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Record W4393189730 · doi:10.1016/j.japh.2024.102076

Patient-perceived understanding of home-going medication with transitions of care services at a pediatric institution

2024· article· en· W4393189730 on OpenAlexaff
Sonya Sebastian, Hannah Thornton, Mahmoud Abdel‐Rasoul, Karielle Shaffery

Bibliographic record

VenueJournal of the American Pharmacists Association · 2024
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCommunity Based Research Centre
Fundersnot available
KeywordsMedicinePharmacyPharmacistPatient satisfactionFamily medicineHealth carePopulationHarmMedical homeHealth literacyPatient safetyMedical emergencyNursingPrimary care

Abstract

fetched live from OpenAlex

BACKGROUND: Transitions of care (TOC) is the coordination and continuity of health care as a patient transfers between different settings. This can include a wide range of services, such as medication reconciliation, patient counseling, bedside delivery of medications, and others that meet individual patient needs. In the pediatric population, patients are at increased risk of potential medication errors and subsequent harm owing to reduced patient and caregiver health literacy, limited dosage form availability, and errors in medication administration. The use of TOC services at the time of hospital discharge in this population has the potential to make a positive impact on patient safety and the treatment of medical conditions. OBJECTIVES: The primary objective of this study was to determine whether patient-perceived understanding of home-going medications was greater in patients and/or caregivers who received medication bedside delivery and education from a pharmacy-led TOC service at a large pediatric academic medical center. The secondary objective was to determine whether the primary practice area of the pharmacist providing medication education led to changes in understanding of home-going medication(s). METHODS: Using institution-wide, patient satisfaction surveys from January 1, 2021, to December 31, 2021, patient and caregiver responses were queried for 2 questions about home-going medications, relating to the understanding of administration and the potential adverse effects. Patients were divided into 2 groups depending on TOC services received, as documented in the electronic medical record (EMR). Survey responses for each of the 2 questions were categorized as top-box percentage by study group. Hypothesis testing between study groups for the primary and secondary outcomes were conducted using chi-squared tests at an alpha of 0.05. Statistical analyses were conducted using SAS version 9.4. RESULTS: Of the 1159 patients included in the study, 441 received TOC services, deemed the intervention group, and 718 did not receive TOC services, deemed the control group. When the intervention and control group were asked about understanding of medication administration, 96.37% versus 93.18% of patients (P = 0.007) gave the most favorable response of "yes, definitely," respectively. Furthermore, 78.51% versus 77.44% of patients (P = 0.053) gave the most favorable response when asked about understanding potential medication adverse effects, respectively. CONCLUSION: Patients receiving TOC services by a member of the pharmacy team had a greater score for understanding of both medication administration and adverse effects. Furthermore, this greater score was consistent among the education provided by the inpatient and outpatient pharmacist.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.349
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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