OtherAmerican journal of physical medicine & rehabilitation2017

Probabilistic Matching Approach to Link Deidentified Data from a Trauma Registry and a Traumatic Brain Injury Model System Center.

Matthew Ryan Kesinger, Raj Gopalan Kumar, Anne Connelly Ritter and 2 others

PMID 27088479

WHAT IT FOUND

Trauma and brain injury rehabilitation records were linked at a single center with high match accuracy and very few false matches.

This is a research method, not a patient treatment finding.

Key findings

01In the algorithm generation set, requiring weight greater than 5 and highest in cluster gave sensitivity 0.89 and positive predictive value 0.98.

02In the validation set, requiring weight greater than 5 and highest in cluster gave sensitivity 0.87 and positive predictive value 0.97.

03In the validation set, also requiring cluster weight difference greater than 5.34 gave sensitivity 0.83 and positive predictive value 0.99.

STILL TO COME

How it was doneWhat they found

Read the rest of this summary

You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.

Already have one?

What it does not show

The algorithm was developed and validated at a single center using 241 TBIMS cases, so it may not perform the same way in other trauma or rehabilitation databases. Medical record numbers were used to know true matches, but the intended future use is deidentified databases without such identifiers. Restricting the trauma registry to head injury by ICD-9 codes excluded 19 TBIMS patients (7.8%) and made true matches impossible for those cases. The cause of missing data was not determined, and missingness can lead to false negatives. Data quality and coding may differ across centers because registrars and input methods differ.

Declared interests

Research support is listed as U.S. government, non-PHS, and NIH extramural. The supplied text does not state author conflicts of interest.

The easy way to misread this

Do not read this as evidence that linked trauma and rehabilitation records have already changed patient care. The study validated a linkage method at a single center using medical record numbers, and it did not test clinical outcomes or treatment effects.

Read it on PubMed →


The study

Participants
241 TBIMS cases; 14,389 trauma registry cases narrowed to 5,338 head injury cases
Certainty of evidence
Low

Browse

    Cite

    Matthew Ryan Kesinger, Raj Gopalan Kumar, Anne Connelly Ritter, et al. Probabilistic Matching Approach to Link Deidentified Data from a Trauma Registry and a Traumatic Brain Injury Model System Center. American journal of physical medicine & rehabilitation. 2017.

    Read the original