The irrational use of antimicrobial agents is an important challenge for global public health. In order to improve medication safety and efficacy in clinical practice, this article systematically explores pharmacist-led interventions and current advances in antimicrobial prescription management, focusing on key processes such as catalog selection, pre-prescription review and evaluation, real-time feedback mechanism, team collaboration mode, etc. With the support of information technology and artificial intelligence, interventions led or participated by pharmacists can help improve the standardization and timeliness of prescription review, reduce the abuse of broad-spectrum antibiotics, and improve patients’ prognosis.With the release of various policies and guidelines and the promotion of medical insurance incentive mechanisms, the role of pharmacists in antimicrobial stewardship is becoming increasingly prominent. This study aims to provide theoretical guidance and practical insights for optimizing antimicrobial use strategies in China.

1.Tang KWK, Millar BC, Moore JE. Antimicrobial resistance (AMR)[J]. Br J Biomed Sci, 2023, 80: 11387. DOI: 10.3389/bjbs.2023.11387.

2.Aierken A, Zhu X, Wang N, et al. Measuring temporal trends and patterns of inpatient antibiotic use in Northwest China's hospitals: data from the Center for Antibacterial Surveillance, 2012-2022[J]. Antibiotics (Basel), 2024, 13(8): 732. DOI: 10.3390/antibiotics13080732.

3.Wushouer H, Zhou Y, Zhang W, et al. Inpatient antibacterial use trends and patterns, China, 2013-2021[J]. Bull World Health Organ, 2023, 101(4): 248-261B. DOI: 10.2471/BLT.22.288862.

4.Mulchandani R, Zhao C, Tiseo K, et al. Predictive mapping of antimicrobial resistance for Escherichia coli, Salmonella, and Campylobacter in food-producing animals, Europe, 2000-2021[J]. Emerg Infect Dis, 2024, 30(1): 96-104. DOI: 10.3201/eid3001.221450.

5.Ramanath K, Gowda M, Valleru L, et al. Assessment of dispensing practice of antibiotics in the selected community pharmacies: a prospective study[J]. J Adv Med Med Res, 2022, 2022: 249861415. DOI: 10.9734/jammr/2022/v34i1931448.

6.Wushouer H, Ko W, Du K, et al. Exploring facilitators and barriers to delayed antibiotic prescribing in rural Northwest China: a qualitative study using the theoretical domains framework and behavior change wheel[J]. Antibiotics, 2023, 12(12): 1741. DOI: 10.3390/antibiotics12121741.

7.Wushouer H, Du K, Yu J, et al. Outpatient antibiotic prescribing patterns in children among primary healthcare institutions in China: a nationwide retrospective study, 2017-2019[J]. Antibiotics, 2024, 13(1): 70. DOI: 10.3390/antibiotics13010070.

8.王珂璇, 刘芳, 涂佳佳, 等. 基于断面时点流行病学调查方法探究医院抗菌药物的使用[J]. 上海交通大学学报（医学版）, 2024, 44(3): 365-372. [Wang KX, Liu F, Tu JJ, et al . Exploration of the use of antibiotics in a hospital based on point prevalence survey[J]. Journal of Shanghai Jiaotong University (Medical Science), 2024, 44(3): 365-372.] DOI: 10.3969/j.issn.1674-8115.2024.03.009.

9.Naghavi M, et al. Global burden of bacterial antimicrobial resistance 1990-2021: a systematic analysis with forecasts to 2050[J]. Lancet, 2024, 404(10459): 1199-1226. DOI: 10.1016/S0140-6736(24)01867-1.

10.Iles RK, Zmuidinaite R, Iles JK, et al. Development of a clinical MALDI-ToF mass spectrometry assay for SARS-CoV-2: rational design and multi-disciplinary team work[J]. Diagnostics (Basel), 2020, 10(10): 746. DOI: 10.3390/diagnostics10100746.

11.Kufel WD, Steele JM, Mahapatra R, et al. A five-year quasi-experimental study to evaluate the impact of empiric antibiotic order sets on antibiotic use metrics among hospitalized adult patients[J]. Infect Control Hosp Epidemiol, 2024, 45(5): 609-617. DOI: 10.1017/ice.2023.293.

12.Ya KZ, Lambiris MJ, Levine GA, et al. Coverage of policies to improve antimicrobial stewardship in human medicine in low and middle income countries: results from the Global Survey of Experts on Antimicrobial Resistance[J]. BMC Public Health, 2024, 24(1): 2297. DOI: 10.1186/s12889-024-19542-2.

13.党红星, 周波, 许峰. 儿童重症监护病房患儿抗菌药物应用评估和管理[J]. 中国小儿急救医学, 2022, 29(5): 321-325. [Dang HX, Zhou B, Xu F. Evaluation and management of application of antibiotics in PICU[J]. Chinese Pediatric Emergency Medicine, 2022, 29(5): 321-325.] DOI: 10.3760/cma.j.issn.1673-4912.2022.05.001.

14.中华医学会儿科学分会呼吸学组, 中华儿科杂志编辑委员会, 中国医药教育协会儿科专业委员会. 儿童社区获得性肺炎管理指南（2024修订）[J]. 中华儿科杂志, 2024, 62(10): 920-930. [Pediatrics Respiratory Group of Chinese Medical Association, Editorial Board of Chinese Journal of Pediatrics, Chinese Association of Pediatrics Professional Committee of Medical Education Association. Guidelines for the management of community-acquired pneumonia in children (2024 revision) [J]. Chinese Journal of Pediatrics, 2024, 62(10): 920-930.] DOI: 10.3760/cma.j.cn112140-20240728-00523.

15.Chen L, Miao C, Chen Y, et al. Age-specific risk factors of severe pneumonia among pediatric patients hospitalized with community-acquired pneumonia[J]. Ital J Pediatr, 2021, 47(1): 100. DOI: 10.1186/s13052-021-01042-3.

16.北京协和医院手术预防使用抗菌药物管理规范编委会. 北京协和医院手术预防使用抗菌药物管理规范（2023）[J]. 协和医学杂志, 2024, 15(2): 303-311. [Peking Union Medical College Hospital Surgical Prophylactic Antibiotics Management Norms Compilation Committee. Management standard on perioperative prophylactic use of antibiotics in peking union medical college hospital (2023)[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(2): 303-311.] DOI: 10.12290/xhyxzz.2023-0593.

17.Dhole S, Mahakalkar C, Kshirsagar S, et al. Antibiotic prophylaxis in surgery: current insights and future directions for surgical site infection prevention[J]. Cureus, 2023, 15(10): e47858. DOI: 10.7759/cureus.47858.

18.Righi E, Mutters NT, Guirao X, et al. ESCMID/EUCIC clinical practice guidelines on perioperative antibiotic prophylaxis in patients colonized by multidrug-resistant Gram-negative bacteria before surgery[J]. Clin Microbiol Infect, 2023, 29(4): 463-479.DOI: 10.1016/j.cmi.2022.12.012.

19.赵全国, 闫家彬, 李卫群. 多部门协作在细菌耐药监测工作中的应用及效果[J]. 中国公共卫生管理, 2024, 40(3): 462-464. [Zhao QG, Yan JB, Li WQ. Application and effect of multi-department collaboration in monitoring bacterial resistance[J]. Chinese Journal of Public Health Management, 2024, 40(3): 462-464.] DOI: 10.19568/j.cnki.23-1318.2024.03.0037.

20.谭瑞, 邹婷婷, 孙伟, 等. 多学科协作诊疗持续药学监护系统在抗感染治疗患者中的应用[J]. 中国药房, 2024, 35(23): 2936-2940. [Tan R, Zou TT, Sun W, et al. Application of the multi-disciplinary treatment-based continuous pharmaceutical care system in patients undergoing anti-infection treatment[J]. China Pharmacy, 2024, 35(23): 2936-2940.] DOI: 10.6039/j.issn.1001-0408.2024.23.16.

21.张永州, 吕维玲, 寇洁健，等. 2020-2021年医院感染病原菌分布及耐药性分析[J]. 中国病原生物学杂志, 2022, 17(10): 1192-1198. [Zhang YZ, Lyu WL, Kou JJ, et al. Investigation on the distribution and drug resistance of pathogenic bacteria in a hospital in Henan from 2020 to 2021[J]. Journal of Parasitic Biology, 2022, 17(10): 1192-1198.] DOI: 10.13350/j.cjpb.221017.

22.肖永红, 喻玮, 肖婷婷, 等. 耐药菌感染治疗新策略研究与应用[R]. 杭州: 浙江大学, 2022.

23.徐伟佳, 谢岳云, 徐李玲, 等. 临床药师参与“国谈”新型抗肿瘤药物MDT管理模式的效果分析[J]. 重庆医学, 2025, 54(1): 114-120. [Xu WJ, Xie YY, Xu LL, et al. Effect analysis of clinical pharmacists participating in national medical insurance negotiation of new anti-tumor drug MDT management mode[J]. Chongqing Medicine, 2025, 54(1): 114-120.] DOI: 10.3969/j.issn.1671-8348.2025.01.021.

24.林文宏, 陈才凤, 赖小卿, 等. 应用蒙特卡罗模拟评估及优化脓毒症患者临床阿米卡星的给药剂量[J]. 海峡药学, 2024, 36(3): 86-89. [Lin WH, Chen CF, Lai XQ, et al. Use of Monte Carlo Simulation to evaluate and optimize the dosage reg-imen of amikacin in patients with sepsis[J]. Strait Pharmaceutical Journal, 2024, 36(3): 86-89.] DOI: 10.3969/j.issn.1006-3765.2024.03.023.

25.朱丽雅, 邵朝朝, 何贵清, 等. 临床决策支持系统在ICU抗菌药物管理中的应用[J]. 医院管理论坛, 2021, 38(12): 43-47.[Zhu LY, Shao ZZ, He GQ, et al. Application of clinical decision support system in management of antibiotics in ICU[J]. Hospital Management Forum, 2021, 38(12): 43-47.] DOI: 10.3969/j.issn.1671-9069.2021.12.011.

26.Popovich K, Ham M, Harris M, et al. SHEA/IDSA/APIC practice recommendation: strategies to prevent methicillin-resistant staphylococcus aureus transmission and infection in acute-care hospitals: 2022 update[J]. Infect Control Hosp Epidemiol, 2023, 44(7): 1039-1067. DOI: 10.1017/ice.2023.102.

27.Fabre V, Cosgrove S, Lessa F, et al. Development of antimicrobial stewardship programs in Central and South America[J]. Open Forum Infect Dis, 2022, 9(Suppl 2): 1-10. https://doi.org/10.1093/ofid/ofac492.788.

28.Pagano F, Amato C, De Marco G, et al. Reduction in broad-spectrum antimicrobial prescriptions by primary care pediatricians following a multifaceted antimicrobial stewardship program[J]. Front Pediatr, 2023, 10: 1070325. DOI: 10.3389/fped.2022.1070325.

29.Ronda M, Gumucio-Sanguino V, Shaw E, et al. Long-term effects of a stepwise, multimodal, non-restrictive antimicrobial stewardship programme for reducing broad-spectrum antibiotic use in the ICU[J]. Antibiotics (Basel), 2024, 13(2): 132. DOI: 10.3390/antibiotics13020132.

30.Hurtado D, Varela M, Juarez A, et al. Impact of antimicrobial stewardship program intervention acceptance on hospital length of stay[J]. Hosp Pharm, 2023, 58(5): 491-495. DOI: 10.1177/00185787231160436.

31.Shallal A, Lahoud C, Merhej D, et al. The impact of a post-prescription review and feedback antimicrobial stewardship program in Lebanon[J]. Antibiotics (Basel), 2022, 11(5): 642. DOI: 10.3390/antibiotics11050642.

32.Uda A, Ebisawa K, Sakon H, et al. Sustained improvements in antimicrobial therapy and clinical outcomes following a pharmacist-led antimicrobial stewardship intervention: uncontrolled before-after study[J]. J Clin Med, 2022, 11(3): 566. DOI: 10.3390/jcm11030566.

33.Catho G. Computerized support to improve antimicrobial prescribing: myth or reality?[J]. Rev Med Suisse, 2023, 19(845): 1846-1850. DOI: 10.53738/REVMED.2023.19.845.1846.

34.Yang J, Eyre D, Lu L, et al. Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections[J]. NPJ Antimicrob Resist, 2023, 1(1): 14. DOI: 10.1101/2023.01.09.23284299.

35.Lau T, Daniel R, Hughes K, et al. A systematic review investigating the use of microbiology outcome measures in randomized controlled trials evaluating antimicrobial stewardship interventions published between 2011 and 2021[J]. JAC Antimicrob Resist, 2022, 4(1): dlac013. DOI: 10.1093/jacamr/dlac013.

36.Abirami MKP. AI clinical decision support system (AI-CDSS) for cardiovascular diseases[C]// 2023 International Conference on Computer Science and Emerging Technologies (CSET)[A]. 2023: 1-7.

37.McGonagle E, Karavite D, Grundmeier R, et al. Evaluation of an antimicrobial stewardship decision support for pediatric infections[J]. Appl Clin Inform, 2022, 14(1): 108-118. DOI: 10.1055/s-0042-1760082.

38.Singla R, Aggarwal S, Bindra J, et al. Developing clinical decision support system using machine learning methods for type 2 diabetes drug management[J]. Indian J Endocrinol Metab, 2022, 26(1): 44-49. DOI: 10.4103/ijem.ijem_435_21.

39.Igwama G, Nwankwo E, Emeihe E, et al. The role of AI in optimizing drug dosage and reducing medication errors[J]. Int J Biol Pharm Res Updat, 2024, 4(1): 18-34. DOI: 10.53430/ijbpru.2024.4.1.0027.

40.Rodger R, Coulter J, Thompson S. P20 Addition of a pharmacy technician to the ward team improves antimicrobial stewardship and patient care and safety[J]. JAC Antimicrob Resis, 2023, 5(Supplement_2): dlad066.024. DOI: 10.1093/jacamr/dlad066.024.

41.Onita T. Antimicrobial dosing individualization based on pharmacokinetic/pharmacodynamic evaluation, considering factors of "Patient", "Site of infection" and "Microorganism"[J]. Yakugaku Zasshi, 2024, 144(10): 937-943. DOI: 10.1248/yakushi.24-00124.

42.Bos M, Schouten J, De Bot C, et al. A hidden gem in multidisciplinary antimicrobial stewardship: a systematic review on bedside nurses' activities in daily practice regarding antibiotic use[J]. JAC Antimicrob Resist, 2023, 5(6): dlad123. DOI: 10.1093/jacamr/dlad123.

43.El-Khamissy T. Antimicrobial stewardship and the role of microbiology laboratory, and pharmacists[J]. ERU Res J, 2022, 1(1): 44-56. DOI: 10.21608/erurj.2022.265663.

44.Verboven L, Callens S, Black J, et al. A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis[J]. PLoS One, 2024, 19(9): e0306101. DOI: 10.1371/journal.pone.0306101.

45.Li W, Shang N, Zhang Z, et al. Development and validation of a machine learning model to improve precision prediction for irrational prescriptions in orthopedic perioperative patients[J]. Expert Opin Drug Saf, 2025, 24(1): 99-109. DOI: 10.1080/14740338.2024.2348569.

46.Patterson E. Navigating alert fatigue: a case study in electronic health record alert design optimization[J]. Stud Health Technol Inform, 2024, 315: 447-451. DOI: 10.3233/SHTI240188.

47.Ardila C, Yadalam P, González-Arroyave D. Integrating whole genome sequencing and machine learning for predicting antimicrobial resistance in critical pathogens: a systematic review of antimicrobial susceptibility tests[J]. PeerJ, 2024, 12: e18213. DOI: 10.7717/peerj.18213.

48.Blechman S, Wright E. Applications of machine learning on electronic health record data to combat antibiotic resistance[J]. J Infect Dis, 2024, 230(5): 1073-1082. DOI: 10.1093/infdis/jiae348.

49.Jani Y, Bourke D. 506 allergy related clinical prescribing alerts in an electronic health record (EHR) system: a descriptive study[J]. Int J Pharm Pract, 2023, 31(Supplement_1): i40. DOI: 10.1093/ijpp/riad021.048.

50.Russmann S, Martinelli F, Jakobs F, et al. Identification of medication prescription errors and factors of clinical relevance in 314 hospitalized patients for improved multidimensional clinical decision support algorithms[J]. J Clin Med, 2023, 12(15): 4920. DOI: 10.3390/jcm12154920.

51.Xu Z, Evans L, Song J, et al. Exploring home healthcare clinicians' needs for using clinical decision support systems for early risk warning[J]. J Am Med Inform Assoc, 2024, 31(11): 2641-2650. DOI: 10.1093/jamia/ocae247.

52.Hanna J, Medford R. Navigating the future: machine learning's role in revolutionizing antimicrobial stewardship and infection prevention and control[J]. Curr Opin Infect Dis, 2024, 37(4): 290-295. DOI: 10.1097/QCO.0000000000001028.

53.Dighriri I, Alnomci B, Aljahdali M, et al. The role of clinical pharmacists in antimicrobial stewardship programs (ASPs): a systematic review[J]. Cureus, 2023, 15(12): e50151. DOI: 10.7759/cureus.50151.

54.Belza A, Efta J, MacDonald N, et al. Putting a CAP on discharge antimicrobial therapy: evaluation of a systematic transitions of care process for patients with community acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD)[J]. Open Forum Infect Dis, 2023, 10(Supplement_2): ofad500.1041. DOI: 10.1093/ofid/ofad500.1041.

55.Szewczyk B, Campion M, Bylsma T, et al. Application of defined daily dose to antibiotic prescribing in Massachusetts jails[J]. Open Forum Infect Dis, 2022, 9(Supplement_2): ofac492.1396. DOI: 10.1093/ofid/ofac492.1396.

56.Chambers D, Preston L, Clowes M, et al. Pharmacist-led primary care interventions to promote medicines optimisation and reduce overprescribing: a systematic review of UK studies and initiatives[J]. BMJ Open, 2024, 14(8): e081934. DOI: 10.1136/bmjopen-2023-081934.

57.Brenes L, Czerny B, Mitsunaga T, et al. Association between antimicrobial stewardship resources and practices reported by California hospitals in the National Healthcare Safety Network annual survey and California Department of Public Health antimicrobial stewardship program honor roll designation[J]. Open Forum Infect Dis, 2023, 10(Supplement_2): S378-S379. DOI: 10.1093/ofid/ofad500.1090.

58.Zhao Z, Sun S, Li Y, et al. Impact of "Chief-Pharmacist System" on drug expenditures and rational drug use[J]. Int J Clin Pharm, 2020, 42(1): 167-173. DOI: 10.1007/s11096-019-00954-9.

59.Sarkhi K, Eljaaly K, Kaki R, et al. Impact of a multidisciplinary antimicrobial stewardship program on antibiotic utilization and clinical outcomes at a tertiary hospital in Saudi Arabia: a quasi-experimental study[J]. Expert Rev Anti Infect Ther, 2024, 22(1-3): 115-120. DOI: 10.1080/14787210.2023.2285425.

60.Nagarajan S. Software data objects application integrity modeling in medication dispensing errors predictions using machine learning algorithms in workflow-based pharmacy software systems[J]. World J Biol Pharm Heal Sci, 2024, 19(3): 571-574. DOI: 10.30574/wjbphs.2024.19.3.0687.

61.Du M, Zhao Y, Fang T, et al. Evaluating the inequality of medical resource allocation based on spatial and non-spatial accessibility: a case study of Wenzhou, China[J]. Sustainability, 2022, 14(14): 8331. DOI: 10.3390/su14148331.

62.Loustalot M, Berdot S, Sabatier P, et al. The impact of interventions by pharmacists collected in a computerised physician order entry context: a prospective observational study with a 10-year reassessment[J]. Swiss Med Wkly, 2019, 149: w20015. DOI: 10.4414/smw.2019.20015.

63.Li L, Fang Z, Li Z, et al. Exploration of competency-oriented standardized training model for clinical pharmacists[J]. Med Heal Res, 2024, 2(2): 44-56. DOI: 10.18686/mhr.v2i2.4120.

64.He S, Shrestha P, Henry A, et al. Leveraging collaborative research networks against antimicrobial resistance in Asia[J]. Front Public Health, 2023, 11: 1191036. DOI: 10.3389/fpubh.2023.1191036.