Strategic Matching -- Tech Note #9
Case Selection Versus Case Classification
Applies to: CODES 2000 Release 2.1.
Last updated: Friday August 24, 2001.
SUMMARY
Your EMS records or Hospital records may include fields such as mechanism of injury or E code that can be used to set a flag to denote motor vehicle crash victims. You can use this crash flag to select cases for linkage. This will reduce the size of the EMS or Hospital table to be linked and the amount of information required for a high quality match. Another approach is to keep all cases and use the crash flag as a match field. This will adjust weights for candidate record pairs based on agreement with a flag on Crash records that is always "Y". The latter approach can reduce the number of false negatives caused by incomplete reporting. It is equivalent to the former approach for the cases set to "Y", and it allows for the possibility of a match based on other evidence for the cases set to "N".
PROCEDURE
First, create a crash flag field named Crash in the Crash table that is equal to "Y" for all records. You can do this in your SelectCrash query by including a column in design view like this:
Crash:"Y"
Second, create a crash flag field named Crash in the EMS or Hospital table that is equal to "Y", "N", or Null for all records. You can do this with the Access IIf function for simple cases. For example, suppose that the EMS table includes a field for mechanism of injury named MECHAN, where MECHAN=1 denotes a motor vehicle crash victim. Then you can create a crash flag field in your SelectEMS query by including a column in design view like this:
Crash:IIf(MECHAN=1,"Y","N")
You may want to create a Visual Basic function for more complicated cases.
Third, replace the frequency table for the Crash field in the Crash database with the frequency table for the Crash field in the EMS or Hospital database. Note that the field may be called Crash1 after standardization. This step is necessary because the current release of CODES 2000 assumes that frequency distributions for linked records are equal to frequency distributions for records in Table B (see Tech Note #4). This is a reasonable assumption if you select only motor vehicle crash victims for Table B but not if you take all cases reported by EMS or Hospitals.
Open the Crash database in your project folder. Select Tables in the database window. Rename the table FreqTblCrashCrash as OldFreqTblCrashCrash. Import the table FreqTblEMSCrash from the EMS database in your project folder. Or, import the table FreqTblHospitalCrash from the Hospital database. Rename the imported table as FreqTblCrashCrash.
Fourth, include the field Crash as a match field in every match pass. Note that the field may be called Crash1 after standardization.
EXAMPLE
Here are the results of linking Crash to EMS using Injured and Crash flags. The flags were used only for case classification, not case selection. Only appropriate Crash records had Injured = "Y" while all EMS records had Injured = "Y". All Crash records had Crash = "Y" while only appropriate EMS records had Crash = "Y".
You can see that a significant number of linked pairs were found for all possible combinations of flag values, even when both flags were "N" (92 cases, or 2.6% of all linked pairs). Only 2,110 cases (60.4%) had both flags equal to "Y". All of the other cases would have become false negatives had both flags been used for case selection.
ANALYSIS
Suppose that the Crash table contains 100,000 records and the EMS table contains 40,000 records. Also suppose that 10,000 of the EMS records (25%) have MECHAN=1 and we expect that all of them should match to Crash records.
The first approach is to use the Crash flag for case selection. Then the prior odds that a random pair of records is a true match using our standard formula are:
Matched / Unmatched = 10,000 / (100,000 X 10,000 - 10,000) = 1 / 99,999
We want posterior odds for a match given observed agreements and disagreements to be at least 9 / 1 (90% probability), so the minimum acceptable odds ratio is
Posterior Odds / Prior Odds = (9 / 1) / (1 / 99,999) = 899,991
The minimum acceptable match weight (cutoff weight) is
log base 2 (899,991) = 19.78
The second approach is the use the Crash flag for matching. Then the prior odds that a random pair of records is a true match are:
Matched / Unmatched = 10,000 / (100,000 X 40,000 - 10,000) = 1 / 399,999
Now the minimum acceptable odds ratio is
Posterior Odds / Prior Odds = (9 / 1) / (1 / 399,999) = 3,599,991
The minimum acceptable match weight (cutoff weight) is
log base 2 (3,599,991) = 21.78
If the EMS Crash field value "Y" is fairly reliable, say 0.01 error probability, then its agree weight for "Y" is approximately
log base 2 (0.99 / 0.25) = 1.99
The agree weight from this new match field almost exactly offsets the increase in cutoff weight due to using the complete EMS table.
The disagree weight for the Crash field is approximately
log base 2 (0.01 / 0.75) = -6.23