Published on in Vol 8, No 3 (2020): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16073, first published .
Detecting Potential Medication Selection Errors During Outpatient Pharmacy Processing of Electronic Prescriptions With the RxNorm Application Programming Interface: Retrospective Observational Cohort Study

Detecting Potential Medication Selection Errors During Outpatient Pharmacy Processing of Electronic Prescriptions With the RxNorm Application Programming Interface: Retrospective Observational Cohort Study

Detecting Potential Medication Selection Errors During Outpatient Pharmacy Processing of Electronic Prescriptions With the RxNorm Application Programming Interface: Retrospective Observational Cohort Study

Authors of this article:

Corey A Lester1 Author Orcid Image ;   Liyun Tu2 Author Orcid Image ;   Yuting Ding1 Author Orcid Image ;   Allen J Flynn3 Author Orcid Image

Journals

  1. Panich J, Larson N, Sojka L, Wallace Z, Lokken J. Assessing automated product selection success rates in transmissions between electronic prescribing and community pharmacy platforms. Journal of the American Medical Informatics Association 2021;28(1):113 View
  2. Pereira N, Avram R, So D, Iturriaga E, Byrne J, Lennon R, Murthy V, Geller N, Goodman S, Rihal C, Rosenberg Y, Bailey K, Pletcher M, Marcus G, Farkouh M, Olgin J. Rationale and design of the TAILOR-PCI digital study: Transitioning a randomized controlled trial to a digital registry. American Heart Journal 2021;232:84 View
  3. Kassem A, Saeed H, El Bassiouny N, Kamal M. Assessment and analysis of outpatient medication errors related to pediatric prescriptions. Saudi Pharmaceutical Journal 2021;29(10):1090 View
  4. Lewis N, Marwitz K, Gaither C, Haugtvedt C, Selkow L, Sinha S. Creating a Stronger Culture of Safety Within US Community Pharmacies. The Joint Commission Journal on Quality and Patient Safety 2023;49(5):280 View
  5. Hilty D, Armstrong C, Smout S, Crawford A, Maheu M, Drude K, Chan S, Yellowlees P, Krupinski E. Findings and Guidelines on Provider Technology, Fatigue, and Well-being: Scoping Review. Journal of Medical Internet Research 2022;24(5):e34451 View
  6. Lester C, Flynn A, Marshall V, Rochowiak S, Rowell B, Bagian J. Comparing the variability of ingredient, strength, and dose form information from electronic prescriptions with RxNorm drug product descriptions. Journal of the American Medical Informatics Association 2022;29(9):1471 View
  7. Lester C, Flynn A, Marshall V, Rochowiak S, Bagian J. Implementation outcomes of the Structured and Codified SIG format in electronic prescription directions. Journal of the American Medical Informatics Association 2022;29(11):1859 View
  8. Gullslett M, Strand Bergmo T. Implementation of E-prescription for Multidose Dispensed Drugs: Qualitative Study of General Practitioners’ Experiences. JMIR Human Factors 2022;9(1):e27431 View
  9. Alshammari A, Aljabreen A, Alramal A, Alshammari N. Efficiency for the implantation Wasfaty prescription programme from the patient’s perspective: A focus-group study ‎. Journal of Advanced Pharmacy Education and Research 2023;13(4):36 View
  10. Egorova E, Useinova A, Shtyrkova L, Radkovskij V. Pharmaceutical examination of prescriptions from pharmacy chains of the Republic of Crimea from 2020 to 2021. HEALTH CARE OF THE RUSSIAN FEDERATION 2024;68(1):32 View
  11. Whitaker, MHI M, Lester C, Rowell B. Handing Off Electronic Prescription Data From Prescribers to Community Pharmacies: A Qualitative Analysis of Pharmacy Staff Perspectives. Journal of Patient Safety 2024 View