scholarly journals Enhancing Usefulness and Usability of a Clinical Decision Support Prototype for Antibiotic Stewardship

Author(s):  
Emily S. Patterson ◽  
Giavanna N. DiLoreto ◽  
Rohith Vanam ◽  
Erinn Hade ◽  
Courtney Hebert

Human factors engineering can enhance software usefulness and usability. We describe a multi-method approach to improve clinical decision support (CDS) for antibiotic stewardship. We employed a heuristic review to generate recommendations to improve the usability of a prototype CDS to support empiric antibiotic prescribing in the hospital setting. We then engaged in a design improvement cycle in collaboration with software programmers, which resulted in additional enhancements to our prototype. Finally, we used the revised prototype during three walkthrough demonstration interviews with physician and pharmacist subject matter experts. These walkthrough interviews generated recommendations to improve the interface, functionality, and tailoring for groups of users. We discuss common elements of the recommendations for models for using clinical decision support in general.

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S409-S409
Author(s):  
Julia K Yarahuan ◽  
Brandon Hunter ◽  
Devin Nadar ◽  
Nitin Gujral ◽  
Andrew M Fine ◽  
...  

Abstract Background Institutional antibiograms play a key role in antimicrobial stewardship and may provide a venue for clinical decision support. Our institution recently transitioned our paper antibiogram to an enhanced digital antibiogram with antibiotic recommendations for common pediatric infections. The objectives of this study were (1) to improve the accessibility of our institutional antibiogram through a digital platform and (2) to improve trainee confidence when selecting empiric antibiotics by integrating clinical decision support. Methods The digital antibiogram was developed and evaluated at a tertiary children’s hospital. The tool was developed iteratively over one year by our innovation and digital health accelerator with recommendations for empiric antibiotic selection provided by experts in pediatric infectious diseases (see Figure 1 for example). Usability pilot testing was performed with a group of ordering providers and the tool was released internally in October 2018. A paired pre- and post- implementation survey evaluated residents’ perceptions of the accessibility of the paper vs. digital antibiogram and their confidence when selecting empiric antibiotics. Data were analyzed by Fisher exact test. Results During the 3 months after release, the digital antibiogram was accessed 1014 times with similar proportions of views for susceptibility data, dosing, and empiric antibiotic recommendations. Of the 31 pediatric residents who responded to both pre- and post- implementation surveys, only 59% had access to a copy of the paper antibiogram. Following release of the digital antibiogram, residents referred to antibiotic susceptibilities more frequently (P < 0.05, Figure 2) and were more frequently more confident when selecting the correct antibiotic dose (P < 0.01, Figure 3). See Figure 4 for dosing recommendation example. Conclusion Providing antibiotic susceptibility and dosing recommendations digitally improved accessibility and resident confidence during antibiotic prescribing. Our digital tool provides a successful platform for displaying the antibiotic data and recommendations that enable appropriate antibiotic use. Disclosures All authors: No reported disclosures.


2020 ◽  
Vol 41 (S1) ◽  
pp. s368-s368
Author(s):  
Mary Acree ◽  
Kamaljit Singh ◽  
Urmila Ravichandran ◽  
Jennifer Grant ◽  
Gary Fleming ◽  
...  

Background: Empiric antibiotic selection is challenging and requires knowledge of the local antibiogram, national guidelines and patient-specific factors, such as drug allergy and recent antibiotic exposure. Clinical decision support for empiric antibiotic selection has the potential to improve adherence to guidelines and improve patient outcomes. Methods: At NorthShore University HealthSystem, a 4-hospital, 789 bed system, an automated point-of-care decision support tool referred to as Antimicrobial Stewardship Assistance Program (ASAP) was created for empiric antibiotic selection for 4 infectious syndromes: pneumonia, skin and soft-tissue infections, urinary tract infection, and intra-abdominal infection. The tool input data from the electronic health record, which can be modified by any user. Using an algorithm created with electronic health record data, antibiogram data, and national guidelines, the tool produces an antibiotic recommendation that can be ordered via a link to order entry. If the tool identifies a patient with a high likelihood for a multidrug-resistant infection, a consultation by an infectious diseases specialist is recommended. Utilization of the tool and associated outcomes were evaluated from July 2018 to May 2019. Results: The ASAP tool was executed by 140 unique, noninfectious diseases providers 790 times. The tool was utilized most often for pneumonia (194 tool uses), followed by urinary tract infection (166 tool uses). The most common provider type to use the tool was an internal medicine hospitalist. The tool increased adherence to the recommended antibiotic regimen for each condition. Antibiotic appropriateness was assessed by an infectious diseases physician. Antibiotics were considered appropriate when they were similar to the antibiotic regimen recommended by the ASAP. Inappropriate antibiotics were classified as broad or narrow. When antibiotic coverage was appropriate, hospital length of stay was statistically significantly shorter (4.8 days vs 6.8 days for broad antibiotics vs 7.4 days for narrow antibiotics; P < .01). No significant differences were identified in mortality or readmission. Conclusions: A clinical decision support tool in the electronic health record can improve adherence to recommended empiric antibiotic therapy. Use of appropriate antibiotics recommended by such a tool can reduce hospital length of stay.Funding: NoneDisclosures: None


2019 ◽  
Vol 41 (3) ◽  
pp. 552-581 ◽  
Author(s):  
Eduardo Carracedo-Martinez ◽  
Christian Gonzalez-Gonzalez ◽  
Antonio Teixeira-Rodrigues ◽  
Jesus Prego-Dominguez ◽  
Bahi Takkouche ◽  
...  

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S166-S166
Author(s):  
Shannon Overly ◽  
Jimish Mehta ◽  
Seth Hayes ◽  
Keith Hamilton ◽  
Dan Peterson

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