Abstract
OBJECTIVE: The effects of opioid use disorder (OUD) are devastating and wide-ranging. Although the information in the >43,000 manuscripts on OUD are searchable, gaining a comprehensive grasp of this information is out of reach to most persons. We present a pilot study to use published data on OUD, repurpose it for rapid comprehension and distribution to the world.
DESIGN: Data from articles on OUD were entered into a data-tree and evaluated to achieve integration of information using the least number of notes.
SETTING: Literature on OUD. Experimental units: A total of 752 articles were selected from PubMed searches. Review articles, case reports, and short series with samples of less than ten were excluded.
OUTCOME MEASURES: The frequency of descriptive note types, and the total number of notes used with and without note sharing.
RESULTS: Four types of notes were found sufficient to describe extracted numeric data from an article; topic (20.1 percent), population (26.2 percent), description of numeric value (28.4 percent), and numeric value (25.3 percent). Notes were entered in parent-child relationships across hierarchical levels, descriptive analyses showed smooth expansion and reduction of notes across the database. Entry rules allowed sharing of parent notes across different numeric values, which reduced that total number of notes by 72.9 percent.
CONCLUSIONS: These results demonstrate a method of data extraction and integration that allows for readily understandable grouping of large amounts of data. This strategy yields a method to extract and make accessible all published data on OUD. We expect that common understanding will improve outcomes for patients and research objectives.