Dataset Open Access
Overuse of antibiotics is one of the main drivers for antimicrobial resistance (AMR). Globally, most antibiotics are prescribed in the outpatient setting. This survey aimed to explore attitudes and practices with regards to microbiology tests, AMR and antibiotic prescribing among healthcare providers at public primary health clinics in Harare, Zimbabwe.
Methods: This cross-sectional survey was conducted in nine primary health clinics located in low-income suburbs of Harare between October and December 2020. In Zimbabwe, primary health clinics provide nurse-led outpatient care for acute and chronic illnesses. Healthcare providers who independently prescribe antibiotics and order diagnostic tests were invited to participate. The survey used self-administered questionnaires. A five-point Likert scale was used to determined attitudes and beliefs.
Results: A total of 91 healthcare providers agreed to participate in the survey. The majority of participants (62/91, 68%) had more than 10 years of work experience. Most participants reported that they consider AMR as a global (75/91, 82%) and/or national (81/91, 89%) problem, while 52/91 (57%) considered AMR to be a problem in their healthcare facilities. A fifth of participants (20/91, 22%) were unsure if AMR was a problem in their clinics. Participants felt that the availability of national guidelines (89/89, 100%), training sessions on antibiotic prescribing (89/89, 100%), and regular audit and feedback on prescribing (82/88, 93%) were helpful interventions to improve prescribing.
Conclusions: These findings support the need for increased availability of data on AMR and antibiotic use in primary care. Educational interventions, regular audit and feedback, and access to practice guidelines may be useful to limit the overuse of antibiotics.
The dataset has a codebook explaining the variables and their coding. The questionnaire used for the survey is also included in the meta-data submitted alongside the dataset.
Missing variables are usually specifically described as missing in the dataset (e.g. "not answered"). Some variables present additional information usually related to a list variable (e.g. other pathogens associated with antimicrobial resistance). If the respondent did not provide any information for the free-text question, the cell is blank. One question asked about training types (how training was delivered). If no training was done, then the additional information on how training was delivered is missing.
Funding provided by: Wellcome Trust
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100010269