Drug Interaction Study Based on Clinical Significance Categories on Outpatient Prescription Patterns

Ovi Amelia  Agustin; Fitrianingsih Fitrianingsih

doi:10.22437/esehad.v1i1.10759

Authors

Ovi Amelia Agustin
Fitrianingsih Fitrianingsih

DOI:

https://doi.org/10.22437/esehad.v1i1.10759

Keywords:

drug interactions, clinical significance, prescription pattern, pharmacist

Abstract

ABSTRACT
Background: Drug interactions are a common issue in prescription patterns that may influence patient outcomes by altering the effects of medications. Understanding the clinical significance of drug interactions is essential to ensure safe and effective therapy. This study aimed to identify the potential drug interactions based on their clinical significance levels in outpatient prescription patterns
Methods: A prospective cohort study was conducted by observing and reviewing 250 outpatient prescriptions collected over one month. Potential drug interactions were identified using the Medscape Drug Interaction Checker and analyzed descriptively according to their clinical significance categories.
Results: Of 250 prescriptions analyzed, 30 prescriptions (12%) showed potential drug interactions involving 48 drug components. The majority were classified as moderate interactions (57.44%), followed by minor (36.17%) and major (6.38%). Most interactions occurred in prescriptions for infectious diseases accompanied by pain (63.33%)..
Conclusion: The findings indicate that drug interactions in outpatient prescriptions remain a relevant concern, particularly moderate-level interactions. Pharmacists play a key role in monitoring, identifying, and managing drug interactions to prevent adverse effects and improve therapeutic outcomes. Strengthening computerized drug screening systems and pharmacist counseling is recommended to enhance patient safety.

References

1. Jooma Z. Drug Interactions. Southern African Journal of Anaesthesia and Analgesia. 2020;S75–9. https://doi.org/10.36303/sajaa.2020.26.6.s3.2543

2. Wahyuni S, Rawitri K, Rahayu YP. Potential Interactions of Hypertension Drug in Medan City Pharmacy. Asian Journal of Pharmaceutical Research and Development. 2022;10(4):1–4. https://doi.org/10.22270/ajprd.v10i4.1163

3. Parulian LP, Listyanti E, Hati AK, Sunnah I. Analisis Hubungan Polifarmasi Dan Interaksi Obat Pada Pasien Rawat Jalan Yang Mendapat Obat Hipertensi Di Rsp. Dr. Ario Wirawan Periode Januari-Maret 2019. Indonesian Journal of Pharmacy and Natural Product. 2019;2(2). https://doi.org/10.35473/ijpnp.v2i2.280

4. Radu A-F, Ţiț DM, Bungău G, Negru PA. Mapping the Global Research on Drug–Drug Interactions: A Multidecadal Evolution Through AI-Driven Terminology Standardization. Bioengineering. 2025;12(7):783. https://doi.org/10.3390/bioengineering12070783

5. Silva A, Costa B, Castro I, Mourão J, Vale N. New Perspective for Drug–Drug Interaction in Perioperative Period. J Clin Med. 2023;12(14):4810. https://doi.org/10.3390/jcm12144810

6. Wang T-C, Trezise D, Ku P, Lu H, Hsu K-C, Hsu P. Effect of Pharmacist Intervention on a Population in Taiwan With High Healthcare Utilization and Excessive Polypharmacy. Int J Environ Res Public Health. 2019;16(12):2208. https://doi.org/10.3390/ijerph16122208

7. Marciniak A, Kotynia A, Szkatuła D, Krzyżak E. The 2-Hydroxy-3-(4-Aryl-1-Piperazinyl)propyl Phthalimide Derivatives as Prodrugs—Spectroscopic and Theoretical Binding Studies With Plasma Proteins. Int J Mol Sci. 2022;23(13):7003. https://doi.org/10.3390/ijms23137003

8. Tian Y, Yi J, Wang N, Wu C, Peng J, Shao L, et al. DDInter 2.0: An Enhanced Drug Interaction Resource With Expanded Data Coverage, New Interaction Types, and Improved User Interface. Nucleic Acids Res. 2024;53(D1):D1356–62. https://doi.org/10.1093/nar/gkae726

9. Ismail M, Khan S, Khan F, Noor S, Sajid H, Yar S, et al. Prevalence and Significance of Potential Drug-Drug Interactions Among Cancer Patients Receiving Chemotherapy. BMC Cancer. 2020;20(1). https://doi.org/10.1186/s12885-020-06855-9

10. Nabila L, Ejaz S, Madury SA. Drug-Related Problems (DRPs) in Geriatric Patients With Type 2 Diabetes Mellitus (T2DM): A Review. Indonesian Journal of Pharmacology and Therapy. 2022; https://doi.org/10.22146/ijpther.2695

11. Ketema DB, Muchie KF, Andargie AA. Time to Poor Treatment Outcome and Its Predictors Among Drug-Resistant Tuberculosis Patients on Second-Line Anti-Tuberculosis Treatment in Amhara Region, Ethiopia: Retrospective Cohort Study. BMC Public Health. 2019;19(1). https://doi.org/10.1186/s12889-019-7838-2

12. Fuad A, Herwanto GB, Pertiwi AAP, Wahyuningtias SD, Harsini H, Maula AW, et al. Design and Prototype of TOMO: An App for Improving Drug Resistant TB Treatment Adherence. F1000Res. 2021; https://doi.org/10.12688/f1000research.67212.1

13. Bakhori NM, Ismail Z, Hassan MZ, Dolah R. Emerging Trends in Nanotechnology: Aerogel-Based Materials for Biomedical Applications. Nanomaterials. 2023; https://doi.org/10.3390/nano13061063

14. Saputra Y, Widiastuti NA. Knowledge Level With Self-Management and Compliance With Diabetes Mellitus Drug Use in Gading Clinic, Yogyakarta. Jurnal Ilmu Kefarmasian Indonesia. 2022; https://doi.org/10.35814/jifi.v20i2.1211

15. Choy RKM, Huston CD. Cryptosporidiosis Should Be Designated as a Tropical Disease by the US Food and Drug Administration. PLoS Negl Trop Dis. 2020; https://doi.org/10.1371/journal.pntd.0008252