U.S. patent application number 11/326249 was filed with the patent office on 2006-07-13 for method and structure for mitigating instrumentation differences.
Invention is credited to John C. Yundt-Pacheco.
Application Number | 20060155487 11/326249 |
Document ID | / |
Family ID | 32094255 |
Filed Date | 2006-07-13 |
United States Patent
Application |
20060155487 |
Kind Code |
A1 |
Yundt-Pacheco; John C. |
July 13, 2006 |
Method and structure for mitigating instrumentation differences
Abstract
A method and system for mitigating instrumentation differences
in laboratory instruments. The system of the present invention
includes one or more groups of laboratory instruments in
communication with a normalization server via a network. Each group
of laboratory instruments communicates instrument control specimen
and testing specimen output data to the normalization server via a
variety of communication methods. Once the normalization server
receives the control specimen data it generates a normalization
curve for the instrument according to a control group. Accordingly,
the normalization server then maps the testing specimen data
according to the normalization curve The normalization server then
outputs the normalized outputs to the groups. In a first
embodiment, a external quality control output from the group is
sent to the normalization server for the purpose of mapping the
outputs to a larger peer output control group. In another
embodiment, a patient sample output from a group of laboratory
instruments is normalized with a previous patient sample test to
allow a progression analysis of the patient. The present invention
allows for the mitigation of instrumentation differences in the
outputs from one or more groups of laboratory equipment to allow
for better data manipulation.
Inventors: |
Yundt-Pacheco; John C.;
(Fairview, TX) |
Correspondence
Address: |
STINSON MORRISON HECKER LLP;ATTN: PATENT GROUP
1201 WALNUT STREET, SUITE 2800
KANSAS CITY
MO
64106-2150
US
|
Family ID: |
32094255 |
Appl. No.: |
11/326249 |
Filed: |
January 5, 2006 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
09519224 |
Mar 6, 2000 |
7010448 |
|
|
11326249 |
Jan 5, 2006 |
|
|
|
Current U.S.
Class: |
702/32 |
Current CPC
Class: |
Y10T 436/114998
20150115; G01D 18/00 20130101; G16H 40/40 20180101 |
Class at
Publication: |
702/032 |
International
Class: |
G06F 19/00 20060101
G06F019/00; G01N 31/00 20060101 G01N031/00 |
Claims
1. A method for modifying data from a group of laboratory
instruments, the method comprising the steps of: obtaining data
indicative of testing specimen outputs of the group of laboratory
instruments; and normalizing the data according to a control
group.
2. The method as recited in claim 1, wherein the obtaining step
includes receiving the group of laboratory instrument outputs via a
network communications link.
3. The method as recited in claim 2, wherein the network
communications link is an Internet web-site interface.
4. The method as recited in claim 1, wherein the obtaining step
includes receiving the group of laboratory instrument outputs via a
manual input.
5. The method as recited in claim 1, wherein the normalization step
includes obtaining control specimen data and generating a
normalization curve according to the control specimen data.
6. The method as recited in claim 5, wherein the normalization
curve is generated by applying a linear regression to the group of
laboratory instrumentation control specimen data.
7. The method as recited in claim 5, wherein the normalization
curve is generated by applying a nonlinear regression to the group
of laboratory instrumentation control specimen data.
8. The method as recited in claim 5, wherein the normalization
curve is generated by applying a spline to the group of laboratory
instrumentation control specimen data.
9. The method as recited in claim 5, wherein the normalization
curve is generated by applying a linear regression, a non-linear
regression, and a spline to the group of laboratory instrument
control specimen data and measuring the curve error for each
curve.
10. The method as recited in claim 9 further comprising returning
the curve with the minimum cumulative curve error as the
normalization curve.
11. The method as recited in claim 9 further comprising returning
the curve with the minimum average curve error as the normalization
curve.
12. The method as recited in claim 5, wherein the normalization
step includes mapping the testing specimen group output according
to the normalization curve.
13. The method as recited in claim 5, wherein the normalization
step includes generating a normalization curve for each laboratory
instrument in the group of laboratory instruments.
14. The method as recited in claim 1, wherein the control group
comprises data indicative of laboratory instrumentation outputs
from one or more groups of laboratory instruments.
15. The method as recited in claim 1, wherein the control group
comprises data indicative of a comparison group of laboratory
instruments.
16. The method as recited in claim 1 further comprising outputting
the normalized data.
17. The method as recited in claim 13, wherein the outputting step
includes sending the normalized data to the group of laboratory
instruments.
18. A computer-readable medium having computer-executable
instructions for performing the steps recited in claim 1.
19. A computer system having a memory, an operating system and a
central processor, the computer system operable to execute the
steps recited in claim 1.
20. A method for modifying data from two or more groups of
laboratory instruments, the method comprising the steps of:
obtaining testing specimen outputs from a first of the two or more
groups of laboratory instruments; obtaining testing specimen
outputs from a second of the two or more groups of laboratory
instruments; and normalizing the testing specimen outputs from the
first and second groups of laboratory instruments.
21. The method as recited in claim 20, wherein at least one of the
obtaining steps includes receiving data via a network
communications link.
22. The method as recited in claim 21, wherein the communications
link is an Internet web-site interface.
23. The method as recited in claim 20, wherein at least one of the
obtaining steps includes receiving data via manual input.
24. The method as recited in claim 20, wherein the normalization
step includes obtaining control specimen data from the first and
second groups of laboratory instruments and generating a
normalization curve according the control specimen data.
25. The method as recited in claim 24, wherein the normalization
curve is generated by applying a linear regression to the first and
second groups instrumentation control specimen outputs.
26. The method as recited in claim 24, wherein the normalization
curve is generated by applying a nonlinear regression to the first
and second groups of instrumentation control specimen outputs.
27. The method as recited in claim 24, wherein the normalization
curve is generated by applying a linear regression, a non-linear
regression, and a spline to the group of laboratory instrument
control specimen data and measuring the curve error for each
curve.
28. The method as recited in claim 27 further comprising returning
the curve with the minimum cumulative curve error.
29. The method as recited in claim 27 further comprising returning
the curve with the minimum average curve error.
30. The method as recited in claim 24, wherein the normalization
step includes applying a spline to the first and second groups of
instrumentation control specimen outputs.
31. The method as recited in claim 24, wherein the normalization
step includes mapping the testing group output of the first group
of laboratory instruments according to the normalization curve.
32. The method as recited in claim 24, wherein the normalization
step includes mapping the testing group of the second group of
laboratory instruments according to the normalization curve.
33. The method as recited in claim 20, wherein the normalization
step includes normalizing the first group testing specimen output
with the second group testing specimen output.
34. The method as recited in claim 20, wherein the normalization
step includes normalizing the first and second group testing
specimen outputs to a control group indicative of a peer group of
laboratory instrument outputs.
35. The method as recited in claim 20 further comprising outputting
at least one of the normalized first and second group outputs.
36. The method as recited in claim 35, wherein the outputting step
includes sending the normalized outputs to at least one of the
first and second laboratory instrument groups.
37. A computer-readable medium having computer-executable
instructions for performing the steps recited in claim 20.
38. A computer system having a memory, an operating system and a
central processor, the computer system being operable to execute
the steps recited in claim 20.
39. A method for modifying data from a group of laboratory
instruments, the method comprising the steps of: obtaining data
indicative of testing specimen outputs of the group of laboratory
instruments; and normalizing the data according to a control group,
wherein said normalizing comprises obtaining control specimen data
and generating a normalization curve according to the control
specimen data, generating a normalization curve for each laboratory
instrument in the group of laboratory instruments, and displaying
the normalized data on a network.
40. A method for modifying data from two or more groups of
laboratory instruments, the method comprising the steps of:
obtaining testing specimen outputs from a first of the two or more
groups of laboratory instruments; obtaining testing specimen
outputs from a second of the two or more groups of laboratory
instruments; normalizing the testing specimen outputs from the
first and second groups of laboratory instruments; and outputting
at least one of the normalized first and second group outputs,
wherein said outputting comprises displaying the normalized outputs
on a network.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a Continuation of U.S. patent
application Ser. No. 09/519,224, filed on Mar. 6, 2000, which is
hereby incorporated in its entirety herein by reference.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
[0002] Not Applicable.
BACKGROUND OF THE INVENTION
[0003] Generally, data outputs from a laboratory instrument testing
of a subject sample may be utilized to monitor the performance of
the instrument or to provide a comparison set of results for the
subject being tested. Specifically, the subject sample being tested
can include a standardized external quality control sample
distributed by a testing organization or an individual patient
sample to be tested and analyzed. For example, if the subject
sample is a standardized external quality control sample, the test
results from the instrument allow the laboratory to ensure that the
instrument is properly functioning by comparing the instrument data
with peer group results of the same sample. Similarly, if the
subject sample is from an individual patient, one or more tests
provide a comparison set of data to measure the progress of the
patient. With either type of subject sample, the results from the
test are critical to the operation of the testing laboratory.
Moreover, the subject testing can be conducted by one or more
instruments to form a laboratory testing group.
[0004] With regard to the testing of a external quality control
sample, a conventional method of control group testing entails
testing and directly comparing the results to a peer group becomes
deficient if the peer group is too small. For example, if a group
of laboratory instruments testing a proficiency sample includes
data from only eight instruments, the relatively small number of
instrument results do not provide an adequate peer group to
construct a proper range of expected results. Accordingly, in such
a scenario, it would be advantageous to utilize a larger peer
group, such as 400 or 500 instruments from a plurality of
laboratories, to develop a proper range of results. However, under
the conventional method, differences between the instruments, in
the form of calibration differences, statistical behavior
differences and/or test method differences, can yield differences
between the laboratory group results and the peer group results.
Thus, the conventional method of a direct comparison between the
results of the two groups could be either impossible or
erroneous.
[0005] With regard to the testing of a patient subject sample, the
conventional method of testing and directly comparing the data
results between a first and second sample can become deficient if
the patient group is mobile and there are differences between the
laboratory instruments. Specifically, a patient sample may be
tested by a first group of laboratory instruments yielding a first
set of results. If a second test is conducted by a second group of
laboratory instruments, differences between the instruments of the
two groups may cause a reviewer to believe there is a larger
discrepancy between the results then there actually is.
[0006] For example, a first test of a patient sample indicates that
the amount of a substance in the patient test sample was 100. If
the second test conducted by another laboratory group indicates
that the amount of the substance in the patient sample is 384, a
direct comparison of the two results would indicate that the
patient sample had a substantial increase in the amount of the
substance present. However, it could be possible that the actual
difference in the amount of the substance in the sample is minimal
and that large difference is due primarily to the differences (e.g.
calibration differences) between the two laboratory instrument
groups. Accordingly, the conventional method of a direct comparison
would cause an improper analysis.
[0007] Thus, there is a need for a method and device for
facilitating the comparison of laboratory group results with peer
group quality control results by mitigating differences in the
instruments. Additionally, there is a need for a method and device
allowing patient sample results to be normalized for comparison by
reducing differences between the groups.
BRIEF SUMMARY OF THE INVENTION
[0008] The present invention satisfies the above-described need by
providing a method and system for mitigating differences in
laboratory instrument outputs by the normalization of the
laboratory instrument output data in accordance with a control
group.
[0009] Generally described, the present invention provides a method
for normalizing a group of laboratory instruments. In accordance
with the method, data indicative of control specimen outputs is
obtained for the group of laboratory instruments, and the data is
normalized according to a control group.
[0010] In another aspect of the present invention, a method for
normalizing two or more groups of laboratory instruments is
provided. In accordance with the method, a first of the two or more
groups of laboratory instruments control specimen outputs is
obtained, a second of the two or more groups of laboratory
instruments control specimen outputs is obtained, and the control
specimen outputs from the first and second groups of laboratory
instruments are normalized.
[0011] In a further aspect of the present invention, a system for
normalizing groups of laboratory instruments is provided. The
system includes one or more groups of laboratory instruments and a
normalization server in communication with the groups of laboratory
instruments. Additionally, the groups of laboratory instruments
send data indicative of outputs to the normalization system and the
normalization system outputs normalized outputs to the groups of
laboratory instruments.
[0012] In yet another aspect of the present invention, a method for
standardizing instrument results from a plurality laboratory
instruments is provided. In accordance with the method, testing
specimen data is obtained from a first of a group of laboratory
instruments, the first laboratory instrument testing specimen data
is normalized according to a first normalization curve, and the
first laboratory instrument data is adjusted according to the first
normalization curve.
[0013] By normalizing the output from a laboratory group, the
present invention reduces the statistical differences between two
or more laboratory group results and allows meaningful data
analysis.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The present invention is described in detail below with
reference to the attached drawing figures, wherein:
[0015] FIG. 1 is a block diagram illustrating the interaction
between one or more groups of laboratory instruments and a
normalization server in accordance with the teachings of the
present invention;
[0016] FIG. 2 is a flow diagram of a preferred normalization setup
method implemented by a normalization server in accordance with the
present invention;
[0017] FIG. 3 is a flow diagram of a preferred normalization usage
method implemented by a normalization server in accordance with the
present invention;
[0018] FIG. 4 is a chart illustrating a comparison of output
results from a laboratory group tests and output values from a
control group;
[0019] FIG. 5 is illustrative of a line fit plot applied to the
laboratory group test output of FIG. 3; and
[0020] FIG. 6 is a chart illustrating a comparison of the output
results from a laboratory group test and output value from a
control group of FIG. 3 and the normalized laboratory group outputs
in accordance with the present invention.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENT
[0021] The present invention provides a method and device for
mitigating instrumentation differences in laboratory equipment
outputs by normalizing the output from the group of laboratory
instruments to a control group. Preferably, the present invention
is implemented in a computing environment commensurate with the
number of laboratory instruments in the system and the quantity of
data being normalized. The invention is operable with numerous
general purpose or special purpose computing system environments.
Examples of well known computing systems that may be suitable for
use with the invention include personal computers, server
computers, hand-held or lap top devices, multiprocessor systems,
network personal computers, minicomputers, and mainframe computers.
As would be readily understood by someone skilled in the art,
additional computing environments are within the scope of the
present invention.
[0022] FIG. 1 is a block diagram illustrative of the normalization
system of the present invention, designated generally by the
reference number 10. The normalization system 10 includes one or
more laboratory instrument groups 12 in communication with a
normalization server 14 via a communications network 16.
[0023] Preferably, each laboratory instrument group 12 includes a
laboratory information system (LIS) 18, which is direct
communication with one or more laboratory instruments 20. As would
be readily understood, the laboratory instrument groups 12 may be
remote from each other and from the normalization server 14.
Additionally, the laboratory instruments 20 connected to the LIS 18
may also be remote from each other and from the LIS 18. Moreover,
the laboratory instruments 20 may include identical instruments
from the same manufacturer, different instruments from the same
manufacturer, or instruments from a variety of manufacturers.
Preferably, the normalization server includes one or more computing
devices to carry out the functions of the normalization server in
accordance with the present invention.
[0024] Preferably, the network 16 includes an Internet-based
network, with the normalization server 14 linked to the groups of
laboratory instruments via a web site interface. As would be
understood, the network can include any variety and/or combination
of Local Area Networks (LAN) or Wide Area Networks (WAN) to
facilitate communication between the laboratory groups and the
normalization server. Additionally, the network 16 may include a
dedicated communications link, such as dial-up telephone modem
connection, between the groups of laboratory instruments 12 and the
normalization server 14.
[0025] FIGS. 2 and 3 are flow diagrams of a preferred normalization
method implemented by the normalization server in accordance with
the present invention. The present invention utilizes this
procedure to establish normalization curves for known ranges of
results and utilize these curves for future external quality
control testing and patient sample testing. Preferably, the
normalization method is characterized into a normalization setup
portion (FIG. 2) and a normalization usage portion (FIG. 3). The
normalization setup portion preferably entails the normalization
server receiving test control specimens outputs from one or more
groups of laboratory instruments and generating a normalization
curve for each instrument. Accordingly, the normalization usage
portion entails the normalization server receiving test data
(either external quality control data or patient sample data) and
normalizing the data according to the individual normalization
curve for the testing instrument.
[0026] FIG. 2 is a flow diagram of a preferred normalization setup
method in accordance with the present invention. As a general rule,
laboratory instrument groups must constantly test and analyze test
control specimens from external quality control organization. At
S21, the normalization server obtains outputs from one or more
groups of laboratory instruments testing control specimens.
Preferably, the normalization server can receive the laboratory
instrument outputs in a variety of manners. In a first embodiment,
the normalization server includes an Internet-based web site which
receives data from each group of laboratory instruments. In such an
embodiment, the LIS (FIG. 1) from each group communicates with the
normalization server and sends the output data from each laboratory
instrument in a manner which is formatted to facilitate
normalization. Alternatively, the web site may include a manual
input screen that allows the data to be manually entered via the
web site.
[0027] In a second embodiment, a direct communications link, such
as a telephone modem connection, is established by the LIS or the
normalization server for the purpose of transferring the output
data. Additionally, prior to sending the laboratory instrument
output data to the normalization server, the LIS may format the
data in a manner to facilitate its processing. alternatively, a
graphical interface may be established between the LIS and the
normalization server, such as an input screen, to allow the manual
entry of the output data over the communications link to the
normalization server. In a third embodiment, the output from the
laboratory instrument group may be physically sent to the
normalization server provider and entered manually via a plurality
of data input methods. As would be understood, alternative data
transfer embodiments or a combination of the above mentioned
embodiments are within the scope of the present invention.
[0028] Once the test specimen output data has been obtained by the
normalization server at S21, the normalization server calculates
and stores normalization curves for each laboratory instrument
being normalized at S22. Preferably, the normalization server
utilizes a variety of normalization methods dependant on the output
data and the type of normalization desired to construct the
normalization curve. For example, in a first embodiment the
normalization server utilizes a liner regression method to
normalize the data. In a second embodiment, the normalization
server utilizes a nonlinear regression method. In a third
embodiment, the normalization server applies a spline to normalize
the data.
[0029] Preferably, the normalization server receives the group
instrument control specimen data and the control group data for the
same control specimen and applies the variety of normalization
methods to construct numerous normalization curves. Then, the
normalization server measures the relative error between the actual
data points and the normalized curve. For example, assume data from
a group of laboratory instruments follows a generally non-linear
trend. As the data is received, the normalization server would
utilize a linear regression, a non-linear regression, a spline and
any other normalization method to map the data points as a curve.
Because the data is generally non-linear, however, it is likely
that the linear regression would have a greater curve error than
the non-linear regression curve. Generally, curve error can be
defined as the difference in values from an actual data point and
the calculated data point of the curve.
[0030] Accordingly, the normalization server would measure the
curve error for each of the generated curves and select the curve
with the least average curve error per data point. Alternatively,
the normalization server may select the curve with the least
cumulative curve error for all the data points. Moreover, the group
of laboratory instruments may also designate a default type of
normalization method irrespective of the curve error analysis. Once
a preferred normalization curve is constructed, the normalization
saves the curve for future use. As would be readily understood, the
determination by the normalization server of a best fitting curve
may utilize additional normalization methods and may utilize
additional statistical calculations (e.g. eliminating extreme data
points). All are within the scope of the present invention.
[0031] FIG. 3 is a flow diagram of a preferred normalization usage
method in accordance with the present invention. Once the
normalization setup method has been executed (FIG. 2), the
normalization server utilizes the individual curve for each
instrument to normalize output data. At S23, the normalization
server obtains outputs from one or more groups of laboratory
instruments testing specimens which can be external quality control
specimens or patient testing samples. Similar to the obtaining step
illustrated at S21, the normalization server can obtain the testing
specimen data from the laboratory instruments or LIS in a variety
of manners.
[0032] Once the testing data has been obtained at S23, the data is
normalized according to the previously stored normalization curve
for each instrument at S24. Preferably, the normalization server
recalls the calculated normalization curve and maps the inputted
data according to the preferred curve. Alternatively, the
normalization server may recall all the calculated normalization
curves, and maps the data into all the curves. Accordingly, a
determination of the best curve for the specific data points may be
selected according to curve error or user choice at that point. All
are considered within the scope of the present invention.
[0033] Once the output data has been normalized according to the
normalization curves at S24, the normalization server outputs the
normalized data to one or more groups of laboratory instruments at
S26. Dependant on the needs of each group of laboratory
instruments, the outputting step can encompass one or more methods.
In a first embodiment, the normalization server displays the
normalized output by group of laboratory instruments on a central
network for access by the specific group of laboratory instruments
or by the entire network. In a second embodiment, the normalization
server outputs the data directly via a network or a direct
communication line to the LIS (FIG. 1) of the laboratory instrument
group. In a third embodiment, the normalization server outputs the
normalized data to a memory for archiving purposes or for later
transmittal to the laboratory instrument group. Additionally, the
normalization server may utilize any combination of the outputting
embodiments to relay the outputted data in more than one
manner.
[0034] FIGS. 4-6 are charts and graphs illustrating the "mapping"
of results from a group of laboratory instruments into a control
group of results in accordance with the methods and structures of
the present invention. With reference to FIG. 4, chart 28
illustrates outputs for five specimens from a group of laboratory
instruments in a second column 30 and outputs for the same specimen
from a control group in a third column 32. As can be seen, a direct
comparison of the results from the laboratory instrument outputs
and the control group outputs yields a big discrepancy in values.
For example, the output results for specimen 1 in row 34 indicate
that the laboratory group result is "98", while the control group
result for the same specimen is "254". Accordingly, the resulting
difference between the two groups appears to be 156. Likewise, a
comparison of rows 36-42 discloses apparent differences of 103,
244, 233 and 73 respectively. Under a conventional analysis, the
results from the group 30 would be considered erroneous or
incompatible with the control group 32. However, the present
invention allows the lab group results to be rectified by a mapping
of the group of laboratory results into the control group
results.
[0035] FIG. 5 is illustrative of a line fit plot 44 applied to the
group of laboratory results (FIG. 4) to map the data into the
control group results in accordance with the present invention.
Specifically, based on the application of a linear regression
method, an equation of y=2.63x+10.4 is calculated to be a preferred
normalization curve in the normalization setup method (FIG. 2). As
illustrated in FIG. 5, the corresponding line 44 generates five
data points, 46-54, corresponding to the original laboratory group
results. For example, data point 46 corresponds to the fifth
specimen result (column 42 of FIG. 4) which is "34" on the x-axis
of the line fit plot 44. Additionally, the data point 46 indicates
the mapped value corresponding to the control group results is
"100", allowing the two groups of results to be better
compared.
[0036] FIG. 6 is a chart 56 illustrating the original laboratory
group instrument outputs in a second column 58, the outputs of a
control group in a third column 60, and the normalized outputs of
the laboratory instrument outputs in a fourth column 62. As
illustrated in rows 64-72, the normalized values of the laboratory
instrument outputs 62 are much closer to the control group values
60, allowing a better comparison of the data. For example, the
value for specimen 1 in column 64 indicates that the original lab
result was "98" while the control group for the specimen was "254".
As mapped by the method and structure of the present invention,
however, the normalized value is "268", better reflecting the
actual differences in testing values between the laboratory group
and the control group.
[0037] The system and method of the present invention can be
implemented in a variety of testing embodiments. In a first
embodiment, a group of laboratory instruments run tests on a
external quality control specimen which is provided by a testing
facility. As would be understood, to provide quality control
testing of the particular instruments, the results from the
laboratory group are compared to a peer group running tests on
specimen samples originating from the same lot. However,
statistical differences between the instruments (especially if the
groups have instruments made by different manufacturers) may cause
the outputs to vary significantly. In a conventional testing
system, the results typically cannot be compared and consequently,
the laboratory instrument groups cannot utilize the larger common
peer group. In contrast, however, the present invention generates
normalization curves allowing the laboratory instrument group
results to be normalized with the control group output by utilizing
normalization curves calculated from previous external quality
control test specimen data. This method allows a laboratory
instrument group facilitator to compare its output data to a larger
peer group because differences between groups can be mitigated.
Moreover, the mapping of the laboratory output allows the
laboratory instrument group to add their data to the peer group as
well.
[0038] In an alternative embodiment, the method and device of the
present invention may also be utilized to provide direct comparison
of lab results from two or more laboratory instrument groups. For
example, a laboratory patient may have a series of tests conducted
at a first laboratory group and the same series of tests conducted
at a second laboratory group. If the laboratory testing groups have
statistical differences in their outputs, the conventional
monitoring method prevents a meaningful analysis of the patient's
progress. In contrast, the present invention allows the second
group outputs to be normalized with the first group outputs for a
direct comparison. Again, the instrumentation differences between
the laboratory group results are mitigated, which is beneficial for
a mobile patient.
[0039] In yet another embodiment, the method and device of the
present invention allows an individual laboratory group to map a
chain of laboratory instruments outputs according to a standardized
output value as the outputs are generated. In this embodiment, a
LIS (FIG. 1) within the group of laboratory instruments receives a
desired value range in which to report the outputs from its
laboratory instruments. As the LIS receives outputs from the
various laboratory instruments in the group, it normalizes the
outputs according to the desired value range prior to outputting
the output from the group. Thus, the normalizing functionality is
built into the LIS for real time processing. As would be readily
understood, the normalized output from the LIS could then be
further implemented in other normalization functions such as those
described in the first and second embodiments.
[0040] In general, the normalization system of the present
invention allows groups of laboratory instruments to submit outputs
indicative of the laboratory instrument testing results to the
normalization server and have the outputs normalized according to a
control group. The normalized outputs can then be utilized to
compare the current results with a previous test and/or to
calibrate the group of laboratory instruments according to a peer
group. Additionally, while many program languages could be used to
create the objects and functions of the present invention, the
present invention is preferably coded by an object-oriented
language such as Microsoft Corporation's "VISUAL C++.RTM." OR
"VISUAL BASIC.RTM." programming languages.
[0041] It will be understood that certain features and
subcombinations are of utility and may be employed without
reference to other features and subcombinations. This is
contemplated by and is within the scope of the claims.
[0042] Since many possible embodiments may be made of the invention
without departing from the scope thereof, it is to be understood
that all matter herein set forth or shown in the accompanying
drawings is to be interpreted as illustrative, and not in a
limiting sense.
[0043] From the foregoing it will be seen that this invention is
one well adapted to attain all ends and objectives herein-above set
forth, together with the other advantages which are obvious and
which are inherent to the invention.
[0044] Since many possible embodiments may be made of the invention
without departing from the scope thereof, is to be understood that
all matters herein set forth or shown in the accompanying drawings
are to be interpreted as illustrative, and not in a limiting
sense.
[0045] While specific embodiments have been shown and discussed,
various modifications may of course be made, and the invention is
not limited to the specific forms or arrangement of parts and steps
described herein, except insofar as such limitations are included
in the following claims. Further, it will be understood that
certain features and sub-combinations are of utility and may be
employed without reference to other features and sub-combinations.
This is contemplated by and is within the scope of the claims.
* * * * *