» Articles » PMID: 34713055

How to Develop and Implement a Computerized Decision Support System Integrated for Antimicrobial Stewardship? Experiences From Two Swiss Hospital Systems

Abstract

Computerized decision support systems (CDSS) provide new opportunities for automating antimicrobial stewardship (AMS) interventions and integrating them in routine healthcare. CDSS are recommended as part of AMS programs by international guidelines but few have been implemented so far. In the context of the publicly funded COMPuterized Antibiotic Stewardship Study (COMPASS), we developed and implemented two CDSSs for antimicrobial prescriptions integrated into the in-house electronic health records of two public hospitals in Switzerland. Developing and implementing such systems was a unique opportunity for learning during which we faced several challenges. In this narrative review we describe key lessons learned. (1) During the initial planning and development stage, start by drafting the CDSS as an algorithm and use a standardized format to communicate clearly the desired functionalities of the tool to all stakeholders. (2) Set up a multidisciplinary team bringing together Information Technologies (IT) specialists with development expertise, clinicians familiar with "real-life" processes in the wards and if possible, involve collaborators having knowledge in both areas. (3) When designing the CDSS, make the underlying decision-making process transparent for physicians and start simple and make sure to find the right balance between force and persuasion to ensure adoption by end-users. (4) Correctly assess the clinical and economic impact of your tool, therefore try to use standardized terminologies and limit the use of free text for analysis purpose. (5) At the implementation stage, plan usability testing early, develop an appropriate training plan suitable to end users' skills and time-constraints and think ahead of additional challenges related to the study design that may occur (such as a cluster randomized trial). Stay also tuned to react quickly during the intervention phase. (6) Finally, during the assessment stage plan ahead maintenance, adaptation and related financial challenges and stay connected with institutional partners to leverage potential synergies with other informatics projects.

Citing Articles

Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship.

Yusuf H, Hillman A, Stegeman J, Cameron A, Badger S Front Vet Sci. 2024; 11:1349188.

PMID: 38895711 PMC: 11184142. DOI: 10.3389/fvets.2024.1349188.


Achieving universal health coverage in low- and middle-income countries through digital antimicrobial stewardship.

Otaigbe I Front Digit Health. 2024; 5:1298861.

PMID: 38162693 PMC: 10757329. DOI: 10.3389/fdgth.2023.1298861.


Implementation of Antimicrobial Stewardship in the Healthcare Setting.

Bankar N, Ugemuge S, Ambad R, Hawale D, Timilsina D Cureus. 2022; 14(7):e26664.

PMID: 35949742 PMC: 9357433. DOI: 10.7759/cureus.26664.


Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.

Catho G, Sauser J, Coray V, Da Silva S, Elzi L, Harbarth S Lancet Infect Dis. 2022; 22(10):1493-1502.

PMID: 35870478 PMC: 9491854. DOI: 10.1016/S1473-3099(22)00308-5.


Machine Learning and Antibiotic Management.

Maviglia R, Michi T, Passaro D, Raggi V, Bocci M, Piervincenzi E Antibiotics (Basel). 2022; 11(3).

PMID: 35326768 PMC: 8944459. DOI: 10.3390/antibiotics11030304.

References
1.
Khairat S, Marc D, Crosby W, Al Sanousi A . Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis. JMIR Med Inform. 2018; 6(2):e24. PMC: 5932331. DOI: 10.2196/medinform.8912. View

2.
Neo J, Niederdeppe J, Vielemeyer O, Lau B, Demetres M, Sadatsafavi H . Evidence-Based Strategies in Using Persuasive Interventions to Optimize Antimicrobial Use in Healthcare: a Narrative Review. J Med Syst. 2020; 44(3):64. DOI: 10.1007/s10916-020-1531-y. View

3.
de Kraker M, Abbas M, Huttner B, Harbarth S . Good epidemiological practice: a narrative review of appropriate scientific methods to evaluate the impact of antimicrobial stewardship interventions. Clin Microbiol Infect. 2017; 23(11):819-825. DOI: 10.1016/j.cmi.2017.05.019. View

4.
Richardson S, Mishuris R, OConnell A, Feldstein D, Hess R, Smith P . "Think aloud" and "Near live" usability testing of two complex clinical decision support tools. Int J Med Inform. 2017; 106:1-8. PMC: 5679128. DOI: 10.1016/j.ijmedinf.2017.06.003. View

5.
Wright A, Goldberg H, Hongsermeier T, Middleton B . A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007; 14(4):489-96. PMC: 2244910. DOI: 10.1197/jamia.M2364. View