Rebuilding the Standing Prescription Renewal Orders

Abstract

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.

Keywords

clinical protocols - prescription drugs - drug classes - instance-based mapping - clinical decision support - knowledge management

Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by the VUMC's Institutional Review Board.

• References

• 1 Baron RJ. What's keeping us so busy in primary care? A snapshot from one practice. N Engl J Med 2010; 362 (17) 1632-1636
• 2 Edwards ST, Rubenstein LV, Meredith LS. , et al. Who is responsible for what tasks within primary care: perceived task allocation among primary care providers and interdisciplinary team members. Healthc (Amst) 2015; 3 (03) 142-149
• 3 Ferrell CW, Aspy CB, Mold JW. Management of prescription refills in primary care: an Oklahoma Physicians Resource/Research Network (OKPRN) study. J Am Board Fam Med 2006; 19 (01) 31-38
• 4 Rim MH, Thomas KC, Hatch B, Kelly M, Tyler LS. Development and implementation of a centralized comprehensive refill authorization program in an academic health system. Am J Health Syst Pharm 2018; 75 (03) 132-138
• 5 Shipman SA, Sinsky CA. Expanding primary care capacity by reducing waste and improving the efficiency of care. Health Aff (Millwood) 2013; 32 (11) 1990-1997
• 6 Winnenburg R, Bodenreider O. A framework for assessing the consistency of drug classes across sources. J Biomed Semantics 2014; 5: 30
• 7 Merabti T, Abdoune H, Letord C, Sakji S, Joubert M, Darmoni SJ. Mapping the ATC classification to the UMLS metathesaurus: some pragmatic applications. Stud Health Technol Inform 2011; 166: 206-213
• 8 Mortensen J, Bodenreider O. , eds. Comparing Pharmacologic Classes in NDF-RT and SNOMED CT. Proceedings of the Fourth International Symposium on Semantic Mining in Biomedicine; 2010
• 9 Bahr NJ, Nelson SD, Winnenburg R, Bodenreider O. Eliciting the intension of drug value sets - principles and quality assurance applications. Stud Health Technol Inform 2017; 245: 843-847
• 10 Nelson SD, Parker J, Lario R. , et al. Interoperability of Medication Classification Systems: lessons learned mapping Established Pharmacologic Classes (EPCs) to SNOMED CT. Stud Health Technol Inform 2017; 245: 920-924
• 11 Guirguis-Blake J, Keppel GA, Force RW, Cauffield J, Monger RM, Baldwin LM. Variation in refill protocols and procedures in a family medicine residency network. Fam Med 2012; 44 (08) 564-568
• 12 Billups SJ, Delate T, Newlon C, Schwiesow S, Jahnke R, Nadrash A. Outcomes of a pharmacist-managed medication refill program. J Am Pharm Assoc (2003) 2013; 53 (05) 505-512
• 13 Riege VJ. A patient safety program & research evaluation of U.S. Navy Pharmacy Refill Clinics. In: Henriksen K, Battles JB, Marks ES, Lewin DI. , eds. Advances in Patient Safety: From Research to Implementation (Vol. 1: Research Findings). Advances in Patient Safety. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); 2005
• 14 Lynch J, Rosen J, Selinger HA, Hickner J. Medication management transactions and errors in family medicine offices: a pilot study. In: Henriksen K, Battles JB, Keyes MA, Grady ML. , eds. Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 4: Technology and Medication Safety). Advances in Patient Safety. Rockville: MD: Agency for Healthcare Research and Quality (AHRQ); 2008