Computer Extraction of Data from Autopsy and Toxicology Reports. Issue 2 (June 2015)

• Record Type: Journal Article
• Authors: Cain, Matthew D.; Robinson, C. Andrew; Park, Seung L.; Davis, Gregory G.
• Is Part Of: Academic forensic pathology. Volume 5:Issue 2(2015)
• Page Start: 291
• Page End: 299
• Publication Date: 2015-06
• Subjects: Forensic pathology -- Extraction -- Toxicology -- Macro -- Excel; Forensic pathology -- Periodicals; Forensic pathology; Electronic journals; Periodicals; 614.1
• DOI: 10.23907/2015.032
• Languages: English
• ISSNs: 1925-3621

Abstract

Purpose: Forensic autopsies contain a wealth of information ranging from toxicology results to organ masses. Extracting data by hand from years of reports is tedious. We report a computer program that extracts information from reports in Word, WordPerfect, or Portable Document Format (PDF). Methods: The program consists of three Excel macros, written in Visual Basic for Applications, which extract information from autopsy and toxicology reports. The user selects a macro, chooses a folder of documents, and inputs key words to guide the search. The macros open each document in the folder sequentially, extract the desired values automatically, and enter the data into the respective case number's row in a spreadsheet. Another macro combines data from the separate autopsy and toxicology reports by matching the unique case number. Extraction of PDF files is a two-step process involving batch conversion from PDF format to Word with subsequent extraction. Results: We have developed a set of macros that extract data from autopsy and toxicology reports, such as age, race, height, manner and cause of death, and drug concentrations. Key words included autopsy headings, such as "Cardiovascular System" and units of measure such as "inches" or "pound." We analyzed roughly 7000 cases and kept 3455 cases. Conclusions: Our system rapidly procures data and places the information in a standardized format. This program will be hosted on our toxicology webpage for others to use. Future goals include combining data from other institutions and uploading the data to an online, queryable database.