Table 2.

Impact of ASPs on Antibiotic Usage, Microbiological, Clinical, and Financial Outcomes

Study Reference No.	Countries	Settings, Design, Time, and Health Personnel Involved	Interventions	Outcome Measured	Impact
Wang et al (2019)156	China	Tertiary hospital. A retrospective observational study. 2011 to 2016 Pharmacists	Multi-aspect interventions: activity program, performance management, and training.	Antibiotic prescriptions, the intensity of consumption, antibiotic prophylaxis, and resistance rates	↓Prescriptions: outpatients - 19.38% to 13.21%, inpatients −64.34% to 34.65%. ↓Intensity: 102.46 to 37.38 DDDa/100 PDb ↓Prophylaxis: 98.94% to 18.93%. ↓Resistance ratesc ↓MRSAd incidence: 68.0% to 37.5% ↑Resistance ratese
Xiao et al (2020)161	China	Secondary and tertiary hospitals A retrospective observational study. 2010 to 2016	AMS campaign	Antibiotic prescriptions, intensity of consumption, antibiotic expense, and resistance rates	↓Prescription: outpatients - 19.5% to 8.5%; surgical patients - 97.9% to 38.3%. ↓Intensity: 85.3% to 48.5% DDD/100 bed-days. ↓Antibiotic procurement costs:22.3% to12.1%. ↓Resistance ratesf: 30.8% to 22.3% ↓MRSA incidence: 54.4% to 34.4%
Mardani et al (2020)162	Iran	Tertiary teaching hospitals. An interventional quasi-experimental study. Before (2017 to 2018) and after (2018 to 2019) ASP implementation. Nurses and physicians.	AMS educational programs	Antibiotic prescriptions, the occurrence of CDI, and positive MDR cases	↓Prescriptiong: 22,464 to 17,262 g. ↓CDIh incidence: 11.2% to 2.7% cases per 10,000 patient days ↓MDRi cases: 145 t0 75
Onorato et al (2020)163	Italy	Intensive care units (ICUs) of a teaching hospital. Prospective, interventional, Interrupted time-series study. Time: 2017–2018.		Antibiotic prescriptions, incidence of BSI, hospital mortality rate, mean LOS, and antibiotic expense.	↓Prescription: 324.8 DDD/100 PD ↓Incidence of BSIj: 5.8 events/100 PD Hospital mortality rate: No difference Mean LOSk: No difference
Savoldi et al (2020)164	Germany	Prospective quasi-experimental, Interrupted time-series study. Tertiary care teaching hospital. 2014 and 2017.	Non-restrictive ASP, 3 phases: 1-year pre-intervention, 2-year multifaceted intervention, and one year of post-intervention.	Antibiotic prescriptions, antibiotic expense, mean LOS, CDI incidence rate, and mortality in the patients’ group were admitted from ED to medical wards.	↓Prescription: 31.1% to 7.2% DDD/100 PD. ↓Incidence of CDI ↓Mean LOS Mortality rate: No difference ↓Antibiotic expense: 691.5 to 263.3 EUROs/100 PDs
Singh et al (2018)165	India	Tertiary teaching hospital. Quasi-experimental study. 2015 to 2017. Infection control team	Post-prescriptive audit and establishment of institutional guidelines	Antibiotic prescriptions, antibiotic expense, compliance with ASP Recommendations	↓Prescription (DDD/100 PD). ↓Mean monthly cost for restricted drugs by 14.4% ↑Compliance: 54%
Wee et al (2020)166	Singapore	Tertiary teaching hospital. A retrospective cohort studies. 2016 to 2018.	Prospective audit and feedback strategy	Adherence to ASP recommendations	↑Adherence: 81.9% (5758/7028)
Abubakar et al (2019)167	Nigeria	Tertiary hospitals. Prospective pre- and post-intervention study. May and December 2016. Pharmacists.	Development of a protocol, educational meeting and audit and feedback	Antibiotic prescriptions, the intensity of consumption, antibiotic expense, and resistance rates	↓Prescription: 19.1% ↓Prescription: third generation cephalosporin (−8.6%), ↓Intensity: (3.8 DDD/procedure) ↓Cost: $4.2/procedure ↑Compliance: Timing (14.2% to 43.3%) and duration (0% to 21.8%)
Brink et al (2017)168	South Africa	Private hospitals. Prospective pre- and post-intervention study. Pharmacist. 2013–2015.	Prospective audit and feedback for perioperative antibiotic prophylaxis	SSI and compliance.	↑Compliance: 66.8% to 83.3% (95% CI 80.8–85.8). ↓SSIl rate 19.7%
Horikoshi et al (2017)155	Japan	Tokyo Metropolitan Children’s Medical Center. Prospective pre- and post-intervention study. Quasi-experimental study. 2010–2017.	Computerized preauthorization and a prospective audit, an electronic chart-based drug ordering system	DOT in the post-intervention period, the resistance rate, and the correlation between DOT and resistance rates, average days of hospitalization, all-cause mortality, and infection-related mortality in the pre- and post-intervention periods.	↓DOTm in the post-intervention period: 59.3% ↓The resistance rate: 72.2% ↑positive correlation ↓Average hospitalization (days) ↓All-cause mortality rate (per 1000 patient-days) ↓Infection-related mortality rate (per 1000 patient-days)
D’Agata et al (2018)169	USA	Outpatient dialysis facilities. Quasi-experimental study. 2015–2016	ASP	Rates of antimicrobial use per 100 patient months, rates of use for specific antimicrobials or antimicrobial groups.	↓Antimicrobial doses per 100 patient months: 6%

Notes: ^cE. coli and P. aeruginosa to fluoroquinolones. ^eE. coli and K. pneumoniae to carbapenems. ^fCarbapenem-resistant Pseudomonas aeruginosa isolates. ^gMeropenem prescriptions. ^hClostridium difficile infections. ↑: Increase. ↓: Decrease.

Abbreviations: ^aPD, patient-days; ^bDDD, defined daily doses; ^dMRSA, methicillin-resistant Staphylococcus aureus; ⁱMDR, multidrug resistance; ^jBSI, bloodstream infections caused by multidrug-resistant (MDR) organisms; ^kLoS, length of stay; ^lSSI, surgical site infections; ^mDOT, day of therapy.