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.

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.