We describe the methodology and impact of merging detailed statewide mortality data into the master patient index for a half million persons who received inpatient or ambulatory care at the University of Virginia Health System since 1992. We employ three broadly inclusive linkage passes designed to result in large numbers of false positives to match the patients to those in the statewide death files using the following criteria: a) Social Security Number; b) Patient Last Name and Birth Date; c) Patient Last Name and Patient First Name. The results from these initial processes are refined by calculation and assignment of a total score comprised of partial scores depending on the quality of matching between the various identifiers. We conclude that we are able to update our internal records with 97% of the 30,000 deaths identified for this population. Only 20% of these deathswould have been detected through in-house records alone. We illustrate the clinical potential of this matching through analysis of those patients who committed suicide. We suggest that our approach represents an efficient and inexpensive way to enrich hospital data with important outcome information for all areas of health care. See hesweb1.med.virginia.edu/
Learning Objectives: 1. Participants will learn the current status death certification in the US and an example of how public death records can be used to augment treatment records to create long term outcome models. Common technical and conceptual problems will be described. Participants can apply this information to their local analytic data for any medical area.
Keywords: Death, Co-morbid
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: University of Virginia Health System, Virginia State Department of Health, Office of Vital Statistics.
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.