Prescribing practices using WHO prescribing indicators and factors associated with antibiotic prescribing in six community pharmacies in Asmara, Eritrea: a cross-sectional study

Abstract

Background: Antibiotics require more prudent prescribing, dispensing and administration than other medicines because these medicines are at a greater risk of antimicrobial resistance (AMR). Studying the current medicine use practices and factors affecting the prescribing of an antibiotic would help decision makers to draft policies that would enable a more rational use of medicines. Methods: A prospective, descriptive, and cross-sectional study was conducted to assess the current prescribing practices including antibiotics use in six community pharmacies in Asmara. A total of 600 encounters were reviewed using the WHO core prescribing indicators between May 5 and May 12, 2019 using stratified random sampling technique. Descriptive statistics and logistic regression were employed using IBM SPSS® (version 22). Results: The average number of medicines per prescription was 1.76 and 83.14% of the medicines were prescribed using generic names while 98.39% of the medicines were from the National Essential Medicines List (NEML). The percentage of prescriptions containing antibiotics was 53%. The number of encounters containing injections was 7.8%. Patient age, gender and number of medicines prescribed were significantly associated with antibiotic prescribing at bivariate and multivariable models. Subjects under the age of 15 were approximately three times more likely to be prescribed antibiotic compared to subjects whose age is 65 and above (Adjusted Odds Ratio (AOR): 2.93, 95%CI: 1.71-5). Similarly, males were more likely to be prescribed antibiotic than females (AOR: 1.57, 95%CI: 1.10-2.24). Subjects to whom three to four medicines prescribed were two times more likely to be prescribed an antibiotic compared to those who were to be prescribed one to two medicines per encounter (AOR: 2.17, 95%CI: 1.35-3.5). A one-unit increase in the number of medicines increased the odds of antibiotic prescribing increased by 2.02 units (COR: 2.02; 95%CI: 1.62-2.52). Conclusions: This study found that the percentage of antibiotics being prescribed at the community pharmacies in Asmara was 53% which deviated significantly from the WHO recommended values (20-26.8%). Furthermore, the percentage of encounters with an injection was 7.8% lower than the WHO value of 13.4-24.0%. Patients' age, gender and number of medicines were significantly associated with antibiotic prescribing.

Evaluation of Drug Use Pattern in Emergency Department of Dilchora Referral Hospital, Dire Dawa, Ethiopia

“…It is less than the finding in the same studies conducted in the Hawassa University Hospital (96.60%) in the eastern part of the country (92%) and Adama hospital (94.70%) [16,23,24]. It is also less than the studies conducted in Asmera, Eritrea (98.39%), and Saudi Arabia (99.2%) [18,21].…”

“…e average number of drugs per prescription was 2.19. is finding was higher than the standard derived as ideal (1.6-1.8) [7,11]. e finding was also higher than the study done at Hawassa University Hospital, Jimma Hospital, and Dilla University Referral Hospital where the average number of drugs prescribed per encounter was 1.9, 1.76, 1.813, and 1.76, respectively [15][16][17][18]. In this study, the average number of drugs per encounter showed the presence of overprescribing in hospitals, polypharmacy.…”

Identifying antibiotic prescribing patterns through multi-level latent profile analyses: a cross-sectional survey of primary care physicians in Hubei of China

“…Although we did not measure combined use of antibiotics directly because it was rare in primary care, the tendency of combined use of antibiotics was likely to be captured through the connection between the volume (indicator 2) and frequency (indicator 3) indicators [26]. Previous studies showed that higher number of medicines prescribed in general is also a signi cant predictor of higher antibiotic prescriptions [27,28].…”

Identifying antibiotic prescribing patterns through multi-level latent profile analyses: a cross-sectional survey of primary care physicians in Hubei of China

“…Although we did not measure combined use of antibiotics directly because it was rare in primary care, the tendency of combined use of antibiotics was likely to be captured through the connection between the volume (indicator 2) and frequency (indicator 3) indicators [26]. Previous studies showed that higher number of medicines prescribed in general is also a significant predictor of higher antibiotic prescriptions [27,28].…”