U.S. patent application number 14/231213 was filed with the patent office on 2014-08-14 for system, method, and computer program product for reducing the burden on scheduling systems by forecasting a demand for medical resources.
This patent application is currently assigned to Syus, LLC. The applicant listed for this patent is Syus, LLC. Invention is credited to Prakash Raghothamachar, David Reynolds, Mark Soileau, Eric Vickery, Milan Zimmermann.
Application Number | 20140229195 14/231213 |
Document ID | / |
Family ID | 38179537 |
Filed Date | 2014-08-14 |
United States Patent
Application |
20140229195 |
Kind Code |
A1 |
Reynolds; David ; et
al. |
August 14, 2014 |
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR REDUCING THE
BURDEN ON SCHEDULING SYSTEMS BY FORECASTING A DEMAND FOR MEDICAL
RESOURCES
Abstract
The present invention generates a forecast factor indicating an
anticipated demand for a medical resource in a medical facility
during a selected time period. The invention generates the forecast
factor using billing data retrieved from one or more billing data
systems wherein the retrieved billing data is from a prior time
period that is comparable to the selected time period. The
invention may also generate a schedule of the medical resource
using the determined forecast factor such that the generated
schedule may substantially correspond to the anticipated demand for
the medical resource during the selected time period. In addition,
the invention may also generate one or more displays of the
determined forecast factor to a user and may also receive a user
input for selecting and/or modifying the protocol used to determine
the forecast factor.
Inventors: |
Reynolds; David; (Hermitage,
TN) ; Raghothamachar; Prakash; (Nashville, TN)
; Soileau; Mark; (Nashville, TN) ; Vickery;
Eric; (Irondale, AL) ; Zimmermann; Milan;
(Oakville, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Syus, LLC |
Nashville |
TN |
US |
|
|
Assignee: |
Syus, LLC
Nashville
TN
|
Family ID: |
38179537 |
Appl. No.: |
14/231213 |
Filed: |
March 31, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13743100 |
Jan 16, 2013 |
8738401 |
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14231213 |
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12953420 |
Nov 23, 2010 |
8380534 |
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13743100 |
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11351353 |
Feb 9, 2006 |
7860728 |
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12953420 |
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Current U.S.
Class: |
705/2 |
Current CPC
Class: |
G06Q 10/06 20130101;
G16H 40/20 20180101; G06Q 40/08 20130101; G06Q 10/04 20130101 |
Class at
Publication: |
705/2 |
International
Class: |
G06Q 50/22 20060101
G06Q050/22 |
Claims
1. A system for optimizing a schedule of at least one medical
resource in at least one medical facility using a supply data set,
the system comprising: a supply system comprising the supply data
corresponding to at least one medical procedure being performed
using the at least one medical resource in the at least one medical
facility during a first time period, the data within the supply
data set being indicative of a utilization of the at least one
medical resource during the first time period; and a forecasting
module in communication with said supply system, wherein said
forecasting module: retrieves the supply data set from the supply
system; converts data within the supply data set into a utilization
data set corresponding to a historical demand for the at least one
medical resource in the at least one medical facility during the
first time period; determines a forecast factor using data within
the utilization data set, the forecast factor corresponding to an
expected demand for the at least one medical resource in the at
least one medical facility during a second time period, the second
time period being subsequent to the first time period; and
generates a schedule for the at least one medical resource based on
the determined forecast factor indicating when during the second
time period the at least one medical resource is expected to be
utilized.
2. A system according to claim 1, wherein said forecasting module
transfers the generated schedule to a scheduling calendar.
3. A system according to claim 1, wherein said forecasting module
comprises a memory device for storing the retrieved supply data
set.
4. A system according to claim 1, further comprising a user
interface for displaying the forecast factor to a user.
5. A system according to claim 4, wherein said user interface is
configured to receive a user input comprising a selection of the
forecast factor.
6. A system according to claim 1, wherein the data within the
supply data set comprises at least one of: an identification code
for identifying a type of the at least one medical procedure; a
time of the at least one medical procedure; a duration of the at
least one medical procedure; a location of the at least one medical
facility; a personnel identification code for identifying a
clinician performing the at least one medical procedure; and
combinations thereof.
7. A system according to claim 1, wherein the forecast factor
comprises at least one of: a percentage of time the at least one
medical facility is in use during the first time period; a number
of clinicians required to staff the at least one medical procedure;
a qualification of a clinician required to staff the at least one
medical procedure; a number of concurrent medical procedures
occurring in the at least one medical facility during the first
time period; and a percentage of time that a selected number of
concurrent medical procedures are occurring in the at least one
medical facility during the first time period.
8. A system according to claim 1 wherein the first and second time
periods are comparable time periods of substantially equivalent
duration comprising at least one of: a day; a week; a month; and a
year.
9. A system according to claim 1, further comprising a conversion
module comprising data and corresponding utilization information,
and wherein said forecasting module interrogates said conversion
module so as to convert the data within the medical process data
set into a utilization data set comprising the utilization
information corresponding to a historical demand for the at least
one medical resource in the at least one medical facility during
the first time period.
10. A system according to claim 4, wherein said forecast module
displays the forecast factor to the user via said user interface in
at least one of: a chart of substantially concurrent medical
procedures in the at least one medical facility during the first
time period; a chart of a quantity of the at least one medical
procedure in the at least one medical facility during the first
time period; and a Gantt chart of the at least one medical
procedure during the first time period.
11. A system according to claim 1, wherein the at least one medical
resource is at least one of: a clinician; and a medical procedure
room within the at least one medical facility.
12. A system according to claim 1, wherein the at least one medical
resource comprises a plurality of like medical resources each being
interchangeable with one another such that a first of the plurality
functions similarly to a second of the plurality; wherein the
forecast factor corresponds to an expected demand for the plurality
of like medical resources, the forecast factor comprising a number
of concurrent medical procedures occurring in the at least one
medical facility during the first time period; and wherein the
forecast factor is configured such that the plurality of like
medical resources can be scheduled for efficient utilization of
each of the plurality during the second time period.
13. A system according to claim 12, wherein said forecasting module
generates the schedule of the at least one medical resource such
that the schedule corresponds to the determined forecast factor
during the second time period, the plurality of like medical
resources each being scheduled for efficient utilization of each of
the plurality during the second time period.
14. A system according to claim 1, wherein the forecasting module
generates the schedule for the at least one medical resource based
on the determined forecast factor indicating at least a date and
time during the second time period when the at least one medical
resource is expected to be utilized.
15. A system according to claim 1, wherein the forecasting module
generates the schedule for the at least one medical resource based
on the determined forecast factor indicating at least a time
interval during the second time period when the at least one
medical resource is expected to be utilized.
16. A system according to claim 1, wherein the forecasting module
generates the schedule for the at least one medical resource based
on the determined forecast factor indicating at least a date range
during the second time period when the at least one medical
resource is expected to be utilized.
17. A method for optimizing a schedule of at least one medical
resource in at least one medical facility using a supply data set
from a supply system, the supply data set corresponding to at least
one medical procedure being performed using the at least one
medical resource in the at least one medical facility during a
first time period, the data within the supply data set being
indicative of a utilization of the at least one medical resource
during the first time period, the method comprising: retrieving the
supply data set from the supply system using a processing element;
converting data within the supply data set into a utilization data
set corresponding to a historical demand for the at least one
medical resource in the at least one medical facility during the
first time period using a processing element; determining a
forecast factor using data within the utilization data set, the
forecast factor corresponding to an expected demand for the at
least one medical resource in the at least one medical facility
during a second time period, the second time period being
subsequent to the first time period using a processing element; and
generating a schedule for the at least one medical resource based
on the determined forecast factor indicating when during the second
time period the at least one medical resource is expected to be
utilized using a processing element.
18. A computer program product for optimizing a schedule of at
least one medical resource in at least one medical facility by
retrieving a supply data set from a supply system, the supply data
set corresponding to at least one medical procedure being performed
using the at least one medical resource in the at least one medical
facility during a first time period, the data within the supply
data set being indicative of a utilization of the at least one
medical resource during the first time period, the computer program
product comprising a non-transitory computer-readable storage
medium having computer-readable program code instructions stored
therein comprising: first computer instruction means for retrieving
the supply data set from the supply system; second computer
instruction means for converting data within the supply data set
into a utilization data set corresponding to a historical demand
for the at least one medical resource in the at least one medical
facility during the first time period; third computer instruction
means for determining a forecast factor using data within the
utilization data set, the forecast factor corresponding to an
expected demand for the at least one medical resource in the at
least one medical facility during a second time period, the second
time period being subsequent to the first time period; and fourth
computer instruction means for generating a schedule for the at
least one medical resource based on the determined forecast factor
indicating at least a date and time during the second time period
when the at least one medical resource is expected to be utilized
using a processing element.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of and claims priority
from allowed, co-pending U.S. patent application Ser. No.
13/743,100 filed on Jan. 16, 2013 and entitled "A SYSTEM, METHOD,
AND COMPUTER PROGRAM PRODUCT FOR REDUCING THE BURDEN ON SCHEDULING
SYSTEMS BY FORECASTING A DEMAND FOR MEDICAL RESOURCES," which
claimed priority to U.S. Pat. No. 8,380,534 that issued from U.S.
patent application Ser. No. 12/953,420 filed on Nov. 23, 2010 and
entitled "A SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR
REDUCING THE BURDEN ON SCHEDULING SYSTEMS BY FORECASTING A DEMAND
FOR MEDICAL RESOURCES USING RETRIEVED BILLING DATA," which claimed
priority to U.S. Pat. No. 7,860,728 that issued from U.S. patent
application Ser. No. 11/351,353, filed on Feb. 9, 2006 and entitled
"A SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR REDUCING THE
BURDEN ON SCHEDULING SYSTEMS BY FORECASTING A DEMAND FOR MEDICAL
RESOURCES USING RETRIEVED BILLING DATA," the entire contents of all
of which are incorporated herein by reference.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The present invention relates to the field of medical
resource utilization including, but not limited to the scheduling
of medical staff and medical facilities. More particularly,
embodiments of the present invention collect and compile billing
data from one or more medical billing systems and convert the
billing data into historical demand information for a medical
resource so as to generate a forecasted demand for the medical
resource within a medical facility during a selected time
period.
[0004] 2. Description of Related Art
[0005] The scheduling of medical personnel, including clinicians,
technicians, and other staff, and other medical resources, such as
procedure rooms, is becoming increasingly complex as medical
facilities grow larger and as multiple medical facilities and
campuses become consolidated under a single administrative and/or
ownership entity such as a health care corporation. However, in
conventional health care administration systems, the scheduling of
specific personnel and medical procedure space within a medical
facility is largely determined by estimations based on maximum
potential demand for a given resource during a selected time
period.
[0006] For example, in an anesthesiology department having a number
of available procedure rooms, a typical weekday may have a peak
demand for procedure rooms and clinicians (which is often
determined by a number of procedures (i.e. administrations of
anesthesia) during a given two-hour span in the middle of the day.
In conventional scheduling methods, scheduling administrators often
schedule sufficient medical personnel (including anesthesiologists
and certified nurse anesthetists, for example) and procedure rooms
to accommodate the peak number of concurrent procedures for an
entire shift (i.e. a 10-hour shift from 0700-1700), where the peak
number of concurrent procedures may be occurring only during a 2
hour span in the middle of the day. However, conventional
scheduling systems and techniques do not utilize concurrent
activities information (such as information on a number of
concurrent medical procedures during a given time period gleaned
from billing data generated in a selected medical facility) that
may inform a scheduling administrator of the time period in which
peak demand for one or more medical resources is expected to be
experienced.
[0007] Furthermore, conventional scheduling systems are not
configured to distill concurrent activities information from
billing data taken from one or more medical billing data systems,
which may provide billing data that may be used (if properly
manipulated and/or interpreted) to aid in the prediction of demand
patterns for a medical resource within a medical facility during a
selected time period. For example, medical billing systems often
contain detailed information regarding the type of procedure
performed and the clinicians and/or staff members required to
perform a specific procedure. Billing data may also include time
stamp information and/or duration information that may be
indicative of the time required to perform a given procedure and/or
the time spent by various clinicians and/or staff members to
perform a given role in a medical procedure. Billing data tied to
particular medical procedures may also provide a more realistic
historical profile of demand for medical resources (such as medical
personnel and/or medical facility space) than, for example, the
historical usage of medical supplies and/or other inventory items.
This may be especially true for medical procedures such as
anesthesia administration, which may utilize relatively few
inventoried medical disposables, but may require significant
medical resources including, for example, facility space for
patient preparation and patient recovery and clinicians to oversee
patient preparation, administration of anesthesia, and patient
recovery.
[0008] While billing data may provide a large amount of data that
is generally indicative of demand for a given medical resource in a
medical facility during a selected time period, such billing data
is often non-standardized across medical facilities and/or across
administrative entities. For example, some billing data may only
include a time stamp and a procedure code indicative of a specific
service performed in a medical procedure. For example, in the
billing of a particular administration of anesthesia, the billing
data may indicate the service codes including, but not limited to:
patient preparation, anesthesia administration, surgery and/or
medical procedure, and patient recovery. Even if these service
codes are accompanied by a time stamp as part of a billing data
set, the billing data set may not be immediately useful to a
scheduling administrator, because such codes do not immediately
indicate the types of personnel, the expected duration, and/or the
type of procedure room required for each service. Thus, it may be
necessary, in some cases, to interpret and/or convert billing data
into alternative data types that may be predictive of the
utilization of particular medical resources during a selected time
period in order to aid a scheduling administrator in meeting a
predicted demand during a future comparable time period.
[0009] Thus limitations in current scheduling systems and
limitations inherent in billing data, that may otherwise aid
scheduling administrators in generating more efficient schedules,
may create a burden on scheduling administration systems as well as
create inefficiencies that may exacerbate the already high costs of
health care. Specifically, since conventional scheduling systems
are not capable of retrieving billing information from a medical
billing system and converting such billing information into usable
scheduling data, such scheduling systems are incapable of
ascertaining an accurate history of the actual demand for specific
medical resources (such as procedure rooms and/or medical
personnel) during a selected time period that may be predictive of
demand for such resources in a comparable subsequent time period.
In order to ensure that sufficient medical resources may be on hand
in a given medical facility during a selected time period,
scheduling administrators may be required to over-schedule
personnel and facilities space to accommodate the busiest portions
of a particular time period. For example, a scheduling
administrator may be required to schedule sufficient medical
personnel and facility space to accommodate 5 substantially
concurrent medical procedures in a particular medical facility for
an entire shift even though the actual demand for such medical
resources may only exist (as indicated by billing data, for
example) during a comparatively short time window during the middle
of the shift. Conventional search systems lack the capability of
accessing billing data for a selected time period, much less
translating and/or converting such billing data into predictive
forecast data that may be either presented to a user prior to the
scheduling of medical resources for a subsequent comparable time
period. Thus, some users (such as scheduling administrators and/or
physicians) will be required to rely on gross estimates ascertained
from "worst-case" maximum demand scenarios. Thus, conventional
scheduling systems may over-schedule medical resources for the
majority of a shift (or other time period) in order to ensure that
sufficient resources are available in a medical facility during a
particular time period.
[0010] Therefore, there exists a need for an improved system to
solve the technical problems outlined above that are associated
with conventional medical resource scheduling systems. More
particularly, there exists a need for a system capable of
converting medical billing data that may be retrieved from a
medical billing system into a format that may be indicative of a
historical demand for a medical resource in a particular medical
facility during a selected time period. There also exists a need
for a system capable of providing scheduling forecast information
to a scheduling administrator (via a display, for example) such
that the administrator may effectively use the converted billing
data in order to generate a schedule of medical resources that is
optimally matched to a predicted demand for medical resources
during a selected time period. In addition, there exists a need for
a system that may export a forecasted demand for medical resources
(as a forecast schedule, for example) into a scheduling system
and/or calendar such that the forecast schedule shown in the
calendar is optimized for efficiency based at least partially upon
the forecasted demand for medical resources (such as medical
personnel and/or medical procedure rooms).
BRIEF SUMMARY OF THE INVENTION
[0011] The needs outlined above are met by the present invention
which, in various embodiments, provides system, method, and
computer program product embodiments that overcome many of the
technical problems discussed above, as well other technical
problems, with regard to the scheduling of medical resources in a
medical facility. Specifically, in one embodiment, a system for
optimizing a schedule of at least one medical resource in at least
one medical facility using a billing data set is provided.
According to some embodiments, the system comprises a medical
billing system comprising the billing data corresponding to at
least one medical procedure being performed using the at least one
medical resource in the at least one medical facility during a
first time period. The data within the billing data may be
indicative of a utilization of the at least one medical resource
during the first time period. The system may further comprise a
forecasting module in communication with said medical billing
system, wherein the forecasting module may retrieve the billing
data set from the medical billing system. Furthermore, the
forecasting module may also convert data within the billing data
set into a utilization data set corresponding to a historical
demand for the medical resource in the medical facility during the
first time period. In addition, the forecasting module may also
determine a forecast factor using data within the billing data set,
wherein the forecast factor corresponds, for example, to an
expected demand for the medical resource in the medical facility
during a second time period (subsequent to the first time period)
such that the at least one medical resource is efficiently utilized
during the second time period. According to various embodiments,
the medical resource for which the expected demand may be
determined may include, but is not limited to: a clinician and a
medical procedure room within the at least one medical
facility.
[0012] In some system embodiments, the forecasting module may
further generate the schedule of the medical resource such that the
schedule corresponds to the determined forecast factor during the
second time period. Furthermore, the forecasting module may also be
configured to transfer the generated schedule to a scheduling
calendar. In some system embodiments, the forecasting module may
also comprise a memory device for storing the retrieved billing
data set and/or a user interface for displaying the forecast factor
to a user. In some such embodiments, the forecast module may
displays the forecast factor to the user via the user interface in
a display that may include, but is not limited to: a chart of
substantially concurrent medical procedures in the at least one
medical facility during the first time period; a chart of a
quantity of the at least one medical procedure in the at least one
medical facility during the first time period; a Gantt chart of the
at least one medical procedure during the first time period; and
combinations thereof.
[0013] According to various system embodiments, the data within the
billing data set may include, but is not limited to: an
identification code for identifying a type of the at least one
medical procedure; a time of the at least one medical procedure; a
duration of the at least one medical procedure; a location of the
at least one medical facility; a personnel identification code for
identifying a clinician performing the at least one medical
procedure; and combinations thereof. Using such billing data, the
system embodiments of the present invention may determine a
forecast factor that may include, but is not limited to: a
percentage of time the at least one medical facility is in use
during the first time period; a number of clinicians required to
staff the at least one medical procedure; a qualification of a
clinician required to staff the at least one medical procedure; a
number of concurrent medical procedures occurring in the at least
one medical facility during the first time period; a percentage of
time that a selected number of concurrent medical procedures are
occurring in the at least one medical facility during the first
time period; and combinations thereof. Furthermore, the first and
second time periods for which the system embodiments operate may be
comparable time periods of substantially equivalent duration
including, but not limited to: a day; a week; a month; and a
year.
[0014] Various system embodiments of the present invention may also
comprise a conversion module in communication with the medical
billing system and/or the forecasting module. The conversion module
may comprise data and corresponding utilization information.
According to some such embodiments, the forecasting module may
interrogate the conversion module so as to convert the data within
the billing data set into a utilization data set comprising the
utilization information corresponding to a historical demand for
the medical resource in the medical facility during the first time
period.
[0015] Further, the present invention also provides methods and/or
computer program products for optimizing a schedule of at least one
medical resource in at least one medical facility using a billing
data set from a medical billing system. As described generally
above, the billing data set may corresponding to at least one
medical procedure being performed using the at least one medical
resource in the at least one medical facility during a first time
period. Furthermore, the data within the billing data set may be
indicative, for example, of a utilization of the at least one
medical resource during the first time period. According to one
embodiment, the method and/or computer program product may comprise
steps for: retrieving the billing data set from the medical billing
system; converting data within the billing data set into a
utilization data set corresponding to a historical demand for the
medical resource in the medical facility during the first time
period; and determining a forecast factor using data within the
billing data set. The forecast factor determined in some
embodiments may correspond, for example, to an expected demand for
the medical resource in the medical facility during a second time
period (subsequent to the first time period) such that the at least
one medical resource is efficiently utilized during the second time
period. According to various method and/or computer program
products, the first and second time periods may be comparable time
periods including, but not limited to: a day; a week; a month; and
a year. Furthermore, in various method and/or computer program
products, the determined forecast factor may apply to forecast
demand for various medical resources including, but not limited to
a clinician and a medical procedure room within the at least one
medical facility.
[0016] Some method and/or computer program embodiments may also
comprise steps for redistributing the schedule of the at least one
medical resource such that the schedule corresponds to the
determined forecast factor during the second time period and/or
steps for transferring the generated schedule to a scheduling
calendar. Furthermore, some method and/or computer program product
embodiments may also comprise displaying the forecast factor to a
user (via a user interface, for example). The displaying step may,
in some embodiments, comprise displaying the forecast factor in a
graphical display that may include, but is not limited to: a chart
of substantially concurrent medical procedures in the at least one
medical facility during the first time period; a chart of a
quantity of the at least one medical procedure in the at least one
medical facility during the first time period; and a Gantt chart of
the at least one medical procedure during the first time
period.
[0017] In some method and/or computer program product embodiments
the data within the retrieved billing data set may include, but is
not limited to: an identification code for identifying a type of
the at least one medical procedure; a time of the at least one
medical procedure; a duration of the at least one medical
procedure; a location of the at least one medical facility; a
personnel identification code for identifying a clinician
performing the at least one medical procedure; and combinations
thereof. Furthermore, the forecast factor generated by the
determining step described above may include, but is not limited
to: a percentage of time the at least one medical facility is in
use during the first time period; a number of clinicians required
to staff the at least one medical procedure; a qualification of a
clinician required to staff the at least one medical procedure; a
number of concurrent medical procedures occurring in the at least
one medical facility during the first time period; and a percentage
of time that a selected number of concurrent medical procedures are
occurring in the at least one medical facility during the first
time period.
[0018] In addition, some method and/or computer program product
embodiments further comprise steps for interrogating a conversion
module comprising data and corresponding utilization information so
as to convert the data within the billing data set into a
utilization data set comprising the utilization information
corresponding to a historical demand for the at least one medical
resource in the at least one medical facility during the first time
period.
[0019] Thus the systems, methods, and computer program products for
optimizing a schedule of at least one medical resource in at least
one medical facility using a billing data set, as described in the
embodiments of the present invention, provide many advantages that
may include, but are not limited to: retrieving billing data set
from a selected time period that may be highly predictive of demand
for a particular medical resource during a subsequent comparable
time period; converting the retrieved billing data set into usable
scheduling information that may be useful to scheduling
administrators for optimizing the scheduling of medical resources
in one or more medical facilities; providing a clear user-friendly
display of a forecasted demand for a particular medical resource in
an upcoming time period so as to allow an administrator and/or user
to prepare an optimized staffing and/or facilities schedule; and
providing forecast factors and/or scheduling predictions or
forecasts based on actual billing data that may be easily exported
to a scheduling and/or calendar software suite.
[0020] These advantages and others that will be evident to those
skilled in the art are provided in the system, method, and computer
program product of the present invention. Importantly, all of these
advantages allow the system to utilize medical billing data to
generate scheduling forecast factor that may be presented to a user
such that the user is less likely to over-schedule and/or
under-schedule medical resources in a manner that may either create
resource waste or overburden medical staff or facilities.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0021] 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:
[0022] FIG. 1 illustrates an exemplary network environment in which
the systems, methods, and computer program products may be
implemented according to one embodiment of the present
invention.
[0023] FIG. 2 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including retrieving billing
data, converting the billing data to usage data, and determining a
forecast factor.
[0024] FIG. 3 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including retrieving billing
data, converting the billing data to usage data, determining a
forecast factor, and redistributing a schedule of a medical
resource using the forecast factor.
[0025] FIG. 4 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including retrieving billing
data, converting the billing data to usage data, determining a
forecast factor, redistributing a schedule of a medical resource
using the forecast factor, and transferring the generated schedule
to a scheduling calendar.
[0026] FIG. 5 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including retrieving billing
data, converting the billing data to usage data, determining a
forecast factor, and displaying the forecast factor to a user.
[0027] FIG. 6 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including retrieving billing
data, interrogating a conversion module, converting the billing
data to usage data, and determining a forecast factor based on the
usage data.
[0028] FIG. 7 is an illustration of the operation flow of the
systems, methods, and computer program products according to one
embodiment of the present invention including receiving a user
input, retrieving billing data, converting the billing data to
usage data, and determining a forecast factor based on the usage
data.
[0029] FIG. 8 is a graphical depiction of a display generated
according to one embodiment of the systems, methods, and computer
program products of the present invention illustrating a forecast
factor plot of required medical personnel versus time during a
first time period.
[0030] FIG. 9 is a graphical depiction of a display generated
according to one embodiment of the systems, methods, and computer
program products of the present invention illustrating a forecast
factor plot of concurrent medical procedures as a percentage of
time during a first time period (a Tuesday, for example).
[0031] FIG. 10 is a graphical depiction of a display generated
according to one embodiment of the systems, methods, and computer
program products of the present invention illustrating a forecast
factor plot of concurrent medical procedures as a percentage of
time during a first time period (a Friday, for example).
[0032] FIG. 11 is a graphical depiction of a Gantt chart display
generated according to one embodiment of the systems, methods, and
computer program products of the present invention illustrating a
forecast factor plot of the start, duration, and end times for at
least one medical procedure on a given Tuesday.
[0033] FIG. 12 is a graphical depiction of a Gantt chart display
generated according to one embodiment of the systems, methods, and
computer program products of the present invention illustrating a
forecast factor plot of the start, duration, and end times for at
least one medical procedure on a given Friday.
[0034] FIG. 13 is a graphical depiction of a user input display
generated by a user interface, according to one embodiment of the
systems, methods, and computer program products of the present
invention, wherein the user input display is configured to receive
a user input comprising a selection of a forecast factor.
DETAILED DESCRIPTION OF THE INVENTION
[0035] 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.
[0036] The various aspects of the present invention mentioned
above, as well as many other aspects of the invention are described
in greater detail below. The systems, methods, and computer program
products of the present invention are described in an
anesthesiology medical practice environment. It must be understood
that this is only one example of the use of the present invention.
Specifically, the systems, methods, and computer program products
of the present invention can be adapted to any number of medical
billing systems and medical resources and are not limited to those
in anesthesiology practices. For example, the present invention may
be used to analyze billing data and develop forecast factors based
thereon in a variety of medical practices and/or medical care
facilities including, but not limited to: surgical practices,
radiology practices, family medicine practices, internal medicine
practices, and other medical facilities.
[0037] FIG. 1 illustrates an example of a typical conventional
network environment 10 in which the systems, methods, and computer
program products of the present invention may be employed. The
network includes a forecast module 12 (housed in a host computer
device, for example). The forecast module 12 is typically connected
to a network 14, such as a LAN, WAN, Intranet, or Internet, for
example. Also connected to the network are various medical billing
systems 11 containing a variety of billing data sets including data
that may be indicative of a utilization of at least one medical
resource in a selected medical facility during a first time period.
For example, data within a billing data set may include, but is not
limited to: service case entries corresponding to various services
performed during the course of a medical procedure during the first
time period (such as a given hour, day, week, month, and/or year,
for example). A service case entry may include, in some examples,
codes for patient preparation (including the administration of
anesthesia, for example), codes for a medical procedure and/or a
surgical procedure (such as a surgical procedure performed under
general anesthesia), and/or codes for patient recovery (including
time spent in a recovery room and/or supervision during recovery by
a clinician). The data within the billing data sets may also
include, but are not limited to: identification codes for
identifying a type of an at least one medical procedure; times of
the at least one medical procedure; durations of the at least one
medical procedure; locations of the at least one medical facility;
personnel identification codes for identifying a clinician
performing the at least one medical procedure; payer class (i.e.
type of insurance coverage for the medical procedure) and
combinations thereof.
[0038] Further, as shown in FIG. 1, users may also be connected to
the network 14 via personal computers 15 or other types of
computing systems. In addition, one or more conversion modules 13
may also be connected to the network 14 such that the forecast
module 12 may be capable of interrogating the conversion module 13
so as to be capable of converting the data within the billing data
set into a utilization data set comprising utilization information
corresponding to a historical demand for the medical resource (such
as a procedure room, a clinician, and/or other medical personnel)
in at least one medical facility during the first time period.
[0039] In operation, the system of the present invention, via the
forecast module 12, may provide a web page or other similar
electronic form to a user. Using the web page or electronic form,
the user may input and/or modify a standard forecast query which
may include, for example, a selection of a second time period that
may be comparable to the first time period from which the billing
data is taken (such as, for example, an upcoming week) or a
selection of a particular medical facility (such as a selected
anesthesiology and/or operating room suite). Based either on this
query, and/or based on a standard query stored in a memory device
22 provided as part of the forecast module 12, the forecast module
12 may, in some embodiments, poll the medical billing systems 11 in
order to retrieve one or more billing data sets from the medical
billing systems 11 (see step 210 of FIG. 2, for example). According
to other embodiments, the retrieval step (see step 210, of FIG. 2,
for example) may also comprise a step wherein the medical billing
systems 11 periodically "push" medical billing data to the forecast
module 12 (as described in further detail below).
[0040] Furthermore, the forecast module 12 may also convert data
within the billing data set into a utilization data set
corresponding to a historical demand for the medical resource in
the medical facility during the first time period (see step 220 of
FIG. 2, for example). As discussed above, the forecast module 12
may interrogate and/or consult a conversion module 13 so as to be
capable of converting the data within the billing data set into a
utilization data set comprising utilization information
corresponding to a historical demand for the medical resource. In
other embodiments, the forecast module 12 may access conversion
algorithms and/or a conversion key stored in a memory device 22
that may be provided as part of a computer system hosting the
forecasting module 12. For example, medical billing data retrieved
from some medical billing systems may not include identifiers for
specific types of medical procedures and may instead indicate only
a start time and/or duration of a given medical procedure within an
anesthesiology practice, for example. In such cases, the forecast
module 12 may interrogate one or more of a conversion module 13
and/or a conversion algorithm stored in a memory device 22 in order
to convert duration information into, for example, a procedure
and/or medical service type. For example, a billed medical
procedure having a five minute duration may correlate to a patient
preparation step (which may require specific medical resources,
such as a registered nurse and a patient prep room). In another
example, a billed medical procedure having a one hour duration may
correlate to a procedure step (which may require specific medical
resources, such as an anesthesiologist and a nurse anesthetist and
a sterile procedure room). In yet another example, a billed medical
procedure having a different duration may correlate to a
post-procedure recovery step (which may require other specific
medical resources, such as a registered nurse and a recovery room).
In such embodiments, the forecasting module 12 may be capable (by
consulting a stored conversion key and/or interrogating a
conversion module 13) of converting certain billing data to a
standardized format (herein referred to a "utilization data set,"
for example) that may be better used to generate a forecast factor.
According to other examples, the conversion module 13 may house a
plurality of different conversion algorithms configured to convert
billing data from various different medical billing systems (each
of which may generate billing data having a different format) into
a standardized "utilization data set" that may be used, in turn, to
generate the forecast factor.
[0041] Therefore in some system embodiments of the present
invention, the forecast module 12 may determine a forecast factor
using data within the utilization data set (see, for example, step
230 of FIG. 2). The forecast factor determined by the forecast
module 12 may correspond to an expected demand for the medical
resource in at least one medical facility during a second time
period, wherein the second time period may be subsequent to the
first time period, such that the at least one medical resource may
be more efficiently utilized and/or scheduled during the second
time period (such as an upcoming hour, day, week, month, or year,
for example).
[0042] According to various system embodiments of the present
invention, the forecast module may be capable of accessing a
calendar (stored in a memory device 22 for example, and/or
accessible via the network 14) such that when determining one or
more forecast factors, the forecast module 12 may take into account
the holiday calendar is so as to ensure weeks of same type (i.e.
"short" holiday weeks) correspond to comparable historical weeks
(having stored billing data, for example) before using such stored
billing data to forecast demand for a medical resource. For
example, time periods with holiday types are matched against
equivalent holiday types in the past time periods, non-holiday time
periods are matched with non-holiday time periods in past years
(not simply by week number, for example). In addition, the forecast
module 12 may also be capable of determining a forecast factor
wherein selection of the first time period is made such that only
full weeks enter the calculations. For example, incomplete weeks at
the end of a given time period (such as month's and/or year's end)
may be truncated and discarded by the forecast module 12 for the
purposes of determining the forecast factor. Such embodiments may
provide a more accurate forecast factor so as to more accurately
assess demand for medical resources during special event weeks such
as Thanksgiving week.
[0043] The forecast factor determined by the forecast module 12,
according to some system embodiments of the present invention, may
include, but is not limited to: a percentage of time the at least
one medical facility is in use during the first time period; a
number of clinicians required to staff the at least one medical
procedure; a qualification of a clinician required to staff the at
least one medical procedure; a number of concurrent medical
procedures occurring in the at least one medical facility during
the first time period; and a percentage of time that a selected
number of concurrent medical procedures are occurring in the at
least one medical facility during the first time period.
[0044] The forecast factors generated by the forecast module 12 of
the present invention may also include one or more graphical and/or
statistical results determined using the retrieved billing data.
For example, the forecast factor may comprise a Gantt chart of
selected medical procedures in a selected medical facility (such as
a selected procedure suite) during a first time period. As shown
generally in FIGS. 11-12, the Gantt Chart forecast factor may
enable a user to obtain a quick and efficient overview of "busy
time of day" and "idle periods" (white areas) in past time periods
of interest.
[0045] Some forecast factors generated by the system embodiments of
the present invention may also comprise financial information
obtained from the medical billing systems 11. For example, the
forecast module 12 may also be capable of determining a percentage
of payer volume (i.e. insurance type volume) within a selected
medical facility during a selected first time period. Payers may be
defined in a 2-level hierarchy comprising: (1) payer group and (2)
payer class (wherein a payer class may comprise one or more payer
groups). Each insurance company may pay different amounts for the
same procedure. Thus, payer volume forecast factors may allow a
user of embodiments of the present system to evaluate how much time
was spent doing "well paid work" as opposed to "poorly paid work"
in a given medical facility. A payer volume forecast factor may be
determined by the forecast module 12 by calculating percentage of
volume (wherein volume is herein defined as a number of man-hours
(mh)) in each payer class or payer group. Such a forecast factor
may also be weighted to emphasize particular payer classes and/or
payer groups when calculating the payer volume forecast factor.
[0046] According to other system embodiments of the present
invention, the forecast module 12 may also be configured to
determine a forecast factor that may be indicative of a number of
concurrent medical procedures occurring in a medical facility (such
as a particular suite of medical procedure rooms). For example,
according to one embodiment, demand for a medical resource (such as
operating room anesthesia staff) may be accurately predicted. For
the purposes of optimizing the forecast factor in one embodiment,
an assumption may be made wherein at any given hour (or other
selected time unit), one anesthesia nurse staff member is needed to
oversee one activity and one anesthesiologist is needed to staff
3-4 concurrent activities. Thus, the concurrent activities forecast
factor may be critical to predicting the correct staffing for
operating room anesthesia staff. Thus, in some embodiments, the
forecast module 12 may determine a concurrent activities forecast
factor by determining a number of concurrent medical procedures
versus a selected time axis point by day (using, for example, the
utilization data set obtained by converting the raw billing data
sets retrieved from the medical billing systems 11). According to
various system embodiments, the forecast module may then perform a
statistical calculation on the number of concurrent medical
procedures to determine various forecast factors, including, but
not limited to: an average number of concurrent medical procedures
occurring in the selected time interval; 50% of the median number
of concurrent medical procedures occurring in the selected time
interval, maximum number of concurrent medical procedures occurring
in the selected time interval, and a distribution of concurrent
medical procedures occurring in the selected time interval.
[0047] In some other system embodiments, the forecast module may
also determine a forecast factor comprising a weekly forecast of
concurrent medical procedures per time interval. For example, the
forecast module 12 may distribute medical procedures (detected by
retrieving the billing data corresponding thereto) into a series of
first time periods (using a holiday calendar as described generally
above to ensure a comparison of comparable seasonal time periods)
and may further utilize a predetermined weighted average (wherein
the weighting factors may be stored in a memory device 22) to
calculate forecast for a comparable second time period (in the
upcoming year, for example). The forecast module 12 may, for
example calculate a weighted average forecast factor that gives the
most weight to the last year and, may use the following weighting
values: 1 year prior: 1.0, 2 years prior: (0.4, 0.6) 3 years prior
(0.2, 0.3, 0.5) (wherein the weighting factors are selected
depending also on the number of billing data points used to
determine the utilization data set).
[0048] In some other system embodiments, the forecast module 12 may
also calculate a forecast factor comprising a weekly forecast of
concurrent medical procedures per time interval using exponential
smoothing (such as triple exponential smoothing, for example)
statistical techniques. The forecasting factors displayed as a
result of such a determination may include, but are not limited to:
forecasted values of concurrent medical procedures per time
interval for a comparable future week; actual concurrent medical
procedures per time interval for the comparable first time period;
and forecasted values plus an indication of the error (MAPE)
inherent in the forecasted value. According to other system
embodiments, the forecast module may also distribute medical
procedures into selected first time periods (such as prior months)
and use linear regression techniques to calculate forecast factor
of volume (in man-minutes, for example) for a second time period
(such as a comparable month in the upcoming year). Thus, the
forecast module may accurately predict volume in man-minutes, which
when determined in line with payer class (as described generally
above) may accurately predict revenues for an upcoming time period.
Monthly volume can display trends important for quarterly planning,
including for example, staff hiring and/or downsizing
requirements.
[0049] Other system embodiments may comprise a forecast module 12
that may determine a forecast factor that may include, but is not
limited to: a maximum number of concurrent medical procedures by
time period (such as by week); a correlation between morning and
afternoon volume (in man-hours, for example) per time period (i.e.
daily); total volume (in man-minutes) per starts (daily or
hourly)(which may indicate average duration of medical procedure in
minutes); a number of medical procedures started per time period;
and a number of medical procedures stopped per time period.
[0050] According to various system embodiments of the present
invention the forecasting module may comprise a memory device 22
for storing multiple retrieved billing data sets from one or more
medical billing systems 11 over the course of a selected number of
time periods in order to compile and utilize a wide range of
historical billing data over the course of, in some embodiments,
several years in order to determine some forecast factors. Thus,
the "utilization data set" used by the forecast module to determine
a forecast factor may comprise, in some embodiments, stored and/or
converted billing data from one or more first time periods that may
be comparable to the second time period for which a medical
resource demand forecast may be sought.
[0051] By converting the billing data to a standardized
"utilization data set" to determine the various types of forecast
factors described above, the forecast module 12 may be capable of
compiling billing data from a number of different medical billing
systems 11 within a large health care system, for example, and
developing powerful and flexible forecast factors for various
administrative levels within the health care system. For example,
as described below with respect to step 710 of FIG. 7 (generally
depicting a method embodiment of the present invention) some system
embodiments of the present invention may further comprise a user
interface configured to receive a user input comprising a selection
of the forecast factor. Thus, a user may input a selection of one
or more medical facilities, medical practices, and/or specific
procedure rooms within a large healthcare system. The forecast
module may then tailor the compilation of billing data to correlate
more closely to the selected forecast factor. For example, if a
user selects a forecast factor for a specific operating room suite
in a specific hospital, the forecast module may only retrieve
billing data corresponding to medical procedures performed in the
same and/or comparable operating room suites within the same health
care system such that the forecast factor generated using the
billing data may be especially reflective of the expected demand
for medical resources (including, for example, procedure room space
and/or certain types of medical personnel) in the selected
operating room suite.
[0052] According to some other system embodiments, the forecast
module 12 may be further configured to generate the schedule of the
at least one medical resource such that the schedule corresponds to
the determined forecast factor during the second time period. For
example, if the forecast factor indicates that a maximum number of
concurrent medical procedures in a four-room surgical suite staffed
by three surgeons are occurring during a two-hour block during the
middle of the day (see FIG. 9, for example), the forecast module 12
may automatically generate a schedule of clinicians and/or
procedure rooms to accommodate the maximum number of concurrent
procedures during the middle of the day without scheduling a
concurrent maximum number of medical resources during a full shift.
In addition, the forecast module 12 may utilize a forecast factor
output 810 (see FIG. 8, for example) in order to provide, for
example, an overlap of working shifts for one or more medical
personnel such that a greater number of medical personnel may be
present in the medical facility during the peak hours of concurrent
medical procedures (as indicated by the forecast factor determined
by analyzing billing data from a previous comparable time period).
In addition, the forecast module 12 may also schedule a maximum
number of procedure rooms (for example 4 procedure rooms) using the
forecast factor output 920 of FIG. 9 (which shows pie chart 920
graphs of the percentage of time during a particular hour that a
given number of concurrent procedures were occurring during a
comparable time period) only during the portion of a particular
time period that multiple concurrent procedures are performed (as
indicated by the billing data). According to further embodiments,
the forecast module 12 may also transfer the generated schedule of
medical resources to a scheduling calendar. For example, the
forecast module 12 may transfer the generated schedule to a
computer device 15 via the network 14 such that the user may view
and/or manually edit the generated schedule generated by the
forecast module 12 in an electronic calendar program and/or
scheduling module.
[0053] As shown generally in FIGS. 8-12, the forecast module 12 may
also generate a display 800 of the forecast factor. Some system
embodiments of the present invention may comprise a user interface
(such as a display 24 provided as a component of the forecast
module 12 and/or a computer device 15 in communication with the
forecast module 12 via the network 14. According to some
embodiments, the forecast module 12 may display the forecast factor
to the user via said user interface in a display 800 that may
include, but is not limited to: a chart of substantially concurrent
medical procedures in the at least one medical facility during the
first time period (see, for example, FIGS. 9-12, generally showing
pie charts of the percentage of time that different numbers of
concurrent medical procedures were billed for a first time period);
a chart of a quantity of the at least one medical procedure in the
at least one medical facility during the first time period; and a
Gantt chart of the at least one medical procedure during the first
time period (see FIGS. 11-12, showing Gantt charts of two different
workdays (Tuesday and Friday) within a given first time period (a
week)).
[0054] FIG. 8 shows a display 800 generated by one forecast module
12 embodiment of the present invention, wherein the display 800
includes a forecast factor plot comprising a plot of a billed
medical resource (in this case, a number of medical personnel)
versus time of day for a particular Monday (as indicated by the
data point legend 840 that may be displayed as part of the display
800). Thus, in some system embodiments, the forecast module 12 may
be capable of displaying billed medical personnel versus time of
day for a plurality of days within a selected time period
concurrently in a single display 800 by utilizing different data
point indicator shapes as shown, for example, in the data point
legend 840). According to various system embodiments of the present
invention, the forecast module 12 may use billing data retrieved
from the billing data systems 11 to determine a number of medical
personnel (including, in some instances a type of medical personnel
(such as a certified nurse anesthetist, and/or an anesthesiologist)
whose time may have been billed during a prior Monday of a
comparable week (i.e. a non-holiday Monday in the middle of the
summer) and determine a forecast factor (i.e. that no more than 10
medical personnel should be scheduled before 0730 or after 1200 on
such a Monday) that may be shown in a display 800 as shown in FIG.
8. The plotted forecast factor 810 of FIG. 8 may also generally
indicate that a scheduling administrator should not schedule 13
medical personnel to work a ten-hour shift from 0700-1700 when the
peak demand for this medical resource (13 medical personnel, for
example) only exists on comparable Mondays for approximately 2
hours (0930-1130).
[0055] Various system embodiments of the present invention also
provide a forecast module 12 that may be capable of generating a
display 800 of a chart of substantially concurrent medical
procedures in the at least one medical facility during the first
time period (such as a given workday). For example, FIGS. 9 and 10
illustrate a display 800 that may be generated by the forecast
module 12 of the present invention to indicate the percentage of
time within a selected time period that a specific number of
concurrent medical procedures are typically running (as ascertained
by the forecast module 12 using billing data retrieved from the
medical billing systems 11, for example). In the example depicted
in FIGS. 9 and 10, a particular medical facility (such as an
anesthesiology department within a hospital) has a multiple-year
history of scheduling four procedure rooms for a three-surgeon
medical team for the weekdays Tuesday, Wednesday, Thursday, and
Friday. FIG. 9 shows, for example, a group of pie charts 920 (for
each hour of a Tuesday) showing the percentage of time within a
specific hour 910, that a number of concurrent medical procedures
may be occurring within a given medical facility (such as a suite
of four procedure rooms). A pie chart 920 corresponding to 1300,
Tuesday, indicates (using the concurrent procedure tags 930) that:
4 procedures were taking place concurrently for 15 percent of the
hour between 1300 and 1400, 3 procedures were taking place
concurrently for 23 percent of the hour between 1300 and 1400, 2
procedures were taking place concurrently for 15 percent of the
hour between 1300 and 1400, 1 procedure was taking place for 23
percent of the hour between 1300 and 1400, and no procedures were
taking place for 23 percent of the hour between 1300 and 1400. As
described below with respect to FIG. 7, some system, method, and
computer program embodiments of the present invention may allow a
user to select the forecast factor that may be determined and
displayed (via the display 800) by the forecast module 12. Thus, a
user may select to plot a forecast factor (such as a concurrent
procedures pie chart 920 for selected medical resources (i.e. the
three-surgeon team, using a 4-room procedure suite, as described
above), over the course of a selected time period (i.e. a Tuesday)
which would lead to a forecast factor plot as shown generally in
FIG. 9. Alternatively, as shown in FIG. 10, the forecast module 12
may also be capable of determining and/or plotting (in a display
800, for example) a forecast factor of concurrent medical
procedures for the three-surgeon team described above for a Friday.
As shown in FIG. 10, for example, the pie chart 930 corresponding
to the 1200 hour 910 indicates that only one procedure was
performed (for only 19 percent of the plotted hour (as indicated by
the concurrent procedure tag 930 in the display 800)). Thus, the
display 800 generated by the forecast module 12 may allow a user
(such as a scheduling administrator and/or clinician) to quickly
identify medical resource scheduling inefficiencies by scanning the
displays 800 for long periods of time having 2 or less concurrent
procedures running For example, the display 800 shown in FIG. 10
may indicate that for Fridays (during a comparable season to the
Friday forecast factor plotted in FIG. 10), the three-surgeon team
may only require, at most, three procedure rooms (for a two hour
block of time) and/or that one of the team members may take a
shortened Friday work schedule.
[0056] FIGS. 11-12 show an alternate Gantt-type forecast factor
display 800 that may be generated by the forecast module 12 of the
present invention according to some system embodiments of the
present invention. For example, as shown in FIG. 11 Gantt chart
display 800 may be generated to plot medical procedures (by
individual billed case number 1120, for example) versus time 1130
for a selected historical first time period that may be comparable
(i.e. a non-holiday, midsummer week) to an upcoming second time
period. The Gantt chart display 800 may depict the duration 1140 of
individual procedures and show how concurrent medical procedures
have lined up during the course of a typical Tuesday (FIG. 11, for
example, corresponds to the display of pie charts 930 shown
generally in FIG. 9). FIG. 12 shows a Gantt chart display 800
showing medical procedures being performed by the three-surgeon
team on a typical Friday (corresponding to the pie chart 930
display 800 of FIG. 10, for example). As FIG. 12 indicates, the
forecast factor generated by the forecast module 12 indicates that
there may be little need for multiple procedure rooms (or medical
staff schedule overlap) on a typical Friday (at least as indicated
by a previous comparable Friday's billing data and/or a weighted
average thereof based on historical data from multiple comparable
time periods).
[0057] As described generally above, some system embodiments of the
present invention may also comprise one or more user interfaces for
displaying the forecast factor to a user. For example, the user
interface may comprise a computer device 15 in communication with
the forecast module 12 via the network 14. In other embodiments,
the user interface may comprise a display 24 and/or keyboard
interface 26 that may be included as part of a computer device that
may host the forecast module 12 of the present invention. In any
case, the user interface may also be configured to receive a user
input comprising a selection of the forecast factor. For example,
as shown generally in FIG. 13, the user interface may be capable of
generating a display 800 including one or more input areas
1310-1390 such that a user may input a query and/or a specific
selection of a forecast factor that they would like the forecast
module to determine based upon the billing data retrieved from one
or more medical billing systems 11. For example, as shown in FIG.
13, the selection display 800 may comprise drop down menus
1310-1330 for selecting a forecast factor based upon certain
utilization data criteria which may include, but are not limited
to: a medical procedure/activity type 1310, a medical resource
(staff) type 1320, and an other staff type 1330 (i.e. non-medical
and/or administrative staff). In other embodiments (see FIG. 13,
for example) the selection display 800 may also comprise text boxes
wherein a user may input other selection criteria for modifying the
parameters of the forecast factor determined by the forecast
module. For example, the selection display 800 may comprise various
text boxes 1330-1390 wherein a user may input forecast factor
criteria including, but not limited to: a medical staff number in
include in the forecast factor determination 1340, a medical staff
number to exclude from the forecast factor determination 1350; a
payer class (insurance company, for example) 1360, a payer class to
exclude from the forecast factor determination 1370; a location
code (corresponding to a selected medical facility, for example)
1380; a location code to exclude from the forecast factor
determination 1390; a procedure code (corresponding to a medical
procedure type to be included in the forecast factor determination.
Thus, as shown generally in FIG. 13, some system embodiments of the
present invention may allow the user to selectively modify the
parameters of the forecast factor determination in order to change
the focus of the forecast factor determination as performed by the
forecast module. For example, a user may choose to focus on
scheduling profitable medical procedures by selecting a forecast
factor that includes profitable payer classes. The user may also
choose to exclude certain staff identification numbers (for staff
members with scheduled vacations during the upcoming second time
period (for which the forecast factor and/or schedule is being
developed)).
[0058] As illustrated in exploded portion of FIG. 1 corresponding
to the forecast module 12, the forecast module 12 of the system
embodiments of the present invention may be generally embodied as a
typical computer, server or mainframe system depending on the
embodiment. The host computer 12 may generally include a processing
element 20, such as a microprocessor, VLSI, ASIC, etc., a storage
device 22, display 24, keyboard and mouse interface 26, and a
network interface 28.
[0059] In some embodiments, the host computer system 12 may poll
one or more medical billing systems 11 for medical billing data
each time a user requests a particular forecast factor (via a
personal computer 15, for example). However, in some embodiments,
such frequent requests may slow down and/or disrupt the medical
billing system 11. Further, accessing the medical billing system 11
may have an associated processing delay. For this reason, in some
embodiments, the forecast module 12 may further include a
prepopulated cache 30 from which medical billing data (and
corresponding medical resource usage data) is derived for providing
forecast factors according to various embodiments of the present
invention. Specifically, as shown in FIG. 1, the forecast module 12
of the present invention includes an availability cache 30 located
in the storage device 22. The availability cache 30 is populated
with medical billing data from a first time period that may be
required for determining a forecast factor for an expected demand
for a medical resource during a comparable subsequent second time
period. In such embodiments, the data retrieved from the
availability cache 30 may also be used to determine a forecast
factor and/or reschedule a medical resource using the forecast
factor, as described above, and be presented to a user's personal
computer 15 (or other user interface) in a display.
[0060] Furthermore, according to various system embodiments of the
present invention, it should be understood that medical billing
data may be transferred from one or more medical billing systems 11
to the forecast module 12 (or a memory device 22 in communication
therewith) via "push" and/or "pull" techniques. For example,
according to "pull" techniques, one skilled in the art will
appreciate that the forecast module 12 may periodically (in
response to a user input, and/or at a predetermined interval, for
example) interrogate one or more medical billing systems 11 to
"pull" medical billing data sets therefrom. Furthermore, according
to other system embodiments, "push" techniques may be used, wherein
one or more medical billing systems 11 may be adapted to
periodically (monthly, weekly, and/or daily, for example) "push"
medical billing data to the forecast module 12 (via a network 14
connection, for example) and/or to the storage device 22 that may
be included as a component of the forecast module 12 of the present
invention. Thus, as described above, either of the described "pull"
or "push" techniques may also be used to populate an availability
cache 30 provided as part of the memory device 22 of the forecast
module 12. As one skilled in the art will appreciate, similar
"push" and/or "pull" techniques may also be used to transfer
descriptive and/or conversion data from one or more conversion
modules 13 to the forecast module 12 (via a network 14, for
example) to aid the forecast module in converting raw medical
billing data into a usable forecast factor that may be displayed to
a user.
[0061] The various operations of the present invention may be
performed either by hardware in the form of ASIC chips or other
specialized hardware or by operation of software ran by a
processing element. In the latter case, the storage device 22 may
also further include the various computer software programs and
modules used to implement the operations of the present
invention.
[0062] FIG. 2 is a generalized illustration of the operations
performed by the systems, methods, and computer program products of
the present invention to generate the various forecast factors
discussed above and to generate the various forecast factor
displays illustrated in FIGS. 2-7. The description of this
operation is given by example to the system schematic shown
generally in FIG. 1, and to the various display illustrations shown
in FIGS. 8-13.
[0063] FIG. 2 shows a method for optimizing a schedule of at least
one medical resource (such as, for example, a clinician and/or a
medical procedure room) in at least one medical facility using a
billing data set retrieved from a medical billing system 11. As
described generally above with respect to the various system
embodiments of the present invention, the billing data set may
corresponding to at least one medical procedure being performed
using the at least one medical resource in the at least one medical
facility during a first time period (such as a comparable past week
and/or a statistical compilation of billing data from a plurality
of comparable past weeks). In addition, the data within the billing
data set may also be indicative of a utilization of the at least
one medical resource during the first time period. As discussed
above, data within the billing data set may include, but is not
limited to: an identification code for identifying a type of the at
least one medical procedure; a time of the at least one medical
procedure; a duration of the at least one medical procedure; a
location of the at least one medical facility; a personnel
identification code for identifying a clinician performing the at
least one medical procedure; and/or combinations thereof.
[0064] As shown generally in FIG. 2, some method embodiments may
comprise step 210 for retrieving the billing data set from the
medical billing system 11, and step 220 for converting data within
the billing data set into a utilization data set corresponding to a
historical demand for the medical resource in the at least one
medical facility during the first time period. Finally, the various
method embodiments of the present invention may also comprise step
230 for determining a forecast factor using data within the
utilization data set. The forecast factor may correspond, for
example, to an expected demand for the medical resource in the at
least one medical facility during a second time period, the second
time period being subsequent to the first time period, such that
the at least one medical resource may be efficiently utilized
during the second time period.
[0065] As described generally above, step 230 may comprise
performing a number of different statistical calculations on the
utilization data set for determining the forecast factor. For
example, step 230 may include, but is not limited to: generating a
Gantt chart of medical procedures billed during the first time
period; calculating an average number of concurrent medical
procedures during a time interval within the first time period;
calculating a percentage of payer volume; calculating forecasts of
concurrent medical procedures during a time interval within the
first time period using statistical techniques such as concurrent
weighted averages, exponential smoothing (such as triple
exponential smoothing, for example), and linear regression; and
calculating an average number of medical procedure starts and stops
during the first time period. According to other method
embodiments, the forecast factor generated in step 230 may include,
but is not limited to: a percentage of time the at least one
medical facility is in use during the first time period; a number
of clinicians required to staff the at least one medical procedure;
a qualification of a clinician required to staff the at least one
medical procedure; a number of concurrent medical procedures
occurring in the at least one medical facility during the first
time period; and a percentage of time that a selected number of
concurrent medical procedures are occurring in the at least one
medical facility during the first time period.
[0066] As shown in FIG. 3, some method embodiments of the present
invention may also comprise step 310 for generating and/or
redistributing the schedule of the at least one medical resource
such that the schedule corresponds to the determined forecast
factor during the second time period. Thus, in some method
embodiments, step 310 may comprise generating and/or redistributing
a schedule of a medical resource (such as reserved procedure rooms
and/or the schedules of physicians and/or other clinical staff)
such that the schedule better aligns with the forecast factor
(which is calculated, at least in part, using historical
utilization data (see step 230) that is based, in turn, upon actual
billing data for a first time period that may be directly
comparable to the second time period (i.e. an upcoming day, week,
month, and/or year for which a schedule is to be developed). For
example, and as discussed generally above with respect to FIG. 9,
if the forecast factor indicates that a maximum number of
concurrent medical procedures in a four-room surgical suite staffed
by three surgeons are occurring during a two-hour block during the
middle of the day (see FIG. 9, for example), the forecast module 12
may automatically generate and/or redistribute a schedule of
clinicians and/or procedure rooms to accommodate the maximum number
of concurrent procedures during the middle of the day without
scheduling a concurrent maximum number of medical resources during
a full shift.
[0067] Furthermore, in some method embodiments (as shown in FIG.
4), the method may further comprise step 410 for transferring the
generated and/or redistributed schedule of medical resources to a
scheduling calendar. For example, as described above with respect
to the various system embodiments of the present invention, the
forecast module 12 may transfer the schedule to a computer device
15 via the network 14 such that the user may view and/or manually
edit the schedule generated by the forecast module 12 in an
electronic calendar program and/or scheduling module.
[0068] FIG. 5 shows another method embodiment of the present
invention further comprising step 510 for displaying the forecast
factor (determined in step 230, for example) to a user. As
discussed above with respect to the system embodiments of the
present invention, the forecast module 12 may, for example,
generate a graphical depiction of a forecast factor in a display
800 (see FIGS. 8-12) such that a user may view a graphical
depiction of the forecast of a projected demand for a specific
medical resource during an upcoming second time period (that may be
comparable to a first time period from which actual billing data
may be retrieved (see step 210) and based upon which medical
resource utilization data 220 is generated. As described in further
detail above with respect to various system embodiments of the
present invention, the displaying step 510 may also further
comprise displaying the forecast factor to the user in a graphical
display 800 (see FIGS. 8-12, for example) that may include, but is
not limited to: a chart of substantially concurrent medical
procedures in the at least one medical facility during the first
time period (see the percentage of concurrent medical procedures
pie charts of FIGS. 9 and 10 (depicting concurrent medical
procedures for a Tuesday and Friday, respectively); a chart of a
quantity of the at least one medical procedure in the at least one
medical facility during the first time period (see for example,
FIG. 8, generally depicting a volume (in man hours) of a medical
resource (corresponding generally to a number of medical
procedures) during a particular Tuesday); and a Gantt chart of the
at least one medical procedure during the first time period (see
generally, FIGS. 11 and 12, showing Gantt charts of medical
procedures in a particular medical treatment suite during a typical
Tuesday and Friday, respectively).
[0069] According to other method embodiments, the display step 510
may also comprise generating a text and/or numerical display of one
or more forecast factors that may be generated according to step
230 in various method embodiments of the present invention. For
example, the forecast factor displayed to the user as part of step
510 may comprise a numerical indication of a forecast medical
procedure volume (in man hours, for a selected second time period
corresponding to a first time period for which billing data
indicating medical procedure volume may be available).
[0070] FIG. 6 shows another alternate method embodiment of the
present invention comprise step 610 for interrogating a conversion
module 13 (which may be in communication with a forecast module 12
via a computer network 14) prior to step 220 for converting data
within the retrieved billing data set (see step 210) into a
utilization data set that may be indicative of historical demand
for a given medical resource at a selected medical facility during
a first time period (which may be comparable to a second time
period for which a medical resource schedule is yet to be
developed). The interrogating step 610 may comprise, in some method
embodiments, interrogating a conversion module 13 (see FIG. 1)
comprising data and corresponding utilization information so as to
convert the data within the billing data set into a utilization
data set comprising the utilization information corresponding to a
historical demand for the at least one medical resource in the at
least one medical facility during the first time period.
[0071] As discussed above with respect to the various system
embodiments of the present invention, the forecast module 12 may
interrogate a conversion module 13 so as to be capable of
converting the data within the billing data set into a utilization
data set comprising utilization information corresponding to a
historical demand for the medical resource. In other embodiments,
the forecast module 12 may access conversion data and/or a
conversion key stored in a memory device 22 that may be provided as
part of a computer system hosting the forecasting module 12. For
example, medical billing data retrieved from some medical billing
systems may not include identifiers for specific types of medical
procedures and may instead indicate only a start time and/or
duration of a given medical procedure within an anesthesiology
practice. In such cases, the forecast module 12 may interrogate one
or more of a conversion module 13 and/or a conversion key stored in
a memory device 22 in order to convert duration information into,
for example, a procedure and/or medical service type.
[0072] Finally, as shown in FIG. 7, some method embodiments of the
present invention may also comprise step 710 for receiving a user
input comprising a selection of the forecast factor. For example,
as shown generally in FIG. 13, various embodiments of the present
invention may generate a user input display 800 for receiving a
user input that may comprise one or more selections for tailoring
one or more parameters of the forecast factor to a specific
information requirement of the user. For example, as shown in FIG.
13, the user may in some embodiments, input a selection of various
forecast factor parameters prior to the performance of steps
210-230 for determining a forecast factor. Such input parameters
may include, but are not limited to: a medical procedure/activity
type 1310; a medical resource (staff) type 1320; general staff type
1330 (i.e. non-medical and/or administrative staff); a medical
staff number in include in the forecast factor determination 1340;
a medical staff number to exclude from the forecast factor
determination 1350; a payer class (insurance company, for example)
1360; a payer class to exclude from the forecast factor
determination 1370; a location code (corresponding to a selected
medical facility, for example) 1380; a location code to exclude
from the forecast factor determination 1390; a procedure code
(corresponding to a medical procedure type to be included in the
forecast factor determination. Thus, as shown generally in FIG. 13,
some method embodiments of the present invention may allow the user
to selectively modify the parameters of the forecast factor
determination in order to change the focus of the forecast factor
determination of step 230.
[0073] In addition to providing apparatus and methods, the present
invention also provides computer program products for performing
the operations described above. The computer program products have
a computer readable storage medium having computer readable program
code means embodied in the medium. With reference to FIG. 1, the
computer readable storage medium may be part of the storage device
22, not shown, and may implement the computer readable program code
means to perform the above discussed operations.
[0074] In this regard, FIGS. 2-7 are block diagram illustrations of
methods, systems and program products according to the invention.
It will be understood that each block or step of the block diagram
and combinations of blocks in the block diagram can be implemented
by computer program instructions. These computer program
instructions may be loaded onto a computer or other programmable
apparatus to produce a machine, such that the instructions which
execute on the computer or other programmable apparatus create
means for implementing the functions specified in the block
diagram, flowchart or control flow block(s) or step(s). These
computer program instructions may also be stored in a
computer-readable memory that can direct a computer or other
programmable 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 which
implement the function specified in the block diagram, flowchart or
control flow block(s) or step(s). The computer program instructions
may also be loaded onto a computer or other programmable 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 which execute on the
computer or other programmable apparatus provide steps for
implementing the functions specified in the block diagram,
flowchart or control flow block(s) or step(s).
[0075] Accordingly, blocks or steps of the block diagram, flowchart
or control flow 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 or step of the block diagram, flowchart or control
flow illustrations, and combinations of blocks or steps in the
block diagram, flowchart or control flow illustrations, can be
implemented by special purpose hardware-based computer systems
which perform the specified functions or steps, or combinations of
special purpose hardware and computer instructions.
[0076] Many modifications and other embodiments of the inventions
set forth herein will come to mind to one skilled in the art to
which these inventions pertain having the benefit of the teachings
presented in the foregoing descriptions and the associated
drawings. Therefore, it is to be understood that the inventions are
not to be limited to the specific embodiments disclosed and that
modifications and other embodiments are intended to be included
within the scope of the appended claims. Although specific terms
are employed herein, they are used in a generic and descriptive
sense only and not for purposes of limitation.
* * * * *