Assessment of prescribing practices for respiratory tract infections in public health facilities, Jinja City, Uganda, June 2022–May 2023

Assessment of prescribing practices for respiratory tract infections in public health facilities, Jinja City, Uganda, June 2022–May 2023 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report Assessment of prescribing practices for respiratory tract infections in public health facilities, Jinja City, Uganda, June 2022–May 2023 Zablon K Igirikwayo, Humphreys Mukaga, Richard Migisha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6260139/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Jan, 2026 Read the published version in Discover Public Health → Version 1 posted 12 You are reading this latest preprint version Abstract Background: Rational drug use ensures that medications are prescribed based on clinical needs, appropriate dosages, and for the right duration, minimizing healthcare costs. Irrational antibiotic use is a key driver of antibiotic resistance (ABR) emergence. We evaluated the conformance of drug prescriptions to the World Health Organization (WHO) prescribing indicators among patients with respiratory tract infections (RTIs) attending public health facilities in Jinja City, Uganda. Methods: A retrospective observational study was conducted across 11 public health facilities in Jinja City, Eastern Uganda, from June 1, 2022, to May 31, 2023. Patient records of those diagnosed with RTIs were selected using systematic random sampling. Several prescribing indicators were assessed, including the number of drugs prescribed per patient encounter, the percentage of encounters with antibiotics, the percentage of drugs from the essential drugs list, the percentage of drugs prescribed by generic name, and the percentage of encounters with injectable medications. Data were analyzed for compliance with WHO prescribing standards. Results: Three indicators met or were close to WHO targets: the average number of drugs prescribed per patient (2.7, WHO target <3), the percentage of encounters with injections prescribed (3.0%, WHO target ≤10%), and the percentage of drugs from the essential drugs list (93.4%, WHO target 100%). However, two indicators did not meet WHO recommendations: the percentage of encounters with antibiotics prescribed (79.8%, WHO target <30%) and the percentage of drugs prescribed by generic name (79.5%, WHO target 100%), suggesting irrational prescribing practices. Among patients prescribed antibiotics, most received only one antibiotic (89.1%). Conclusion: This study revealed gaps in adherence to WHO prescribing standards, particularly regarding excessive antibiotic prescriptions for RTIs. These irrational prescribing practices may contribute to the emergence of ABR. There is a need for targeted interventions to promote rational drug use and improve prescribing practices across health facilities in the region. Respiratory tract infections Antibiotic prescription Antibiotic resistance Rational drug use Uganda Figures Figure 1 Figure 2 Figure 3 Introduction Rational drug use is defined as ensuring that patients receive medications appropriate to their clinical needs, in doses tailored to their individual requirements, for the appropriate duration, and at the lowest cost to both the patient and the community [ 1 ]. Medicines are a cornerstone of healthcare systems and represent a significant portion of national budgets, accounting for 10–20% in developed countries and 20–40% in developing countries[ 2 ]. However, irrational drug use is a major challenge that increases government spending on medicines, out-of-pocket costs for patients, and contributes to health risks, including antibiotic resistance (ABR). ABR, driven by the misuse of antibiotics, is a global public health concern, complicating treatment, raising healthcare costs, and causing approximately 1.27 million deaths annually[ 3 – 5 ]. Respiratory tract infections (RTIs), a common and high-prevalence group of diseases, account for 29.8% of outpatient visits in Uganda, and upper respiratory infections contribute 42.8% to the global burden of disease[ 6 , 7 ]. Given the high burden of RTIs, irrational treatment practices can lead to significant resource wastage and exacerbate the problem of ABR. The irrational use of medicines is a long-standing public health challenge, particularly in low- and middle-income countries (LMICs), and it may worsen as the pharmaceutical industry continues to evolve[ 8 ]. In LMICs, poorer households spend approximately 9.5% of their income on medicines, compared to 3.5% in developed countries[ 9 ]. The World Health Organization (WHO) estimates that more than half of all medicines are either prescribed, dispensed, or sold inappropriately, and that many patients fail to adhere to prescribed regimens [ 10 ]. In Uganda, the National Medicines Policy 2015 aims to ensure access to essential medicines while promoting their appropriate use [ 11 ]. Despite these efforts, irrational drug use remains prevalent. For example, only 35% of health workers in public health facilities are able to correctly diagnose common conditions [ 12 ], and in the 2013/2014 financial year, only 31% of upper respiratory tract infections were treated according to standard guidelines [ 11 ]. This reflects broader regional trends, with prescribing indicators in Africa often falling below WHO reference targets[ 13 ]. In Ethiopia, 67.9% of patients with respiratory tract infections were prescribed antibiotics, and studies in Uganda have reported antibiotic prescription rates ranging from 40–80% for RTIs, well above the WHO threshold of less than 30% [ 14 – 16 ]. Moreover, a recent study in Uganda revealed a significant increase in ABR rates across various commonly used antibiotics for both gram-negative and gram-positive organisms[ 17 ]. These trends highlight the need for continuous monitoring of medicine use to identify the causes of irrational drug use and implement effective interventions. Given the limited research on rational drug use in Eastern Uganda, particularly in Jinja City, this study aims to assess the level of rational prescribing among patients with respiratory tract infections in public health facilities using WHO prescribing indicators. METHODOLOGY Study design, setting and study population. The detailed methods for this study have been published previously[ 18 ]. Briefly, we conducted a retrospective observational study involving outpatients from 11 public health facilities in Jinja City, Eastern Uganda, from June 1, 2022, to May 31, 2023. Patient data for those diagnosed with respiratory tract infections (RTIs) were collected from the health facility registers. The selected health facilities included Jinja Regional Referral Hospital (n = 1), four Health Centers IV (n = 4), and six Health Centers III (n = 6). Jinja City's public health system comprises 26 public health facilities, including 13 Health Centers II, 8 Health Centers III, 4 Health Centers IV, and 1 Regional Referral Hospital (RRH). Uganda's healthcare system follows a tiered structure, with Village Health Teams (VHTs) at the community level, followed by Health Centers II, III, IV, general hospitals, regional referral hospitals, and the National Referral Hospital (NRH) at the national level. The staffing and services provided increase with the hierarchy; the lowest-tier health facilities refer patients to higher-level health facilities. Medicines at Uganda's public health facilities are provided by the government at no cost to patients. Inclusion and exclusion criteria We retrieved patient records for patients diagnosed with RTIs from the registers of public health facilities in Jinja City between June 1, 2022, and May 31, 2023. Records with missing information on age, sex, or diagnosis were excluded. Furthermore, records from Health Center IIs (HCIIs) were also excluded, as these facilities only have nurse prescribers who are not trained to prescribe medications within their professional scope. Sample size and sampling procedure. The sample size was determined based on the WHO-recommended minimum of 600 prescriptions for studies evaluating medication use in health facilities, with a requirement of at least 100 prescriptions per facility (WHO, 1993). We selected a total of 1,542 patient records from individuals diagnosed with respiratory tract infections (RTIs), ensuring that the sample size for each facility met the requirement of at least 100 records and that the overall sample included at least 1,100 records from the 11 public health facilities. The sample size for each health facility was calculated based on the RTI patient load during the study period using the following formula: Facility sample size = (total number of RTI outpatients at the facility) / (total number of RTI outpatients across all facilities) × study sample size The total number of patients diagnosed with RTIs in each facility was obtained from the Health Management Information System (HMIS) 105 monthly report, which provides a summary of outpatient diagnoses for each disease condition. Due to logistical constraints, we included only 11 out of the 26 public health facilities in Jinja City. Health Centers III, IV, and the Regional Referral Hospital (RRH) were included as they have qualified prescribers. The only public RRH and all four HCIVs were included due to their unique status in Jinja City. Six out of the eight HCIIIs in Jinja City were selected using simple random sampling. At each selected facility, patient records were randomly chosen from outpatient registers using systematic random sampling. The sampling interval (K) was calculated as: K = N / n where K is the sampling interval, N is the total number of patient records available at the facility, and n is the sample size for that facility. Data Collection and study variables For each RTI patient included, data on facility service level, category of RTI diagnosed, whether antibiotics were prescribed or not, list of antibiotics prescribed, number of antibiotics prescribed, WHO AWaRe category of antibiotics, sum antibiotics, sum of antibiotics and other drugs, total drugs prescribed by generic name and from EDL, number of injection dosages were recorded into the Kobo collect software. This data was used to determine the prescribing indicators and assess their conformance to the WHO standard. These included: average of number of drugs prescribed per patient encounter, percentage of encounter with injections prescribed, percentage of drugs prescribed from essential drugs list, percentage encounter with antibiotics and percentage of drugs prescribed by generic name. The proportion of patients who received one, two or three antibiotics was determined. We also categorized the prescribed antibiotics into the Access, Watch and Reserve groups to determine the most prescribed group. Quality control Our research assistants were health professional workers. We first trained them on how to use the data abstraction form mobilized in kobo collect software and how to be ethical. During the training each research assistant was given an opportunity to practice using the software mobilized tool to enter five patients records. We reviewed the data collected by each research assistant after every one hour for the first three days and thereafter at end of every day. Data analysis: The data was downloaded from the Kobo Collect software, cleaned, and analyzed using a simple calculator to determine the five WHO/INRUD prescribing indicators [ 19 ]. These indicators include the percentage of encounters with antibiotics, the average number of drugs per prescription, the percentage of antibiotics prescribed by generic name, the percentage of antibiotics prescribed from the essential drugs list, and the percentage of encounters with injectables. The calculations followed the WHO guidelines: the average number of drugs per encounter was determined by dividing the total number of drugs prescribed by the number of patients surveyed. The percentage of drugs prescribed by generic name was calculated by dividing the total number of drugs prescribed generically by the total number of drugs prescribed, then multiplying by 100. The percentage of encounters with antibiotics was derived by dividing the number of patients diagnosed with RTIs who were prescribed antibiotics by the total number of RTI patients, and multiplying by 100. Similarly, the percentage of drugs prescribed from the essential drugs list or Uganda Clinical Guidelines was calculated by dividing the number of prescribed drugs listed in the essential drugs list or Uganda Clinical Guidelines by the total number of drugs prescribed, then multiplying by 100. Lastly, the percentage of encounters with injectables was determined by dividing the number of encounters where an injectable was prescribed by the total number of encounters surveyed. We compared these calculated values to the WHO reference ranges for each indicator to assess the quality of prescribing. Any prescribing indicator falling outside the WHO standard was considered a sign of irrational prescribing. The optimal values for these indicators, as used in recent studies such as that of Umar et al [ 20 ] ( Table 1 ). Table 1 showing optimal prescribing indicators and scores. WHO prescribing indicators (percentage) Optimal level (%) Non-polypharmacy prescriptions ≤ 3 Drugs prescribed by generic names 100 Prescriptions with antibiotics ≤ 30 Prescriptions with injections ≤ 10 Drugs prescribed from the Essential Drug List (EDL) 100 We considered the percentage encounter with antibiotics higher than the WHO optimal level (less than 30%) to indicate existence of inappropriate antibiotic prescription for RTIs [ 19 ]. This is because RTIs are largely viral in nature and the optimal value of antibiotic prescription for a majority of them accept for bronchitis and pneumonia is < 20% [ 21 ]. A higher cut off was preferred since there was no assessment of the basis for antibiotic prescription for the individual patients and to guarantee that any values higher than 30% would undoubtably indicate inappropriate antibiotic prescription for RTIs. We compared the percentage encounter of antibiotics across facility service levels to get snap shot of any possible difference in the of appropriateness of antibiotic prescription for RTI outpatients across the same and different facility service level. Results A total of 1,542 outpatient records with a diagnosis of RTIs were analyzed. The majority of patients (55.0%) were female, and most sought care from HCIVs (44.9%) and HCIIIs (43.7%) (Table 2 ). Table 2 Socio-demographic characteristics of study participants and prevalence of respiratory tract infections. Variable Frequencies (N = 1,542) Percentages (%) Health facility HCIIIs 675 43.7 HCIVs 691 44.9 Referral Hospital 176 11.4 Sex Male 694 45.0 Female 848 55.0 Age (years) 30 354 23.0 RTI diagnosed Pneumonia 65 4.2 Un-categorized acute RTI 551 35.7 Acute pharyngitis 57 3.7 common cold 250 16.2 acute tonsillitis 41 2.7 Un-categorized upper RTI 403 26.1 Acute bronchitis 37 2.4 Acute laryngitis 8 0.5 Acute sinusitis 5 0.3 Chronic RTI 7 0.5 Cough 49 3.2 Influenza 26 1.7 Un-categorized lower RTI 24 1.6 Acute otitis media 19 1.2 HC: Health center, RTI: Respiratory tract infection Assessment of use of antibiotics. Out of the 1,542 patient records reviewed, 79.8% (n = 1,230) received antibiotics. Most patients received one antibiotic (89.1%, n = 1,096), while a minority received two antibiotics (10.4%, n = 128). Instances where > 3 antibiotics were prescribed were rare (0.5%) (Fig. 1 ). A total of 1,387 antibiotics were prescribed, averaging approximately one antibiotic per patient (Fig. 1 ). The majority of prescribed antibiotics belonged to the Access group (86.6%; n = 1,197) (Fig. 2 ), with Amoxicillin being the most commonly prescribed drug (50.45%; n = 700), followed by cotrimoxazole (17.3%; n = 340) (Fig. 3 ). Evaluation of the quality of prescribing Overall, the quality of prescribing across all facility service levels was suboptimal, as indicated by the WHO prescribing indicators. Three indicators met WHO standards: the average number of drugs per patient (2.7), percentage of encounters with injections (3.0%), and percentage of drugs from the essential drugs list (93.4%) (Table 3 ). However, two indicators did not meet standards: percentage of drugs prescribed by generic names (79.5% vs. WHO standard of 100%) and percentage of patients encountering antibiotics (79.8% vs. WHO standard of < 30%). Table 3 Prescribing indicator scores at public facilities in Jinja City, Eastern Uganda, June 1, 2022 to May 31, 2023 Prescribing indicator Overall for all health facilities Regional Referral Hospital HCIVs HCIIIs WHO Optimal value. Total number of Patients 1542 176 691 675 Patient encounter with antibiotic prescribed 1230 130 531 569 Sum of drugs prescribed 4224 437 1918 1869 Drugs prescribed by generic name 3357 315 1510 1532 Drugs from essential drugs list 3947 405 1805 1737 Encounter with injections dosages prescribed. 47 1 25 21 Percentage encounter with antibiotics. 79.8 73.9 76.9 84.3 < 30% Number of drugs prescribed per patient encounter 2.7 2.5 2.8 2.8 < 3 Percentage of drugs prescribed by generic name. 79.5% 72.4% 78.7 82.2% 100% Percentage of encounter with injections prescribed. 3.0% 0.6% 3.6% 3.1% ≤ 10 Percentage of drugs prescribed from essential drugs list 93.4% 92.7% 94.1% 92.9% 100% Discussion The study assessed the quality of prescribing based on the WHO prescribing indicators among patients with RTIs seeking ambulatory care at public health facilities in Jinja City. Overall, the results revealed suboptimal prescribing practices, with only three out of five indicators conforming to or closely aligning with WHO standards. The prescribing indictors that conformed to the WHO standard were average of number of drugs prescribed per patient encounter, percentage of encounter with injections prescribed and percentage of drugs prescribed from essential drugs list. However, the percentage encounter with antibiotics (79.8%) and percentage of drugs prescribed by generic name (79.5%) did not conform. In this study, the average number of drugs prescribed per patient encounter were 2.7 of which 1 was an antibiotic. This conformed to the WHO standard of less than 3.0 drugs [ 19 ]. However, this does not necessarily indicate rational prescribing, given that as respiratory tract infections (RTIs) are primarily viral and often only require supportive treatment. Ideally, the number of drugs prescribed should have been lower. Therefore, the observed figure suggests over-prescription. The average of 2.7 drugs per encounter in this study was comparable to findings in Mbarara City Southwestern Uganda (2.5), indicating that factors contributing to over-prescription in patients with RTIs, across Uganda may be similar and could benefit from similar targeted interventions [ 22 ]. In contrast, the average number of drugs prescribed in this study was higher than in Eritrea (1.8) [ 23 ], and Tanzania (1.99) [ 24 ] but lower than what was reported in systematic studies in Africa (3.1) [ 13 ], India (3.08) [ 25 ] and in Changarupattu, Tamil Nadu, India by Raja [ 26 ] (3.7). The lower prescribing rate in Eritrea may be attributed to the presence of government-owned community pharmacies, which provide medications for patients who cannot obtain them at public health facilities. The higher prescribing rates observed in Africa and India could be due to differences in healthcare settings, regulations, and controls. Increasing awareness among patients about the risks of overuse of medications and improving access to essential medicines at public health facilities may promote rational prescribing practices[ 27 ]. The prescription of medicines from the Essential Drugs List (EDL) is associated with higher quality of care, better management of medicines, more cost-effective use of available resources, and adherence to prescribing regulations[ 28 ]. In this study, the percentage of drugs prescribed from the EDL was 93.4%, which closely aligns with the WHO standard of 100%. This figure is higher than what was observed in Bushenyi District, Western Uganda (79.0%) [ 16 ], the WHO African Region (88%) [ 13 ], Afghanistan 67% [ 29 ] and in most studies done in Ethiopia up to the year 2020, < 92% [ 30 ]. The lower percentage in Bushenyi could be attributed to the study being conducted in a private hospital, which has more flexibility in determining its medicine requirements. In contrast, public hospitals, where all drugs are procured and provided by the government, are more likely to adhere to the EDL. This is supported by findings from a systematic study in Africa, which showed poorer prescribing indicators in private facilities compared to public ones[ 13 ]. Interestingly, a study in Eritrea reported 98.4% of drugs being prescribed from the EDL[ 23 ], reflecting a strong adherence to the list. The lower percentage in Afghanistan could be because of the poor health indicators of weak health system after many years of war. On the other hand, studies reporting higher adherence to the EDL, closer to or equal to the WHO standard, include those from Cameroon (99.9%) [ 31 ], Eretria (98.4%) [ 23 ] [ 32 ], Sri lanka (98.9%) [ 33 ], North-West Ethiopia 95.3% [ 34 ], Ethiopia (100%) [ 35 ], Jordanian (99.8%) [ 36 ], and Saudi Arabia (100%) [ 37 ]. A systematic review of 42 studies in India found that only 2.4% adhered to 100% EDL prescriptions, indicating that very few settings fully comply with the WHO standard[ 25 ]. This highlights the need for stronger health policies to support adherence to the EDL. In this study, the percentage of drugs prescribed by generic name was 79.5%, which fell short of the WHO standard of 100%. This figure was lower than the percentages observed in Bushenyi (90.2%) and Mbarara (84%) districts in Uganda [ 22 , 38 ], Cameroon (98.4%) [ 31 ], Ethiopia (97.6%) [ 35 ], Eritrea (83.1%) [ 23 ], Sri lanka (84.3%) [ 33 ] but higher than that in Rivers state, Nigeria 43.7% [ 32 ], WHO African region (68.0%) [ 13 ], Afghanistan 35.1% [ 29 ], Nigerian study [ 39 ], Saudi Arabia [ 37 ], and Jordan [ 36 ]. Notably, the deviation from the WHO standard was more pronounced for the prescription of generic names than for drugs prescribed from the EDL. This could be attributed to widespread skepticism among prescribers regarding the quality and efficacy of various brands available in the market, prompting them to favor specific brands they trust [ 40 ]. In our study, the percentage of encounters with antibiotics was 79.8%, which exceeds the WHO standard of 30%. This high rate suggests a significant level of irrational prescribing, especially given that the study focused on RTIs, which are predominantly viral. Compared to other studies, our rate was higher than those observed in Japan (49.2%) [ 41 ], South Korea 30.6%, [ 42 ], Bahrain (31.8%) [ 43 ], Malta (45%) [ 44 ] and Pakistan (69.8)[ 45 ]. It was also higher than studies conducted in Uganda, including those in Kampala (43%) [ 46 ], and Mbarara City (70%) [ 47 ]. The rate was however lower than that in Ecuador, (90.3%)[ 48 ], and Vietnam (97.0%) [ 49 ]. This trend suggests that developed countries generally have lower antibiotic prescription rates for RTIs, likely due to stricter prescribing regulations, robust antibiotic stewardship programs, and clear treatment guidelines, such as the National Institute for Health and Care Excellence (NICE) guidelines in the UK. In China, earlier studies reported antibiotic prescription rates exceeding 80%[ 50 ], but more recent studies show a decline. For instance, a nationwide study among upper respiratory tract infection (URTI) outpatients found a prescription rate of 40.8%, while a retrospective study on pediatric patients reported a much lower rate of 27.1%[ 51 ]. The average number of antibiotics per patient in our study was approximately 1.0. This was high given that each patient approximately got one antibiotic for an RTI that was most likely viral in nature. This was lower than what was reported in by other studies like Saudi Arabia, 1.26[ 37 ], Jordan (2.9) [ 36 ], Ethiopia (2.0) [ 35 ] and Cameroon (1.14) [ 31 ] reported the number of antibiotics prescribed to be 1.6. However, these studies often included a broader range of patients, not solely those with RTIs, which could explain the higher average in those settings. Although the average number of antibiotics prescribed for RTIs in our study is lower than for other morbidities, RTIs, due to their higher prevalence, likely consume a significant share of antibiotics prescribed across health care settings. Strengths and limitations of the study One limitation of this study was the inability to reassess patients clinically or use laboratory or point-of-care diagnostic tests for RTIs, which would have helped evaluate the prescriber's rationale for antibiotic prescriptions. As a retrospective study, patient histories could only be retrieved from existing records, and direct clinical assessments were not possible. Prospective studies, which could have provided more detailed information, were not conducted due to the potential for the Hawthorne effect [ 52 ]. A strength of the study was the large sample size of 1,542 patient records, well-distributed across 11 health facilities, which exceeded the WHO's recommended minimum of 600 records. Furthermore, the study covered all months of the annual calendar, ensuring that seasonal variations in RTI severity did not unduly influence the findings. Conclusion This study revealed significant irrational prescribing practices for RTI patients, with antibiotics being frequently and inappropriately prescribed. Such practices not only elevate the risk of antibiotic resistance (ABR) but also contribute to unnecessary healthcare costs. To address these challenges, it is crucial to implement targeted interventions that focus on improving the rational use of antibiotics. We recommend enhancing prescriber training on the appropriate use of antibiotics, strengthening antibiotic stewardship programs, and promoting the use of diagnostic tools to differentiate between bacterial and viral infections. Additionally, raising awareness among healthcare providers about the importance of adhering to national prescribing guidelines could help reduce unnecessary antibiotic prescriptions. Future research is recommended to investigate the factors contributing to the lower percentage of drugs prescribed from the Essential Drugs List (EDL) in this setting. Such studies would provide valuable insights to develop effective strategies to optimize prescribing practices and ensure more consistent adherence to national health policies. Abbreviations ABR antibiotic resistance EDL Essential drugs list HC Health Center RTI Respiratory tract infections WHO World Health Organization Declarations Ethical approval and consent to participate Approval to conduct this study was sought and approved by Mbarara University of Science and Technology Research and Ethics Committee (MUST-REC): reference number MUST- 2023-814. The study was also approved by National Council of Science and Technology under registration number. HS3499ES. Permission to conduct the study in public facilities Jinja City was thought from the City health officer of Jinja City and the Director of Jinja Regional Referral Hospital. Patient name and other identifiers were concealed throughout the study. Consent for publication Not applicable Competing interests The authors declare no competing interest. Acknowledgements We extend great appreciation to the City Health Officer and the Director Jinja Regional Referral Hospital who permitted the study to be done in Public Health facilities in Jinja City. Author Contributions ZKI conceptualized and designed the study, collected the data and drafted the manuscript. HM designed the software for data collection. ZKI, RM and HM contributed to the, analysis, interpretation of data and discussion of the results. ZIG drafted the manuscript while RM critically reviewed and revised it. All authors approved the final version of the manuscript. ZKI, RM and HM are personally accountable for the integrity of this work. Funding The authors didn’t receive any funding to do the research or publish the findings. Availability of data and materials The excel data sheet of the collected data used to arrive at the conclusions can be availed on request to the corresponding Author through his email: [email protected] Author details 1 Department of Community Health, Mbarara University of Science and Technology, Mbarara, Uganda 2 Department of Physiology, Mbarara University of Science and Technology, Mbarara, Uganda 3 Department of disease control and environmental health, Makerere University school of public health Email: [email protected] *Correspondence: Department of Community Health, Mbarara University of Science and Technology, Mbarara, P.O Box 1410, Uganda, Tel: +256782024793; Email: [email protected] References Organization, W.H., WRational drug use of medicines: Progress in implementing the WHO medicines strategy report by the secretariat. Executive board 118th session provisional agenda item 5.3. 2006. Yenet, A., G. Nibret, and B.A. Tegegne, Challenges to the availability and affordability of essential medicines in African countries: a scoping review. ClinicoEconomics and Outcomes Research, 2023: p. 443-458. WHO, The growing public health burden of antimicrobial resistance. . 2021. Kasimanickam, V., M. Kasimanickam, and R. Kasimanickam, Antibiotics use in food animal production: escalation of antimicrobial resistance: where are we now in combating AMR? Medical Sciences, 2021. 9 (1): p. 14. Poudel, A.N., et al., The economic burden of antibiotic resistance: A systematic review and meta-analysis. Plos one, 2023. 18 (5): p. e0285170. Health, M.o., Annual health sector performance report financial year 2019/2020. . 2021. Jin, X., et al., Global burden of upper respiratory infections in 204 countries and territories, from 1990 to 2019. EClinicalMedicine, 2021. 37 . IMS institute for health informatics, Global medicines use in 2020 outllook and implications. 2015. Wagner, A.K., et al., Access to care and medicines, burden of health care expenditures, and risk protection: results from the World Health Survey. Health policy, 2011. 100 (2-3): p. 151-158. WHO, Health products policy and standards. 2024. Health, M.o., National medicines Policy. Available at: https://www.health.go.ug/ . 2015. Wane, W. and G. Martin, Education and health services in Uganda: data for results and accountability. 2013. Ofori-Asenso, R., P. Brhlikova, and A.M. Pollock, Prescribing indicators at primary health care centers within the WHO African region: a systematic analysis (1995–2015). BMC public health, 2016. 16 : p. 1-14. Goruntla, N., et al., Evaluation of rational drug use based on who/inrud core drug use indicators in a secondary care hospital: a cross-sectional study in western Uganda. Drug, Healthcare and Patient Safety, 2023: p. 125-135. Lanyero, H., et al., Use of antibacterials in the management of symptoms of acute respiratory tract infections among children under five years in Gulu, northern Uganda: Prevalence and determinants. PloS one, 2020. 15 (6): p. e0235164. Sekoni, K.F., I.A. Oreagba, and F.A. Oladoja, Antibiotic utilization study in a teaching hospital in Nigeria. JAC-Antimicrobial Resistance, 2022. 4 (5): p. dlac093. Namubiru, S., et al., Increasing trends of antibiotic resistance in Uganda: analysis of the national antimicrobial resistance surveillance data, 2018–2021. BMC Infectious Diseases, 2024. 24 (1): p. 930. Igirikwayo, Z.K., et al., Prescription patterns of antibiotics and associated factors among outpatients diagnosed with respiratory tract infections in Jinja city, Uganda, June 2022–May 2023. BMC Pulmonary Medicine, 2024. 24 (1): p. 446. Organization, W.H., How to investigate drug use in health facilities: selected drug use indicators . 1993, World Health Organization. Umar, L.W., et al., Outpatient prescribing and antibiotic use for children in a tertiary hospital. Sahel Medical Journal, 2020. 23 (2): p. 109-115. Adriaenssens, N., et al., European Surveillance of Antimicrobial Consumption (ESAC): disease-specific quality indicators for outpatient antibiotic prescribing. BMJ quality & safety, 2011. 20 (9): p. 764-772. Muwanguzi, T.E., T.M. Yadesa, and A.G. Agaba, Antibacterial prescription and the associated factors among outpatients diagnosed with respiratory tract infections in Mbarara Municipality, Uganda. BMC Pulmonary Medicine, 2021. 21 : p. 1-11. Amaha, N.D., et al., Prescribing practices using WHO prescribing indicators and factors associated with antibiotic prescribing in six community pharmacies in Asmara, Eritrea: a cross-sectional study. Antimicrobial Resistance & Infection Control, 2019. 8 : p. 1-7. Kilipamwambu, A., et al., WHO/INRUD core prescribing indicators and antibiotic utilization patterns among primary health care facilities in Ilala district, Tanzania. JAC-Antimicrobial Resistance, 2021. 3 (2): p. dlab049. Gujar, A., V. Gulecha, and A. Zalte, Drug utilization studies using WHO prescribing indicators from India: a systematic review. Health Policy and Technology, 2021. 10 (3): p. 100547. Raja, D. and S. Sasithra, Assessment of the Antibiotics and Other Drug Prescribing Patterns in a Primary Health Care Setting. Journal of Communicable Diseases (E-ISSN: 2581-351X & P-ISSN: 0019-5138), 2021. 53 (4): p. 70-75. Duan, L., et al., The vicious cycle of the public's irrational use of antibiotics for upper respiratory tract infections: A mixed methods systematic review. Frontiers in Public Health, 2022. 10 : p. 985188. Kar, S.S., H.S. Pradhan, and G.P. Mohanta, Concept of essential medicines and rational use in public health. Indian Journal of Community Medicine, 2010. 35 (1): p. 10-13. Habibyar, A.F. and Q.A. Nazari, Evaluation of prescribing patterns using WHO core drug use indicators in a pediatric hospital of Kabul Afghanistan: A prospective cross-sectional study. Heliyon, 2023. 9 (11). Mamo, D.B. and B.K. Alemu, Rational drug-use evaluation based on World Health Organization core drug-use indicators in a tertiary referral hospital, Northeast Ethiopia: a cross-sectional Study. Drug, Healthcare and Patient Safety, 2020: p. 15-21. Anong, D.N. and J.-F.K. Akoachere, Prescribing patterns and associated factors of antibiotic prescription in primary health care facilities of Kumbo East and Kumbo West Health Districts, North West Cameroon. PloS one, 2018. 13 (3): p. e0193353. Samuel, O.K., Z. Zorte, and O.D. Samuel, Quality of Drug Prescription and Dispensing Practices in a Teaching Hospital in a developing country. medRxiv, 2023: p. 2023.03. 03.23286781. Ranasinghe, P., et al., National survey on World Health Organization/International Network of Rational Use of Drugs core drug use indicators in the outpatient setting and availability of medicines in a developing South Asian country. Journal of Pharmaceutical Health Services Research, 2022. 13 (2): p. 158-165. Yimenu, D.K., et al., Assessment of antibiotic prescribing patterns at outpatient pharmacy using World Health Organization prescribing indicators. Journal of primary care & community health, 2019. 10 : p. 2150132719886942. Demoz, G.T., et al., Prescribing pattern of antibiotics using WHO prescribing indicators among inpatients in Ethiopia: a need for antibiotic stewardship program. Infection and Drug Resistance, 2020: p. 2783-2794. Al-Azayzih, A., et al., Evaluation of drug-prescribing patterns based on the WHO prescribing indicators at outpatient clinics of five hospitals in Jordan: a cross-sectional study. Int J Clin Pharmacol Ther, 2017. 55 (5): p. 425-432. Alanazi, M.Q., et al., An evaluation of antibiotics prescribing patterns in the emergency department of a tertiary care hospital in Saudi Arabia. Infection and Drug Resistance, 2019: p. 3241-3247. Adedapo, A.D. and O.O. Akunne, Patterns of antimicrobials prescribed to patients admitted to a tertiary care hospital: a prescription quality audit. Cureus, 2021. 13 (6). Ilori, T. and O. Odeyinka, Drug Prescription Pattern in a Primary Care Clinic, Southwest, Nigeria. Journal of Drug Delivery and Therapeutics, 2022. 12 (3): p. 74-79. Ofori-Asenso, R., A closer look at the World Health Organization's prescribing indicators. Journal of Pharmacology and Pharmacotherapeutics, 2016. 7 (1): p. 51-54. Araki, Y., et al., Prescription pattern analysis for antibiotics in working-age workers diagnosed with common cold. Scientific Reports, 2021. 11 (1): p. 22701. Kim, Y.C., et al., Prescriptions patterns and appropriateness of usage of antibiotics in non-teaching community hospitals in South Korea: a multicentre retrospective study. Antimicrobial Resistance & Infection Control, 2022. 11 (1): p. 40. Sulis, G., et al., Antibiotic prescription practices in primary care in low-and middle-income countries: a systematic review and meta-analysis. PLoS medicine, 2020. 17 (6): p. e1003139. Saliba-Gustafsson, E.A., et al., Barriers and facilitators to prudent antibiotic prescribing for acute respiratory tract infections: a qualitative study with general practitioners in Malta. PLoS One, 2021. 16 (2): p. e0246782. Hashmi, H., et al., Prescribing patterns for upper respiratory tract infections: a prescription-review of primary care practice in Quetta, Pakistan and the implications. Frontiers in Public Health, 2021. 9 : p. 787933. Kizito, M., et al., Antibiotic consumption and utilization at a large tertiary care level hospital in Uganda: A point prevalence survey. PloS one, 2025. 20 (1): p. e0313587. Kagoya, E.K., et al., Experiences and views of healthcare professionals on the prescription of antibiotics in Eastern Uganda: A qualitative study. Journal of global antimicrobial resistance, 2021. 25 : p. 66-71. Sánchez Choez, X., M.L. Armijos Acurio, and R.E. Jimbo Sotomayor, Appropriateness and adequacy of antibiotic prescription for upper respiratory tract infections in ambulatory health care centers in Ecuador. BMC Pharmacology and Toxicology, 2018. 19 : p. 1-11. Van An, N., et al., Distribution and antibiotic resistance characteristics of bacteria isolated from blood culture in a teaching hospital in Vietnam during 2014–2021. Infection and Drug Resistance, 2023: p. 1677-1692. Zhao, H., et al., Appropriateness of antibiotic prescriptions in ambulatory care in China: a nationwide descriptive database study. The Lancet Infectious Diseases, 2021. 21 (6): p. 847-857. Xue, F., et al., Antibiotic prescriptions for children younger than 5 years with acute upper respiratory infections in China: a retrospective nationwide claims database study. BMC infectious diseases, 2021. 21 : p. 1-10. McCambridge, J., J. Witton, and D.R. Elbourne, Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. Journal of clinical epidemiology, 2014. 67 (3): p. 267-277. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Jan, 2026 Read the published version in Discover Public Health → Version 1 posted Editorial decision: Revision requested 11 Jul, 2025 Reviews received at journal 30 Jun, 2025 Reviewers agreed at journal 30 Jun, 2025 Reviews received at journal 28 May, 2025 Reviewers agreed at journal 16 May, 2025 Reviews received at journal 10 May, 2025 Reviewers agreed at journal 09 May, 2025 Reviewers agreed at journal 09 May, 2025 Reviewers invited by journal 09 May, 2025 Editor assigned by journal 07 May, 2025 Submission checks completed at journal 30 Apr, 2025 First submitted to journal 30 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6260139","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":455258057,"identity":"b8bde690-efdd-464e-b487-6e7ad72bb8b1","order_by":0,"name":"Zablon K Igirikwayo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYFACHsYDDAwScvzsDUCOgQVRWhiAWiyMJXsOgLRIEK2lInHDjAQQjwgt8u1nDxz4uEOCcYPk86sbfhRIMPC3dyfg1cLYk5dwcOYZCWZz6Zyymz1Ah0mcObsBrxZmhhyDw7xtEmyWs3PSbvAAtRhI5OLXwsb/BqyFx+DmmbSbf4jRwiMBsUXC4Ab7sdtE2SIh8Q7olzYJA8meHLbbMgYSPAT9It+fe/DBx7a6+n72489uvvljI8ff3otfC7IbDcAkscpBgP0BKapHwSgYBaNgBAEA5HdHbpZeRQcAAAAASUVORK5CYII=","orcid":"","institution":"Mbarara University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Zablon","middleName":"K","lastName":"Igirikwayo","suffix":""},{"id":455258058,"identity":"32e282b2-415b-4d21-9d1f-129f6d56d6ab","order_by":1,"name":"Humphreys Mukaga","email":"","orcid":"","institution":"Makerere University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Humphreys","middleName":"","lastName":"Mukaga","suffix":""},{"id":455258059,"identity":"2dd67357-1fc0-4636-9d29-592bdc74db92","order_by":2,"name":"Richard Migisha","email":"","orcid":"","institution":"Mbarara University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Migisha","suffix":""}],"badges":[],"createdAt":"2025-03-19 09:38:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6260139/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6260139/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12982-026-01425-z","type":"published","date":"2026-01-30T15:59:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82793675,"identity":"3e979813-4529-41f1-95ef-d3fd5f8b99a7","added_by":"auto","created_at":"2025-05-15 10:26:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20339,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercentage of patients with RTIs who encountered a certain number of antibiotics in public health facilities, Jinja City, Uganda, June 1, 2022 to May 31, 2023\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6260139/v1/54bc4ba808618cdd767d9c18.png"},{"id":82793672,"identity":"ca0d6705-9103-4558-b4c8-03bc8c6c23ff","added_by":"auto","created_at":"2025-05-15 10:26:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63264,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of Antibiotics prescribed by WHO AWaRe group to patients with respiratory tract infections, in public health facilities, Jinja City, Uganda, June 1, 2022 to May 31, 2023\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6260139/v1/4a85b23a5f44c3827689c5a9.png"},{"id":82795240,"identity":"4b20b62c-cfd8-438b-a495-e07872f3a2cd","added_by":"auto","created_at":"2025-05-15 10:34:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31513,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of specific antibiotics prescribed for out-patients with RTI in public health facilities in Jinja City from June 1, 2022 to May 31, 2023.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6260139/v1/591ba713187789e5ee8bf838.png"},{"id":101690890,"identity":"ddcd0b1c-3193-4485-b614-d360f44cf01a","added_by":"auto","created_at":"2026-02-02 16:10:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1216683,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260139/v1/48503e76-b5fe-4444-8b4f-665794d4095a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssessment of prescribing practices for respiratory tract infections in public health facilities, Jinja City, Uganda, June 2022–May 2023\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRational drug use is defined as ensuring that patients receive medications appropriate to their clinical needs, in doses tailored to their individual requirements, for the appropriate duration, and at the lowest cost to both the patient and the community [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Medicines are a cornerstone of healthcare systems and represent a significant portion of national budgets, accounting for 10\u0026ndash;20% in developed countries and 20\u0026ndash;40% in developing countries[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, irrational drug use is a major challenge that increases government spending on medicines, out-of-pocket costs for patients, and contributes to health risks, including antibiotic resistance (ABR). ABR, driven by the misuse of antibiotics, is a global public health concern, complicating treatment, raising healthcare costs, and causing approximately 1.27\u0026nbsp;million deaths annually[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Respiratory tract infections (RTIs), a common and high-prevalence group of diseases, account for 29.8% of outpatient visits in Uganda, and upper respiratory infections contribute 42.8% to the global burden of disease[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Given the high burden of RTIs, irrational treatment practices can lead to significant resource wastage and exacerbate the problem of ABR. The irrational use of medicines is a long-standing public health challenge, particularly in low- and middle-income countries (LMICs), and it may worsen as the pharmaceutical industry continues to evolve[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In LMICs, poorer households spend approximately 9.5% of their income on medicines, compared to 3.5% in developed countries[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The World Health Organization (WHO) estimates that more than half of all medicines are either prescribed, dispensed, or sold inappropriately, and that many patients fail to adhere to prescribed regimens [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Uganda, the National Medicines Policy 2015 aims to ensure access to essential medicines while promoting their appropriate use [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Despite these efforts, irrational drug use remains prevalent. For example, only 35% of health workers in public health facilities are able to correctly diagnose common conditions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and in the 2013/2014 financial year, only 31% of upper respiratory tract infections were treated according to standard guidelines [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This reflects broader regional trends, with prescribing indicators in Africa often falling below WHO reference targets[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In Ethiopia, 67.9% of patients with respiratory tract infections were prescribed antibiotics, and studies in Uganda have reported antibiotic prescription rates ranging from 40\u0026ndash;80% for RTIs, well above the WHO threshold of less than 30% [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, a recent study in Uganda revealed a significant increase in ABR rates across various commonly used antibiotics for both gram-negative and gram-positive organisms[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These trends highlight the need for continuous monitoring of medicine use to identify the causes of irrational drug use and implement effective interventions. Given the limited research on rational drug use in Eastern Uganda, particularly in Jinja City, this study aims to assess the level of rational prescribing among patients with respiratory tract infections in public health facilities using WHO prescribing indicators.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e \u003cb\u003eStudy design, setting and study population.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe detailed methods for this study have been published previously[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Briefly, we conducted a retrospective observational study involving outpatients from 11 public health facilities in Jinja City, Eastern Uganda, from June 1, 2022, to May 31, 2023. Patient data for those diagnosed with respiratory tract infections (RTIs) were collected from the health facility registers. The selected health facilities included Jinja Regional Referral Hospital (n\u0026thinsp;=\u0026thinsp;1), four Health Centers IV (n\u0026thinsp;=\u0026thinsp;4), and six Health Centers III (n\u0026thinsp;=\u0026thinsp;6). Jinja City's public health system comprises 26 public health facilities, including 13 Health Centers II, 8 Health Centers III, 4 Health Centers IV, and 1 Regional Referral Hospital (RRH). Uganda's healthcare system follows a tiered structure, with Village Health Teams (VHTs) at the community level, followed by Health Centers II, III, IV, general hospitals, regional referral hospitals, and the National Referral Hospital (NRH) at the national level. The staffing and services provided increase with the hierarchy; the lowest-tier health facilities refer patients to higher-level health facilities. Medicines at Uganda's public health facilities are provided by the government at no cost to patients.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eWe retrieved patient records for patients diagnosed with RTIs from the registers of public health facilities in Jinja City between June 1, 2022, and May 31, 2023. Records with missing information on age, sex, or diagnosis were excluded. Furthermore, records from Health Center IIs (HCIIs) were also excluded, as these facilities only have nurse prescribers who are not trained to prescribe medications within their professional scope.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample size and sampling procedure.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sample size was determined based on the WHO-recommended minimum of 600 prescriptions for studies evaluating medication use in health facilities, with a requirement of at least 100 prescriptions per facility (WHO, 1993). We selected a total of 1,542 patient records from individuals diagnosed with respiratory tract infections (RTIs), ensuring that the sample size for each facility met the requirement of at least 100 records and that the overall sample included at least 1,100 records from the 11 public health facilities.\u003c/p\u003e \u003cp\u003eThe sample size for each health facility was calculated based on the RTI patient load during the study period using the following formula:\u003c/p\u003e \u003cp\u003e \u003cb\u003eFacility sample size\u003c/b\u003e = (total number of RTI outpatients at the facility) / (total number of RTI outpatients across all facilities) \u0026times; study sample size\u003c/p\u003e \u003cp\u003eThe total number of patients diagnosed with RTIs in each facility was obtained from the Health Management Information System (HMIS) 105 monthly report, which provides a summary of outpatient diagnoses for each disease condition. Due to logistical constraints, we included only 11 out of the 26 public health facilities in Jinja City. Health Centers III, IV, and the Regional Referral Hospital (RRH) were included as they have qualified prescribers. The only public RRH and all four HCIVs were included due to their unique status in Jinja City. Six out of the eight HCIIIs in Jinja City were selected using simple random sampling.\u003c/p\u003e \u003cp\u003eAt each selected facility, patient records were randomly chosen from outpatient registers using systematic random sampling. The sampling interval (K) was calculated as:\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eK = N / n\u003c/h3\u003e\n\u003cp\u003ewhere \u003cb\u003eK\u003c/b\u003e is the sampling interval, \u003cb\u003eN\u003c/b\u003e is the total number of patient records available at the facility, and \u003cb\u003en\u003c/b\u003e is the sample size for that facility.\u003c/p\u003e\n\u003ch3\u003eData Collection and study variables\u003c/h3\u003e\n\u003cp\u003eFor each RTI patient included, data on facility service level, category of RTI diagnosed, whether antibiotics were prescribed or not, list of antibiotics prescribed, number of antibiotics prescribed, WHO AWaRe category of antibiotics, sum antibiotics, sum of antibiotics and other drugs, total drugs prescribed by generic name and from EDL, number of injection dosages were recorded into the Kobo collect software. This data was used to determine the prescribing indicators and assess their conformance to the WHO standard. These included: average of number of drugs prescribed per patient encounter, percentage of encounter with injections prescribed, percentage of drugs prescribed from essential drugs list, percentage encounter with antibiotics and percentage of drugs prescribed by generic name. The proportion of patients who received one, two or three antibiotics was determined. We also categorized the prescribed antibiotics into the Access, Watch and Reserve groups to determine the most prescribed group.\u003c/p\u003e\n\u003ch3\u003eQuality control\u003c/h3\u003e\n\u003cp\u003eOur research assistants were health professional workers. We first trained them on how to use the data abstraction form mobilized in kobo collect software and how to be ethical. During the training each research assistant was given an opportunity to practice using the software mobilized tool to enter five patients records. We reviewed the data collected by each research assistant after every one hour for the first three days and thereafter at end of every day.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis:\u003c/h2\u003e \u003cp\u003eThe data was downloaded from the Kobo Collect software, cleaned, and analyzed using a simple calculator to determine the five WHO/INRUD prescribing indicators [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These indicators include the percentage of encounters with antibiotics, the average number of drugs per prescription, the percentage of antibiotics prescribed by generic name, the percentage of antibiotics prescribed from the essential drugs list, and the percentage of encounters with injectables. The calculations followed the WHO guidelines: the average number of drugs per encounter was determined by dividing the total number of drugs prescribed by the number of patients surveyed. The percentage of drugs prescribed by generic name was calculated by dividing the total number of drugs prescribed generically by the total number of drugs prescribed, then multiplying by 100. The percentage of encounters with antibiotics was derived by dividing the number of patients diagnosed with RTIs who were prescribed antibiotics by the total number of RTI patients, and multiplying by 100. Similarly, the percentage of drugs prescribed from the essential drugs list or Uganda Clinical Guidelines was calculated by dividing the number of prescribed drugs listed in the essential drugs list or Uganda Clinical Guidelines by the total number of drugs prescribed, then multiplying by 100. Lastly, the percentage of encounters with injectables was determined by dividing the number of encounters where an injectable was prescribed by the total number of encounters surveyed.\u003c/p\u003e \u003cp\u003eWe compared these calculated values to the WHO reference ranges for each indicator to assess the quality of prescribing. Any prescribing indicator falling outside the WHO standard was considered a sign of irrational prescribing. The optimal values for these indicators, as used in recent studies such as that of Umar et al [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] ( Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eshowing optimal prescribing indicators and scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO prescribing indicators (percentage)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimal level (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-polypharmacy prescriptions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs prescribed by generic names\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescriptions with antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescriptions with injections\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs prescribed from the Essential Drug List (EDL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe considered the percentage encounter with antibiotics higher than the WHO optimal level (less than 30%) to indicate existence of inappropriate antibiotic prescription for RTIs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This is because RTIs are largely viral in nature and the optimal value of antibiotic prescription for a majority of them accept for bronchitis and pneumonia is \u0026lt;\u0026thinsp;20% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A higher cut off was preferred since there was no assessment of the basis for antibiotic prescription for the individual patients and to guarantee that any values higher than 30% would undoubtably indicate inappropriate antibiotic prescription for RTIs.\u003c/p\u003e \u003cp\u003eWe compared the percentage encounter of antibiotics across facility service levels to get snap shot of any possible difference in the of appropriateness of antibiotic prescription for RTI outpatients across the same and different facility service level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1,542 outpatient records with a diagnosis of RTIs were analyzed. The majority of patients (55.0%) were female, and most sought care from HCIVs (44.9%) and HCIIIs (43.7%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of study participants and prevalence of respiratory tract infections.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequencies (N\u0026thinsp;=\u0026thinsp;1,542)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentages (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth facility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCIIIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCIVs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferral Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRTI diagnosed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUn-categorized acute RTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute pharyngitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecommon cold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eacute tonsillitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUn-categorized upper RTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute bronchitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute laryngitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute sinusitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic RTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUn-categorized lower RTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute otitis media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eHC: Health center, RTI: Respiratory tract infection\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eAssessment of use of antibiotics.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOut of the 1,542 patient records reviewed, 79.8% (n\u0026thinsp;=\u0026thinsp;1,230) received antibiotics. Most patients received one antibiotic (89.1%, n\u0026thinsp;=\u0026thinsp;1,096), while a minority received two antibiotics (10.4%, n\u0026thinsp;=\u0026thinsp;128). Instances where \u0026gt;\u0026thinsp;3 antibiotics were prescribed were rare (0.5%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 1,387 antibiotics were prescribed, averaging approximately one antibiotic per patient (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The majority of prescribed antibiotics belonged to the Access group (86.6%; n\u0026thinsp;=\u0026thinsp;1,197) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with Amoxicillin being the most commonly prescribed drug (50.45%; n\u0026thinsp;=\u0026thinsp;700), followed by cotrimoxazole (17.3%; n\u0026thinsp;=\u0026thinsp;340) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEvaluation of the quality of prescribing\u003c/h3\u003e\n\u003cp\u003eOverall, the quality of prescribing across all facility service levels was suboptimal, as indicated by the WHO prescribing indicators. Three indicators met WHO standards: the average number of drugs per patient (2.7), percentage of encounters with injections (3.0%), and percentage of drugs from the essential drugs list (93.4%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, two indicators did not meet standards: percentage of drugs prescribed by generic names (79.5% vs. WHO standard of 100%) and percentage of patients encountering antibiotics (79.8% vs. WHO standard of \u0026lt;\u0026thinsp;30%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrescribing indicator scores at public facilities in Jinja City, Eastern Uganda, June 1, 2022 to May 31, 2023\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescribing indicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall for all health facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegional Referral Hospital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHCIVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHCIIIs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWHO Optimal value.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of Patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient encounter with antibiotic prescribed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum of drugs prescribed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs prescribed by generic name\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs from essential drugs list\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEncounter with injections dosages prescribed.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage encounter with antibiotics.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of drugs prescribed per patient encounter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage of drugs prescribed by generic name.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage of encounter with injections prescribed.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage of drugs prescribed from essential drugs list\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study assessed the quality of prescribing based on the WHO prescribing indicators among patients with RTIs seeking ambulatory care at public health facilities in Jinja City. Overall, the results revealed suboptimal prescribing practices, with only three out of five indicators conforming to or closely aligning with WHO standards. The prescribing indictors that conformed to the WHO standard were average of number of drugs prescribed per patient encounter, percentage of encounter with injections prescribed and percentage of drugs prescribed from essential drugs list. However, the percentage encounter with antibiotics (79.8%) and percentage of drugs prescribed by generic name (79.5%) did not conform.\u003c/p\u003e \u003cp\u003eIn this study, the average number of drugs prescribed per patient encounter were 2.7 of which 1 was an antibiotic. This conformed to the WHO standard of less than 3.0 drugs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, this does not necessarily indicate rational prescribing, given that as respiratory tract infections (RTIs) are primarily viral and often only require supportive treatment. Ideally, the number of drugs prescribed should have been lower. Therefore, the observed figure suggests over-prescription. The average of 2.7 drugs per encounter in this study was comparable to findings in Mbarara City Southwestern Uganda (2.5), indicating that factors contributing to over-prescription in patients with RTIs, across Uganda may be similar and could benefit from similar targeted interventions [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In contrast, the average number of drugs prescribed in this study was higher than in Eritrea (1.8) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and Tanzania (1.99) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] but lower than what was reported in systematic studies in Africa (3.1) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], India (3.08) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and in Changarupattu, Tamil Nadu, India by Raja [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] (3.7). The lower prescribing rate in Eritrea may be attributed to the presence of government-owned community pharmacies, which provide medications for patients who cannot obtain them at public health facilities. The higher prescribing rates observed in Africa and India could be due to differences in healthcare settings, regulations, and controls. Increasing awareness among patients about the risks of overuse of medications and improving access to essential medicines at public health facilities may promote rational prescribing practices[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe prescription of medicines from the Essential Drugs List (EDL) is associated with higher quality of care, better management of medicines, more cost-effective use of available resources, and adherence to prescribing regulations[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this study, the percentage of drugs prescribed from the EDL was 93.4%, which closely aligns with the WHO standard of 100%. This figure is higher than what was observed in Bushenyi District, Western Uganda (79.0%) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], the WHO African Region (88%) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Afghanistan 67% [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and in most studies done in Ethiopia up to the year 2020, \u0026lt;\u0026thinsp;92% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The lower percentage in Bushenyi could be attributed to the study being conducted in a private hospital, which has more flexibility in determining its medicine requirements. In contrast, public hospitals, where all drugs are procured and provided by the government, are more likely to adhere to the EDL. This is supported by findings from a systematic study in Africa, which showed poorer prescribing indicators in private facilities compared to public ones[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Interestingly, a study in Eritrea reported 98.4% of drugs being prescribed from the EDL[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], reflecting a strong adherence to the list. The lower percentage in Afghanistan could be because of the poor health indicators of weak health system after many years of war. On the other hand, studies reporting higher adherence to the EDL, closer to or equal to the WHO standard, include those from Cameroon (99.9%) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Eretria (98.4%) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], Sri lanka (98.9%) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], North-West Ethiopia 95.3% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Ethiopia (100%) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], Jordanian (99.8%) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and Saudi Arabia (100%) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. A systematic review of 42 studies in India found that only 2.4% adhered to 100% EDL prescriptions, indicating that very few settings fully comply with the WHO standard[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This highlights the need for stronger health policies to support adherence to the EDL.\u003c/p\u003e \u003cp\u003eIn this study, the percentage of drugs prescribed by generic name was 79.5%, which fell short of the WHO standard of 100%. This figure was lower than the percentages observed in Bushenyi (90.2%) and Mbarara (84%) districts in Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], Cameroon (98.4%) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Ethiopia (97.6%) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], Eritrea (83.1%) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Sri lanka (84.3%) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] but higher than that in Rivers state, Nigeria 43.7% [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], WHO African region (68.0%) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Afghanistan 35.1% [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], Nigerian study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], Saudi Arabia [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and Jordan [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Notably, the deviation from the WHO standard was more pronounced for the prescription of generic names than for drugs prescribed from the EDL. This could be attributed to widespread skepticism among prescribers regarding the quality and efficacy of various brands available in the market, prompting them to favor specific brands they trust [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, the percentage of encounters with antibiotics was 79.8%, which exceeds the WHO standard of 30%. This high rate suggests a significant level of irrational prescribing, especially given that the study focused on RTIs, which are predominantly viral. Compared to other studies, our rate was higher than those observed in Japan (49.2%) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], South Korea 30.6%, [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], Bahrain (31.8%) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], Malta (45%) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and Pakistan (69.8)[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. It was also higher than studies conducted in Uganda, including those in Kampala (43%) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and Mbarara City (70%) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The rate was however lower than that in Ecuador, (90.3%)[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and Vietnam (97.0%) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This trend suggests that developed countries generally have lower antibiotic prescription rates for RTIs, likely due to stricter prescribing regulations, robust antibiotic stewardship programs, and clear treatment guidelines, such as the National Institute for Health and Care Excellence (NICE) guidelines in the UK. In China, earlier studies reported antibiotic prescription rates exceeding 80%[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], but more recent studies show a decline. For instance, a nationwide study among upper respiratory tract infection (URTI) outpatients found a prescription rate of 40.8%, while a retrospective study on pediatric patients reported a much lower rate of 27.1%[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe average number of antibiotics per patient in our study was approximately 1.0. This was high given that each patient approximately got one antibiotic for an RTI that was most likely viral in nature. This was lower than what was reported in by other studies like Saudi Arabia, 1.26[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], Jordan (2.9) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], Ethiopia (2.0) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and Cameroon (1.14) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] reported the number of antibiotics prescribed to be 1.6. However, these studies often included a broader range of patients, not solely those with RTIs, which could explain the higher average in those settings. Although the average number of antibiotics prescribed for RTIs in our study is lower than for other morbidities, RTIs, due to their higher prevalence, likely consume a significant share of antibiotics prescribed across health care settings.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations of the study\u003c/h2\u003e \u003cp\u003eOne limitation of this study was the inability to reassess patients clinically or use laboratory or point-of-care diagnostic tests for RTIs, which would have helped evaluate the prescriber's rationale for antibiotic prescriptions. As a retrospective study, patient histories could only be retrieved from existing records, and direct clinical assessments were not possible. Prospective studies, which could have provided more detailed information, were not conducted due to the potential for the Hawthorne effect [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA strength of the study was the large sample size of 1,542 patient records, well-distributed across 11 health facilities, which exceeded the WHO's recommended minimum of 600 records. Furthermore, the study covered all months of the annual calendar, ensuring that seasonal variations in RTI severity did not unduly influence the findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed significant irrational prescribing practices for RTI patients, with antibiotics being frequently and inappropriately prescribed. Such practices not only elevate the risk of antibiotic resistance (ABR) but also contribute to unnecessary healthcare costs. To address these challenges, it is crucial to implement targeted interventions that focus on improving the rational use of antibiotics. We recommend enhancing prescriber training on the appropriate use of antibiotics, strengthening antibiotic stewardship programs, and promoting the use of diagnostic tools to differentiate between bacterial and viral infections. Additionally, raising awareness among healthcare providers about the importance of adhering to national prescribing guidelines could help reduce unnecessary antibiotic prescriptions. Future research is recommended to investigate the factors contributing to the lower percentage of drugs prescribed from the Essential Drugs List (EDL) in this setting. Such studies would provide valuable insights to develop effective strategies to optimize prescribing practices and ensure more consistent adherence to national health policies.\u003c/p\u003e"},{"header":"Abbreviations ","content":"\u003cp\u003eABR \u0026nbsp; \u0026nbsp; \u0026nbsp;antibiotic resistance\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEDL \u0026nbsp; \u0026nbsp; \u0026nbsp;Essential drugs list\u003c/p\u003e\n\u003cp\u003eHC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Health Center\u003c/p\u003e\n\u003cp\u003eRTI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Respiratory tract infections\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO \u0026nbsp; \u0026nbsp;World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval to conduct this study was sought and approved by Mbarara University of Science and Technology Research and Ethics Committee (MUST-REC): reference number MUST- 2023-814. The study was also approved by National Council of Science and Technology under registration number. HS3499ES. Permission to conduct the study in public facilities Jinja City was thought from the City health officer of Jinja City and the Director of Jinja Regional Referral Hospital. Patient name and other identifiers were concealed throughout the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend great appreciation to the City Health Officer and the Director Jinja Regional Referral Hospital who permitted the study to be done in Public Health facilities in Jinja City.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZKI conceptualized and designed the study, collected the data and drafted the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHM designed the software for data collection.\u003c/p\u003e\n\u003cp\u003eZKI, RM and HM contributed to the, analysis, interpretation of data and discussion of the results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eZIG drafted the manuscript while RM critically reviewed and revised it.\u003c/p\u003e\n\u003cp\u003eAll authors approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eZKI, RM and HM are personally accountable for the integrity of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors didn\u0026rsquo;t receive any funding to do the research or publish the findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe excel data sheet of the collected data used to arrive at the conclusions can be availed on request to the corresponding Author through his email:[email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Community Health, Mbarara University of Science and Technology, Mbarara, Uganda\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Physiology, Mbarara University of Science and Technology, Mbarara, Uganda\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of disease control and environmental health, Makerere University school of public health Email: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e*Correspondence: Department of Community Health, Mbarara University of Science and Technology, Mbarara, P.O Box 1410, Uganda, Tel: +256782024793; Email:[email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eOrganization, W.H., \u003cem\u003eWRational drug use of medicines: Progress in implementing the WHO medicines strategy report by the secretariat. Executive board 118th session provisional agenda item 5.3.\u003c/em\u003e 2006.\u003c/li\u003e\n \u003cli\u003eYenet, A., G. Nibret, and B.A. Tegegne, \u003cem\u003eChallenges to the availability and affordability of essential medicines in African countries: a scoping review.\u003c/em\u003e ClinicoEconomics and Outcomes Research, 2023: p. 443-458.\u003c/li\u003e\n \u003cli\u003eWHO, \u003cem\u003eThe growing public health burden of antimicrobial resistance. .\u003c/em\u003e 2021.\u003c/li\u003e\n \u003cli\u003eKasimanickam, V., M. Kasimanickam, and R. Kasimanickam, \u003cem\u003eAntibiotics use in food animal production: escalation of antimicrobial resistance: where are we now in combating AMR?\u003c/em\u003e Medical Sciences, 2021. \u003cstrong\u003e9\u003c/strong\u003e(1): p. 14.\u003c/li\u003e\n \u003cli\u003ePoudel, A.N., et al., \u003cem\u003eThe economic burden of antibiotic resistance: A systematic review and meta-analysis.\u003c/em\u003e Plos one, 2023. \u003cstrong\u003e18\u003c/strong\u003e(5): p. e0285170.\u003c/li\u003e\n \u003cli\u003eHealth, M.o.,\u003cem\u003e\u0026nbsp;Annual health sector performance report financial year 2019/2020. .\u003c/em\u003e 2021.\u003c/li\u003e\n \u003cli\u003eJin, X., et al., \u003cem\u003eGlobal burden of upper respiratory infections in 204 countries and territories, from 1990 to 2019.\u003c/em\u003e EClinicalMedicine, 2021. \u003cstrong\u003e37\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003eIMS institute for health informatics, \u003cem\u003eGlobal medicines use in 2020 outllook and implications.\u003c/em\u003e 2015.\u003c/li\u003e\n \u003cli\u003eWagner, A.K., et al., \u003cem\u003eAccess to care and medicines, burden of health care expenditures, and risk protection: results from the World Health Survey.\u003c/em\u003e Health policy, 2011. \u003cstrong\u003e100\u003c/strong\u003e(2-3): p. 151-158.\u003c/li\u003e\n \u003cli\u003eWHO, \u003cem\u003eHealth products policy and standards.\u003c/em\u003e 2024.\u003c/li\u003e\n \u003cli\u003eHealth, M.o., \u003cem\u003eNational medicines Policy. Available at:\u0026nbsp;\u003c/em\u003e\u003cem\u003ehttps://www.health.go.ug/\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 2015.\u003c/li\u003e\n \u003cli\u003eWane, W. and G. Martin, \u003cem\u003eEducation and health services in Uganda: data for results and accountability.\u003c/em\u003e 2013.\u003c/li\u003e\n \u003cli\u003eOfori-Asenso, R., P. Brhlikova, and A.M. Pollock, \u003cem\u003ePrescribing indicators at primary health care centers within the WHO African region: a systematic analysis (1995\u0026ndash;2015).\u003c/em\u003e BMC public health, 2016. \u003cstrong\u003e16\u003c/strong\u003e: p. 1-14.\u003c/li\u003e\n \u003cli\u003eGoruntla, N., et al., \u003cem\u003eEvaluation of rational drug use based on who/inrud core drug use indicators in a secondary care hospital: a cross-sectional study in western Uganda.\u003c/em\u003e Drug, Healthcare and Patient Safety, 2023: p. 125-135.\u003c/li\u003e\n \u003cli\u003eLanyero, H., et al., \u003cem\u003eUse of antibacterials in the management of symptoms of acute respiratory tract infections among children under five years in Gulu, northern Uganda: Prevalence and determinants.\u003c/em\u003e PloS one, 2020. \u003cstrong\u003e15\u003c/strong\u003e(6): p. e0235164.\u003c/li\u003e\n \u003cli\u003eSekoni, K.F., I.A. Oreagba, and F.A. Oladoja, \u003cem\u003eAntibiotic utilization study in a teaching hospital in Nigeria.\u003c/em\u003e JAC-Antimicrobial Resistance, 2022. \u003cstrong\u003e4\u003c/strong\u003e(5): p. dlac093.\u003c/li\u003e\n \u003cli\u003eNamubiru, S., et al., \u003cem\u003eIncreasing trends of antibiotic resistance in Uganda: analysis of the national antimicrobial resistance surveillance data, 2018\u0026ndash;2021.\u003c/em\u003e BMC Infectious Diseases, 2024. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 930.\u003c/li\u003e\n \u003cli\u003eIgirikwayo, Z.K., et al., \u003cem\u003ePrescription patterns of antibiotics and associated factors among outpatients diagnosed with respiratory tract infections in Jinja city, Uganda, June 2022\u0026ndash;May 2023.\u003c/em\u003e BMC Pulmonary Medicine, 2024. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 446.\u003c/li\u003e\n \u003cli\u003eOrganization, W.H., \u003cem\u003eHow to investigate drug use in health facilities: selected drug use indicators\u003c/em\u003e. 1993, World Health Organization.\u003c/li\u003e\n \u003cli\u003eUmar, L.W., et al., \u003cem\u003eOutpatient prescribing and antibiotic use for children in a tertiary hospital.\u003c/em\u003e Sahel Medical Journal, 2020. \u003cstrong\u003e23\u003c/strong\u003e(2): p. 109-115.\u003c/li\u003e\n \u003cli\u003eAdriaenssens, N., et al., \u003cem\u003eEuropean Surveillance of Antimicrobial Consumption (ESAC): disease-specific quality indicators for outpatient antibiotic prescribing.\u003c/em\u003e BMJ quality \u0026amp; safety, 2011. \u003cstrong\u003e20\u003c/strong\u003e(9): p. 764-772.\u003c/li\u003e\n \u003cli\u003eMuwanguzi, T.E., T.M. Yadesa, and A.G. Agaba, \u003cem\u003eAntibacterial prescription and the associated factors among outpatients diagnosed with respiratory tract infections in Mbarara Municipality, Uganda.\u003c/em\u003e BMC Pulmonary Medicine, 2021. \u003cstrong\u003e21\u003c/strong\u003e: p. 1-11.\u003c/li\u003e\n \u003cli\u003eAmaha, N.D., et al., \u003cem\u003ePrescribing practices using WHO prescribing indicators and factors associated with antibiotic prescribing in six community pharmacies in Asmara, Eritrea: a cross-sectional study.\u003c/em\u003e Antimicrobial Resistance \u0026amp; Infection Control, 2019. \u003cstrong\u003e8\u003c/strong\u003e: p. 1-7.\u003c/li\u003e\n \u003cli\u003eKilipamwambu, A., et al., \u003cem\u003eWHO/INRUD core prescribing indicators and antibiotic utilization patterns among primary health care facilities in Ilala district, Tanzania.\u003c/em\u003e JAC-Antimicrobial Resistance, 2021. \u003cstrong\u003e3\u003c/strong\u003e(2): p. dlab049.\u003c/li\u003e\n \u003cli\u003eGujar, A., V. Gulecha, and A. Zalte, \u003cem\u003eDrug utilization studies using WHO prescribing indicators from India: a systematic review.\u003c/em\u003e Health Policy and Technology, 2021. \u003cstrong\u003e10\u003c/strong\u003e(3): p. 100547.\u003c/li\u003e\n \u003cli\u003eRaja, D. and S. Sasithra, \u003cem\u003eAssessment of the Antibiotics and Other Drug Prescribing Patterns in a Primary Health Care Setting.\u003c/em\u003e Journal of Communicable Diseases (E-ISSN: 2581-351X \u0026amp; P-ISSN: 0019-5138), 2021. \u003cstrong\u003e53\u003c/strong\u003e(4): p. 70-75.\u003c/li\u003e\n \u003cli\u003eDuan, L., et al., \u003cem\u003eThe vicious cycle of the public\u0026apos;s irrational use of antibiotics for upper respiratory tract infections: A mixed methods systematic review.\u003c/em\u003e Frontiers in Public Health, 2022. \u003cstrong\u003e10\u003c/strong\u003e: p. 985188.\u003c/li\u003e\n \u003cli\u003eKar, S.S., H.S. Pradhan, and G.P. Mohanta, \u003cem\u003eConcept of essential medicines and rational use in public health.\u003c/em\u003e Indian Journal of Community Medicine, 2010. \u003cstrong\u003e35\u003c/strong\u003e(1): p. 10-13.\u003c/li\u003e\n \u003cli\u003eHabibyar, A.F. and Q.A. Nazari, \u003cem\u003eEvaluation of prescribing patterns using WHO core drug use indicators in a pediatric hospital of Kabul Afghanistan: A prospective cross-sectional study.\u003c/em\u003e Heliyon, 2023. \u003cstrong\u003e9\u003c/strong\u003e(11).\u003c/li\u003e\n \u003cli\u003eMamo, D.B. and B.K. Alemu, \u003cem\u003eRational drug-use evaluation based on World Health Organization core drug-use indicators in a tertiary referral hospital, Northeast Ethiopia: a cross-sectional Study.\u003c/em\u003e Drug, Healthcare and Patient Safety, 2020: p. 15-21.\u003c/li\u003e\n \u003cli\u003eAnong, D.N. and J.-F.K. Akoachere, \u003cem\u003ePrescribing patterns and associated factors of antibiotic prescription in primary health care facilities of Kumbo East and Kumbo West Health Districts, North West Cameroon.\u003c/em\u003e PloS one, 2018. \u003cstrong\u003e13\u003c/strong\u003e(3): p. e0193353.\u003c/li\u003e\n \u003cli\u003eSamuel, O.K., Z. Zorte, and O.D. Samuel, \u003cem\u003eQuality of Drug Prescription and Dispensing Practices in a Teaching Hospital in a developing country.\u003c/em\u003e medRxiv, 2023: p. 2023.03. 03.23286781.\u003c/li\u003e\n \u003cli\u003eRanasinghe, P., et al., \u003cem\u003eNational survey on World Health Organization/International Network of Rational Use of Drugs core drug use indicators in the outpatient setting and availability of medicines in a developing South Asian country.\u003c/em\u003e Journal of Pharmaceutical Health Services Research, 2022. \u003cstrong\u003e13\u003c/strong\u003e(2): p. 158-165.\u003c/li\u003e\n \u003cli\u003eYimenu, D.K., et al., \u003cem\u003eAssessment of antibiotic prescribing patterns at outpatient pharmacy using World Health Organization prescribing indicators.\u003c/em\u003e Journal of primary care \u0026amp; community health, 2019. \u003cstrong\u003e10\u003c/strong\u003e: p. 2150132719886942.\u003c/li\u003e\n \u003cli\u003eDemoz, G.T., et al., \u003cem\u003ePrescribing pattern of antibiotics using WHO prescribing indicators among inpatients in Ethiopia: a need for antibiotic stewardship program.\u003c/em\u003e Infection and Drug Resistance, 2020: p. 2783-2794.\u003c/li\u003e\n \u003cli\u003eAl-Azayzih, A., et al., \u003cem\u003eEvaluation of drug-prescribing patterns based on the WHO prescribing indicators at outpatient clinics of five hospitals in Jordan: a cross-sectional study.\u003c/em\u003e Int J Clin Pharmacol Ther, 2017. \u003cstrong\u003e55\u003c/strong\u003e(5): p. 425-432.\u003c/li\u003e\n \u003cli\u003eAlanazi, M.Q., et al., \u003cem\u003eAn evaluation of antibiotics prescribing patterns in the emergency department of a tertiary care hospital in Saudi Arabia.\u003c/em\u003e Infection and Drug Resistance, 2019: p. 3241-3247.\u003c/li\u003e\n \u003cli\u003eAdedapo, A.D. and O.O. Akunne, \u003cem\u003ePatterns of antimicrobials prescribed to patients admitted to a tertiary care hospital: a prescription quality audit.\u003c/em\u003e Cureus, 2021. \u003cstrong\u003e13\u003c/strong\u003e(6).\u003c/li\u003e\n \u003cli\u003eIlori, T. and O. Odeyinka, \u003cem\u003eDrug Prescription Pattern in a Primary Care Clinic, Southwest, Nigeria.\u003c/em\u003e Journal of Drug Delivery and Therapeutics, 2022. \u003cstrong\u003e12\u003c/strong\u003e(3): p. 74-79.\u003c/li\u003e\n \u003cli\u003eOfori-Asenso, R., \u003cem\u003eA closer look at the World Health Organization\u0026apos;s prescribing indicators.\u003c/em\u003e Journal of Pharmacology and Pharmacotherapeutics, 2016. \u003cstrong\u003e7\u003c/strong\u003e(1): p. 51-54.\u003c/li\u003e\n \u003cli\u003eAraki, Y., et al., \u003cem\u003ePrescription pattern analysis for antibiotics in working-age workers diagnosed with common cold.\u003c/em\u003e Scientific Reports, 2021. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 22701.\u003c/li\u003e\n \u003cli\u003eKim, Y.C., et al., \u003cem\u003ePrescriptions patterns and appropriateness of usage of antibiotics in non-teaching community hospitals in South Korea: a multicentre retrospective study.\u003c/em\u003e Antimicrobial Resistance \u0026amp; Infection Control, 2022. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 40.\u003c/li\u003e\n \u003cli\u003eSulis, G., et al., \u003cem\u003eAntibiotic prescription practices in primary care in low-and middle-income countries: a systematic review and meta-analysis.\u003c/em\u003e PLoS medicine, 2020. \u003cstrong\u003e17\u003c/strong\u003e(6): p. e1003139.\u003c/li\u003e\n \u003cli\u003eSaliba-Gustafsson, E.A., et al., \u003cem\u003eBarriers and facilitators to prudent antibiotic prescribing for acute respiratory tract infections: a qualitative study with general practitioners in Malta.\u003c/em\u003e PLoS One, 2021. \u003cstrong\u003e16\u003c/strong\u003e(2): p. e0246782.\u003c/li\u003e\n \u003cli\u003eHashmi, H., et al., \u003cem\u003ePrescribing patterns for upper respiratory tract infections: a prescription-review of primary care practice in Quetta, Pakistan and the implications.\u003c/em\u003e Frontiers in Public Health, 2021. \u003cstrong\u003e9\u003c/strong\u003e: p. 787933.\u003c/li\u003e\n \u003cli\u003eKizito, M., et al., \u003cem\u003eAntibiotic consumption and utilization at a large tertiary care level hospital in Uganda: A point prevalence survey.\u003c/em\u003e PloS one, 2025. \u003cstrong\u003e20\u003c/strong\u003e(1): p. e0313587.\u003c/li\u003e\n \u003cli\u003eKagoya, E.K., et al., \u003cem\u003eExperiences and views of healthcare professionals on the prescription of antibiotics in Eastern Uganda: A qualitative study.\u003c/em\u003e Journal of global antimicrobial resistance, 2021. \u003cstrong\u003e25\u003c/strong\u003e: p. 66-71.\u003c/li\u003e\n \u003cli\u003eS\u0026aacute;nchez Choez, X., M.L. Armijos Acurio, and R.E. Jimbo Sotomayor, \u003cem\u003eAppropriateness and adequacy of antibiotic prescription for upper respiratory tract infections in ambulatory health care centers in Ecuador.\u003c/em\u003e BMC Pharmacology and Toxicology, 2018. \u003cstrong\u003e19\u003c/strong\u003e: p. 1-11.\u003c/li\u003e\n \u003cli\u003eVan An, N., et al., \u003cem\u003eDistribution and antibiotic resistance characteristics of bacteria isolated from blood culture in a teaching hospital in Vietnam during 2014\u0026ndash;2021.\u003c/em\u003e Infection and Drug Resistance, 2023: p. 1677-1692.\u003c/li\u003e\n \u003cli\u003eZhao, H., et al., \u003cem\u003eAppropriateness of antibiotic prescriptions in ambulatory care in China: a nationwide descriptive database study.\u003c/em\u003e The Lancet Infectious Diseases, 2021. \u003cstrong\u003e21\u003c/strong\u003e(6): p. 847-857.\u003c/li\u003e\n \u003cli\u003eXue, F., et al., \u003cem\u003eAntibiotic prescriptions for children younger than 5 years with acute upper respiratory infections in China: a retrospective nationwide claims database study.\u003c/em\u003e BMC infectious diseases, 2021. \u003cstrong\u003e21\u003c/strong\u003e: p. 1-10.\u003c/li\u003e\n \u003cli\u003eMcCambridge, J., J. Witton, and D.R. Elbourne, \u003cem\u003eSystematic review of the Hawthorne effect: new concepts are needed to study research participation effects.\u003c/em\u003e Journal of clinical epidemiology, 2014. \u003cstrong\u003e67\u003c/strong\u003e(3): p. 267-277.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Respiratory tract infections, Antibiotic prescription, Antibiotic resistance, Rational drug use, Uganda","lastPublishedDoi":"10.21203/rs.3.rs-6260139/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6260139/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003cbr\u003e\n \u003c/strong\u003eRational drug use ensures that medications are prescribed based on clinical needs, appropriate dosages, and for the right duration, minimizing healthcare costs. Irrational antibiotic use is a key driver of antibiotic resistance (ABR) emergence. We evaluated the conformance of drug prescriptions to the World Health Organization (WHO) prescribing indicators among patients with respiratory tract infections (RTIs) attending public health facilities in Jinja City, Uganda.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003cbr\u003e\n \u003c/strong\u003eA retrospective observational study was conducted across 11 public health facilities in Jinja City, Eastern Uganda, from June 1, 2022, to May 31, 2023. Patient records of those diagnosed with RTIs were selected using systematic random sampling. Several prescribing indicators were assessed, including the number of drugs prescribed per patient encounter, the percentage of encounters with antibiotics, the percentage of drugs from the essential drugs list, the percentage of drugs prescribed by generic name, and the percentage of encounters with injectable medications. Data were analyzed for compliance with WHO prescribing standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003cbr\u003e\n \u003c/strong\u003eThree indicators met or were close to WHO targets: the average number of drugs prescribed per patient (2.7, WHO target \u0026lt;3), the percentage of encounters with injections prescribed (3.0%, WHO target ≤10%), and the percentage of drugs from the essential drugs list (93.4%, WHO target 100%). However, two indicators did not meet WHO recommendations: the percentage of encounters with antibiotics prescribed (79.8%, WHO target \u0026lt;30%) and the percentage of drugs prescribed by generic name (79.5%, WHO target 100%), suggesting irrational prescribing practices. Among patients prescribed antibiotics, most received only one antibiotic (89.1%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003cbr\u003e\n \u003c/strong\u003eThis study revealed gaps in adherence to WHO prescribing standards, particularly regarding excessive antibiotic prescriptions for RTIs. These irrational prescribing practices may contribute to the emergence of ABR. There is a need for targeted interventions to promote rational drug use and improve prescribing practices across health facilities in the region.\u003c/p\u003e","manuscriptTitle":"Assessment of prescribing practices for respiratory tract infections in public health facilities, Jinja City, Uganda, June 2022–May 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-15 10:25:55","doi":"10.21203/rs.3.rs-6260139/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-11T18:35:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-30T17:39:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86814869520752892254380842653432883071","date":"2025-06-30T05:49:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-28T19:37:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38372858543410167070344089372916680757","date":"2025-05-16T18:02:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-10T13:26:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224340561246053545032290649608550509916","date":"2025-05-09T11:49:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30384185600902131239809407890549002967","date":"2025-05-09T11:20:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-09T10:50:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-07T14:41:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-30T05:47:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-04-30T05:45:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa228f7d-1363-4ad7-a4dc-e6d9f7e03f4e","owner":[],"postedDate":"May 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:07:40+00:00","versionOfRecord":{"articleIdentity":"rs-6260139","link":"https://doi.org/10.1186/s12982-026-01425-z","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2026-01-30 15:59:19","publishedOnDateReadable":"January 30th, 2026"},"versionCreatedAt":"2025-05-15 10:25:55","video":"","vorDoi":"10.1186/s12982-026-01425-z","vorDoiUrl":"https://doi.org/10.1186/s12982-026-01425-z","workflowStages":[]},"version":"v1","identity":"rs-6260139","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6260139","identity":"rs-6260139","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}