A point prevalence survey of antimicrobial use in two hospitals in Western Kenya

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The aim of the present study was to document the use of antimicrobial agents at two hospitals in Western Kenya, namely Bungoma County Referral Hospital (BCRH) and Webuye County Hospital (WCH). Methods The World Health Organization (WHO) Global Point Prevalence Survey (G-PPS) tool was used to collect sociodemographic information of study participants, the type of antimicrobial agents used, indications for antimicrobial use, and diagnostic tests conducted on participants. Files were selected over 24 hours, data was abstracted between July and October 2022, and analysis was carried out on SPSS version 26. Results Among the 361 patients, 223 (61.8%) were on antibiotics. The most common antibiotics used were ceftriaxone (123/237; 34.5%), metronidazole (89/237; 24.9%), and flucloxacillin (36/237; 10.1%). Most (60/237; 25.4%) antibiotics at the WCH were prescribed empirically, while most (46/237; 19.5%) antibiotics at the BCRH were prescribed for prophylaxis. Pneumonia was the leading indication for antibiotic prescriptions at BCRH (18/169, 9.5%), while clinical sepsis (17/169;9.9%) was the leading indication for antibiotic prescriptions at the WCH. 16/237 (6.8%) of the patients who had an antibiotic prescribed were subjected to culture and sensitivity testing, but only 9/16 (81.8%) received the results of the antimicrobial susceptibility tests within the study period. Conclusions Penicillins and Cephalosporins were widely used, prescribing/clinical practices vary from one hospital to another, and microbiological tests were underutilized in the study area. There is a need for enhanced antimicrobial and diagnostic stewardship in the study area. Point prevalence survey antimicrobial resistance antimicrobial stewardship antimicrobial use diagnostic stewardship Western Kenya Figures Figure 1 Figure 2 Figure 3 Background Antimicrobial resistance (AMR) is one of the most pressing global health threats of the 21st century, endangering the efficacy of life-saving treatments and complicating the management of infectious diseases [ 1 – 3 ]. The World Health Organization (WHO) highlights AMR as a critical challenge, predicting that drug-resistant infections could lead to 10 million deaths annually by 2050 if unaddressed [ 4 , 5 ]. The issue is particularly dire in developing countries, where limited resources and infrastructure hinder effective AMR management [ 6 , 7 ]. In Sub-Saharan Africa, including Kenya, AMR rates are rising, driven by factors such as inadequate infection control, limited diagnostic capacity, and suboptimal prescribing practices [ 8 – 10 ]. These challenges are compounded by a general lack of public awareness about the importance of appropriate use of antimicrobials. Kenya, like many other low- and middle-income countries, is grappling with the consequences of AMR. The country's National Action Plan (NAP), established in 2018 and revised in 2023, aims to curb AMR through coordinated efforts such as governance and administration, public awareness and education, strengthening surveillance and monitoring, improving infection prevention and control, and promoting appropriate use of antimicrobials through antimicrobial stewardship [ 11 , 12 ]. Through the NAP, Bungoma County has established a County Antimicrobial Stewardship Interagency Committee (CASIC) to coordinate the implementation of AMR mitigation strategies [ 13 , 14 ]. The County has made significant strides in addressing AMR, showcasing what can be achieved with dedicated resources and coordinated efforts. However, applying these strategies in practice remains challenging due to various constraints. Efforts to promote the appropriate use of AMAs depend on antimicrobial use data [ 15 , 16 ]. Unfortunately, African countries, including Kenya, often lack sufficient data on antimicrobial use. To address this gap, point prevalence surveys (PPS) are used to evaluate antimicrobial use and the quality of prescriptions [ 17 , 18 ]. These surveys are easy to administer, generate essential data, highlight problematic aspects of care quality e.g. the accuracy of prescriptions, and can support ASPs [ 19 ]. The present study aimed to assess the patterns of antimicrobial use, identify prevalent prescribing practices, and evaluate the extent of microbiological testing in two major hospitals in Bungoma County namely Webuye County Hospital (WCH), and Bungoma County Referral Hospital (BCRH) using the WHO standardized Global Point Prevalence Survey (G-PPS) tool. Methods Ethics statement This study was approved by the Ministry of Health (Kenya) and the Department of Health and Sanitation, County Government of Bungoma, as part of their ongoing efforts to support and implement the National AMR action plan. Confidentiality was ensured throughout the study where all patient files were serialised with unique identifiers to avoid linking the data to the patients. The identity of the prescriber was also concealed. Study site Bungoma county is in Western Kenya and borders Uganda to the Northwest, Trans-Nzoia County to the Northeast, Kakamega County to the East and Southeast and Busia County to the West and South West. Figure 1 . It has an area of 3, 032 square km, and has an estimated population of 1,670,570 [ 20 ]. There are 9 sub-counties in Bungoma county where 275 health facilities are domiciled. These are stratified as either faith-based, non-governmental (NGO`s) or County government organizations. Bungoma County Referral Hospital (BCRH), in Kanduyi subcounty, and Webuye County Hospital (WCH), in Webuye East subcounty are the two main public health facilities in the county. Data collection and analysis This study used a modified World Health Organization (WHO) point-prevalence survey (PPS) tool [ 21 ] which was uploaded on Kobo collect. Information on the socio-demographics of the study participants, prevalence of antibiotic use, indications of antibiotic use, and the microbiological tests were collected. Patients who met the inclusion criteria (patients admitted at the time of study for more than 24 hours excluding those on topical antibiotics) were recruited into the study and their files serialised for ease of identification. Data was extracted between July and October 2022, transferred to excel, checked for quality, completeness, and analysed using SPSS version 26. Results Sociodemographic information of the patients on antibiotics at the Webuye County Hospital and Bungoma County Referral Hospital during the study period A total of three hundred and sixty-one patients were recruited into the study comprising of 138 (38.2%) males and 223 (61.8%) females. Out of this, 67.4% (242) were adults with adolescents making up the smallest proportion (Table 1). Majority of the patients were recruited from the antenatal and post-natal wards (91; 25.2%), paediatric medical ward (49; 13.6%) and newborn units (48; 13.3%), two hundred and thirty-seven patients (65.7%) had a prescription which had an antibiotic (119; 33.0% at Webuye County Hospital) and (118; 32.7% at Bungoma County Referral Hospital). Most antibiotic prescriptions were written by clinical officers (78; 33.1%) and clinical officer interns (92; 39.0%). Table 1 : Socio-demographic information of the patients on antibiotics at the Webuye County Hospital and Bungoma County Referral Hospital Variable (n=361) WCH BCRH Total Gender Male Female 68 (18.8%) 103 (28.5%) 70 (19.4%) 120 (33.2%) 138 (38.2%) 223 (61.8%) Age* Neonates (0-28 days) Infants (29 days-2 years) Children (2 -12 years) Adolescent (13-16 years) Adults (>17 years) Unknown (age not specified) 17 (4.7%) 14 (3.9%) 15 (4.2%) 2 (0.6) 123 (34.3%) 1 (0.3%) 26 (7.2%) 17 (4.7%) 23 (6.4%) 3 (0.8%) 119 (33.1%) 1 (0.3%) 43 (12.0%) 31 (8.6%) 38 (10.6%) 5 (1.4%) 242 (67.4%) 2 (0.6%) Ward Antenatal and post-natal ward Pediatric Medical Ward Newborn unit Male Surgical ward Female Medical ward Male medical ward Female Surgical ward Pediatric Surgical Ward Emergency department/Casualty 31 (8.6%) 18 (5.0%) 17 (4.7%) 27 (7.5%) 26 (7.2%) 15 (4.2%) 25 (6.9%) 11 (3.0%) 1 (0.3%) 60 (16.6%) 31 (8.6%) 31 (8.6%) 20 (5.5%) 15 (4.2%) 21 (5.8%) 5 (1.4%) 7 (1.9%) 0 (0.0%) 91 (25.2%) 49 (13.6%) 48 (13.3%) 47 (13.0%) 41 (11.4%) 36 (10.0%) 30 (8.3%) 18 (5.0%) 1 (0.3%) Antibiotics prescribed Yes No 119 (33.0%) 52 (14.4%) 118 (32.7%) 72 (19.9%) 237 (65.7%) 124 (34.3%) WCH: Webuye County Hospital, BCRH: Bungoma County Referral Hospital Antibiotic prescription patterns at the Webuye County Hospital and Bungoma County Referral Hospital during the study period Ceftriaxone was the most prescribed antibiotic in both hospitals (123; 38.8%) followed by metronidazole (89; 28.0%) and flucloxacillin (36; 11.3%) while meropenem was the least prescribed antibiotic (1; 0.88%) (Figure 2). Most of the antibiotics prescribed were from the “Watch” and “Access” category of the AWARE categorization. Comparison of the indications for antibiotic use at Webuye County Hospital and Bungoma County Referral Hospital during the study period Most antibiotics were prescribed empirically at the WCH (60; 25.4 %), while most antibiotics were prescribed prophylactically at the BCRH (46; 19.5%) (Table 2). In both hospitals, most prophylactic antibiotics were used in obstetrics and gynaecology departments. Clinical sepsis (17; 9.9%) was the leading indication for antibiotic prescriptions at the WCH while pneumonia (18; 9.5%) was the leading indication for antibiotic prescription at the BCRH. Table 2 : Comparison of the indications for antibiotic use at the Webuye County Hospital and Bungoma County Referral Hospital during the study period Indications Facility WCH BCRH Total Reason for antibiotic use Empirical Treatment 60(25.4%) 25(10.6%) 85(36.0%) Definitive Treatment 28(11.9%) 39(16.5%) 67(28.4%) Prophylactic Treatment 27(11.4%) 46(19.5%) 73(30.9%) Not recorded 3(1.3%) 8(3.4%) 11(4.7%) Reason for prophylaxis Surgery of GIT, liver, or biliary tree 2(2.7%) 2(2.7%) 4(5.5%) Open fracture and other bone surgeries 6(8.2%) 3(4.1%) 9(12.3%) OBSGYN surgery/caesarean 10(13.7%) 22(30.1%) 32(43.8%) Drugs used in medical prophylaxis 0(0%) 4(5.5%) 4(5.5%) Other 9(12.3%) 15(20.5%) 24(32.9%) Reasons for treatment Bone and joint infections 9(5.3%) 4(2.1%) 13(7.9%) Clinical sepsis 17(9.9%) 8(4.2%) 25(15%) GIT infections 3(1.8%) 2(1.1%) 5(3%) Infections of ear, nose, throat, larynx, and mouth 1(0.6%) 1(0.5%) 2(1.2%) Obstetrics Gynaecological infections 8(4.7%) 2(1.1%) 10(6%) Pneumonia (other than TB) 16(9.5%) 18(10.6%) 34(20.1%) Soft tissue infections not involving bone 15(8.8%) 6(3.2%) 21(12.6%) CNS infections 9(5.3%) 1(0.5%) 10(6%) Intra-abdominal sepsis 1(0.6%) 1(0.5%) 2(1.2%) Lab confirmed bacteraemia 0(0.0%) 7(3.7%) 7(4.2%) Symptomatic lower UTI 2(1.2%) 2(1.1%) 4(1.2%) Symptomatic upper UTI 1(0.6%) 2(1.1%) 3(1.8%) Hospital based infections (Pneumonia, UTI, Surgical site infections etc) 1(0.6%) 2(1.1%) 3(1.8%) Other 19(11.1%) 11(5.8%) 30(18%) WCH: Webuye County Hospital, BCRH: Bungoma County Referral Hospital Uptake of microbiology lab services in informing antibiotic use in the study area Among the 237 (65.7%) of the patients who were on antibiotics, 16 (6.8%) were subjected to culture and sensitivity testing and 9 (81.8%) had their susceptibility results availed within the time of the study period (Table 3). Eight (88.9%) of the prescriptions with susceptibility testing were reviewed according to the sensitivity patterns as advised by the microbiology laboratory results. Of the 15 microbiological specimens, 10 (66.7%) were taken prior to initiation of the antibiotics, while 5 (33.3%) of them were taken after initiation of antibiotics. Table 3 : Utilization of the microbiology laboratory to inform antimicrobial selection at Webuye County Hospital and Bungoma County Referral Hospital during the study period Microbiological culture ordered (n=237) Facility WCH BCRH Total Yes No 9 (3.8%) 110 (46.4%) 7 (3.0%) 111 (46.8%) 16 (6.8%) 221 (93.2%) Were microbiological tests ordered prior to initiation of antibiotics? (n=15) Yes 5 (33.3%) 5 (33.3%) 10 (66.7%) No 3 (20.0%) 2 (13.3%) 5 (33.3%) Were culture results availed? (n=16) Yes 4 (25.0%) 7 (43.8%) 11 (68.8%) No 5 (31.3%) 0 (0.0%) 5 (31.3%) Were AM susceptibility test results availed? (n=11) Yes 2 (18.2%) 7 (63.6%) 9 (81.8%) No 2 (18.2%) 0 (0.0%) 2 (18.2%) Were prescriptions reviewed according to culture and susceptibility results? (n=9) Yes 1 (11.1%) 7 (77.8%) 8 (88.9%) No 1 (11.1%) 0 (0.0%) 1 (11.1%) WCH: Webuye County Hospital, BCRH: Bungoma County Referral Hospital Types of samples collected for culture and sensitivity in the study area Sixteen samples were collected for microbiology testing; seven (43.8%) were from the CSF, 4 (25.0%) were from pus swabs, 3(18.8%) (Figure 3). Other diagnostic tests at WCH and BCRH Other diagnostic tests carried out at the WCH and BCRH that informed antibiotic prescriptions during the study period included full hemogram 200 (35.4%), imaging 78 (13.8%), and urinalysis 25(4.4%) tests (Table 4). Table 4 : Other diagnostic tests carried out at Webuye County Hospital and Bungoma County Referral Hospital to inform antibiotic prescriptions during the study period Diagnostic Test Facility WCH BCRH Total Full hemogram 86 (43.0%) 114 (57.0%) 200 (35.4%) Renal function test 23 (21.9%) 82 (78.1%) 105 (18.6%) Imaging/Radiology 75 (96.2%) 3 (3.8%) 78 (13.8%) BS for mps 31 (50.8%) 30 (49.2%) 61 (10.8%) Liver function test 20 (39.2%) 31 (60.8%) 51 (9.0%) Urinalysis 17 (68.0%) 8 (32.0%) 25 (4.4%) Other 11 (52.4%) 10 (47.6%) 21 (3.7%) ESR 4 (57.1%) 3 (42.9%) 7 (1.2%) Gene Expert/AFB 6 (100.0%) 0 (0.0%) 6 (1.1%) Creative protein 4 (100.0%) 0 (0.0%) 4 (0.7%) Salmonella antigen test 3 (100.0%) 0 (0.0%) 3 (0.5%) Antistreptolysin O titer (ASOT) 2 (100.0%) 0 (0.0%) 2 (0.4%) VDRL 2 (100.0%) 0 (0.0%) 2 (0.4%) H.pylori 0 (0.0%) 0 (0.0%) 0 (0.0%) WCH: Webuye County Hospital, BCRH: Bungoma County Referral Hospital Discussion Antimicrobial resistance is a growing global threat to humanity. Antimicrobial point-prevalence surveys are feasible early tools for evaluating antimicrobial use and identifying gaps for improvement [ 22 , 23 ]. In this study, we assessed antimicrobial use, prescription practices and microbiological testing in two major hospitals in Bungoma County, Western Kenya. We found that 237 (65.7%) were on antibiotics. Similar studies done in Vietnam indicated 67.4% of patients were given antibiotics [ 23 ]. This study had a general rate of prescription at a similar level to our study. Among the specific antibiotics, ceftriaxone (34.5%) was the most commonly prescribed antibiotics and this has also been documented in other studies in sub-Saharan Africa [ 24 , 25 ]. Ceftriaxone is widely utilized in sub-Saharan Africa (SSA) due to its cost-effectiveness and safety in treating various infections. However, studies have reported a high rate of inappropriate use, and there is increasing concern about bacterial resistance in ceftriaxone users, which may compromise its effectiveness for treating infections. For example, Sie et al reported that Penicillins were the most used class of antibiotics among children under 5 years in Burkina Faso [ 24 ], and Akintan et al reported that third generation cephalosporins were the most frequently prescribed antibiotic at the paediatric department of the Lagos Teaching Hospital in South-Western Nigeria [ 25 ]. The distinction between empirical treatment at WCH and prophylactic use at BCRH underscores the variability in clinical practices and resource availability. Empirical antibiotic use, while necessary in certain cases, poses a risk of inappropriate use, potentially increasing the threat of AMR [ 26 , 27 ]. On the other hand, prophylactic use must be judicious to prevent unnecessary exposure to antibiotics [ 28 – 31 ]. The observed discrepancies in antibiotic prescribing practices between WCH and BCRH indicate the need for standardized treatment guidelines. Additionally, implementing antimicrobial stewardship programs can help monitor and optimize antibiotic use [ 32 – 35 ]. The low utilization of microbiological testing to inform antibiotic prescription among patients is alarming and highlights a significant gap in diagnostic capabilities. This low rate of testing is consistent with reports from other low-resource settings, where laboratory services are often limited [ 36 – 39 ]. The clinical microbiology laboratory plays a vital role in the management of bacterial infections. Relying solely on symptoms can lead to significant misdiagnosis of infections. Although susceptibility results influenced a significant number of prescriptions, delayed testing poses risks of inappropriate initial treatment. Improved diagnostic practices are essential for guiding appropriate antimicrobial therapy and mitigating AMR [ 41 – 44 ]. Internationally, point prevalence surveys have been important in identifying trends and informing AMR strategies. For example, the European Surveillance of Antimicrobial Consumption Network (ESAC-Net) found significant variation in antibiotic use across Europe, underscoring the impact of local guidelines and stewardship programs [ 45 ]. Regionally, studies in Uganda and Tanzania have reported similar issues with empirical prescribing and limited diagnostic testing, reinforcing the challenges faced in sub-Saharan Africa [ 46 – 50 ]. Locally, data from Kenyan hospitals align with the findings of this study, highlighting the need for a coordinated national approach to antimicrobial stewardship [ 51 – 56 ]. Limitations of the study This study is limited by its cross-sectional design and focus on two hospitals in Western Kenya, potentially limiting generalizability. Future research should expand to a broader geographic area and longitudinal studies to capture any trends in antibiotic use and resistance patterns. Conclusions and recommendations The study reveals significant gaps in antimicrobial use and diagnostic practices in the selected hospitals in Bungoma County. Addressing these issues through enhanced diagnostic capabilities, standardized prescribing practices, and robust stewardship programs is essential to mitigate AMR and improve patient outcomes. Continuous education for healthcare providers on AMR and rational antibiotic use is key as is the development and enforcement of national guidelines for antibiotic prescribing. This will ensure consistency across healthcare facilities in the county. The findings from our study will help inform targeted interventions and policy decisions to improve AMR management in Bungoma County and could serve as a model for other regions facing similar challenges. Declarations Funding: Government of the United Kingdom of Great Britain and Northern Ireland under the Fleming Fund project (GCP/GLO/710/UK) and the Global Health Security Agenda (OSRO-GLO-507-USA) through United States Agency for International Development (USAID). Conflicts of interest/Competing interests: The authors declare no conflict of interest Data availability: The datasets associated with this manuscript are available from the corresponding author upon reasonable request. Code availability: Not applicable Informed Consent Statement: Participants’ consent was given as per Section 25 – 32 of the World Medical Association’s Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects [57]. All participants gave their informed consent to participate in the study. Author Contributions : Conceptualization, E.M., J.W., C.N., V.L., L.A., P.K. ,J.O., and R.O.,; methodology, E.M.,, E.O., T.K., J.O., and R.O.,; software, J.O., and R.O.,.; validation, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; formal analysis, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; investigation, J.O.; resources, R.O., T.K., E.O.,., and E.M.,.; data curation, E.M., T.K., E.O.,J.O.,M.O.,and R.O.,; writing—original draft preparation, J.O., E.M., T.K., E.O., J.O., M.O., and R.O.,; writing—review and editing, E.M., T.K., E.O.,J.O., M.O., and R.O.,.; visualization, E.M., T.K., E.O.,J.O., M.O., and R.O.,; supervision, E.M., T.K., E.O.,J.O., M.O., and R.O.,; project administration, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; funding acquisition, T.K., E.O.,and R.O.,; All authors have read and agreed to the published version of the manuscript. References Dhingra S, Rahman NAA, Peile E, Rahman M, Sartelli M, Hassali MA, et al. 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Front Med. 2019;6:205. https://doi.org/10.3389/fmed.2019.00205 Iregbu KC, Osuagwu CS, Umeokonkwo CD, Fowotade AA, Ola-Bello OI, Nwajiobi-Princewill PI, et al. Underutilization of the clinical microbiology laboratory by physicians in Nigeria. African J Clin Exp Microbiol. 2020;21:53–9. https://doi.org/10.4314/ajcem.v21i1.7 Godman B, Egwuenu A, Haque M, Malande OO, Schellack N, Kumar S, et al. Strategies to improve antimicrobial utilization with a special focus on developing countries. Life. 2021;11:528. https://doi.org/10.3390/life11060528 Vasala A, Hytönen VP, Laitinen OH. Modern tools for rapid diagnostics of antimicrobial resistance. Front Cell Infect Microbiol. 2020;10:308. https://doi.org/10.3389/fcimb.2020.00308 Hage CA, Carmona EM, Epelbaum O, Evans SE, Gabe LM, Haydour Q, et al. Microbiological laboratory testing in the diagnosis of fungal infections in pulmonary and critical care practice. An official American Thoracic Society clinical practice guideline. Am J Respir Crit Care Med. 2019;200:535–50. https://doi.org/10.1164/rccm.201906-1185ST Sieswerda E, De Boer MGJ, Bonten MMJ, Boersma WG, Jonkers RE, Aleva RM, et al. Recommendations for antibacterial therapy in adults with COVID-19–an evidence based guideline. Clin Microbiol Infect. 2021;27:61–6. Zarb P, Goossens H. European surveillance of antimicrobial consumption (ESAC) value of a point-prevalence survey of antimicrobial use across europe. Drugs. 2011;71:745–55. https://doi.org/10.1016/j.cmi.2020.09.041 Horumpende PG, Mshana SE, Mouw EF, Mmbaga BT, Chilongola JO, de Mast Q. Point prevalence survey of antimicrobial use in three hospitals in North-Eastern Tanzania. Antimicrob Resist Infect Control. 2020;9:1–6. https://doi.org/10.1186/s13756-020-00809-3 Seni J, Mapunjo SG, Wittenauer R, Valimba R, Stergachis A, Werth BJ, et al. Antimicrobial use across six referral hospitals in Tanzania: a point prevalence survey. BMJ Open. 2020;10:e042819. https://doi.org/10.1136/bmjopen-2020-042819 Katyali D, Kawau G, Blomberg B, Manyahi J. Antibiotic use at a tertiary hospital in Tanzania: findings from a point prevalence survey. Antimicrob Resist Infect Control. 2023;12:112. https://doi.org/10.1186/s13756-023-01317-w Kiggundu R, Wittenauer R, Waswa JP, Nakambale HN, Kitutu FE, Murungi M, et al. Point prevalence survey of antibiotic use across 13 hospitals in Uganda. Antibiotics. 2022;11:199. https://doi.org/10.3390/antibiotics11020199 D’Arcy N, Ashiru-Oredope D, Olaoye O, Afriyie D, Akello Z, Ankrah D, et al. Antibiotic prescribing patterns in Ghana, Uganda, Zambia and Tanzania hospitals: results from the global point prevalence survey (G-PPS) on antimicrobial use and stewardship interventions implemented. Antibiotics. 2021;10:1122. https://doi.org/10.3390/antibiotics10091122 Okoth C, Opanga S, Okalebo F, Oluka M, Baker Kurdi A, Godman B. Point prevalence survey of antibiotic use and resistance at a referral hospital in Kenya: findings and implications. Hosp Pract. 2018;46:128–36. https://doi.org/10.1080/21548331.2018.1464872 Omulo S, Oluka M, Achieng L, Osoro E, Kinuthia R, Guantai A, et al. Point-prevalence survey of antibiotic use at three public referral hospitals in Kenya. PLoS One. 2022;17:e0270048. https://doi.org/10.1371/journal.pone.0270048 Momanyi L, Opanga S, Nyamu D, Oluka M, Kurdi A, Godman B. Antibiotic prescribing patterns at a leading referral hospital in Kenya: a point prevalence survey. J Res Pharm Pract. 2019;8:149. https://doi.org/10.4103/jrpp.JRPP_18_68 Kamita M, Maina M, Kimani R, Mwangi R, Mureithi D, Nduta C, et al. Point prevalence survey to assess antibiotic prescribing pattern among hospitalized patients in a county referral hospital in Kenya. Front Antibiot. 2022;1:993271. https://doi.org/10.3389/frabi.2022.993271 Karanja PW, Kiunga A. Point Prevalence Survey and Patterns of Antibiotic Use at Kirinyaga County Hospitals, Kenya. East Africa Sci. 2023;5:67–72. Muyu MG. Antimicrobial Use Practices in Mbagathi Hospital, Nairobi-kenya-a Point Prevalence Survey. 2020.Available from http://erepository.uonbi.ac.ke/handle/11295/154623. Accessed 20 Apr 2024. WMA Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects – WMA – The World Medical Association. Available from https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/. Accessed 7 Aug 2024. Additional Declarations No competing interests reported. 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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-4889823","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":349278941,"identity":"db85aef6-e222-4642-896b-3531aff6e746","order_by":0,"name":"Emmah Nyaboke","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBCDBAYeBsYHQAYPHylamA1AWthI0cImAWIR1MIv3XtMurDNLo+f5/Cxyq85djJsDMwPH93Ao0Vyzrk06ZltycWSvW1pt2W3JQMdxmZsnINHi8GNHDNp3jbmxA3necxuS25jBmrhYZPGp8UeoqUeqIX/W7HktnrCWgwkwFoOJ24428PG+HHbYcJaJG7kGFvznDteLNlzzFiacdtxHjZmAn7hn5FjeJunrBoYYskPP/7cVm3Pz9788DE+LUDAIsEIjQtmHjCJXzlYyQeGPxAW4w/CqkfBKBgFo2AEAgBWbkH+GXN4qgAAAABJRU5ErkJggg==","orcid":"","institution":"County Government of Bungoma","correspondingAuthor":true,"prefix":"","firstName":"Emmah","middleName":"","lastName":"Nyaboke","suffix":""},{"id":349278942,"identity":"6c2d4f58-3ac1-44b5-a688-bdb8418c1d2c","order_by":1,"name":"Joseph Ogola","email":"","orcid":"","institution":"Department of Livestock, Agriculture, Fisheries, and Cooperatives","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Ogola","suffix":""},{"id":349278943,"identity":"895af2b7-019b-40bd-983e-b7490a8bfa6c","order_by":2,"name":"Mitchel Okumu","email":"","orcid":"","institution":"Jaramogi Oginga Odinga Teaching and Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mitchel","middleName":"","lastName":"Okumu","suffix":""},{"id":349278944,"identity":"37f1087e-4120-472d-94d0-c25f552bfc90","order_by":3,"name":"Joan Wasike","email":"","orcid":"","institution":"County Government of Bungoma","correspondingAuthor":false,"prefix":"","firstName":"Joan","middleName":"","lastName":"Wasike","suffix":""},{"id":349278945,"identity":"3a205411-138e-4341-82e6-4332a206d828","order_by":4,"name":"Carolyne Naliaka","email":"","orcid":"","institution":"Bungoma County Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Carolyne","middleName":"","lastName":"Naliaka","suffix":""},{"id":349278946,"identity":"c0ab59b1-f7df-4472-9286-e32eae132ca5","order_by":5,"name":"Victor Lusweti","email":"","orcid":"","institution":"Bungoma County Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"","lastName":"Lusweti","suffix":""},{"id":349278947,"identity":"2b288591-9b0d-4f44-9774-4885a9e96a2f","order_by":6,"name":"Lydia Anyanzwa","email":"","orcid":"","institution":"Bungoma County Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lydia","middleName":"","lastName":"Anyanzwa","suffix":""},{"id":349278948,"identity":"1b4ffaca-8011-4243-b9a0-5b96cf81d04a","order_by":7,"name":"Peter Kamau","email":"","orcid":"","institution":"Webuye County Hospital","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Kamau","suffix":""},{"id":349278949,"identity":"b98f8e7d-46bd-4a16-86cd-834e5808536f","order_by":8,"name":"Eunice Omesa","email":"","orcid":"","institution":"World Health Organization. Kenya Country Office","correspondingAuthor":false,"prefix":"","firstName":"Eunice","middleName":"","lastName":"Omesa","suffix":""},{"id":349278950,"identity":"40e1de57-0b8e-4054-bf33-b3512d02851d","order_by":9,"name":"Tabitha Kimani","email":"","orcid":"","institution":"Food and Agriculture Organization of the United Nations-ECTAD Regional Office for Eastern Africa","correspondingAuthor":false,"prefix":"","firstName":"Tabitha","middleName":"","lastName":"Kimani","suffix":""},{"id":349278951,"identity":"fa19e52d-b144-4581-89bc-efb8498af88a","order_by":10,"name":"Ruth Omani","email":"","orcid":"","institution":"Food and Agriculture Organization of the United Nations-ECTAD Regional Office for Eastern Africa","correspondingAuthor":false,"prefix":"","firstName":"Ruth","middleName":"","lastName":"Omani","suffix":""}],"badges":[],"createdAt":"2024-08-10 03:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4889823/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4889823/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12982-025-00619-1","type":"published","date":"2025-05-04T15:57:43+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66565713,"identity":"a2c1de47-3f95-4738-9f59-f2dc1d205145","added_by":"auto","created_at":"2024-10-14 10:40:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":338956,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Bungoma county showing the location of Bungoma County Referral Hospital and Webuye County Hospital: CRH (County Referral Hospital), CH: County Hospital\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4889823/v1/2cc9d56ab3f290da2cc21b56.png"},{"id":66565711,"identity":"7a16841c-a0df-4109-a42c-1b1f7e55c7f3","added_by":"auto","created_at":"2024-10-14 10:40:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44451,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of the antibiotics prescribed in the study area\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4889823/v1/64aa38167a431f88225babb6.png"},{"id":66566124,"identity":"ced73fd7-21b9-439a-b0c3-472f0bac8390","added_by":"auto","created_at":"2024-10-14 10:48:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54232,"visible":true,"origin":"","legend":"\u003cp\u003eTypes of samples collected for culture and sensitivity at Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4889823/v1/01e0010efbcc7f1b452e60b4.png"},{"id":81987804,"identity":"d3b39f92-1e60-4fb3-bc02-ce2bcf3797f3","added_by":"auto","created_at":"2025-05-05 16:06:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1554464,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4889823/v1/a21b8d1c-a026-4364-bd6f-5e0a96fd5fee.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A point prevalence survey of antimicrobial use in two hospitals in Western Kenya","fulltext":[{"header":"Background","content":"\u003cp\u003eAntimicrobial resistance (AMR) is one of the most pressing global health threats of the 21st century, endangering the efficacy of life-saving treatments and complicating the management of infectious diseases [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The World Health Organization (WHO) highlights AMR as a critical challenge, predicting that drug-resistant infections could lead to 10\u0026nbsp;million deaths annually by 2050 if unaddressed [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The issue is particularly dire in developing countries, where limited resources and infrastructure hinder effective AMR management [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In Sub-Saharan Africa, including Kenya, AMR rates are rising, driven by factors such as inadequate infection control, limited diagnostic capacity, and suboptimal prescribing practices [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These challenges are compounded by a general lack of public awareness about the importance of appropriate use of antimicrobials.\u003c/p\u003e \u003cp\u003eKenya, like many other low- and middle-income countries, is grappling with the consequences of AMR. The country's National Action Plan (NAP), established in 2018 and revised in 2023, aims to curb AMR through coordinated efforts such as governance and administration, public awareness and education, strengthening surveillance and monitoring, improving infection prevention and control, and promoting appropriate use of antimicrobials through antimicrobial stewardship [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Through the NAP, Bungoma County has established a County Antimicrobial Stewardship Interagency Committee (CASIC) to coordinate the implementation of AMR mitigation strategies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The County has made significant strides in addressing AMR, showcasing what can be achieved with dedicated resources and coordinated efforts. However, applying these strategies in practice remains challenging due to various constraints.\u003c/p\u003e \u003cp\u003eEfforts to promote the appropriate use of AMAs depend on antimicrobial use data [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Unfortunately, African countries, including Kenya, often lack sufficient data on antimicrobial use. To address this gap, point prevalence surveys (PPS) are used to evaluate antimicrobial use and the quality of prescriptions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These surveys are easy to administer, generate essential data, highlight problematic aspects of care quality e.g. the accuracy of prescriptions, and can support ASPs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe present study aimed to assess the patterns of antimicrobial use, identify prevalent prescribing practices, and evaluate the extent of microbiological testing in two major hospitals in Bungoma County namely Webuye County Hospital (WCH), and Bungoma County Referral Hospital (BCRH) using the WHO standardized Global Point Prevalence Survey (G-PPS) tool.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement\u003c/h2\u003e \u003cp\u003e This study was approved by the Ministry of Health (Kenya) and the Department of Health and Sanitation, County Government of Bungoma, as part of their ongoing efforts to support and implement the National AMR action plan. Confidentiality was ensured throughout the study where all patient files were serialised with unique identifiers to avoid linking the data to the patients. The identity of the prescriber was also concealed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eBungoma county is in Western Kenya and borders Uganda to the Northwest, Trans-Nzoia County to the Northeast, Kakamega County to the East and Southeast and Busia County to the West and South West. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. It has an area of 3, 032 square km, and has an estimated population of 1,670,570 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. There are 9 sub-counties in Bungoma county where 275 health facilities are domiciled. These are stratified as either faith-based, non-governmental (NGO`s) or County government organizations. Bungoma County Referral Hospital (BCRH), in Kanduyi subcounty, and Webuye County Hospital (WCH), in Webuye East subcounty are the two main public health facilities in the county.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection and analysis\u003c/h2\u003e \u003cp\u003eThis study used a modified World Health Organization (WHO) point-prevalence survey (PPS) tool [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] which was uploaded on Kobo collect. Information on the socio-demographics of the study participants, prevalence of antibiotic use, indications of antibiotic use, and the microbiological tests were collected. Patients who met the inclusion criteria (patients admitted at the time of study for more than 24 hours excluding those on topical antibiotics) were recruited into the study and their files serialised for ease of identification. Data was extracted between July and October 2022, transferred to excel, checked for quality, completeness, and analysed using SPSS version 26.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSociodemographic information of the patients on antibiotics at the Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of three hundred and sixty-one patients were recruited into the study comprising of 138 (38.2%) males and 223 (61.8%) females. Out of this, 67.4% (242) were adults with adolescents making up the smallest proportion (Table 1). Majority of the patients were recruited from the antenatal and post-natal wards (91; 25.2%), paediatric medical ward (49; 13.6%) and newborn units (48; 13.3%), two hundred and thirty-seven patients (65.7%) had a prescription which had an antibiotic (119; 33.0% at Webuye County Hospital) and (118; 32.7% at Bungoma County Referral Hospital). Most antibiotic prescriptions were written by clinical officers (78; 33.1%) and clinical officer interns (92; 39.0%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Socio-demographic information of the patients on antibiotics at the Webuye County Hospital and Bungoma County Referral Hospital\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"97%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.144329896907216%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable (n=361)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eWCH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68041237113402%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBCRH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.144329896907216%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" valign=\"bottom\"\u003e\n \u003cp\u003e68 (18.8%)\u003c/p\u003e\n \u003cp\u003e103 (28.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68041237113402%\" valign=\"bottom\"\u003e\n \u003cp\u003e70 (19.4%)\u003c/p\u003e\n \u003cp\u003e120 (33.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"bottom\"\u003e\n \u003cp\u003e138 (38.2%)\u003c/p\u003e\n \u003cp\u003e223 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.144329896907216%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNeonates (0-28 days)\u003c/p\u003e\n \u003cp\u003eInfants (29 days-2 years)\u003c/p\u003e\n \u003cp\u003eChildren (2 -12 years)\u003c/p\u003e\n \u003cp\u003eAdolescent (13-16 years)\u003c/p\u003e\n \u003cp\u003eAdults (\u0026gt;17 years)\u003c/p\u003e\n \u003cp\u003eUnknown (age not specified)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" valign=\"bottom\"\u003e\n \u003cp\u003e17 (4.7%)\u003c/p\u003e\n \u003cp\u003e14 (3.9%)\u003c/p\u003e\n \u003cp\u003e15 (4.2%)\u003c/p\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003cp\u003e123 (34.3%)\u003c/p\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68041237113402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26 (7.2%)\u003c/p\u003e\n \u003cp\u003e17 (4.7%)\u003c/p\u003e\n \u003cp\u003e23 (6.4%)\u003c/p\u003e\n \u003cp\u003e3 (0.8%)\u003c/p\u003e\n \u003cp\u003e119 (33.1%)\u003c/p\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"bottom\"\u003e\n \u003cp\u003e43 (12.0%)\u003c/p\u003e\n \u003cp\u003e31 (8.6%)\u003c/p\u003e\n \u003cp\u003e38 (10.6%)\u003c/p\u003e\n \u003cp\u003e5 (1.4%)\u003c/p\u003e\n \u003cp\u003e242 (67.4%)\u003c/p\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.144329896907216%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWard\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAntenatal and post-natal ward\u003c/p\u003e\n \u003cp\u003ePediatric Medical Ward\u003c/p\u003e\n \u003cp\u003eNewborn unit\u003c/p\u003e\n \u003cp\u003eMale Surgical ward\u003c/p\u003e\n \u003cp\u003eFemale Medical ward\u003c/p\u003e\n \u003cp\u003eMale medical ward\u003c/p\u003e\n \u003cp\u003eFemale Surgical ward\u003c/p\u003e\n \u003cp\u003ePediatric Surgical Ward\u003c/p\u003e\n \u003cp\u003eEmergency department/Casualty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (8.6%)\u003c/p\u003e\n \u003cp\u003e18 (5.0%)\u003c/p\u003e\n \u003cp\u003e17 (4.7%)\u003c/p\u003e\n \u003cp\u003e27 (7.5%)\u003c/p\u003e\n \u003cp\u003e26 (7.2%)\u003c/p\u003e\n \u003cp\u003e15 (4.2%)\u003c/p\u003e\n \u003cp\u003e25 (6.9%)\u003c/p\u003e\n \u003cp\u003e11 (3.0%)\u003c/p\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68041237113402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60 (16.6%)\u003c/p\u003e\n \u003cp\u003e31 (8.6%)\u003c/p\u003e\n \u003cp\u003e31 (8.6%)\u003c/p\u003e\n \u003cp\u003e20 (5.5%)\u003c/p\u003e\n \u003cp\u003e15 (4.2%)\u003c/p\u003e\n \u003cp\u003e21 (5.8%)\u003c/p\u003e\n \u003cp\u003e5 (1.4%)\u003c/p\u003e\n \u003cp\u003e7 (1.9%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91 (25.2%)\u003c/p\u003e\n \u003cp\u003e49 (13.6%)\u003c/p\u003e\n \u003cp\u003e48 (13.3%)\u003c/p\u003e\n \u003cp\u003e47 (13.0%)\u003c/p\u003e\n \u003cp\u003e41 (11.4%)\u003c/p\u003e\n \u003cp\u003e36 (10.0%)\u003c/p\u003e\n \u003cp\u003e30 (8.3%)\u003c/p\u003e\n \u003cp\u003e18 (5.0%)\u003c/p\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.144329896907216%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics prescribed\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e119 (33.0%)\u003c/p\u003e\n \u003cp\u003e52 (14.4%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68041237113402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e118 (32.7%)\u003c/p\u003e\n \u003cp\u003e72 (19.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e237 (65.7%)\u003c/p\u003e\n \u003cp\u003e124 (34.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eWCH:\u0026nbsp;\u003c/strong\u003eWebuye County Hospital,\u003cstrong\u003e\u0026nbsp;BCRH:\u0026nbsp;\u003c/strong\u003eBungoma County Referral Hospital\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibiotic prescription patterns at the Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCeftriaxone was the most prescribed antibiotic in both hospitals (123; 38.8%) followed by metronidazole (89; 28.0%) and flucloxacillin (36; 11.3%) while meropenem was the least prescribed antibiotic (1; 0.88%) (Figure 2). Most of the antibiotics prescribed were from the \u0026ldquo;Watch\u0026rdquo; and \u0026ldquo;Access\u0026rdquo; category of the AWARE categorization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of the indications for antibiotic use at Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost antibiotics were prescribed empirically at the WCH (60; 25.4 %), while most antibiotics were prescribed prophylactically at the BCRH (46; 19.5%) (Table 2). In both hospitals, most prophylactic antibiotics were used in obstetrics and gynaecology departments. Clinical sepsis (17; 9.9%) was the leading indication for antibiotic prescriptions at the WCH while pneumonia (18; 9.5%) was the leading indication for antibiotic prescription at the BCRH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eComparison of the indications for antibiotic use at the Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"112%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.97959183673469%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIndications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.69387755102041%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWCH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBCRH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.402061855670103%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReason for antibiotic use\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.08247422680412%\" valign=\"top\"\u003e\n \u003cp\u003eEmpirical Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e60(25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e25(10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e85(36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eDefinitive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e28(11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e39(16.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e67(28.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eProphylactic Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e27(11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e46(19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e73(30.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eNot recorded\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e3(1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e8(3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e11(4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.402061855670103%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReason for prophylaxis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.08247422680412%\" valign=\"top\"\u003e\n \u003cp\u003eSurgery of GIT, liver, or biliary tree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e2(2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e2(2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e4(5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOpen fracture and other bone surgeries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e6(8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e3(4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e9(12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOBSGYN surgery/caesarean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e10(13.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e22(30.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e32(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eDrugs used in medical prophylaxis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e0(0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e4(5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e4(5.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e9(12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e15(20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e24(32.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.402061855670103%\" rowspan=\"14\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReasons for treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.08247422680412%\" valign=\"top\"\u003e\n \u003cp\u003eBone and joint infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003e9(5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003e4(2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e13(7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eClinical sepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e17(9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e8(4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e25(15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eGIT infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e3(1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e5(3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eInfections of ear, nose, throat, larynx, and mouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eObstetrics Gynaecological infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e8(4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e10(6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003ePneumonia (other than TB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e16(9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e18(10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e34(20.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eSoft tissue infections not involving bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e15(8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e6(3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e21(12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eCNS infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e9(5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e10(6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eIntra-abdominal sepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eLab confirmed bacteraemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e7(3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e7(4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eSymptomatic lower UTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e4(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eSymptomatic upper UTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e3(1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eHospital based infections (Pneumonia, UTI, Surgical site infections etc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e1(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e2(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e3(1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e19(11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" valign=\"top\"\u003e\n \u003cp\u003e11(5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e30(18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eWCH:\u0026nbsp;\u003c/strong\u003eWebuye County Hospital,\u003cstrong\u003e\u0026nbsp;BCRH:\u0026nbsp;\u003c/strong\u003eBungoma County Referral Hospital\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUptake of microbiology lab services in informing antibiotic use in the study area\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 237 (65.7%) of the patients who were on antibiotics, 16 (6.8%) were subjected to culture and sensitivity testing and 9 (81.8%) had their susceptibility results availed within the time of the study period (Table 3). Eight (88.9%) of the prescriptions with susceptibility testing were reviewed according to the sensitivity patterns as advised by the microbiology laboratory results. Of the 15 microbiological specimens, 10 (66.7%) were taken prior to initiation of the antibiotics, while 5 (33.3%) of them were taken after initiation of antibiotics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Utilization of the microbiology laboratory to inform antimicrobial selection at Webuye County Hospital and Bungoma County Referral Hospital during the study period\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMicrobiological culture\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eordered (n=237)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.484848484848484%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.746031746031747%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eWCH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.44444444444444%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBCRH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.80952380952381%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e9 (3.8%)\u003c/p\u003e\n \u003cp\u003e110 (46.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e7 (3.0%)\u003c/p\u003e\n \u003cp\u003e111 (46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e16 (6.8%)\u003c/p\u003e\n \u003cp\u003e221 (93.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWere microbiological tests ordered prior to initiation of antibiotics? (n=15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWere culture results availed? (n=16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e4 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e7 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e11 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWere AM susceptibility test results availed? (n=11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e9 (81.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWere prescriptions reviewed according to culture and susceptibility results? (n=9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"top\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"top\"\u003e\n \u003cp\u003e7 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e8 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eWCH:\u0026nbsp;\u003c/strong\u003eWebuye County Hospital,\u003cstrong\u003e\u0026nbsp;BCRH:\u0026nbsp;\u003c/strong\u003eBungoma County Referral Hospital\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypes of samples collected for culture and sensitivity in the study area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSixteen samples were collected for microbiology testing; seven (43.8%) were from the CSF, 4 (25.0%) were from pus swabs, 3(18.8%) (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther diagnostic tests at WCH and BCRH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOther diagnostic tests carried out at the WCH and BCRH that informed antibiotic prescriptions during the study period included full hemogram 200 (35.4%), imaging 78 (13.8%), and urinalysis 25(4.4%) tests (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Other diagnostic tests carried out at Webuye County Hospital and Bungoma County Referral Hospital to inform antibiotic prescriptions during the study period\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"708\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.79661016949152%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.972789115646258%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eWCH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBCRH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.292517006802722%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eFull hemogram\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e86 (43.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e114 (57.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e200 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eRenal function test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e23 (21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e82 (78.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e105 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eImaging/Radiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e75 (96.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e78 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBS for mps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e31 (50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e30 (49.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e61 (10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eLiver function test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e20 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e31 (60.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e51 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eUrinalysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e17 (68.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e8 (32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e25 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e10 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e21 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eESR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e7 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eGene Expert/AFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e6 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e6 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eCreative protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eSalmonella antigen test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eAntistreptolysin O titer (ASOT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003eVDRL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.71186440677966%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eH.pylori\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.915254237288135%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.88135593220339%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eWCH:\u0026nbsp;\u003c/strong\u003eWebuye County Hospital,\u003cstrong\u003e\u0026nbsp;BCRH:\u0026nbsp;\u003c/strong\u003eBungoma County Referral Hospital\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAntimicrobial resistance is a growing global threat to humanity. Antimicrobial point-prevalence surveys are feasible early tools for evaluating antimicrobial use and identifying gaps for improvement [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, we assessed antimicrobial use, prescription practices and microbiological testing in two major hospitals in Bungoma County, Western Kenya. We found that 237 (65.7%) were on antibiotics. Similar studies done in Vietnam indicated 67.4% of patients were given antibiotics [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This study had a general rate of prescription at a similar level to our study. Among the specific antibiotics, ceftriaxone (34.5%) was the most commonly prescribed antibiotics and this has also been documented in other studies in sub-Saharan Africa [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Ceftriaxone is widely utilized in sub-Saharan Africa (SSA) due to its cost-effectiveness and safety in treating various infections. However, studies have reported a high rate of inappropriate use, and there is increasing concern about bacterial resistance in ceftriaxone users, which may compromise its effectiveness for treating infections. For example, Sie et al reported that Penicillins were the most used class of antibiotics among children under 5 years in Burkina Faso [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and Akintan et al reported that third generation cephalosporins were the most frequently prescribed antibiotic at the paediatric department of the Lagos Teaching Hospital in South-Western Nigeria [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe distinction between empirical treatment at WCH and prophylactic use at BCRH underscores the variability in clinical practices and resource availability. Empirical antibiotic use, while necessary in certain cases, poses a risk of inappropriate use, potentially increasing the threat of AMR [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. On the other hand, prophylactic use must be judicious to prevent unnecessary exposure to antibiotics [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e–\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The observed discrepancies in antibiotic prescribing practices between WCH and BCRH indicate the need for standardized treatment guidelines. Additionally, implementing antimicrobial stewardship programs can help monitor and optimize antibiotic use [\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e–\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe low utilization of microbiological testing to inform antibiotic prescription among patients is alarming and highlights a significant gap in diagnostic capabilities. This low rate of testing is consistent with reports from other low-resource settings, where laboratory services are often limited [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e–\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The clinical microbiology laboratory plays a vital role in the management of bacterial infections. Relying solely on symptoms can lead to significant misdiagnosis of infections. Although susceptibility results influenced a significant number of prescriptions, delayed testing poses risks of inappropriate initial treatment. Improved diagnostic practices are essential for guiding appropriate antimicrobial therapy and mitigating AMR [\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e–\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInternationally, point prevalence surveys have been important in identifying trends and informing AMR strategies. For example, the European Surveillance of Antimicrobial Consumption Network (ESAC-Net) found significant variation in antibiotic use across Europe, underscoring the impact of local guidelines and stewardship programs [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Regionally, studies in Uganda and Tanzania have reported similar issues with empirical prescribing and limited diagnostic testing, reinforcing the challenges faced in sub-Saharan Africa [\u003cspan additionalcitationids=\"CR47 CR48 CR49\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e–\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Locally, data from Kenyan hospitals align with the findings of this study, highlighting the need for a coordinated national approach to antimicrobial stewardship [\u003cspan additionalcitationids=\"CR52 CR53 CR54 CR55\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e–\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of the study\u003c/h2\u003e \u003cp\u003eThis study is limited by its cross-sectional design and focus on two hospitals in Western Kenya, potentially limiting generalizability. Future research should expand to a broader geographic area and longitudinal studies to capture any trends in antibiotic use and resistance patterns.\u003c/p\u003e \u003c/div\u003e "},{"header":"Conclusions and recommendations","content":"\u003cp\u003eThe study reveals significant gaps in antimicrobial use and diagnostic practices in the selected hospitals in Bungoma County. Addressing these issues through enhanced diagnostic capabilities, standardized prescribing practices, and robust stewardship programs is essential to mitigate AMR and improve patient outcomes. Continuous education for healthcare providers on AMR and rational antibiotic use is key as is the development and enforcement of national guidelines for antibiotic prescribing. This will ensure consistency across healthcare facilities in the county. The findings from our study will help inform targeted interventions and policy decisions to improve AMR management in Bungoma County and could serve as a model for other regions facing similar challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Government of the United Kingdom of Great Britain and Northern Ireland under the Fleming Fund project (GCP/GLO/710/UK) and the Global Health Security Agenda (OSRO-GLO-507-USA) through United States Agency for International Development (USAID).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests:\u003c/strong\u003e The authors declare no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets associated with this manuscript are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e Participants\u0026rsquo; consent was given as per Section 25 \u0026ndash; 32 of the World Medical Association\u0026rsquo;s Declaration of Helsinki \u0026ndash; Ethical Principles for Medical Research Involving Human Subjects\u0026nbsp;[57]. All participants gave their informed consent to participate in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Conceptualization, E.M., J.W., C.N., V.L., L.A., P.K. ,J.O., and R.O.,; methodology, E.M.,, E.O., T.K., J.O., and R.O.,; software, J.O., and R.O.,.; validation, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; formal analysis, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; investigation, J.O.; resources, R.O., T.K., E.O.,., and E.M.,.; data curation, E.M., T.K., E.O.,J.O.,M.O.,and R.O.,; writing\u0026mdash;original draft preparation, J.O., E.M., T.K., E.O., J.O., M.O., and R.O.,; writing\u0026mdash;review and editing, E.M., T.K., E.O.,J.O., M.O., and R.O.,.; visualization, E.M., T.K., E.O.,J.O., M.O., and R.O.,; supervision, E.M., T.K., E.O.,J.O., M.O., and R.O.,; project administration, E.M., R.O., T.K., E.O.,J.O., M.O., and R.O.,; funding acquisition, T.K., E.O.,and R.O.,; All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDhingra S, Rahman NAA, Peile E, Rahman M, Sartelli M, Hassali MA, et al. 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J Glob Antimicrob Resist. 2020;22:317\u0026ndash;24. https://doi.org/10.1016/j.jgar.2020.03.009\u003c/li\u003e\n\u003cli\u003eRawson TM, Wilson RC, O\u0026rsquo;Hare D, Herrero P, Kambugu A, Lamorde M, et al. Optimizing antimicrobial use: challenges, advances and opportunities. Nat Rev Microbiol. 2021;19:747\u0026ndash;58. https://doi.org/10.1038/s41579-021-00578-9\u003c/li\u003e\n\u003cli\u003eRonat J-B, Natale A, Kesteman T, Andremont A, Elamin W, Hardy L, et al. AMR in low-resource settings: M\u0026eacute;decins Sans Fronti\u0026egrave;res bridges surveillance gaps by developing a turnkey solution, the Mini-Lab. Clin Microbiol Infect. 2021;27:1414\u0026ndash;21. https://doi.org/10.1016/j.cmi.2021.04.015\u003c/li\u003e\n\u003cli\u003eIskandar K, Molinier L, Hallit S, Sartelli M, Hardcastle TC, Haque M, et al. Surveillance of antimicrobial resistance in low-and middle-income countries: a scattered picture. Antimicrob Resist Infect Control. 2021;10:1\u0026ndash;19. https://doi.org/10.1186/s13756-021-00931-w\u003c/li\u003e\n\u003cli\u003eWertheim HFL, Huong VTL, Kuijper EJ. Clinical microbiology laboratories in low-resource settings, it is not only about equipment and reagents, but also good governance for sustainability. Clin Microbiol Infect. 2021;27:1389\u0026ndash;90. https://doi.org/10.1016/j.cmi.2021.07.027\u003c/li\u003e\n\u003cli\u003eJacobs J, Hardy L, Semret M, Lunguya O, Phe T, Affolabi D, et al. Diagnostic bacteriology in district hospitals in sub-Saharan Africa: at the forefront of the containment of antimicrobial resistance. Front Med. 2019;6:205. https://doi.org/10.3389/fmed.2019.00205\u003c/li\u003e\n\u003cli\u003eIregbu KC, Osuagwu CS, Umeokonkwo CD, Fowotade AA, Ola-Bello OI, Nwajiobi-Princewill PI, et al. Underutilization of the clinical microbiology laboratory by physicians in Nigeria. African J Clin Exp Microbiol. 2020;21:53\u0026ndash;9. https://doi.org/10.4314/ajcem.v21i1.7\u003c/li\u003e\n\u003cli\u003eGodman B, Egwuenu A, Haque M, Malande OO, Schellack N, Kumar S, et al. Strategies to improve antimicrobial utilization with a special focus on developing countries. Life. 2021;11:528. https://doi.org/10.3390/life11060528\u003c/li\u003e\n\u003cli\u003eVasala A, Hyt\u0026ouml;nen VP, Laitinen OH. Modern tools for rapid diagnostics of antimicrobial resistance. Front Cell Infect Microbiol. 2020;10:308. https://doi.org/10.3389/fcimb.2020.00308\u003c/li\u003e\n\u003cli\u003eHage CA, Carmona EM, Epelbaum O, Evans SE, Gabe LM, Haydour Q, et al. Microbiological laboratory testing in the diagnosis of fungal infections in pulmonary and critical care practice. An official American Thoracic Society clinical practice guideline. Am J Respir Crit Care Med. 2019;200:535\u0026ndash;50. https://doi.org/10.1164/rccm.201906-1185ST\u003c/li\u003e\n\u003cli\u003eSieswerda E, De Boer MGJ, Bonten MMJ, Boersma WG, Jonkers RE, Aleva RM, et al. Recommendations for antibacterial therapy in adults with COVID-19\u0026ndash;an evidence based guideline. Clin Microbiol Infect. 2021;27:61\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eZarb P, Goossens H. European surveillance of antimicrobial consumption (ESAC) value of a point-prevalence survey of antimicrobial use across europe. Drugs. 2011;71:745\u0026ndash;55. https://doi.org/10.1016/j.cmi.2020.09.041\u003c/li\u003e\n\u003cli\u003eHorumpende PG, Mshana SE, Mouw EF, Mmbaga BT, Chilongola JO, de Mast Q. Point prevalence survey of antimicrobial use in three hospitals in North-Eastern Tanzania. Antimicrob Resist Infect Control. 2020;9:1\u0026ndash;6. https://doi.org/10.1186/s13756-020-00809-3\u003c/li\u003e\n\u003cli\u003eSeni J, Mapunjo SG, Wittenauer R, Valimba R, Stergachis A, Werth BJ, et al. Antimicrobial use across six referral hospitals in Tanzania: a point prevalence survey. BMJ Open. 2020;10:e042819. https://doi.org/10.1136/bmjopen-2020-042819\u003c/li\u003e\n\u003cli\u003eKatyali D, Kawau G, Blomberg B, Manyahi J. Antibiotic use at a tertiary hospital in Tanzania: findings from a point prevalence survey. Antimicrob Resist Infect Control. 2023;12:112. https://doi.org/10.1186/s13756-023-01317-w\u003c/li\u003e\n\u003cli\u003eKiggundu R, Wittenauer R, Waswa JP, Nakambale HN, Kitutu FE, Murungi M, et al. Point prevalence survey of antibiotic use across 13 hospitals in Uganda. Antibiotics. 2022;11:199. https://doi.org/10.3390/antibiotics11020199\u003c/li\u003e\n\u003cli\u003eD\u0026rsquo;Arcy N, Ashiru-Oredope D, Olaoye O, Afriyie D, Akello Z, Ankrah D, et al. 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Antibiotic prescribing patterns at a leading referral hospital in Kenya: a point prevalence survey. J Res Pharm Pract. 2019;8:149. https://doi.org/10.4103/jrpp.JRPP_18_68\u003c/li\u003e\n\u003cli\u003eKamita M, Maina M, Kimani R, Mwangi R, Mureithi D, Nduta C, et al. Point prevalence survey to assess antibiotic prescribing pattern among hospitalized patients in a county referral hospital in Kenya. Front Antibiot. 2022;1:993271. https://doi.org/10.3389/frabi.2022.993271\u003c/li\u003e\n\u003cli\u003eKaranja PW, Kiunga A. Point Prevalence Survey and Patterns of Antibiotic Use at Kirinyaga County Hospitals, Kenya. East Africa Sci. 2023;5:67\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eMuyu MG. Antimicrobial Use Practices in Mbagathi Hospital, Nairobi-kenya-a Point Prevalence Survey. 2020.Available from http://erepository.uonbi.ac.ke/handle/11295/154623. Accessed 20 Apr 2024. \u003c/li\u003e\n\u003cli\u003eWMA Declaration of Helsinki \u0026ndash; Ethical Principles for Medical Research Involving Human Subjects \u0026ndash; WMA \u0026ndash; The World Medical Association. Available from https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/. Accessed 7 Aug 2024.\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":"Point prevalence survey, antimicrobial resistance, antimicrobial stewardship, antimicrobial use, diagnostic stewardship, Western Kenya","lastPublishedDoi":"10.21203/rs.3.rs-4889823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4889823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInformation from point prevalence surveys can guide antimicrobial stewardship programs (ASPs). The aim of the present study was to document the use of antimicrobial agents at two hospitals in Western Kenya, namely Bungoma County Referral Hospital (BCRH) and Webuye County Hospital (WCH).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe World Health Organization (WHO) Global Point Prevalence Survey (G-PPS) tool was used to collect sociodemographic information of study participants, the type of antimicrobial agents used, indications for antimicrobial use, and diagnostic tests conducted on participants. Files were selected over 24 hours, data was abstracted between July and October 2022, and analysis was carried out on SPSS version 26.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the 361 patients, 223 (61.8%) were on antibiotics. The most common antibiotics used were ceftriaxone (123/237; 34.5%), metronidazole (89/237; 24.9%), and flucloxacillin (36/237; 10.1%). Most (60/237; 25.4%) antibiotics at the WCH were prescribed empirically, while most (46/237; 19.5%) antibiotics at the BCRH were prescribed for prophylaxis. Pneumonia was the leading indication for antibiotic prescriptions at BCRH (18/169, 9.5%), while clinical sepsis (17/169;9.9%) was the leading indication for antibiotic prescriptions at the WCH. 16/237 (6.8%) of the patients who had an antibiotic prescribed were subjected to culture and sensitivity testing, but only 9/16 (81.8%) received the results of the antimicrobial susceptibility tests within the study period.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePenicillins and Cephalosporins were widely used, prescribing/clinical practices vary from one hospital to another, and microbiological tests were underutilized in the study area. There is a need for enhanced antimicrobial and diagnostic stewardship in the study area.\u003c/p\u003e","manuscriptTitle":"A point prevalence survey of antimicrobial use in two hospitals in Western Kenya","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 10:39:57","doi":"10.21203/rs.3.rs-4889823/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-04T05:56:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-03T15:10:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283305081213181788295460722068159200598","date":"2024-08-30T12:36:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-26T06:54:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13836498667878792347401440850614672367","date":"2024-08-24T06:31:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-23T14:49:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-20T11:34:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-19T06:53:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2024-08-10T03:45:53+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":"3c6debf4-e586-4433-9a47-5de200e193db","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T16:01:53+00:00","versionOfRecord":{"articleIdentity":"rs-4889823","link":"https://doi.org/10.1186/s12982-025-00619-1","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2025-05-04 15:57:43","publishedOnDateReadable":"May 4th, 2025"},"versionCreatedAt":"2024-10-14 10:39:57","video":"","vorDoi":"10.1186/s12982-025-00619-1","vorDoiUrl":"https://doi.org/10.1186/s12982-025-00619-1","workflowStages":[]},"version":"v1","identity":"rs-4889823","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4889823","identity":"rs-4889823","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}