Evidence map›Paper›PMID 29345553›Full record

ArticleJournal of managed care & specialty pharmacy2018

Quality and Variability of Patient Directions in Electronic Prescriptions in the Ambulatory Care Setting.

Yuze Yang, Stacy Ward-Charlerie, Ajit A Dhavle, Michael T Rupp, James Green

Abstract read
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. E-prescribing and medication safety in community settings: A rapid scoping review.Exploratory research in clinical and social pharmacy · 2023
    Article
  3. Implementation outcomes of the Structured and Codified SIG format in electronic prescription directions.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  4. Article
  5. Article
  6. Article
  7. Observational
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

5 authors.

Yuze Yang1 Surescripts, Arlington, Virginia.
Stacy Ward-Charlerie1 Surescripts, Arlington, Virginia.
Ajit A Dhavle1 Surescripts, Arlington, Virginia.
Michael T Rupp2 Midwestern University, Glendale, Arizona.
James Green1 Surescripts, Arlington, Virginia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prescriber's directions to the patient (Sig) are one of the most quality-sensitive components of a prescription order. Owing to their free-text format, the Sig data that are transmitted in electronic prescriptions (e-prescriptions) have the potential to produce interpretation challenges at receiving pharmacies that may threaten patient safety and also negatively affect medication labeling and patient counseling. Ensuring that all data transmitted in the e-prescription are complete and unambiguous is essential for minimizing disruptions in workflow at prescribers' offices and receiving pharmacies and optimizing the safety and effectiveness of patient care.

objectivesTo (a) assess the quality and variability of free-text Sig strings in ambulatory e-prescriptions and (b) propose best-practice recommendations to improve the use of this quality-sensitive field.

methodsA retrospective qualitative analysis was performed on a nationally representative sample of 25,000 e-prescriptions issued by 22,152 community-based prescribers across the United States using 501 electronic health records (EHRs) or e-prescribing software applications. The content of Sig text strings in e-prescriptions was classified according to a Sig classification scheme developed with guidance from an expert advisory panel. The Sig text strings were also analyzed for quality-related events (QREs). For purposes of this analysis, QREs were defined as Sig text content that could impair accurate and unambiguous interpretation by staff at receiving pharmacies.

resultsA total of 3,797 unique Sig concepts were identified in the 25,000 Sig text strings analyzed; more than 50% of all Sigs could be categorized into 25 unique Sig concepts. Even Sig strings that expressed apparently simple and straightforward concepts displayed substantial variability; for example, the sample contained 832 permutations of words and phrases used to convey the Sig concept of "Take 1 tablet by mouth once daily." Approximately 10% of Sigs contained QREs that could pose patient safety risks or workflow disruptions that could necessitate pharmacist callbacks to prescribers for clarification or other manual interventions.

conclusionsThe quality of free-text patient directions in e-prescriptions can vary dramatically. However, more than half of all patient directions sent in the ambulatory setting can be categorized into only 25 Sig concepts. This suggests an immediate, practical opportunity to improve patient safety and workflow efficiency for both prescribers and pharmacies. Recommendations include implementing enhancements to Sig creation tools in e-prescribing and EHR software applications, adoption of the Structured and Codified Sig format supported by the current national e-prescribing standard, and improved usability testing and end-user training for generating complete and unambiguous patient directions. Such quality improvements are essential for optimizing the safety and effectiveness of patient care as well as for minimizing workflow disruptions to both prescribers and pharmacies. DISCLOSURES: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Yang, Ward-Charlerie, Dhavle, and Green are employed by Surescripts. Rupp reported receiving consulting fees from Surescripts during the conduct of this study. No other disclosures were reported. The content in this article is solely the responsibility of the authors and does not necessarily represent the official views of Surescripts and Midwestern University or any of the affiliated institutions of the authors. Study concept and design were contributed by all the authors. Yang and Ward-Charlerie collected the data, and data interpretion was performed by Yang, Ward-Charlerie and Dhavle. The manuscript was primarily written by Yang, along with Dhavle and Green, and revised by Yang, Dhavle, Rupp, and Green.

Indexed as

Quality ImprovementAmbulatory CareDrug LabelingDrug PrescriptionsElectronic Health RecordsElectronic PrescribingMedication ErrorsPatient SafetyPharmaciesQualitative ResearchRetrospective StudiesUnited States

Identifiers

PMID29345553
PMCPMC10398147

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.