| Identifier |
20230314_nanos_posters_316 |
| Title |
A Validated Algorithm for Identifying Neuro-Ophthalmic Conditions in Electronic Health Record Data |
| Creator |
Lindsey De Lott; Lizbeth Gonzalez; Chris Andrews; Joshua Stein |
| Affiliation |
(LD) (CA) (JS) University of Michigan; (LG) University of Michigan, Ann Arbor |
| Subject |
Optic Neuritis; Neuro-ophth & Systemic Disease (eg. MS, MG, Thyroid) |
| Description |
Most administrative data studies rely primarily on billing codes, but it is uncertain whether this strategy accurately identifies patients with conditions of interest. Our aim was to develop an algorithm using clinical data captured in electronic health records (EHR), in addition to billing codes, to accurately identify neuro-ophthalmic conditions, such as acute optic neuritis (ON). |
| Date |
2023-03-14 |
| References |
None provided. |
| Language |
eng |
| Format |
application/pdf |
| Type |
Text |
| Source |
2023 North American Neuro-Ophthalmology Society Annual Meeting |
| Relation is Part of |
NANOS Annual Meeting 2023: Poster Session II: New Diagnostic Measurement Techniques |
| Collection |
Neuro-ophthalmology Virtual Education Library: NOVEL http://NOVEL.utah.edu |
| Publisher |
Spencer S. Eccles Health Sciences Library, University of Utah |
| Holding Institution |
North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416 |
| Rights Management |
Copyright 2023. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
| ARK |
ark:/87278/s6zjs8w9 |
| Setname |
ehsl_novel_nam |
| ID |
2335521 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6zjs8w9 |
