Evidence map›Paper›PMID 30699459›Full record

ArticleApplied clinical informatics2019

Rebuilding the Standing Prescription Renewal Orders.

Scott D Nelson, Hayley H Rector, Daniel Brashear, Janos L Mathe, Haomin Wen, Stacey Lynn English, William Hedges, Christoph U Lehmann, Asli Ozdas-Weitkamp, Shane P Stenner

Abstract read
In one paragraph

Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Scott D NelsonDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Hayley H RectorPharmacy Department, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Daniel BrashearCollege of Pharmacy and Health Sciences, Lipscomb University, Nashville, Tennessee, United States.
Janos L MatheHealthIT, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Haomin WenHealthIT, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Stacey Lynn EnglishCollege of Pharmacy and Health Sciences, Lipscomb University, Nashville, Tennessee, United States.
William HedgesCollege of Pharmacy and Health Sciences, Lipscomb University, Nashville, Tennessee, United States.
Christoph U LehmannDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Asli Ozdas-WeitkampDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Shane P StennerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundManaging 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.

objectiveThis 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).

methodsWe 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.

resultsSeventy-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.

conclusionWe describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.

Indexed as

Drug PrescriptionsStanding OrdersElectronic Health RecordsReference Standards

Identifiers

PMID30699459
PMCPMC6353649

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.