A Comparison of Two User-Friendly Methods to Identify and Support Correction of Misspelled Medications

Details

• Personal Author:
  Dasaro CR ; Jeon Y ; Sabra A ; Sloan NL ; Teitelbaum SL ; Todd AC ; Williams TA
• Description:
  Objective: To identify and support correction of misspelled medication names recorded as free text, we compared the relative effectiveness of two user-friendly methods, used without reliance on clinical knowledge. Methods: Leveraging the SAS® COMPGED function, fuzzy string search programs examined 1.8 million medication records from 183,600 World Trade Center General Responder Cohort monitoring visits conducted in New York and New Jersey between 7/16/2002 and 3/31/2021, producing replicable generalized edit distance scores between the reported and correct spelling. Scores < 120 were selected as optimal and compared to Stedman's 2020 Plus Medical/Pharmaceutical Spell Checker first suggested word, used as the comparative standard because it employs both spelling and phonetic similarities to suggest matching words. We coded each methods' results as identifying or not identifying the medications within each visit. Results: Most types of medications (94.4 % anxiety, 98.4 % asthma and 94.6 % ulcer/gastroesophageal reflux disease) were correctly spelled. Cross tabulations assessed the agreement (anxiety 99.9 %, asthma 99.6 % and 98.4 % ulcer/ gastroesophageal reflux disease), false positive (respectively 0.02 %, 0.03 % and 2.0 %) and false negative (respectively 1.9 %, 0.5 % and 1.0 %) values. Scores < 120 occasionally correctly identified medications missed by the spell checker. We observed no difference in medication misspellings across socio-economically and culturally diverse patient characteristics. Conclusions: Both methods efficiently identified most misspelled medications, greatly minimizing the review and rectification needed. The fuzzy method is more universally applicable for condition-specific medications identification, but requires more programming skills. The spell checker is inexpensive, but benefits from modest programming skills and is only available in some languages. [Description provided by NIOSH]
• Subjects:
  Automation Biopharmaceutics Cohort Studies Health Care Facilities Workforce And Services Occupational Health Safety September 11 Terrorist Attacks
• Keywords:
  Author Keywords: Free Text Medication Names Cohort Studies Data Processing Diversity And Medications Information Electronic Health Records Fuzzy String Matching Medical Monitoring Medications Spell Checker Medications Spelling Correction Pharmaceuticals Prescription Drugs World Trade Center WTC

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• ISSN:
  2211-3355
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  New York ; OSHA Region 2
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  43
• NIOSHTIC Number:
  nn:20069753
• Citation:
  Prev Med Rep 2024 Jul; 43:102765
• Contact Point Address:
  Christopher R. Dasaro, World Trade Center Health Program General Responder Data Center, Department of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, 17 East 102 Street, 2nd Floor, New York, NY 10029
• Email:
  christopher.dasaro@mssm.edu
• Federal Fiscal Year:
  2024
• Performing Organization:
  State University of New York Stony Brook
• Peer Reviewed:
  False
• Start Date:
  20040715
• Source Full Name:
  Preventive Medicine Reports
• End Date:
  20110630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:4ff73d6d28de850a988c3c900302d130daaeed03a777e40b8ebca36351cee14a7919677a46f8990df366966d67db6f74e3f3c36e2fdc8a51ec0b3b3aa22bf6a1
• Download URL:
  https://stacks.cdc.gov/view/cdc/208113/cdc_208113_DS1.pdf
• File Type:
  [PDF - 396.57 KB ]