ArticleInnovations in pharmacy2021
Identifying Potential High-Risk Medication Errors Using Telepharmacy and a Web-Based Survey Tool.
Article in Innovations in pharmacy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06108674 (Evaluation of the Effectiveness of Telepharmacy on Clinical Outcomes of Patients With Arterial Hypertension), which is not on this map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Evaluation of the Effectiveness of Telepharmacy on Clinical Outcomes of Patients With Arterial Hypertension: Celeste Randomized Clinical Trial
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Health Technology Interventions for Improving Medication Safety: Systematic Review of Economic Evaluations.Journal of medical Internet research · 2025Pooled it
- Survey of the patients' perspectives and preferences in adopting telepharmacy versus in-person visits to the pharmacy: a feasibility study during the COVID-19 pandemic.BMC medical informatics and decision making · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
introductionObtaining patient medication histories during emergency department (ED) admissions is an important step towards identifying potential errors that could otherwise remain in the patient's active medication list. This is a descriptive report of a standardized, electronic data collection tool created to document potential medication errors in patients receiving high-risk medications during ED admissions. MATERIALS AND
methodsTrained pharmacy technicians completed a survey following medication history collection using a secure web platform called REDCap®. Data collected included patient-specific information, the number and type of high-risk medications, and potential medication errors identified in the collection process.
resultsDuring a pilot period of April 2019 to October 2020, 191 patient records were completed using the survey tool. Out of a total of 1088 medications recorded, 41% were considered high-risk medications. 42% of potential medication errors were classified as high-risk medication errors. Results from this survey tool demonstrated that 58% of high-risk medication orders could potentially result in a medication error that can be carried through patient admission and discharge. DISCUSSION: Accurate medication history and transitions of care can significantly impact patient quality of life. The cost of addressing a medication related-adverse event is also substantial. Based on published reports, annual gross savings to a hospital is estimated to be $4532 per harmful error in 2020, after adjusting for inflation. This equated to approximately $1,182,852 in estimated savings for Ascension Texas in 18 months. Nationwide, preventing potential medication errors in an outpatient setting can save on average $3.5 billion per year.
conclusionThis web-based survey tool has improved the quality and efficiency of potential error identification during medication history collection by pharmacy technicians. This information can be easily retrieved and aid in discussions regarding medication reconciliation at the leadership level and impact patient treatment outcomes by developing virtual processes that may result in fewer medication related events.
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Registered trials
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.