scholarly journals Data science for infection management and antimicrobial stewardship

2021 ◽  
Author(s):  
◽  
Christian Luz
2017 ◽  
Vol 137 (5) ◽  
pp. 643-650 ◽  
Author(s):  
Kengo Ohashi ◽  
Tomoko Matsuoka ◽  
Yasutaka Shinoda ◽  
Shinya Yoshida ◽  
Kaori Arai ◽  
...  

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S181-S182
Author(s):  
Elizabeth Gulleen ◽  
Margaret Lubwama ◽  
Alfred Komakech ◽  
Elizabeth M Krantz ◽  
Catherine Liu ◽  
...  

Abstract Background As access to cancer treatment has increased in sub-Saharan Africa (sSA), infection-related complications are a growing concern. Little is known about infection management practices in this setting. Understanding the unique challenges to diagnosing and treating infections can inform the development of targeted strategies to improve infection management for cancer treatment programs throughout sSA. Methods We conducted a cross-sectional survey of doctors, nurses, and pharmacists at the Uganda Cancer Institute (UCI), a national cancer referral hospital in Kampala, Uganda. The 25-item survey was designed to assess staff knowledge of antimicrobial resistance and antimicrobial stewardship, investigate antibiotic decision-making practices, and identify barriers to diagnosing and treating infections. Results Of the 61 respondents, 25 (41%) were doctors, 7 (11%) were pharmacists, and 29 (48%) were nurses. In total, 98% (60/61) had heard of the term “antimicrobial resistance” and 84% (51/61) agreed that antimicrobial resistance is an important problem at UCI. Multiple factors were felt to contribute to antimicrobial resistance including the use of too many antibiotics, patient insistence on antibiotics, and poor patient adherence (Fig 1). While 72% (44/61) had heard of the term “antimicrobial stewardship”, only 25% (15/61) knew a lot about what it meant. Numerous factors were considered important to antibiotic decision-making including patient white blood cell count and severity of illness (Fig 2). Perceived barriers to infection diagnosis included the inability to obtain blood cultures and to regularly measure patient temperatures; perceived barriers to obtaining blood cultures included patient cost and availability of supplies (Fig 3). Figure 1. Factors that doctors, pharmacists, and nurses working at the Uganda Cancer Institute (UCI) perceive as contributing to antimicrobial resistance at the UCI. Percentages shown next to bars represent the combined total percentage of respondents reporting that the factor does not or usually does not contribute (left of bars, main chart), occasionally or frequently contributes (right of bars, main chart), or neither contributes nor does not contribute (right of neutral chart). Figure 2. Factors that doctors, pharmacists, and nurses working at the Uganda Cancer Institute consider to be important when choosing antibiotics to treat infections. Percentages shown next to bars represent the combined total percentage of respondents reporting that the factor is somewhat or very unimportant (left of bars, main chart), somewhat or very important (right of bars, main chart), or neither important nor unimportant (right of neutral chart). Figure 3. Factors that doctors, pharmacists, and nurses working at the Uganda Cancer Institute perceive as limiting the ability to diagnose infections and obtain blood cultures. Conclusion While most staff recognized the term “antimicrobial resistance” and identified this as a major local problem, fewer were familiar with the term “antimicrobial stewardship”. We identified numerous perceived barriers to infection diagnosis and treatment, including the ability to consistently measure temperatures and the cost of blood cultures. A multipronged approach is needed to improve staff knowledge of antimicrobial stewardship and to address the systematic barriers to infection management at UCI. Disclosures All Authors: No reported disclosures


10.2196/12843 ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. e12843 ◽  
Author(s):  
Christian Friedemann Luz ◽  
Matthijs S Berends ◽  
Jan-Willem H Dik ◽  
Mariëtte Lokate ◽  
Céline Pulcini ◽  
...  

2018 ◽  
Author(s):  
Christian Friedemann Luz ◽  
Matthijs S Berends ◽  
Jan-Willem H Dik ◽  
Mariëtte Lokate ◽  
Céline Pulcini ◽  
...  

BACKGROUND Analyzing process and outcome measures for all patients diagnosed with an infection in a hospital, including those suspected of having an infection, requires not only processing of large datasets but also accounting for numerous patient parameters and guidelines. Substantial technical expertise is required to conduct such rapid, reproducible, and adaptable analyses; however, such analyses can yield valuable insights for infection management and antimicrobial stewardship (AMS) teams. OBJECTIVE The aim of this study was to present the design, development, and testing of RadaR (Rapid analysis of diagnostic and antimicrobial patterns in R), a software app for infection management, and to ascertain whether RadaR can facilitate user-friendly, intuitive, and interactive analyses of large datasets in the absence of prior in-depth software or programming knowledge. METHODS RadaR was built in the open-source programming language R, using Shiny, an additional package to implement Web-app frameworks in R. It was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions. RESULTS RadaR enabled visualization of analytical graphs and statistical summaries in a rapid and interactive manner. It allowed users to filter patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results including antimicrobial resistance, and outcome in length of stay. Furthermore, with RadaR, results can be stratified and grouped to compare defined patient groups on the basis of individual patient features. CONCLUSIONS AMS teams can use RadaR to identify areas within their institutions that might benefit from increased support and targeted interventions. It can be used for the assessment of diagnostic and therapeutic procedures and for visualizing and communicating analyses. RadaR demonstrated the feasibility of developing software tools for use in infection management and for AMS teams in an open-source approach, thus making it free to use and adaptable to different settings.


2018 ◽  
Author(s):  
Christian F. Luz ◽  
Matthijs S. Berends ◽  
Jan-Willem H. Dik ◽  
Mariëtte Lokate ◽  
Céline Pulcini ◽  
...  

AbstractObjectivesAnalysing process and outcome measures for patients suspected of or having an infection in an entire hospital requires processing large datasets and accounting for numerous patient parameters and treatment guidelines. Rapid, reproducible and adaptable analyses usually need substantial technical expertise but can yield valuable insight for infection management and antimicrobial stewardship (AMS) teams. We describe a software application (RadaR - Rapid analysis of diagnostic and antimicrobial patterns in R) for infection management allowing user-friendly, intuitive and interactive analysis of large datasets without prior in-depth statistical or software knowledge.Methods and ResultsRadaR was built in R, an open source programming language, making it free to use and adaptable to different settings. Shiny, an additional open source package to implement web-application frameworks in R, was used to develop the application. RadaR was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions.RadaR visualizes analytical graphs and statistical summaries in an interactive manner within seconds. Users can filter large patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results, and outcome in length of stay. Results can easily be stratified and grouped to compare individually defined patient groups. Finally, datasets of identified patients / groups can be downloaded for further analyses.ConclusionRadaR facilitates understanding and communication of trends in antimicrobial use, diagnostic use and patient outcome by linking and aggregating individual patient data in one user-friendly application. RadaR can produce aggregated data analysis while preserving patients’ features in the data to adjust and stratify results in detail. AMS teams can use RadaR to identify areas, both for diagnostic and therapeutic procedures, within their institutions that might benefit from increased support and to target their interventions.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

MedPharmRes ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 34-39
Author(s):  
Thi-Hai-Yen Nguyen ◽  
Truong Van Dat ◽  
Phuong-Thao Huynh ◽  
Chi-Thuong Tang ◽  
Vinh-Chau Van Nguyen ◽  
...  

Vietnam has one of the highest multi drug resistance in Asia. Although, despite many efforts to implement the Antimicrobial Stewardship Programs (the ASP) since 2016, studies that on the implementation policy are very lacking of this program are limited. For that reason, we conducted this cross-sectional study to analyze the viewpoint of health workers (HWs) on the implementation of the ASP at some hospitals in Ho Chi Minh City (HCMC). An assessment of 234 HWs showed that the implementation of the ASP in HCMC hospitals was above average (62.7/100.0). A barrier to the implementation consisted of the deficiency in finances, guidelines for diagnosis, and specific interventions for some common infections, such as distributing current antibiogram and monitoring rate of Clostridioides difficile infections. These were the widely recognized problems in initially implementing the ASP. Although most HWs are aware of the importance of implementing the ASP (79.1%), the specific assessment has not been recorded clearly due to the numerous neutral responses. Despite the support of the leadership, the implementation still faces many difficulties and limitations, especially in 3rd and 4th class hospitals. Besides, there was a lack of wide dissemination of information on the ASP at each unit. To generalize the status of the ASP implementation, researchers should conduct qualitative and quantitative studies with a larger scale.


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