Rebuilding the Standing Prescription Renewal Orders.
Journal
Applied clinical informatics
ISSN: 1869-0327
Titre abrégé: Appl Clin Inform
Pays: Germany
ID NLM: 101537732
Informations de publication
Date de publication:
01 2019
01 2019
Historique:
entrez:
31
1
2019
pubmed:
31
1
2019
medline:
31
3
2020
Statut:
ppublish
Résumé
Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging. This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR). We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria. Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse. We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.
Sections du résumé
BACKGROUND
Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging.
OBJECTIVE
This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR).
METHODS
We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria.
RESULTS
Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse.
CONCLUSION
We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.
Identifiants
pubmed: 30699459
doi: 10.1055/s-0038-1675813
pmc: PMC6353649
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
77-86Informations de copyright
Georg Thieme Verlag KG Stuttgart · New York.
Déclaration de conflit d'intérêts
None.
Références
Am J Health Syst Pharm. 2018 Feb 1;75(3):132-138
pubmed: 29371194
Healthc (Amst). 2015 Sep;3(3):142-9
pubmed: 26384225
Fam Med. 2012 Sep;44(8):564-8
pubmed: 22930121
N Engl J Med. 2010 Apr 29;362(17):1632-6
pubmed: 20427812
Stud Health Technol Inform. 2011;166:206-13
pubmed: 21685626
J Am Board Fam Med. 2006 Jan-Feb;19(1):31-8
pubmed: 16492003
Stud Health Technol Inform. 2017;245:920-924
pubmed: 29295234
J Am Pharm Assoc (2003). 2013 Sep-Oct;53(5):505-12
pubmed: 24030128
J Biomed Semantics. 2014 Jul 09;5:30
pubmed: 25101165
Health Aff (Millwood). 2013 Nov;32(11):1990-7
pubmed: 24191091
Stud Health Technol Inform. 2017;245:843-847
pubmed: 29295218