Evidence map›Paper›PMID 35928648›Full record

ArticlePerspectives in clinical research

A cross-sectional study on current prescription trends and errors in outpatient department of a Bangladeshi secondary care district hospital.

Md Mizanur Rahman, Ashfia Tasnim Munia, K M Yasif Kayes Sikdar, Md Raihan Sarkar

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Article in Perspectives in clinical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Md Mizanur RahmanDepartment of Pharmacy, University of Dhaka, Dhaka, Bangladesh.
Ashfia Tasnim MuniaInstitute of Statistical Research and Training, University of Dhaka, Dhaka, Bangladesh.
K M Yasif Kayes SikdarDepartment of Pharmaceutical Technology, University of Dhaka, Dhaka, Bangladesh.
Md Raihan SarkarDepartment of Pharmaceutical Technology, University of Dhaka, Dhaka, Bangladesh.
University of Dhaka · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Context: The rational prescription leads to a healthy and good-quality life of a patient. Irrational, inappropriate, and unnecessary prescriptions are major therapeutic issues in Bangladesh, which can cause severe consequences. Aim: This cross-sectional study was conducted to evaluate the prescription patterns and errors as well as to review the most frequently prescribed drug classes among outpatients at a secondary hospital in Pabna, a district of Bangladesh. Methods: A total of 400 prescriptions were reviewed from March 2019 to May 2019. In this study, statistical data analysis was implemented by IBM SPSS Statistics V22 and data revealed in frequencies, mean, and percentage. Spearman's rank correlation coefficient was calculated to show the correlation between bivariate coded variables. Results: The results revealed that majority of the prescription were prescribed for females (73.5%) where proton-pump inhibitors (PPIs), analgesics, vitamins, and single antibiotics were most frequently prescribed medicine for the female patients compared to male patients. Almost half of the collected prescription contained four medicines (47%). Maximum number of prescriptions contained two (30.5%) essential drugs and among 1402 medicines of 400 prescriptions, antiulcerants were most frequently prescribed medicine (23.32%) where esomeprazole was highly prescribed generic drug (44.75%). Moreover, Spearman's rank correlation coefficient suggested that PPIs and analgesics were frequently prescribed medicines at a time for the patients (0.182). According to the age group, the study also got some significant variations in prescribing pattern. However, most common prescription errors were prescriber's name not mentioned (100%), diagnosis not mentioned (96.75%), dose not indicated (15.41%), and wrong drug name (0.36%). Conclusion: Findings of the current study represent the existing prescribing trends of different therapeutic classes of drugs and common prescription errors in a secondary health facility of Bangladesh. From this study, it is observed that physicians prescribed rationally in some cases but need to ensure rationality in all prescriptions. Continuous monitoring of drug use, development of prescribing guidelines, and training are recommended to ensure and implement good-quality prescribing practices for promoting the rational and cost-effective use of drugs.

Indexed as

Prescription errorsprescription patternrational drug usesecondary hospital

Identifiers

PMID35928648
PMCPMC9345250
OpenAlexW3138401449

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.