Knowledge and Beliefs of Health Care Professionals Towards Antimicrobial Resistance in Hiwot Fana Specialized University Hospital, in Harar, Ethiopia

BACKGROUND: Antimicrobial resistance (AMR) results in treatment failure and spread of the infection, which will cause prolonged illness, increased mortality, and financial burdens. Some factors that are responsible for inappropriate use of antimicrobials include lack of expertise by health care professionals and problems in diagnosis. OBJECTIVE: To assess the knowledge and belief related to AMR among health care professionals in HFSUH in Harar, Ethiopia. METHODOLOGY: A cross-sectional study was conducted on 153 physicians, nurses, and pharmacists from HFSUH, which were selected using stratified sampling with proportional allocation. Data were collected from March 1 to March 30, 2017, and were analyzed using the Statistical Package for Social Sciences (SPSS 20.0). RESULTS: Only 132 participants were willing to participate from the 153 health care providers; of whom, 35 (26.5%) were physicians, 86 (65.2%) were nurses, and 11 (8.3%) were pharmacists. MRSA was mentioned as the prominent resistant bacteria by 74.3% of the physician, 59.3% of the nurses, and 63.6% of the pharmacists. The majority consider the overuse of antibiotics, poor infection control, sub-standard antibiotic, and patients’ poor adherence as factors for AMR. AMR was considered a problem worldwide, country, and hospital level. Forty percent of the physicians, 32.6% of the nurses, and 63.6% of the pharmacists consider the patient influence on the prescriber as the cause; whereas, 31.4% of the physician, 48.8% nurses, and 36.4% of the pharmacists consider the failure of previous treatment as the major cause of unnecessary antimicrobial prescription. CONCLUSION: The information the health care professionals have about the different resistant bacteria, on the different factors that cause unnecessary antibiotic prescription and on how to use susceptibility testing is low. All professionals should take regular AMR training and select antibiotics based on tests and minimize the risk of AMR.