Extracting and Standardizing Medical Examiner Data to Improve Health

Authors

Shamsi Daneshvari Berry, Department of Health Informatics and Information Management, University of Mississippi Medical Center, Jackson, MS, USA
Heather J H Edgar, Department of Anthropology, University of New Mexico, Albuquerque, NM, USA; Office of the Medical Investigator, University of New Mexico, Albuquerque, NM, USA

Document Type

Article

Publication Date

5-30-2020

Abstract

Data from medical examiner offices are not commonly used in informatics but may contain information not in medical records. However, the vast majority of data is not standardized and is available only in large free text fields. We sought to extract information from the medical examiner database using Canary, a natural language processing tool. The text was then standardized to fit the selected normative answer list for each field. Multiple terminology and vocabulary standards from a variety of settings were utilized as data came from the medical examiner and interviews with next of kin. Thirty-seven percent of the metadata fields could be mapped directly to existing standards, twenty-five percent required a modification, and thirty-eight required creation of a standardized normative answer list. The newly formed database (New Mexico Decedent Image Database (NMDID)), will be available to researchers and educators at the beginning of 2020.

Recommended Citation

Berry SD, Edgar HJH. Extracting and Standardizing Medical Examiner Data to Improve Health. AMIA Jt Summits Transl Sci Proc. 2020 May 30;2020:63-70. PMID: 32477624; PMCID: PMC7233086.