for automatically
identifying fraud and abuse in electronic prescription
transactions.
BACKGROUND OF THE INVENTION
[0003] A significant problem confronting the healthcare industry is
ensuring that prescription drugs are properly being dispensed to
those having a legitimate need and prescription for drugs.
Increasingly, perpetrators are using pharmacies as a mechanism to
fraudulently acquire prescription drugs. As healthcare
professionals, pharmacists must not only meet state and federal
requirements for dispensing controlled substances, but also face an
ethical responsibility to prevent prescription drug abuse and
diversion. In fact, the law holds the pharmacist responsible for
knowingly dispensing a prescription that was not issued in the
usual course of professional treatment. Additionally, insurance
companies face state regulations that address the growing problem
related to fraudulent claims.
[0004] To prevent prescription drug fraud and abuse, those in the
healthcare industry must be on constant lookout for fraudulent
activity. For instance, fraudulent prescriptions can occur through
stolen prescription pads and prescriptions written for fictitious
patients, or through altered physician prescriptions (e.g., an
altered prescription quantity, or an altered physician call back
number to an accomplice's telephone number). Furthermore, collusion
among pharmacists, physicians, and patients results in complicated,
sophisticated activity that can be extremely difficult to
uncover.
[0005] Current fraud prevention techniques are often inadequate to
identify prescription fraud and abuse. For instance, present
techniques require pharmacists to know the prescriber's signature,
DEA registration number, the patient, and/or to check the date on
the prescription order to determine if it is presented within a
reasonable length of time from when it was written. The problem is
exacerbated when the pharmacist or multiple parties are involved in
the fraudulent activity. Other more subjective fraud and abuse
detection techniques require an investigator to identify anything
in the prescription transaction that may raise suspicion.
Unfortunately, effectively identifying fraudulent transactions
using any of the above methods is extremely difficult due to the
high volume of transactions and the often subtle differences that
may exist between a legitimate transaction and a fraudulent
one.
[0006] Despite the inadequacies of current fraud and abuse
techniques, it will be appreciated that a number of criteria and
factors may be used to indicate that a purported prescription was
not issued for a legitimate medical purpose. These include where
there are a significant number of prescriptions from a particular
practitioner as compared to other practitioners in an area,
frequent prescription submissions from a particular patient, or
where a prescriber writes prescriptions for antagonistic drugs,
such as depressants and stimulants, at the same time. Additional
characteristics include patients that often present prescriptions
written in the names of other people, where a number of people
appear simultaneously or within a short time, each bearing similar
prescriptions from the same physician, or a high volume of people
who are not regular patrons or residents of a nearby community that
show up with prescriptions from the same physician. Furthermore,
forged prescriptions typically include characteristics such as
differing quantities, directions or dosages differing from usual
medical usage, prescriptions that do not comply with the acceptable
standard abbreviations, directions written in full with no
abbreviations, and like characteristics.
[0007] Despite these indicators, it is clear that existing pharmacy
fraud and abuse identification techniques do not adequately protect
against fraud and abuse in pharmaceutical transactions. What is
needed is an automated system and method for intelligently
detecting fraud and abuse based on fraud criteria and factors such
that subjective criteria and subtleties identified by pharmacists
during the filling of a prescription are not the only means to
prevent fraudulent prescription transactions. It would be
advantageous if the system assigned fraud scores that could be used
to prioritize claims, and reason codes to understand problematic
claims, during retrospective analysis. There is further a need for
a system and method that monitors prescription transactions for
possible fraud and abuse and generates messages when there is a
likelihood that a fraudulent transaction has occurred. Furthermore,
it would be beneficial if such a system allowed payers to identify
reasons why a transaction is identified as fraudulent so that the
payers can communicate with pharmacies to determine the problems
identified in a prescription transaction.
SUMMARY OF THE INVENTION
[0008] Systems and methods of the present invention automatically
identify fraud and abuse in electronic prescription transactions.
More specifically, systems and methods of the present invention
intercept and analyze prescription claims to determine the
likelihood that a claim is fraudulent. To effect this, the present
invention utilizes a fraud scoring engine and a fraud management
interface. The fraud scoring engine utilizes a compilation of
expert rules and profiling engine methodologies to determine the
likelihood that a prescription claim is the result of fraudulent or
abusive behavior. The fraud scoring engine assigns a fraud score to
rate the probability that a claim is fraudulent in nature. The
fraud management interface is an interface that enables payers to
view a rejected claim and the reasons why a claim is rejected so
that the reasons can be explained to a pharmacist, should the
pharmacist contact the payer. Additionally, the fraud management
interface may be used by payers to retrospectively analyze,
prioritize, and manage the claims during the recovery process.
[0009] Using the fraud scoring engine-generated fraud score, a
payer, such as an insurance company, can adjudicate a claim as
normal, ask the pharmacist to call the payer for manual review, or
reject the claim with a specific message for the pharmacist. These
decisions are made in real-time before the claim is approved for
payment. Additionally, the present invention provides a payer's
fraud staff tools to quickly determine why a claim received a
particular fraud score so that they can provide explanation to the
pharmacist. By identifying fraud and abuse, the present invention
enables payers to reduce their payments for claims resulting from
fraud and abuse.
[0010] According to one embodiment of the present invention, there
is disclosed a method for identifying fraudulent prescription
claims. The method includes the steps of receiving a prescription
claim, the prescription claim identifying a drug product and the
pharmacy submitting the prescription claim, analyzing the
prescription claim to generate a fraud score, the fraud score based
upon the likelihood that the prescription claim is fraudulent,
comparing the fraud score to business rules generated at least in
part by a payer, wherein the business rules define a threshold
value, and, rejecting the prescription claim as fraudulent where
the fraud score exceeds the threshold value.
[0011] According to one aspect of the invention, the method further
includes the step of processing the prescription claim where the
fraud score fails to exceed the threshold value. According to
another aspect of the invention, the step of rejecting further
comprising providing the pharmacy at least one reason code for
rejecting the prescription claim. According to yet another aspect
of the present invention, the step of analyzing comprises the step
of analyzing the prescription claim to generate a fraud score,
wherein the fraud score is based at least in part upon profile
information.
[0012] Furthermore, the step of analyzing can include the step of
analyzing the prescription claim to generate a fraud score, wherein
the fraud score is based at least in part upon short-term
transaction patterns. The method can also include the step of
forwarding the prescription claim to the payer where the fraud
score fails to exceed the threshold value.
[0013] According to another embodiment of the present invention,
there is disclosed a system for identifying fraudulent prescription
claims. The system includes means for receiving a prescription
claim, the prescription claim identifying a drug product and the
pharmacy submitting the prescription claim, and a processor
functionally coupled to the means for receiving a prescription
claim and configured for executing computer-executable instructions
for: analyzing the prescription claim to generate a fraud score,
the fraud score based upon the likelihood that the prescription
claim is fraudulent; comparing the fraud score to business rules
generated at least in part by a payer, wherein the business rules
define a threshold value; and rejecting the prescription claim as
fraudulent where the fraud score exceeds the threshold value.
[0014] According to one aspect of the present invention, the
processor further includes computer-executable instructions for
processing the prescription claim where the fraud score fails to
exceed the threshold value. According to another aspect of the
present invention, the processor further includes
computer-executable instructions for providing the pharmacy at
least one reason code for rejecting the prescription claim.
According to yet another aspect of the present invention, the
processor further includes computer-executable instructions for
analyzing the prescription claim to generate a fraud score, wherein
the fraud score is based at least in part upon profile
information.
[0015] The processor may also include computer-executable
instructions for analyzing the prescription claim to generate a
fraud score, wherein the fraud score is based at least in part upon
short-term transaction patterns. Additionally, the processor may
also include computer-executable instructions for forwarding the
prescription claim to the payer where the fraud score fails to
exceed the threshold value.
[0016] According to yet another embodiment of the present
invention, there is disclosed a system for identifying fraudulent
prescription claims. The system comprises at least one pharmacy
point-of-sale (POS) device, and a host sever, in communication with
the at least one pharmacy POS device via a network connection,
wherein the host server comprises a fraud and abuse module. The
fraud and abuse module includes means for analyzing a prescription
claim transmitted to the host server from the at least one pharmacy
POS device, wherein the means for analyzing are operable to
generate a fraud score corresponding to the prescription claim,
means for comparing the fraud score to at least one threshold value
generated at least in part by a payer, and means for rejecting the
prescription claim as fraudulent where the fraud score exceeds the
threshold value.
[0017] These and other features, aspect and embodiments of the
invention will be described in more detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Having thus described the invention in general terms,
reference will now be made to the accompanying drawings, which are
not necessarily drawn to scale, and wherein:
[0019] FIG. 1 is a block diagram illustrating an exemplary system
in accordance with certain exemplary embodiments of the present
invention.
[0020] FIG. 2 is a flow chart illustrating an exemplary expert
fraud and abuse scoring method in accordance with certain exemplary
embodiments of the present invention.
[0021] FIG. 3 is a flow chart illustrating an exemplary fraud and
abuse reporting method in accordance with certain exemplary
embodiments of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0022] The present inventions now will be described more fully
hereinafter with reference to the accompanying drawings, in which
some, but not all embodiments of the invention are shown. Indeed,
these inventions may be embodied in many different forms and should
not be construed as limited to the embodiments set forth herein;
rather, these embodiments are provided so that this disclosure will
satisfy applicable legal requirements. Like numbers refer to like
elements throughout.
[0023] The present invention provides systems and methods for fraud
and abuse notification. The systems and methods of the present
invention monitor prescription transactions and return appropriate
notification messages to pharmacists or other health care providers
when the characteristics of a prescription transaction indicate the
possibility that a particular claim may be fraudulent. One or more
fraud and abuse screening processes described with respect to FIG.
2 are used to screen prescription transactions for possible
fraudulent claims.
[0024] Exemplary embodiments of the present invention will
hereinafter be described with reference to the figures, in which
like numerals indicate like elements throughout the several
drawings. The present invention is described below with reference
to block diagrams and flowchart illustrations of systems, methods,
apparatuses and computer program products according to an
embodiment of the invention. It will be understood that each block
of the block diagrams and flowchart illustrations, and combinations
of blocks in the block diagrams and flowchart illustrations,
respectively, can be implemented by computer program instructions.
These computer program instructions may be loaded onto a general
purpose computer, special purpose computer, or other programmable
data processing apparatus to produce a machine, such that the
instructions which execute on the computer or other programmable
data processing apparatus create means for implementing the
functions specified in the flowchart block or blocks.
[0025] These computer program instructions may also be stored in a
computer-readable memory that can direct a computer or other
programmable data processing apparatus to function in a particular
manner, such that the instructions stored in the computer-readable
memory produce an article of manufacture including instruction
means that implement the function specified in the flowchart block
or blocks. The computer program instructions may also be loaded
onto a computer or other programmable data processing apparatus to
cause a series of operational steps to be performed on the computer
or other programmable apparatus to produce a computer implemented
process such that the instructions that execute on the computer or
other programmable apparatus provide steps for implementing the
functions specified in the flowchart block or blocks.
[0026] Accordingly, blocks of the block diagrams and flowchart
illustrations support combinations of means for performing the
specified functions, combinations of steps for performing the
specified functions and program instruction means for performing
the specified functions. It will also be understood that each block
of the block diagrams and flowchart illustrations, and combinations
of blocks in the block diagrams and flowchart illustrations, can be
implemented by special purpose hardware-based computer systems that
perform the specified functions or steps, or combinations of
special purpose hardware and computer instructions.
[0027] FIG. 1 is a block diagram illustrating an exemplary
operating environment for implementation of certain embodiments of
the present invention. The exemplary operating environment
encompasses a pharmacy point-of-service ("POS") device 102, a host
server 104 and a payer system 108, which are each configured for
accessing and reading associated computer-readable media having
stored thereon data and/or computer-executable instructions for
implementing the various methods of the present invention.
Generally, network devices and systems include hardware and/or
software for transmitting and receiving data and/or
computer-executable instructions over a communications link and a
memory for storing data and/or computer-executable instructions.
Network devices and systems may also include a processor for
processing data and executing computer-executable instructions, as
well as other internal and peripheral components that are well
known in the art. As used herein, the term "computer-readable
medium" describes any form of memory or a propagated signal
transmission medium. Propagated signals representing data and
computer-executable instructions are transferred between network
devices and systems.
[0028] As shown in FIG. 1, a pharmacy POS device 102 may be in
communication with the host server 104 via a network 106. The
pharmacy POS device 102 may be configured for receiving
prescription claim data, creating prescription transactions
therefrom and transmitting said prescription transactions to the
host server 104. Prescription claim data includes any data that is
typically provided by a patient, pharmacist and/or other health
care provider in relation to filling a prescription and/or
requesting approval or authorization for payment from a payer or
claim adjudicator. A payer may be an insurance company, a financial
institution or another financial service provider. Prescription
claim data may be input to the pharmacy POS device 102 by a
pharmacist or other health care provider or may be received by the
pharmacy POS device 102 in electronic form from an electronic
prescription service (not shown). The pharmacy POS device 102 may
be configured for handling other types of prescription
transactions.
[0029] Prescription claim transactions are electronic records or
messages intended to facilitate the communication of prescription
information. For example, prescription claim transactions are
intended to communicate prescription claim data between pharmacies
and payers. Although prescription claim transactions will be
discussed hereinafter, it should be understood that the various
systems and methods of the invention may be practiced in connection
with other types of prescription transactions or independently of
prescription transactions (e.g., raw prescription data). The
content and format of a prescription claim may vary depending on
which standard or protocol is used. In general, however,
prescription claim transactions will identify at least the drug
product to be dispensed, e.g., by National Drug Code number
("NDC#"), the quantity to be dispensed and the days supply, whether
the prescription claim relates to a new prescription or a refill
prescription, and billing-related information.
[0030] Prescription claim transactions may be transmitted from the
pharmacy POS device 102 to the host server 104 in batch, real-time
or near real-time. In certain embodiments, the host server 104 may
serve as a clearinghouse for multiple payer systems 108. As noted
above, payer systems 108 may include systems operated by insurance
companies, financial institutions and other financial service
providers. In its capacity as a clearinghouse, the host server 104
is operable to parse prescription claim transactions and forward
them to the appropriate payer system 108 for processing. Approval,
authorization or rejection messages may be returned to the host
server 104 from the payer systems 108 and such messages may be
forwarded by the host server 104 to the pharmacy POS device
102.
[0031] In serving as a clearinghouse, the host server 104 may also
be configured for performing pre-processing and post-processing of
prescription claim transactions. Pre-processing and post-processing
refers to real-time or near real-time validation and management of
prescription claim data in order to maximize prescription claim
reimbursement and minimize claim submission errors. Pre-processing
and post-processing may generate messaging alerts and/or
retrospective reports supporting "usual and customary" price
comparisons, average wholesale price ("AWP") edits, dispense as
written ("DAW") brand appropriateness, and numerous other screening
processes for facilitating rapid and accurate validation of
prescription claims.
[0032] In accordance with the present invention, the host server
104 may be configured for performing certain fraud screening
processes for the detection of possible fraud and abuse (hereafter
referred to collectively as "fraud") in a prescription transaction.
More particularly, the host server 104 examines the characteristics
of a prescription claim to determine the possibility that the claim
is fraudulent. In the case where the host server 104 functions as a
clearinghouse, the screening processes for detection of possible
fraud may be implemented as pre-processing and/or post-processing
methods. In other embodiments, the host server 104 may not serve as
a clearinghouse for prescription claim transactions and may be
dedicated to performing such tasks as fraud screening. The fraud
screening processes of the present invention may be designed to
generate alerts (also referred to as "reject messages") that are
transmitted to the pharmacy POS device 102 when a potential
fraudulent transaction is detected. Reject messages may indicate
that a prescription claim has been rejected, provide a pharmacist
with information about the potential fraudulent transaction, and
may encourage the pharmacist to verify the prescription claim. The
fraud screening processes according to the present invention are
also designed to capture certain prescription claim data for
subsequent analysis and reporting related to fraudulent, or
suspected fraudulent, transactions.
[0033] The pharmacy POS device 102 may be any processor-driven
device, such as a personal computer, laptop computer, handheld
computer and the like. In addition to a processor 110, the pharmacy
POS device 102 may further include a memory 112, input/output
("I/O") interface(s) 114 and a network interface 116. The memory
112 may store data files 118 and various program modules, such as
an operating system ("OS") 120 and a practice management module
122. The practice management module 122 may comprise
computer-executable instructions for performing various routines,
such as those for creating and submitting prescription claim
transactions. I/O interface(s) 114 facilitate communication between
the processor 110 and various I/O devices, such as a keyboard,
mouse, printer, microphone, speaker, monitor, etc. The network
interface 116 may take any of a number of forms, such as a network
interface card, a modem, etc. These and other components of the
pharmacy POS device 102 will be apparent to those of ordinary skill
in the art and are therefore not discussed in more detail
herein.
[0034] Similarly, the host server 104 may be any processor-driven
device that is configured for receiving and fulfilling requests
related to prescription claim transactions. The host server 104 may
therefore include a processor 126, a memory 128, input/output
("I/O") interface(s) 130 and a network interface 132. The memory
128 may store data files 134 and various program modules, such as
an operating system ("OS") 136, a database management system
("DBMS") 138 and a fraud and abuse module 140. The fraud and abuse
module 140 may comprise computer-executable instructions for
performing various screening processes for detecting possible fraud
in pharmacy transactions and for managing related messaging and
reporting functions. The host server 104 may include additional
program modules (not shown) for performing other pre-processing or
post-processing methods and for providing clearinghouse services.
Those skilled in the art will appreciate that the host server 104
may include alternate and/or additional components, hardware or
software. In addition, the host server 104 may be connected to a
local or wide area network (not shown) that includes other devices,
such as routers, firewalls, gateways, etc.
[0035] The host server 104 may include or be in communication with
one or more database 105. The database 105 may store, for example,
data relating to pharmacies, doctors, and consumers, such as
typical doses filled by consumers, typical drugs prescribed by
doctors, most common daily dose values, common daily dose values,
likelihood indicators and other data used in the various fraud and
abuse screening processes of the present invention. The database
105 may also store reports and other data relating to the results
of the fraud and abuse screening processes. The database 105 may of
course also store any other data used or generated by the host
server 104, such as data used in other pre-processing and
post-processing methods and reports generated thereby. Although a
single database 105 is referred to herein for simplicity, those
skilled in the art will appreciate that multiple physical and/or
logical databases may be used to store the above mentioned data.
For security, the host server 104 may have a dedicated connection
to the database 105, as shown. However, the host server 104 may
also communicate with the database 105 via a network 106.
[0036] The network 106 may comprise any telecommunication and/or
data network, whether public or private, such as a local area
network, a wide area network, an intranet, an internet and/or any
combination thereof and may be wired and/or wireless. Due to
network connectivity, various methodologies as described herein may
be practiced in the context of distributed computing environments.
Although the exemplary pharmacy POS device 102 is shown for
simplicity as being in communication with the host server 104 via
one intervening network 106, it is to be understood that any other
network configuration is possible. For example, the pharmacy POS
device 102 may be connected to a pharmacy's local or wide area
network, which may include other devices, such as gateways and
routers, for interfacing with another public or private network
106. Instead of or in addition to a network 106, dedicated
communication links may be used to connect the various devices of
the present invention.
[0037] Those skilled in the art will appreciate that the operating
environment shown in and described with respect to FIG. 1 is
provided by way of example only. Numerous other operating
environments, system architectures and device configurations are
possible. For example, the invention may in certain embodiments be
implemented in a non-networked environment, in which a stand-alone
pharmacy POS device 102 executes one or more fraud and abuse
module(s) 140. Accordingly, the present invention should not be
construed as being limited to any particular operating environment,
system architecture or device configuration.
[0038] FIG. 2 is a flow chart illustrating an exemplary fraud and
abuse scoring method in accordance with certain exemplary
embodiments of the present invention. According to one aspect of
the invention, the fraud and abuse scoring method will be
implemented by the fraud and abuse module 122 after the reception,
at block 140, of a prescription claim transaction received by the
host server 104 from a pharmacy POS device 102. Briefly, the fraud
and abuse module 122 evaluates a prescription claim (hereafter
referred to as a "claim") and assigns a fraud score and reason
codes based upon the claim. The fraud score is based on a
compilation of fraudulent screening processes implemented by
statistical model evaluations and expert rules, as explained in
detail below, and indicates the likelihood that a transaction is
the result of fraudulent or abusive behavior. The reason codes are
assigned to a claim to describe the basis for fraud score. In this
regard, the reason codes are similar to reason codes assigned to
credit report scores for explaining the reason for a particular
score.
[0039] After reception of a prescription claim transaction (block
140), the claim transaction is parsed to identify the information
contained therein, including patient specific data, physician
specific information, submitted drug product, daily dosage, whether
the transaction relates to a new prescription or a refill, as well
as additional prescription-related information. The drug product
and daily dosage values may be specified in the prescription claim
transaction or may need to be derived from the prescription claim
data. For example, the prescription claim data included in the
transaction may include an NDC# or other code to identify the
submitted drug product. The prescription claim data may also
identify a quantity to be dispensed and a days supply, from which a
submitted daily dosage value can be derived.
[0040] After the claim is parsed to determine its components, the
claim undergoes processing by the fraud and abuse module 122, and
more specifically, the claim is compared to statistical models
(blocks 142, 144). More particularly, after a claim is parsed, the
fraud and abuse module determines which statistical models (block
142) should be used to evaluate the pharmacy-submitted claim.
Statistical models are used to evaluate each claim to determine the
likelihood that the claim is fraudulent, and include objective
statistics relating to pharmacists, doctors and consumer. For
instance, statistics could include: the relative distance between
each of the prescriber, pharmacy and consumer; the average number
of prescriptions filled hourly, daily, or weekly by a particular
pharmacy; the average number of times a prescription for a
particular pharmaceutical is filled, prescribed by the prescriber,
or filled by the transmitting pharmacy; and any additional
objective criteria that may be used to establish whether a
particular claim evidences behavior falling outside a statistical
average illustrating normal behavior for patients, physicians,
pharmacies. Therefore, each or certain available statistical model
relating to a claim, and more specifically, related to the
consumer, pharmacy, prescriber, and pharmaceutical prescribed, are
retrieved.
[0041] Such statistical models are stored within the host server
104 data files 134 or within the databases 105. Additionally, it
will be appreciated that the fraud and abuse module 122 may
communicate with one or more third party servers via the I/O
interfaces 130 and/or network interface 132 and the network 106 to
collect the necessary comparison data to execute the evaluations.
For instance, where the address of a physician is compared to the
address of a pharmacy, a mapping or like program may be accessed to
determine the relative distance between the physician office and
the pharmacy. Once pertinent statistical models are identified, the
claim contents are evaluated (block 144) against the models to
determine what, if any, claim components fall outside ranges
established for each statistical element. For instance, if
statistics show that an average consumer lives no more than 10-15
miles from pharmacies used to fill that consumer's prescriptions,
if the fraud and abuse module 122 determines that the consumer
lives 50 miles from the pharmacy at which a prescription is filled,
the fraud and abuse module can identify that this is greater than
the average, and can increase the fraud score for that transaction.
The score may be increased according to scoring tables associated
with each statistical model or with each claim field. Therefore,
the scoring table may provide for a higher score where the claim is
further from the statistical average for a particular analysis.
Each individual statistical model may be used to increase the fraud
score assigned to a prescription transaction, thus increasing the
chances that the transaction will be deemed fraudulent.
[0042] In addition to statistical models, expert rules (blocks 148,
150) may be used to evaluate the likelihood for fraud in a
prescription transaction. These expert rules may be payer-specific
rules that payers have found to be useful in their prior attempts
at managing fraud and abuse. For instance, if payers have
determined that payers from a particular zipcode fulfilling
prescriptions in a second particular zipcode evidence an extremely
high rate of fraud, claims may be examined to determine whether or
not they meet this criteria. If so, the fraud score may be
increased in the same manner the statistical models may increase
the fraud score. Such an analysis may utilize one or more of the
statistical models described above. Like the statistical model
analysis above, the pertinent expert rules are first retrieved
(block 148), for instance, from within the host server 104 data
files 134 or within the databases 105. Thereafter the expert rules
are used to evaluate the claim (block 150). It will be appreciated
that the expert rules may seek to identify any combination of
factors in a claim that increase the likelihood of a fraudulent
transaction, such as the time a prescription is fulfilled, the type
of drug prescribed, the frequency with which a consumer fills
prescriptions, or any other factors based on the claim content,
consumer, pharmacy, prescriber, or circumstances related to the
filling of a prescription.
[0043] After the claim has been evaluated based on the statistical
profiles (blocks 142, 144) and the expert rules (blocks 148, 150),
the fraud score, along with reason codes, are assigned (block 156)
by the fraud scoring engine of the fraud and abuse module 122. To
assign the fraud score the fraud scoring engine may simply sum
values assigned by each of the statistical model and expert rule
evaluations described above. Alternatively, one or more of the
scores may be weighted based upon a determination, based upon
historical information, that one or more of the considerations
discussed above is particularly accurate in determining the
likelihood of fraud in a prescription transaction.
[0044] In addition to a fraud score, reason codes for the score are
assigned. According to one embodiment of the present invention, the
reason codes are generated independently by the fraud and abuse
module 122, such that every time the screening processes performed
by the module increase the fraud score, explanations for increasing
the fraud score are identified. According to another aspect of the
present invention, reason codes are automatically assigned for any
fraud score, such that reasons for a low, or even zero, fraud score
may be viewed. These reason codes may be predefined for each
possible outcome generated by the screening processes, and are
preferably short form codes.
[0045] FIG. 3 is a flow chart illustrating an exemplary fraud and
abuse reporting method in accordance with certain exemplary
embodiments of the present invention. After a fraud score is
assigned at block 156, the method advances to step 160 where
payer-defined business rules are implemented. According to one
aspect of the invention, each payer can define its own rules for
rejected claims based upon the fraud score. For instance, where the
fraud score is on a 1000 point basis, where the greater the number,
the greater the risk of fraud, one payer may wish to reject all
claims having scores 700 and higher as fraudulent, while another
payer may wish to reject only those claims having fraud scores of
900 and higher as fraudulent. These payer-defined business rules
are stored in the data files 134 or in the database(s) 105.
Therefore, the payer-defined business rules are accessed and
compared against the fraud score to determine if a claim is
rejected as fraudulent. Thus, a reject message may be transmitted
by the fraud and abuse module 122 when the fraud score exceeds the
fraud score identified by a payer for rejecting transactions as
potentially fraudulent.
[0046] In addition to scoring rules, the payer-defined business
rules may also dictate what messages are transmitted to a pharmacy
when a transaction occurs. For instance, a first payer may wish to
identify every reason code when a claim is rejected as fraudulent,
whereas a second payer may wish not to identify any such codes. It
will be appreciated that inclusion of multiple messages in a reject
message may be redundant or otherwise unnecessary. Therefore, if
the prescription claim transaction is to be rejected based on the
results of the fraud screening processes of the present invention,
logic may be employed to prioritize and select the message or
messages to be included in a claim reject message. Payers may also
define the text of the messages transmitted to pharmacies when a
claim is rejected. Preferably, rejection messages transmitted to
the pharmacies are in NCPDP format. Similarly, where a claim is
approved (i.e., its fraud score is less than that defined by a
payer), the claim is passed to the payer systems(s) 108 for
processing.
[0047] If the transaction is passed through without a fraud
rejection, then the transaction is passed to the payer (block 164).
Alternatively, where a transaction is rejected, the pharmacy is
notified (block 162). In this situation, the fraud and abuse module
will send a reject message (or fraud flag) to the pharmacy on
behalf of the payer without delivering the rejected claim to the
payer in real-time. This message will preferably not require any
modification to existing pharmacy claim processing systems for
adjudicating claims. Furthermore, in such circumstances, the payer
can receive these rejected transactions, for recordation purposes,
via a nightly batch feed (block 168). When rejected claims are
transmitted to the payer via the nightly batch feed, the data
transmitted to the payer will also include the reasons for the
fraud score so that the payers can use this information on an
ongoing basis and in case pharmacies or patients call to discuss
the claim with the payer at a later time. According to another
aspect of the invention, reason codes are also assigned to all
claims, even accepted claims, and such reason codes are stored by
the payer for later analysis.
[0048] After a reject message is transmitted to the pharmacy, the
pharmacy can contact the payer 166 to discuss the claim. According
to one aspect of the invention, the reject message includes a
toll-free telephone number to call to discuss the transaction, and
in particular, to determine if there is any manual validation which
can occur to approve the claim. The pharmacies can also enable the
payer to speak with the consumer to discuss the issues identified
by the present invention. Referring again to FIG. 3, where a
pharmacy calls a payer to discuss a claim rejection, the payer can
access a fraud management interface (blocks 170, 172) to view the
rejected claim. As shown in FIG. 3, the fraud management interface
is in communication with the payer-defined business rules such that
the interface can identify why the claim was rejected based upon
up-to-date business rules.
[0049] Preferably, the fraud management interface allows a payer
operator to view a rejected claim almost immediately after it is
rejected. Thus, the interface enables payers to quickly locate the
claim and to view the reason codes that the claim was rejected so
that the payer can explain those reasons to the pharmacist.
Optionally, the fraud management interface also allows a payer to
view reason codes for claims processed by the fraud and abuse
module 122 and accepted by the payer. This component also
preferably provides a case management tool that displays historical
rejection information, such as the consumers, pharmacists, and
prescribers as they relate to claims with certain fraud scores.
Therefore, this interface allows payers to analyze behaviors and
better understand claims that may be fraudulent. Additionally, this
interface will enable retrospective analysis and recoveries for
fraudulent claims.
[0050] Furthermore, it should be appreciated that the fraud
management interface may be configured to accept "overrides" from
payers. In other words, a payer may be able to override a rejection
of a prescription claim and cause the prescription claim to be
processed. The payer may need to provide a code or some other
identifier that indicates his/her authority to request the
override. In certain embodiments, if an override is submitted, any
messages previously produced by the fraud screening processes may
be attached to post-edit message delivered to the pharmacist.
[0051] It should be appreciated that the exemplary aspects and
features of the present invention as described above are not
intended to be interpreted as required or essential elements of the
invention, unless explicitly stated as such. It should also be
appreciated that the foregoing description of exemplary embodiments
was provided by way of illustration only and that many other
modifications, features, embodiments and operating environments are
possible. For example, the present invention is not intended to be
limited to the prescription claim editing environment. In other
embodiments, one or more of the fraud screening processes can be
readily adapted for application in other electronic prescription
systems, hospital inpatient medication ordering systems, and the
like.
[0052] Therefore, it is contemplated that any and all such
embodiments are included in the present invention as may fall
within the literal or equivalent scope of the appended claims. The
scope of the present invention is to be limited only by the
following claims and not by the foregoing description of exemplary
and alternative embodiments.
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