DOI: 10.6084/m9.figshare.28539008.v1
title: Antibiotic Prevalance (Responses).xlsx

description: Antimicrobial resistance is a significant global health problem with new resistance patterns emerging around the world (1). It is also the cause of public health problems as resistant organisms lead to longer illness, increased mortality, and increased cost of treatment. The current global AMR crisis is the result of a number of factors, including overprescribing and over dispensing of antimicrobial medicines by health workers, noncompliance with treatment courses, low-quality medicines and incorrect prescription with wrong dosage, poor infection prevention and control practices in hospitals and clinics, and lack of hygiene and poor sanitation. AMR is a complex problem with many interrelated causes. Excessive and inappropriate use of antibiotics is highly associated with the emergence of antibiotic resistance, which presents a major threat to global public health.Antibiotic resistance reduces the effectiveness of and number of options for antibiotic treatment, leading to increased morbidity, mortality, and health care expenditures. A recent prevalence survey in the United States found that 75% of hospitalized patients received more than one antimicrobial at the time of the survey and studies have shown that a relatively large proportion of antibiotic use is inappropriate or unnecessary.Other factors influencing AMR, such as poor infection prevention and control in healthcare facilities and lack of available, inexpensive, and rapid diagnostic tests, are also important factors that require urgent address. It is likely that inappropriate use of antibiotics is widespread; however, information on antibiotic consumption and use is scarce in low- and middle-income countries. In order to inform effective policies and interventions that optimize use and promote equitable access to medicines, it is essential to collect information on the current situation of antibiotic use in all countries. Collecting hospital data and subsequently implementing informed interventions to optimize antibiotic use in hospitals has significant potential to lower antibiotic resistance at local and higher levels.<br><b>Objective :</b>· To describe the antibiotic use among in-patients in a tertiary care hospital· To determine the crude prevalence of patients with at least one antibiotic.<br><b>METHODOLOGY</b><br><br>a) <b>Study design:</b> A cross-sectional point prevalence studyb) <b>Study settings:</b> medical, surgical, and critical care units of Pondicherry Institute of Medical Sciencesc) <b>Study period:</b> 2 monthsd) <b>Study population:</b> All in-patients admitted in the various medical and surgical wards at 0800 h on the survey day.<b>e)</b><b> </b><b>Inclusion criteria:</b>a. Patients on antibiotic therapy (oral, parental, inhalational, topical or rectal routes) at 08:00 on the day of the survey<b>f)</b><b> </b><b>Exclusion criteria:</b>· Patients admitted to the ward after 08:00· Antibiotic therapy is initiated after 08:00 on the day of the survey· Antibiotic therapy was stopped before 08:00 on the day of the survey.<b>g)</b><b> </b><b>Sample size: </b>All patients meeting the inclusion criteria were surveyed (13).h) <b>Study tool: </b>WHO Point prevalence antibiotic survey tool.<i>Data collection</i>The audit was done across various medical, surgical wards, and critical care units for a period of 2 weeks each. The data was collected from the records on a daily basis using the WHO Point prevalence antibiotic survey tool (13). For each patient with an antimicrobial prescribed and charted, the following information was obtained from the records and entered on the data collection form: demographic details, diagnosis, indications, Antibiotic drug, dosage, route, frequency, and duration, start and review/stop date, escalation and deescalation of the antibiotic. Data was also collected for any patient who was prescribed a stat dose of an antimicrobial or surgical antibiotic prophylaxis since 0800 a.m. the previous day. All the study data was anonymized and each form was given a unique identification number.Statistical analysis was performed with SPSS statistics software. Means and standard deviations (SD), ranges and frequencies (%) were calculated where appropriate.