U.S. patent application number 13/613928 was filed with the patent office on 2013-02-14 for method and apparatus for analyzing patient medical records.
This patent application is currently assigned to Nuance Communications, Inc.. The applicant listed for this patent is Meir Gottlieb, Sheldon H. Gottlieb, Gabriel Weise. Invention is credited to Meir Gottlieb, Sheldon H. Gottlieb, Gabriel Weise.
Application Number | 20130041682 13/613928 |
Document ID | / |
Family ID | 32926545 |
Filed Date | 2013-02-14 |
United States Patent
Application |
20130041682 |
Kind Code |
A1 |
Gottlieb; Meir ; et
al. |
February 14, 2013 |
METHOD AND APPARATUS FOR ANALYZING PATIENT MEDICAL RECORDS
Abstract
A medical form is marked by a clinician during a
patient/clinician encounter to generate a record with information
related to a current complaint. The form is partitioned into
several regions related to patient history, examination and medical
decision, respectively. The form is automatically analyzed and
using the locations of the marks on the form and a predetermined
set of rules, a billing code is generated. The billing code
determines the fee to be paid to the clinician or health
provider.
Inventors: |
Gottlieb; Meir; (Baltimore,
MD) ; Gottlieb; Sheldon H.; (Baltimore, MD) ;
Weise; Gabriel; (Baltimore, MD) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Gottlieb; Meir
Gottlieb; Sheldon H.
Weise; Gabriel |
Baltimore
Baltimore
Baltimore |
MD
MD
MD |
US
US
US |
|
|
Assignee: |
Nuance Communications, Inc.
Burlington
MA
|
Family ID: |
32926545 |
Appl. No.: |
13/613928 |
Filed: |
September 13, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
10378748 |
Mar 4, 2003 |
8326653 |
|
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13613928 |
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Current U.S.
Class: |
705/2 |
Current CPC
Class: |
G16H 10/20 20180101;
G16H 15/00 20180101; G16H 10/60 20180101; G06Q 40/02 20130101; G06Q
10/10 20130101 |
Class at
Publication: |
705/2 |
International
Class: |
G06Q 50/24 20120101
G06Q050/24 |
Claims
1. A method of analyzing a prepopulated form having regions, with
markings in some of said regions, comprising the steps of:
detecting markings within each region to determine a number of said
markings and the positions of the markings within the regions;
applying a set of predetermined rules to the detected markings; and
generating a code based on said rules.
2. The method of generating a billing code associated with an
encounter record on a form, said form having regions partitioned
into one or more subdivisions, said method comprising: detecting
the locations of markings in each said subdivisions; determining a
plurality of parameters based on a preselected set of rules and
said locations; and selecting a billing code based on said
plurality of parameters.
3. The method of claim 2 wherein said regions include a history
region, an examination region and a medical decision region, with
one parameter of said plurality of parameters being assigned to
each of said regions.
4. The method of claim 3 wherein at least one subdivision includes
a plurality of areas for receiving markings, further comprising
counting the number of areas with markings.
5. The method of claim 2 further comprising scanning said form to
generate an electronic version.
6. The method of claim 5 wherein said step of detecting said
locations includes analyzing said electronic version.
7. The method of claim 2 wherein each said region is associated
with an activity associated with a patient/clinician encounter, and
wherein said parameters for each said region is determined based on
a complexity and number of tasks performed by the clinician during
said patient/clinician encounter.
8. An apparatus for generating a medical billing code from a
populated form resulting from a patient/clinician encounter,
comprising: a detector adapted to detect the locations of marks on
said form, within predetermined regions defined thereon; and an
analyzer adapted to analyze said locations and to generate a
medical billing code based on said locations and a predetermined
set of rules.
9. The apparatus of claim 8 wherein said form is hard-copy form and
said detector includes a scanner that scans said hard-copy
form.
10. The apparatus of claim 7 wherein said detector includes an
electronic data collection device adapted to generate an image of
said form and wherein said tablet PC is adapted to detect markings
entered on said electronic data collection device.
11. The apparatus of claim 10 wherein said electronic data
collection device is a tablet PC.
Description
RELATED APPLICATIONS
[0001] None
BACKGROUND OF THE INVENTION
[0002] a. Field of Invention
[0003] This invention pertains to a method and apparatus for
reviewing, preferably automatically, patient medical records, and
to generate a characteristic code for each record that is related
to the health of the patient and to medical services provided by a
clinician for the patient during a particular encounter. The method
and apparatus is particularly useful for generating codes for
generating bills to the patient or for a third party, such as a
governmental or private health insurance organization.
[0004] b. Description of the Prior Art
[0005] In this application, the term `encounter` is used to refer
to any event between a patient and a clinician associated with the
health of a patient. Thus, an encounter may occur at a clinician's
office, in the emergency room of a hospital, at a normal bed in the
hospital, in an ICU unit, etc. It is well established that any
encounter must be memorialized in a corresponding medical record.
These records are very important for every person and organization
involved, including the patient, the clinician, the facility (e.g.,
hospital) where the encounter occurs, insurance companies, health
organizations and so on. The record provides the clinician with
information for providing immediate, as well as future care for the
patient; it provides information for other clinicians in a simple
and effective mater to insure consistence and continuity and to
avoid duplication during subsequent encounters; it provides
information useful for monitoring the performance of the clinician
and/or health facility; it provides information that can be
collected from several locations for statistical analyses used in
research and education.
[0006] Importantly, the record is the source used to generate
billing and to support claims review. The services requiring
medical records are generally referred to as Evaluation and
Management (or E/M) Services.
[0007] The content of medical records has been studied extensively,
and has been the subject of guidelines promulgated by several
organizations, including the AMA and the CMS (Center for Medicare
and Medicaid Services). For instance, the `1995 Documentation
Guidelines for Evaluation & Management services` (`Guidelines`)
is promulgated by the CMS and widely used throughout the United
States. The actual form of the record may vary from one hospital to
another and even from one department to another, within the same
hospital; however, as promulgated by the guidelines, a typical
record must include a description of the history of the patient,
the examination performed by the clinician, and the medical
decision reached by the clinician. Each of these components may
include a number of topics and subtopics, depending on the illness
of the patient and the severity of the illness.
[0008] Importantly, CMS also publishes a set of regulations that
defines a payment scale to the clinician based on the record. These
regulations must be used by any entity applying to the CMS for a
payment. The same or similar regulations may be used by other
health insurance organizations.
[0009] Thus the use of a comprehensive and standardized record has
become not only desirable, but mandatory in the field of health
care. Typically, the record is generated by the clinician by
filling out a standardized form. This form may be several pages
long. Ideally, the clinician, or his assistant, can fill in the
form during or immediately after the encounter. Alternatively, the
clinician dictates the required information, and the record is
generated from the transcribed information. In real life, the
generation of the record is delayed by several days or even weeks.
Once the record is generated, it is stored and/or disseminated as
required.
[0010] As discussed above, one important function of the record is
to provide information that may be used for the generation of the
bills. More specifically, the record itself must be used to
generate billing code which then determines how much the clinician
or the health care facility gets paid by an insurance organization.
In addition, the record must be preserved to provide backup for the
bills in case of an audit. In most instances the rules or
regulations governing billing of health insurers and other
organizations, such as Medicare and Medicaid, are very complicated,
and they are related to the level of complexity of the services
provided for each component of the report. Therefore, the clinician
or his assistant may make an educated guess at what the code should
be. This approach is not very productive because, if the wrong code
is used, the amount paid by the insurance organization is either
too high, and the clinician may be liable for a penalty, or too
low, and therefore unprofitable.
[0011] Large organizations may employ special personnel whose
function is to review each record and generate therefrom the
appropriate billing code. This approach is expensive, and since the
personnel has no medical training, mistakes can be made anyway.
[0012] It has also been suggested that billing codes be generated
using special computer programs, for example from Medinotes
Corporation. However, these programs are always menu or template
driven and require a long time to fill out, time that the clinician
does not have. Moreover, data entry is performed on a keyboard, and
most clinicians do not want to rely on keyboards. Finally, the
programs are very complicated and require long and intensive
training periods. One such system is disclosed in U.S. Pat. No.
5,483,443, incorporated herein by reference.
OBJECTIVES AND SUMMARY OF THE INVENTION
[0013] In view of the above disadvantages of the prior art, it is
an objective of the present invention to provide an easy, simple,
and user-friendly method and apparatus of generating billing
codes.
[0014] A further objective is to provide a method and apparatus
capable of analyzing a record in an existing media or format and to
generate a report or other output associated with and descriptive
of the record.
[0015] Yet another objective is to provide a method and apparatus
that is flexible so that it can be modified quickly and easily to
records having new and unusual formats.
[0016] Other objectives and advantages of the invention shall
become apparent from the following description.
[0017] Briefly, for every encounter between a patient and a
clinician, a record is generated by the clinician with information
associated with the patient's current complaint. The information is
normally stored on a pre-printed form with regions associated with
the various phases of the encounter, including patient history,
physical examination and medical decision. Each region includes
several subdivisions. The clinician enters markings (which may
consist of Xs, checkmarks, alphanumeric text, etc.) on the form.
The form can be generated electronically on an electronic device
such as tablet PC or a hand-held device, and the clinician can
enter his marks (and thereby populate the form) directly on the
electronic device
[0018] According to this invention, in order to generate a billing
code, the form is electronically scanned to detect the location of
the markings within each region. Then a set of predetermined rules
is used on the markings to generate a billing code. More
particularly, a parameter is derived for each region, based on, for
example, the number of markings, or rows with markings that the
clinician used. The billing code is then determined from these
parameters. The billing code is then forwarded to a medical
insurance company which uses a preset scale to determine the fee
paid to the clinician or associated health care provided.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] FIG. 1 shows a somewhat abbreviated form used to generate a
record of a patient encounter;
[0020] FIG. 2 shows a flow chart of the method used in accordance
with this invention to generate a desired output, such as a billing
code using information from the form of FIG. 1;
[0021] FIG. 3 shows a schematic diagram of a system used for
implementing the method;
[0022] FIG. 4 shows a flow chart for determining the history
parameter.
DETAILED DESCRIPTION OF THE INVENTION
[0023] FIG. 1 shows a form used by a clinician to document an
encounter with a patient. For the sake of simplicity, the form has
been abbreviated, it being understood that in actuality, more
comprehensive forms are used. As promulgated by the AMA, a typical
encounter between a clinician and a patient consists of three
phases: establishing the history, performing an examination and
making a medical decision. The purpose of the form shown in FIG. 1
is to enable the clinician to capture information associated with
each of these phases, thereby generating the record for the
encounter. Once this record has been completed, it can be stored
for future review, disseminated to other clinician as necessary,
used to generate a billing code, etc. The regulations promulgated
by the CMS and other organizations, require that the billing codes
be related to each phase of the record generating process, as
described in detail below.
[0024] Therefore, the form of FIG. 1 is considered to have four
areas; ID, H, E and MD. The area ID includes patient information
such as name, address, physician, ID number, etc. Area H is
dedicated to information related to patient history. Area E is
dedicated to information related to the physical examination of the
patient and area MD is related to the medical decision.
[0025] Each of the last three areas are broken down into
subdivisions. The number and physical size of these subdivisions
can vary depending on a large number of factors including the type
of the patient's illness, internal policies of the clinician and/or
associated health care organization etc. For example, the history
area H is normally partitioned into four subdivisions: current (or
chief) complaint, history of present illness (HPI), review of
systems (ROS) and past, family and/or social history (PFSH).
[0026] The examination area E is partitioned into subdivisions
covering the major organs of the body, as shown.
[0027] Finally, at the end of the encounter, the clinician makes a
medical decision for treating the patient. This decision can be
classified as hold (i.e. do nothing), recommend surgical
intervention, recommend drug treatment, or recommend further
diagnostic testing.
[0028] The form provided to the clinician is preprinted with
legends that identify the various areas and their subdivisions.
Blank boxes or rows are then provided in which the clinician enters
the requested information, if any. Some entries may consist simply
of check marks, X's etc., while other entries may consist of
written words and sentences.
[0029] It is important to note that, within each area, the amount
of information entered by the clinician and the number of
subdivisions within each zone in which he enters the information is
directly related to the amount of effort he has to spend in order
to complete the record, and, accordingly, it bears a direct
relation to the billing code.
[0030] The process for generating a billing code is described
generally in the flow chart of FIG. 2 while FIG. 3 shows a system
20 for implementing the process. In step 100 the clinician obtains
a form, such as the one shown in FIG. 1, and populates it during
the encounter. As discussed above, this process includes asking the
patient questions, performing a physical examination, considering
available data such lab and test results and then making a medical
decision. If the form is provided on paper, then this step is
performed by writing on the form with a pen or a pencil, and when
completed the form is scanned using the scanner 22 in FIG. 3. In
step 102 data corresponding to the scanned form is acquired.
[0031] In FIG. 2 step 104 a set of preliminary tests is performed
by the pretester 24 to insure that the form has been filled out
properly and that the patient has been correctly identified. For
example, the pretester 24 may determine that at least one zone in
each area of the form has been marked. The pretester 24 may also be
determine if the patient has been correctly identified. For this
purpose a bar code strip may be affixed to the ID zone.
Alternatively, patient ID information may be typed in initially,
and then the pretester 24 may use an OCR scheme to convert the
markings in the ID zone to obtain the patient information found in
the zone. The pretester 24 then accesses a patient data bank and
compares the patient ID as recorded on zone ID with information
from the patient data bank. If there is a discrepancy, the form may
be rejected or a message may be generated to identify the
problem.
[0032] In step 106 the pretester 24 makes a determination whether
the process should continue or the form should be rejected.
[0033] If the process continues, then in step 108, the data from
the scanner 22 is passed to a zone detector 28. This zone detector
identifies the critical zones on the form and the various
subdivisions in each zone and generates an indication of which of
the respective subdivisions has any markings at all. This
information is passed on to a processor 30. In step 11 the
processor 30 accesses the applicable rules for billing codes. This
rules are stored in a memory 32. The processor then applies the
rules to the data received from the zone detector 28 and then
generates an output in step 112, preferably in the form of a
billing code. This output may be displayed on a screen, printed, or
transmitted directly to an automated billing system.
[0034] Several different schemes may be used to recognize whether
the clinician has made any entries into a critical zone, or not.
For example, the form may be printed using ink of one color, and
the clinician can use an ink of a different color to make his
entries. The zone detector 28 can then perform an analysis which
critical zones have been marked with the designated color.
[0035] Alternatively, a computer operator can fill out a computer
based form (via a thick application or a web page), selecting the
zones in which there were entries. A computer program on processor
30 can then perform an analysis of the scanned-in data and
correlate the scanned-in data with an internal model of the form
via a combination of well known machine vision (edge detection,
huff transforms, snakes for stroke detection, etc) techniques to
determine which data were inputted into which zone.
[0036] It is believed that initially most clinicians will prefer to
mark up the forms manually. However, eventually, they may find it
more advantageous to use some form of automated data acquisition,
such as a tablet PC. In this latter case, in the system 20, the
scanner 22 is replaced by the tablet PC which automatically
generates in INK format or other similar formats an indication of
what information has been entered by the clinician and on what part
of the form. (An electronic version of the form is displayed by the
PC tablet). This electronic data is then analyzed by the zone
detector 30 to determine which critical zones have been used by the
clinician to generate the record. In this embodiment, the PC tablet
controls that store the "Ink" can prevent the user from performing
a single stroke that crosses the boundary between zones, resulting
in absolute knowledge of which zones have been used.
[0037] Alternatively, on a tablet PC, the user can be allowed to
write anywhere on the form using ink, and then the application can
compare what areas were written in predefined regions of the form.
For example, if the form was represented in pixels on the screen,
the processor could know where the fields are based on rectangles
defined by the upper left hand corner and the lower right hand
corner in pixels. For example Field 1 might be defined as (1,1) to
(100,20) and Field 2 might be defined as (1,22) to (100,42). The
processor could then use the Ink ActiveX controls provided by
Microsoft to determine in which fields entries were made by the
user.
[0038] In FIG. 3, the pretester 24 and zone detector 28 are shown
as separate and distinct elements for the sake of clarity. However
it should be understood that the functions of these elements may be
performed by software on the processor 30. Moreover, if a PC tablet
is used, its processor may be used to perform either some, or all
of the functions of the pretester 24, the zone detector 28 and even
the processor 30.
[0039] Once the processor 30 analyzes the various zones and
subdivisions of the record, it then determines the billing code in
accordance with the rules stored in memory 32. Some typical rules
for generating billing codes shall now be described, it being
understood that the invention is not limited to these rules but is
applicable to other rules as well.
[0040] The commonly used `1995 Documentation Guidelines for
Evaluation & Management Services` provide several
classifications for each of the three phases of a patient
encounter. History is provided with four classifications that are
dependent on the following factors: History of Present Illness
(HPI), Review of Systems (ROS) and past, family and social history
(PFSH). The four classifications are defined as follows:
TABLE-US-00001 HPI ROS PFSH CLASSIFICATION Brief n/a n/a PROBLEM
FOCUSED Brief Problem Pertinent n/a EXPANDED PROBLEM FOCUSED
Extended Extended Pertinent DETAILED Extended Complete Complete
COMPREHENSIVE
[0041] Typical forms include several HPI rows for entering
information characterizing the present complaint, such as location,
quality, severity, duration, timing, context, modifying factors,
signs and symptoms, and so on. The number of such rows can be
anywhere from 0 to 8. The difference between Brief and Extended HPI
is dependent on the amount of detail required to define the
respective clinical problems, or in terms of the actual forms, the
number of rows on which information has been entered. In the
present invention, the HPI factor is determined by the number of
rows that have entries. For example, if a form has a total of 8
entries (on 8 respective rows), the number of rows is counted and
if this number is less than a predetermined number (for example 4)
then the HPI factor is designated as being `Brief`. Otherwise the
HPI factor is designated as being `Extended`.
[0042] Similarly, a typical form has a number of entries or rows
for the ROS factor. A typical form may have fourteen such rows.
Again, to determine the ROS factor, in the present invention the
number of rows with entries is counted. Typically, for up to 3
entries the ROS factor is designated as `Problem Pertinent`, for
between 4 and 9 entries the ROS factor is designated as `Extended`
and 10 or more entries are designated `Complete.`
[0043] Finally, typically three or more rows are dedicated for
PFSH, covering respectively, past medical history, family medical
history and social history. The number of entries are counted and
at least one entry is designated as pertinent and two or more
entries are designated as `Complete.`
[0044] Thus, for the form of FIG. 1 the decision for determining
the type of history is performed as illustrated in FIG. 4 and is
reduced to counting the number of rows in each subdivision of zone
H. In steps 200, 202 and 204 the number of entries for rows in each
of the subdivisions HPI, ROS and PFSH is counted.
[0045] Generally speaking, the History parameter can be determined
by looking at the number of elements or rows completed for the HPI,
ROS, and PFSH subdivisions and then applying the relevant rules to
these numbers. All the rules are based on minimums. The process
starts by looking at the minimum requirements for the highest level
of History classification. If these requirements are met, the
History parameter is set and the process for determining this
parameter is complete. If the requirements for the highest history
classification are not met, the level below it is examined. The
levels are defined in descending order as: Comprehensive, Detailed,
Expanded Problem Focused, Problem Focused, and No History.
[0046] More specifically, as indicated in FIG. 4, the following
steps are first performed to calculate the history parameter: Step
200--count the number of rows in the HPI subdivision. Step
202--count the number of rows in the ROS subdivision. Step
204--count the number of rows in the PFSH subdivision. Step
206--check if there is at least 4 elements or rows in the HPI
subdivision, at least 10 elements in the ROS, at least 2 elements
in the PFSH. If so, classify the history as comprehensive. Step
208--check if there is at least 4 elements in the HPI, at least 4
elements in the ROS, at least 1 element in the PFSH. If so,
classify the History parameter as detailed. Step 210--check if
there is at least 1 Element in the HPI, and at least 1 element in
the ROS. If so, classify the history parameter as expanded problem
focused. Step 212--check if there is at least 1 HPI, If so,
classify the history parameter as problem focused. If none of these
criteria are met, then a `no history` classification is set.
[0047] Alternatively, the determination of the history
classification is reversed. First a test is performed for the
lowest classification, then the next higher classification, and so
on.
[0048] The examination zone E is analyzed using the same general
principles. The examination is divided into five levels (from
highest to lowest): Comprehensive, Detailed, Expanded Problem
Focused, Problem Focused, and No Exam. The level of the Exam is
based on the number of body areas or organ systems examined and the
completeness of the examination of those body areas or organ
systems. Zone E in the form is divided into regions and sub
regions. Exam regions include (but are not limited to):
Constitutional, Eyes, Head/Mouth/Teeth, Chest, Cardiovascular, GI,
MSK, GU, Derm, Neuro, Psych, and Blood/Lymph. These regions are
then divided into sub regions. For example, the section for
Cardiovascular is further divided into regions for all the various
measurements and pulse readings that a Cardiologist would measure
during a cardiovascular exam. The number of regions determines the
number of organ systems examined. The number of sub-regions
completed for a body area or organ system determines the extent of
the examination of that body area or organ system. For each type of
region (Eyes, Chest, etc.) there are a 2 thresholds defined to
determine 3 levels: Brief<=T1<Detailed<=T2<Complete. If
the number of sub-regions written in for a region is less that or
equal to T1, then the Exam of that region is Brief. If the number
of sub-regions written in is >T1 and <=T2, then the exam of
that region is Detailed. If the number of sub-regions written in is
>T2 then the exam of that region is complete. These two
thresholds are defined for each body area/organ system.
Furthermore, the division into sub-regions of the regions of an
organ system/body area can be tailored or the situation that the
form will be used in. For example, a cardiologist might have the
cardiovascular regions subdivided more than an Ophthalmologist,
while the Ophthalmologist would more likely have the Eyes region
broken down into more sub regions. However, in the case of General
Medicine, it is possible that all body areas/organ systems are
divided into many sub regions. The choice to not subdivide regions
would be for specialties where it is unlikely that they would
perform a comprehensive exam of a particular body area/organ
system.
[0049] To determine the level of the examination parameter, the
process starts looking for the highest level. If the criteria is
met, the E classification is set at that level. Otherwise the next
level of the exam is checked. For each region (corresponding to a
single body area/organ system) in the Exam, the region is
classified as Brief. Detailed, or Completed based on the threshold
system described above.
[0050] If there is a Complete examination of a single region, then
exam is considered Comprehensive. If at least 8 regions are Brief,
the exam would also be considered Comprehensive.
[0051] If at least 2-7 regions were Detailed, the Exam would be
considered Detailed. If at least 2-7 regions were Brief, the exam
would be recorded Expanded Problem Focused.
[0052] If at least one regions was Brief the exam is recorded as
Problem Focused. (7) Otherwise, the Exam is marked as No Exam.
[0053] The last parameter to be considered is the medical decision.
This parameter is dependent on four factors: the number of
diagnoses or management options applicable to the respective chief
complaint, the amount and complexity of the data reviewed by the
clinician to make his decision and the risk of complication or
morbidity. The four classifications for this parameter and their
definition is as follows:
TABLE-US-00002 NUMBER OF AMOUNT RISK OF DECISION DIAG. OPTIONS OF
DATA COMPLICATION MAKING Minimal Minimal Minimal STRAIGHT- FORWARD
Limited Limited Low LOW COMPLEXITY Multiple Moderate Moderate MOD.
COMPLEXITY Extensive Extensive High HIGH COMPLEXITY
[0054] It has been suggested that a point system be used for
determining the values of the first two factors. More specifically,
the following table illustrates a point system for the first
factor:
TABLE-US-00003 CURRENT VALUE COMPLAINT ASSIGNED POINTS SUBTOTAL
Old- XXX 1 X Self- XXX 1 X limited/minor 2(max) Old- XXX 2 X
Stable/improved Old- X worsening 3 XXX 4 X New-no 1 X additional
work New- 1 X followup planned TOTAL T1
[0055] The points are determined based on fields completed in the
form. In the form there is space for multiple problems. For each
problem there is space for the provider to indicate whether the
problem is a new problem or an established problem, and whether the
problem is getting worse, stable, getting better, or
self-limited/minor. Additionally there is space on the form to
indicate the treatment plan for the problem. Alternatively, the
treatment plan could be determined from other parts of the form
indicating orders (such as medication, tests, or surgery). When the
form is scanned, based on the boxes filled in, the processor
classifies the problem as one of the 5 rows illustrated above and
assigns the appropriate number of points. The points are then
tallied across all the problems.
[0056] In order to determine the amount and complexity of data to
be reviewed, the form is scanned to determine what other
information he clinician has reviewed or ordered, or other actions
taken by the clinician as part of the encounter. For example, as
part of an encounter, the clinician may receive various test
results based on tests conducted prior to the encounter. The
clinician reviews the tests, and marks on the form the test results
that he thinks are pertinent. More specifically, many forms include
a subdivision (shown in FIG. 1 in the history area H) with a
plurality of rows, each row indicating a test (e.g. lab tests,
including blood tests, urine tests, etc., radiology tests,
catscans, etc.). The clinician enters a notation on the rows
corresponding to the tests that he has reviewed. Conversely, if
insufficient information is available, the clinician orders some
tests. This request is entered on the form in the MD area.
[0057] In some instances, the clinician may decide to consult with
another clinician who has seen the patient, has performed one or
more of the tests, or for some other reason. A subdivision is
provided on the form, for example in the history area H, as shown,
providing a row for each such discussion.
[0058] Other activities that the clinician may take include
ordering old history and records, performing additional independent
review of the specimen etc. These additional activities are also
noted on the form.
[0059] As discussed above, during processing, the form is reviewed
by essentially counting all the relevant rows on which entries for
the various activities are marked. Some activities, such as the
independent review of specimen, may be more labor intensive and so,
during counting of the rows, a weighting system can be used so that
entries in certain rows are accorded more relevance then entries
from other rows. Once these rows are counted, a value is assigned
to data complexity factor.
[0060] Next, the risk of complication is classified. Many
complaints are associated with well known levels of complications
and therefore can be readily classified by the clinician. An
appropriate row can be provided for this purpose, for example as
part of the current complaint subdivision.
[0061] For other encounters, the risk of complications is
classified from other information readily available from the
record. For example, as part of history, the clinician requests
information about the medication that the patient is taking and/or
surgery or other procedures that have been performed. The clinician
records this information by marking the appropriate rows of the
drugs and surgery subdivisions, respectively. Moreover, the
clinician can also recommend surgical intervention and/or drugs by
marking the relevant subdivisions of the MD area. It is well known
in the medical field that taking certain drugs or performing
certain types of surgeries and other procedure are associated with
certain risks of complications. The types of tests either performed
prior to the encounter (and marked in the history area H) or
ordered by the clinician (and marked in the MD area) are also
indicative of the level of risks of complication. The form has
space for tests that are pre-classified for Risk. For example, for
a form used by Cardiology, there would be space on the form for
information about Cardiac Catheterization, Electrophysiology (such
as temporary pacing), EKG, Stress test, etc. If the clinician
marked that he/she ordered a Cardiac Catheterization, the risk
would be marked as Moderate.
[0062] Additionally the level of risk is dependent on the
presenting problems. The provider can be asked to classify
problems, self-limited/minor, stable chronic, acute uncomplicated,
acute complicated, life-threatening. Based on the classification of
the problem and the number of problems, the level of risk can be
determined. For example, a single life-threatening problem such as
an acute myocardial infarction is considered High Risk.
Alternatively, possible problems can be listed on the sheet and
circled by the clinician. In this way, the problem can be
pre-classified to determine level of risk. This option in most
attractive for specialties where there is a limited number of
problems that the clinician is considering. A hybrid approach could
be used where problems are listed and pre-classified, but the
clinician is asked to classify problems that are not listed. This
way the clinician simply circles the appropriate problem the
majority of the time, but can easily write-in problems that are not
on the list.
[0063] Preferably the level of risk of complication is determined
either directly by the clinician, or is determined indirectly by
reviewing the record for certain predetermined drugs, surgical (or
other procedures) and tests.
[0064] As can be seen from the above discussion, the information
required to classify each phase of an encounter in most cases
readily available from the record. In some cases additional
subdivisions may have to be added to the standard form to insure
that all the information required to classify each phase is
properly entered. As an alternate, and possibly intermediate
solution, some of the information can be obtained from additional
sources. For example, if at the end of the encounter the clinician
orders some additional tests to be taken and/or prescribes some
medicine to the patient using some additional forms, these forms
can be intercepted and reviewed as well, in the same manner as the
record, to gather the additional required information.
[0065] Once the three phrases are properly classified, a billing
code is readily generated by the processor in steps 110 and 112 of
FIG. 2. Some typical billing codes are defined by the AMA as
follows:
TABLE-US-00004 HISTORY EXAM MED DECISION CODE problem focused
Problem focused straightforward 99201 expanded expanded
straightforward 99202 problem focused problem focused detailed
detailed low complexity 99203 comp. comprehensive mod. complexity
99204 comp. comprehensive high complexity 99205
[0066] To summarize, every encounter between a clinician and a
patient must result in a record on a standardized form. The present
invention analyzes the record to determine what part of the form
has been marked by the clinician as part of generating the record.
This information is then used to classify each phase of the
encounter. Finally this classification is used to generate an
appropriate billing code. Of course, it should be understood that
the process may be used for additional purposes as well.
[0067] As described above, the process for generating a billing
code involves detecting markings on a predetermined form and based
on the number and location of the markings on the form, generating
the code using a set of predetermined rules. However, it should be
appreciated that the process is transparent to the actual content
of the form.
[0068] While the invention has been described with reference to
several particular embodiments, it is to be understood that these
embodiments are merely illustrative of the principles of the
invention. Accordingly, the embodiments described in particular
should be considered as exemplary, not limiting, with respect to
the following claims.
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