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    • At Johns Hopkins Aramco Health

    2024-03-21

    At Johns Hopkins Aramco Health (JHAH), we started an ASP in 2011 with an educational program of physicians and pharmacist. The program was enhanced mid-2012 with the following interventions: a re-designed antibiotic sensitivity report [2], intravenous to oral conversion program, vancomycin pharmacokinetic program [7], automatic renal dosing, antibiotic de-escalation, pre-operative antibiotic protocols utilizing adapted orders, and a multi-facteted approach to decrease SKL2001 mg for respiratory tract infections [8]. The program incorporated “if you cannot measure it, you cannot improve it,” and thus included periodic measurement and monitoring of antibiotic use, and comparing data within the institution and with other institutions [1], [9]. To standardize the units for comparison, we used the most common definitions: defined daily dose (DDD), and days of therapy (DOT). DDD is as an average of the maintenance dose of a single antibiotic in its main indication for adults per day [10]. According to the World Health Organization (WHO), each drug has an anatomical therapeutics chemical (ATC) code and a DDD value in grams [10]. To define the exact consumption rate, it was recommended to express DDD per 100 bed-days in hospitals and DDDs per 1000 inhabitant-days for out-patients [11], [12], [13]. DOT is the number of days that a patient receives an antibiotic regardless of the dose [1]. DDD has better estimation than DOT, especially in patients receiving a combination of antibiotics or one dose only (e.g., surgical prophylaxis), and it can be calculated even in the absence of a computerized pharmacy system [1]. A better measure for comparing DDD with an external hospital, is the quantitative assessment of antibiotics use, with adjustment for severity of illness among hospitalized patients, using the case mix index (CMI) [11], [14]. There are limited studies of antibiotic utilization in Saudi Arabia [15]. In this study, we compare the DDD, DOT, DDD per 100 bed-days, and the adjusted DDD according to CMI.
    Materials and methods The study was carried out at Dhahran Health Center as a part of Johns Hopkins Aramco Healthcare (JHAH), which serves a population of approximately 370,000 patients [16]. Dhahran Health Center is the main general hospital with a 380-bed capacity and five intensive care units (Cardiac, medical, surgical, pediatric, and neonatal) [16]. The hospital provides acute, general medicine and surgery, intensive care services, and management of hematological and solid organ malignancies [16]. A computerized database was generated for all prescribed antibiotics. Antibiotic data were collected for 2011 to have a baseline, and then retrospectively for 2013–2015. All data were collected for the first 6 months of 2011, 2013–2015. To minimize the drawback of using DDD, only adult patients (above 15 years of age) were included in the study. The data were transferred to an Excel spreadsheet. The World Health Organization 2013 Guidelines for Anatomical Therapeutic Chemical/Defined Daily Dose (ATC/DDD) were utilized for the calculation of DDD. DDD for each antibiotic was calculated separately, the total number of grams administered for each antibiotic per year was divided by the WHO DDD in grams [10]. Thus, the DDD is an estimate of the number of days of antibiotic therapy. Data of day surgery was not included in calculating the bed days. Antibiotic usage was adjusted per 100 bed-days by dividing DDD by daily occupied beds and multiplied by 100. A direct measure of the number of days of therapy (DOTs) is a common method of antibiotic usage evaluation. DOT is simply the sum of the total number of days of all used antibiotics. Thus, when the same patient receives more than one antibiotic, more than one DOT was counted. The case mix index (CMI), an economic surrogate marker, was calculated by dividing total cost weights for all inpatient in specific period by the number of admission [17], as provided by the hospital information department. CMI describes the average patients' morbidity of individual hospitals [17].