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Re: [Gnumed-devel] Lab import (data) matching

From: James Busser
Subject: Re: [Gnumed-devel] Lab import (data) matching
Date: Sat, 16 Aug 2008 09:02:25 -0700

On 3-Feb-08, at 7:43 PM, James Busser wrote:

Of interest, a registry study that tested match keys based on various combinations (name substrings, date of birth, gender, and health center) to link encounter and laboratory files found that an optimal match key was the first two letters of the last name with the date of birth, which had a sensitivity of 92.7% and a positive predictive value of 99.5% (even across ethnicity). This would suffice for auto-matching for research, but not for clinical care, with one obvious vulnerability being a multiple-birth within a family. This implies that we should perhaps consider multiple-birth as an attribute of a GNUmed person identity

Karsten and I have been working off-list on lab import, but I wanted these further thoughts (and a reference) to make it into the list archive.

The approach cited above yielded a low chance of incorrect matches (99.5% correct). I did not dig up the original article, to know the size of the patient populations being worked with, but as they were real-world, they may be guessed to be typical.

The requirement for a match on the complete last name (instead of just the first two characters) in a different study (URL captured below) was associated with similar match certainty of 97-99%. While the addition of a requirement to match the first name increased the certainty, it did so by <1% and lowered the successful match rate of 88-93% by a further 10%.

Gaining some additional certainty by requiring *some* kind of match at the "first name(s)" level may be achievable by requiring only 2 characters from the incoming message "firstnames" equivalent to match the first two characters of *any* name among a patient's possibly- multiple first names in GNUmed.

Vancouver being relatively tolerant of all sexualities, we may experience a higher rate of trans-gender whose coding variance between the laboratory and GNUmed could spoil matches. I think, though, that I will resist the urge to remove gender from the auto- match criteria because an independent criterion for a match exists anyway (see wiki LabImporters) and, where a gender miscode would have spoiled a match, it could be made apparent through a GNUmed wizard showing suggested matches for unmatched records.

Assessing record linkage between health care and Vital Statistics databases using deterministic methods.
Li B, Quan H, Fong A, Lu M.
Department of Community Health Sciences, University of Calgary
BMC Health Serv Res. 2006 Apr 5;6:48. ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubm ed_DiscoveryPanel.Pubmed_Discovery_RA&linkpos=5&log $=relatedarticles&logdbfrom=pubmed

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