Author(s):
Shammin Haque, Nazmun N. Alam, Moinuddin Ahmed, Nusrat Sultana, Sumaiya Mushroor
Email(s):
shammin322@gmail.com
DOI:
10.5958/0974-360X.2018.00435.3
Address:
Shammin Haque1*, Nazmun N. Alam2, Moinuddin Ahmed3, Nusrat Sultana4, Sumaiya Mushroor5
1Associate Professor, Department of Pharmacology, Dr. Sirajul Islam Medical College and Hospital, Dhaka, Bangladesh.
2Lecturer, Faculty of Medicine, AIMST University, Malaysia.
3Associate Professor, Department of Community Medicine, Medical College for Women and Hospital, Dhaka, Bangladesh.
4Assistant Professor, Department of Pharmacology, Medical College for Women and Hospital, Dhaka, Bangladesh.
5Assistant Professor, Department of Community Medicine, Dr. Sirajul Islam Medical College and Hospital, Dhaka, Bangladesh.
*Corresponding Author
Published In:
Volume - 11,
Issue - 6,
Year - 2018
ABSTRACT:
Objective: To determine the opinion of clinicians about using an automated online tool for instant detection of drug interactions. Material and methods: This descriptive type of prospective cross-sectional study was carried out among the general physicians and specialists involved in various hospitals in Dhaka from September to November 2017. A pre-designed and pre-tested questionnaire comprising of both closed and open ended questions was used. After taking informed consent, they voluntarily participated in the study. Data were analysed using Microsoft Excel 2003 and results were expressed using descriptive statistics such as frequency and percentages. Some questions had multiple options, therefore, the sum of percentage is not always 100%. Results: Among a total of 50 participants, most of them (52%) could not recall the correct definition of drug interaction, though 60% know its types. Only 36% know drug interactions can produce adverse effects. Most (46%) were not sure about common drug interactions occurring in all specialities. Fiftysix percent report patients with polypharmacy suffer maximum from drug interactions, followed by elderly and children, revealed by 28% and 24%, respectively. Majority (60%) stated steroids produce maximum drug interactions among all drug groups, followed by 48% and 18% who revealed antibiotics and beta blockers are also responsible. Fifty percent followed by 30% and 20% reported hypertension, diabetes mellitus and bronchial asthma are the disease conditions where drug interactions occur commonly. Seventyfour percent find searching information on drug interaction while prescribing is time consuming from various sources. Simultaneously, 54% think an online drug interaction checker can be an instant easy option, while 50% state it can also prevent drug interactions. Generic name of drugs, common adverse effects, dose and type of drug interaction were opted to be included in the checker by 58%, 62%, 40% and 38%, respectively. More than half (58%), think outdoor patients will be benefitted most. Majority (54%) prefer online checker to be presented in both English and Bangla language. Fifty percent encounter drug interactions every six months, of moderate intensity by 62%. Fourty percent always give priority to drug interactions while prescribing. Sixty percent depend on drug leaflets for drug interaction information while prescribing, followed by 44% on drug reference books and 34% recall from previous knowledge. Only 24% always check drug interaction information while prescribing. Fiftyfour percent find available information inadequate to avoid drug interaction. Maximum (84%) previously did not use any online checker. Conclusion: Online drug databases can reduce the time for information procurement, ease decision making while prescribing, improve prescribing potential and prevent drug related adverse events.
Cite this article:
Shammin Haque, Nazmun N. Alam, Moinuddin Ahmed, Nusrat Sultana, Sumaiya Mushroor. Detection of Drug Interactions by using an Automated Tool-A Prospective Study. Research J. Pharm. and Tech 2018; 11(6): 2345-2350. doi: 10.5958/0974-360X.2018.00435.3
Cite(Electronic):
Shammin Haque, Nazmun N. Alam, Moinuddin Ahmed, Nusrat Sultana, Sumaiya Mushroor. Detection of Drug Interactions by using an Automated Tool-A Prospective Study. Research J. Pharm. and Tech 2018; 11(6): 2345-2350. doi: 10.5958/0974-360X.2018.00435.3 Available on: https://rjptonline.org/AbstractView.aspx?PID=2018-11-6-36