Name
Abstract | ||
|---|---|---|
Secondary use of electronic health record (EHR) data is enabled by accurate and complete retrieval of the relevant patient cohort, which requires searching both structured and unstructured data. Clinical text poses difficulties to searching, although chart notes incorporate structure that may facilitate accurate retrieval. We developed rules identifying clinical document sections, which can be indexed in search engines that allow faceted searches, such as Lucene or Essie, an NLM search engine. We developed 22 clinical cohorts and two queries for each cohort, one utilizing section headings and the other searching the whole document. We manually evaluated a subset of retrieved documents to compare query performance. Querying by section had lower recall than whole-document queries (0.83 vs 0.95), higher precision (0.73 vs 0.54), and higher F (0.78 vs 0.69). This evaluation suggests that searching specific sections may improve precision under certain conditions and often with loss of recall. |
Year | Venue | Field |
|---|---|---|
2017 | AMIA | Search engine,Information retrieval,Computer science,Text segmentation,Document retrieval,Cohort |
DocType | Volume | Citations |
Conference | 2017 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tracy Edinger | 1 | 0 | 0.34 |
| Dina Demner Fushman | 2 | 1717 | 147.70 |
| Aaron M. Cohen | 3 | 6 | 1.19 |
| Steven Bedrick | 4 | 218 | 20.02 |
| William Hersh | 5 | 2491 | 307.00 |