Participatory implementation of an antibiotic stewardship programme supported by an innovative surveillance and clinical decision-support system

Participatory antimicrobial stewardship: fostering patient and public engagement to counter antimicrobial resistance

International governments defined antimicrobial stewardship (AS) as an essential ally against antimicrobial resistance (AMR). Patient and public engagement (PPE) in AS was pointed out as an imperative requirement to be embraced. We discuss PPE state of the art in AS and methodological reflections on how to achieve its effective implementation.

Using Theories, Models, and Frameworks to Inform Implementation Cycles of Computerized Clinical Decision Support Systems in Tertiary Health Care Settings: Scoping Review

BACKGROUND

Computerized clinical decision support systems (CDSSs) are essential components of modern health system service delivery, particularly within acute care settings such as hospitals. Theories, models, and frameworks may assist in facilitating the implementation processes associated with CDSS innovation and its use within these care settings. These processes include context assessments to identify key determinants, implementation plans for adoption, promoting ongoing uptake, adherence, and long-term evaluation. However, there has been no prior review synthesizing the literature regarding the theories, models, and frameworks that have informed the implementation and adoption of CDSSs within hospitals.

OBJECTIVE

This scoping review aims to identify the theory, model, and framework approaches that have been used to facilitate the implementation and adoption of CDSSs in tertiary health care settings, including hospitals. The rationales reported for selecting these approaches, including the limitations and strengths, are described.

METHODS

A total of 5 electronic databases were searched (CINAHL via EBSCOhost, PubMed, Scopus, PsycINFO, and Embase) to identify studies that implemented or adopted a CDSS in a tertiary health care setting using an implementation theory, model, or framework. No date or language limits were applied. A narrative synthesis was conducted using full-text publications and abstracts. Implementation phases were classified according to the "Active Implementation Framework stages": exploration (feasibility and organizational readiness), installation (organizational preparation), initial implementation (initiating implementation, ie, training), full implementation (sustainment), and nontranslational effectiveness studies.

RESULTS

A total of 81 records (42 full text and 39 abstracts) were included. Full-text studies and abstracts are reported separately. For full-text studies, models (18/42, 43%), followed by determinants frameworks (14/42,33%), were most frequently used to guide adoption and evaluation strategies. Most studies (36/42, 86%) did not list the limitations associated with applying a specific theory, model, or framework.

CONCLUSIONS

Models and related quality improvement methods were most frequently used to inform CDSS adoption. Models were not typically combined with each other or with theory to inform full-cycle implementation strategies. The findings highlight a gap in the application of implementation methods including theories, models, and frameworks to facilitate full-cycle implementation strategies for hospital CDSSs.

The Infomóvel-An information system for managing HIV/AIDS patients in rural areas of Mozambique

BACKGROUND

Mobile health is gradually revolutionizing the way medical care is delivered worldwide. In Mozambique, a country with a high human immunodeficiency virus prevalence, where antiretroviral treatment coverage is 77% accompanied by a 67% of retention rate, the use of mobile health technology may boost the antiretroviral treatment, by delivering care beyond health facilities and reaching underrepresented groups. Leveraging new technologies is crucial to reach the 95-95-95 United Nations target by 2030. The design, development, implementation, and evaluation of a mobile health platform called Infomóvel were covered in this article. Its intended use involves collaboration with community health workers and aims to increase human immunodeficiency virus patient access, adherence, and retention to care.

METHODS

Using the Design Science Research Methodology, Infomóvel was created, as well as this publication. The explanation of various actions includes everything from problem description to observational study and goal-following for a solution, which results in the design and development of a platform proposal. Before the utility assessment of Infomóvel was conducted to make adjustments, a demonstration phase was conducted in one region of Mozambique.

RESULTS

The initial subjects of the Infomóvel flowchart and physical process design were patients receiving antiretroviral medication who were enrolled in the patients tracking system and who had consented to home visits. The case manager examines the file before importing it into the Infomóvel database stored on a cloud server using the website www.commcarehq.org . The case manager application synchronises with the Infomóvel server database, enabling the import of latest data and access to the lists of new patients and community health workers. The community health worker uses his phone to access his application, which allows him to record the geographic coordinates and sort the list of patients by priority and type of visit.

CONCLUSION

Results from Infomóvel add to the growing body of data showing that mobile health techniques are beneficial for managing stable individuals with chronic conditions in Mozambique. These approaches can be scaled up and better utilised. However, additional studies should be conducted to quantify the resources needed to implement on a larger scale.

Factors Influencing Clinicians' Use of Hospital Information Systems for Infection Prevention and Control: Cross-Sectional Study Based on the Extended DeLone and McLean Model

BACKGROUND

Healthcare-associated infections have become a serious public health problem. Various types of information systems have begun to be applied in hospital infection prevention and control (IPC) practice. Clinicians are the key users of these systems, but few studies have assessed the use of infection prevention and control information systems (IPCISs) from their perspective.

OBJECTIVE

This study aimed to (1) apply the extended DeLone and McLean Information Systems Success model (D&M model) that incorporates IPC culture to examine how technical factors like information quality, system quality, and service quality, as well as organizational culture factors affect clinicians' use intention, satisfaction, and perceived net benefits, and (2) identify which factors are the most important for clinicians' use intention.

METHODS

A total of 12,317 clinicians from secondary and tertiary hospitals were surveyed online. Data were analyzed using partial least squares-structural equation modeling and the importance-performance matrix analysis.

RESULTS

Among the technical factors, system quality (β=.089-.252; P<.001), information quality (β=.294-.102; P<.001), and service quality (β=.126-.411; P<.001) were significantly related to user satisfaction (R2=0.833), use intention (R2=0.821), and perceived net benefits (communication benefits [R2=0.676], decision-making benefits [R2=0.624], and organizational benefits [R2=0.656]). IPC culture had an effect on use intention (β=.059; P<.001), and it also indirectly affected perceived net benefits (β=.461-.474; P<.001). In the importance-performance matrix analysis, the attributes of service quality (providing user training) and information quality (readability) were present in the fourth quadrant, indicating their high importance and low performance.

CONCLUSIONS

This study provides valuable insights into IPCIS usage among clinicians from the perspectives of technology and organization culture factors. It found that technical factors (system quality, information quality, and service quality) and hospital IPC culture have an impact on the successful use of IPCISs after evaluating the application of IPCISs based on the extended D&M model. Furthermore, service quality and information quality showed higher importance and lower performance for use intention. These findings provide empirical evidence and specific practical directions for further improving the construction of IPCISs.

Factors influencing the implementation of decision support systems for antibiotic prescription in hospitals: a systematic review

BACKGROUND

Antibiotic resistance is a major health threat. Inappropriate antibiotic use has been shown to be an important determinant of the emergence of antibiotic resistance. Decision support systems for antimicrobial management can support clinicians to optimize antibiotic prescription.

OBJECTIVE

The aim of this systematic review is to identify factors influencing the implementation of decision support systems for antibiotic prescription in hospitals.

METHODS

A systematic search of factors impeding or facilitating successful implementation of decision support systems for antibiotic prescription was performed in January 2022 in the databases PubMed, Web of Science and The Cochrane Library. Only studies were included which comprised decision support systems in hospitals for prescribing antibiotic therapy, published in English with a qualitative, quantitative or mixed-methods study design and between 2011 and 2021. Factors influencing the implementation were identified through text analysis by two reviewers.

RESULTS

A total of 14 publications were identified matching the inclusion criteria. The majority of factors relate to technological and organizational aspects of decision support system implementation. Some factors include the integration of the decision support systems into existing systems, system design, consideration of potential end-users as well as training and support for end-users. In addition, user-related factors, like user attitude towards the system, computer literacy and prior experience with the system seem to be important for successful implementation of decision support systems for antibiotic prescription in hospitals.

CONCLUSION

The results indicate a broad spectrum of factors of decision support system implementation for antibiotic prescription and contributes to the literature by identifying important organizational as well as user-related factors. Wider organizational dimensions as well as the interaction between user and technology appear important for supporting implementation.

Digital interventions for antimicrobial prescribing and monitoring: a qualitative meta-synthesis of factors influencing user acceptance

OBJECTIVE

To understand and synthesize factors influencing user acceptance of digital interventions used for antimicrobial prescribing and monitoring in hospitals.

MATERIALS AND METHODS

A meta-synthesis was conducted to identify qualitative studies that explored user acceptance of digital interventions for antimicrobial prescribing and/or monitoring in hospitals. Databases were searched and qualitative data were extracted and systematically classified using the unified theory of acceptance and use of technology (UTAUT) model.

RESULTS

Fifteen qualitative studies met the inclusion criteria. Eleven papers used interviews and four used focus groups. Most digital interventions evaluated in studies were decision support for prescribing (n = 13). Majority of perceptions were classified in the UTAUT performance expectancy domain in perceived usefulness and relative advantage constructs. Key facilitators in this domain included systems being trusted and credible sources of information, improving performance of tasks and increasing efficiency. Reported barriers were that interventions were not considered useful for all settings or patient conditions. Facilitating conditions was the second largest domain, which highlights the importance of users having infrastructure to support system use. Digital interventions were viewed positively if they were compatible with values, needs, and experiences of users.

CONCLUSIONS

User perceptions that drive users to accept and utilize digital interventions for antimicrobial prescribing and monitoring were predominantly related to performance expectations and facilitating conditions. To ensure digital interventions for antimicrobial prescribing are accepted and used, we recommend organizations ensure systems are evaluated and benefits are conveyed to users, that utility meets expectations, and that appropriate infrastructure is in place to support use.

Electronic information systems for One Health surveillance of antimicrobial resistance: a systematic scoping review

INTRODUCTION

Electronic information systems (EIS) that implement a 'One Health' approach by integrating antimicrobial resistance (AMR) data across the human, animal and environmental health sectors, have been identified as a global priority. However, evidence on the availability, technical capacities and effectiveness of such EIS is scarce.

METHODS

Through a qualitative synthesis of evidence, this systematic scoping review aims to: identify EIS for AMR surveillance that operate across human, animal and environmental health sectors; describe their technical characteristics and capabilities; and assess whether there is evidence for the effectiveness of the various EIS for AMR surveillance. Studies and reports between 1 January 2000 and 21 July 2021 from peer-reviewed and grey literature in the English language were included.

RESULTS

26 studies and reports were included in the final review, of which 27 EIS were described. None of the EIS integrated AMR data in a One Health approach across all three sectors. While there was a lack of evidence of thorough evaluations of the effectiveness of the identified EIS, several surveillance system effectiveness indicators were reported for most EIS. Standardised reporting of the effectiveness of EIS is recommended for future publications. The capabilities of the EIS varied in their technical design features, in terms of usability, data display tools and desired outputs. EIS that included interactive features, and geospatial maps are increasingly relevant for future trends in AMR data analytics.

CONCLUSION

No EIS for AMR surveillance was identified that was designed to integrate a broad range of AMR data from humans, animals and the environment, representing a major gap in global efforts to implement One Health approaches to address AMR.

OUP accepted manuscript

Background

Antimicrobial stewardship programmes (ASPs) have been widely implemented in medical practice to improve antimicrobial prescribing and reduce selection for multidrug-resistant pathogens.

Objectives

To implement different antimicrobial stewardship intervention packages in 135 veterinary practices and assess their impact on antimicrobial prescribing.

Methods

In October 2018, general veterinary clinics were assigned to one of three levels of ASP, education only (CON), intermediate (AMS1) or intensive (AMS2). De-identified prescribing data (1 October 2016 to 31 October 2020), sourced from VetCompass Australia, were analysed and a Poisson regression model fitted to identify the effect of the interventions on the incidence rates of antimicrobial prescribing.

Results

The overall incidence rate (IR) of antimicrobial prescribing for dogs and cats prior to the intervention was 3.7/100 consultations, which declined by 36% (2.4/100) in the implementation period, and by 50% (1.9/100) during the post-implementation period. Compared with CON, in AMS2 there was a 4% and 6% reduction in the overall IR of antimicrobial prescribing, and a 24% and 24% reduction in IR of high importance antimicrobial prescribing, attributable to the intervention in the implementation and post-implementation periods, respectively. A greater mean difference in the IR of antimicrobial prescribing was seen in high-prescribing clinics.

Conclusions

These AMS interventions had a positive impact in a large group of general veterinary practices, resulting in a decline in overall antimicrobial use and a shift towards use of antimicrobials rated as low importance, with the greatest impact in high-prescribing clinics.

Which Biomarkers Can Be Used as Diagnostic Tools for Infection in Suspected Sepsis?

The diagnosis of infection in patients with suspected sepsis is frequently difficult to achieve with a reasonable degree of certainty. Currently, the diagnosis of infection still relies on a combination of systemic manifestations, manifestations of organ dysfunction, and microbiological documentation. In addition, the microbiologic confirmation of infection is obtained only after 2 to 3 days of empiric antibiotic therapy. These criteria are far from perfect being at least in part responsible for the overuse and misuse of antibiotics, in the community and in hospital, and probably the main drive for antibiotic resistance. Biomarkers have been studied and used in several clinical settings as surrogate markers of infection to improve their diagnostic accuracy as well as in the assessment of response to antibiotics and in antibiotic stewardship programs. The aim of this review is to provide a clear overview of the current evidence of usefulness of biomarkers in several clinical scenarios, namely, to diagnose infection to prescribe antibiotics, to exclude infection to withhold antibiotics, and to identify the causative pathogen to target antimicrobial treatment. In recent years, new evidence with "old" biomarkers, like C-reactive protein and procalcitonin, as well as new biomarkers and molecular tests, as breathomics or bacterial DNA identification by polymerase chain reaction, increased markedly in different areas adding useful information for clinical decision making at the bedside when adequately used. The recent evidence shows that the information given by biomarkers can support the suspicion of infection and pathogen identification but also, and not less important, can exclude its diagnosis. Although the ideal biomarker has not yet been found, there are various promising biomarkers that represent true evolutions in the diagnosis of infection in patients with suspected sepsis.

The role of Design Science Research Methodology in developing pharmacy eHealth services

The increasing focus on efficiency of care has prompted health systems to look for innovative solutions that yield maximum value for care. Integration of care and eHealth are seen as the most promising solutions in the high technological environment of the coming decades. Pharmacy services have been developed to a point where the face of community pharmacy has changed dramatically. Thus, service design and implementation has become an area of increased attention by Pharmacy practice researchers, and the arrival of eHealth concepts to Pharmacy is driving the need to find alternative ways to design new services. Moreover, known barriers and challenges remain when securing integration of pharmacy services with the health systems. In this paper, Design Science Research Methodology (DSRM), a user-centered alternative methodology to the design, development and implementation of health services, especially eHealth services, is presented. This alternative, originally from the Information Sciences field, has been adopted as a service design methodology in diverse settings, including health care. Here, case studies are used to explain how a DSRM process should be conducted in a health care setting, illustrating what methods to choose in each step of the process. Finally, the advantages of DSRM compared to other user-centered methodologies for service design are presented, hopefully prompting the discussion on the use of DSRM for the study of the implementation and sustainability of pharmacy services.

Co-Design for People-Centred Care Digital Solutions: A Literature Review

Introduction:

The implementation of people-centred care requires strategies that respond to local conditions and contexts, with the participation of local stakeholders in collaborative approaches such as co-design. Within this framework, the authors performed a literature review to identify the most implemented practices in health and social care services for co-designing digital solutions.

Methods:

The literature review was conducted following five steps: (i) Definition of the Keywords and their relations; (ii) Definition of the selection criteria; (iii) Search in PubMed; (iv) Selection of papers; and (v) Analysis of the selected papers.

Results:

20 papers addressed to co-design health digital solutions with stakeholders were analysed in terms of the activities implemented and participants involved.

Discussion:

Previous studies using co-design methods for the deployment of health digital solutions employed a wide range of activities, most of them combining activities and/or mixed target groups.

Conclusion:

Co-design is the key to deliver people-centred care as it allows to involve stakeholders in the development of health digital solutions. Implementing one or more of the co-design methods identified in this literature review should be considered to better address the needs and specific projects and target groups.

Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management

The study evaluated individual and setting-specific factors that moderate clinicians’ perception regarding use of clinical decision support systems (CDSS) for antibiotic management. A cross-sectional online survey examined clinicians’ perceptions about CDSS implementation for antibiotic management in Australia. Multivariable logistic regression determined the association between drivers of CDSS adoption and different moderators. Clinical experience, CDSS use and care setting were important predictors of clinicians’ perception concerning CDSS adoption. Compared to nonusers, CDSS users were less likely to lack confidence in CDSS (OR = 0.63, 95%, CI = 0.32, 0.94) and consider it a threat to professional autonomy (OR = 0.47, 95%, CI = 0.08, 0.83). Conversely, there was higher likelihood in experienced clinicians (>20 years) to distrust CDSS (OR = 1.58, 95%, CI = 1.08, 2.23) due to fear of comprising their clinical judgement (OR = 1.68, 95%, CI = 1.27, 2.85). In primary care, clinicians were more likely to perceive time constraints (OR = 1.96, 95%, CI = 1.04, 3.70) and patient preference (OR = 1.84, 95%, CI = 1.19, 2.78) as barriers to CDSS adoption for antibiotic prescribing. Our findings provide differentiated understanding of the CDSS implementation landscape by identifying different individual, organisational and system-level factors that influence system adoption. The individual and setting characteristics can help understand the variability in CDSS adoption for antibiotic management in different clinicians.

An Artificial Neural Network Approach and a Data Augmentation Algorithm to Systematize the Diagnosis of Deep-Vein Thrombosis by Using Wells’ Criteria

The use of a back-propagation artificial neural network (ANN) to systematize the reliability of a Deep Vein Thrombosis (DVT) diagnostic by using Wells’ criteria is introduced herein. In this paper, a new ANN model is proposed to improve the Accuracy when dealing with a highly unbalanced dataset. To create the training dataset, a new data augmentation algorithm based on statistical data known as the prevalence of DVT of real cases reported in literature and from the public hospital is proposed. The above is used to generate one dataset of 10,000 synthetic cases. Each synthetic case has nine risk factors according to Wells’ criteria and also the use of two additional factors, such as gender and age, is proposed. According to interviews with medical specialists, a training scheme was established. In addition, a new algorithm is presented to improve the Accuracy and Sensitivity/Recall. According to the proposed algorithm, two thresholds of decision were found, the first one is 0.484, which is to improve Accuracy. The other one is 0.138 to improve Sensitivity/Recall. The Accuracy achieved is 90.99%, which is greater than that obtained with other related machine learning methods. The proposed ANN model was validated performing the k-fold cross validation technique using a dataset with 10,000 synthetic cases. The test was performed by using 59 real cases obtained from a regional hospital, achieving an Accuracy of 98.30%.

Mapping hospital antimicrobial stewardship programmes in the Gulf Cooperation Council states against international standards: a systematic review

BACKGROUND

While there is evidence of implementation of antimicrobial stewardship programmes (ASPs) in the Gulf Cooperation Council (GCC) states, there has been limited benchmarking and mapping to international standards and frameworks.

AIM

To critically appraise and synthesize the evidence of ASP implementation in GCC hospitals with reference to the framework of the Centers for Disease Control and Prevention (CDC), identifying key facilitators and barriers.

METHODS

A systematic review protocol was developed based on Preferred Reporting Items for Systematic Reviews and Meta-analyses for Protocols guidelines. Five electronic databases were searched for studies published in English from 2010 onwards. Study selection, quality assessment and data extraction were performed independently by two reviewers. A narrative synthesis was conducted with ASP interventions mapped to CDC core elements.

FINDINGS

Seventeen studies were identified, most of which (N=11) were from Saudi Arabia. Mapping to the CDC framework identified key areas of strengths and weaknesses in reporting implementation. Studies more commonly reported core elements of pharmacy expertise, selected aspects of implementation actions, tracking, antibiotic use and resistance, and education. Little emphasis was placed on the reporting of leadership and accountability. Key implementation facilitators were physician and organization support, information systems and education, and barriers were dedicated staff, workload and funding.

CONCLUSION

There is a need to enhance the reporting of ASP implementation in GCC hospitals. The CDC framework should be used as a guide during the development, implementation and reporting of ASP interventions. Action is required to identify facilitators and overcome barriers, where possible.

Effectiveness of Electronic Guidelines (GERH®) to Improve the Clinical Use of Antibiotics in An Intensive Care Unit

The objective of the study was to evaluate the capacity of GERH^®-derived local resistance maps (LRMs) to predict antibiotic susceptibility profiles and recommend the appropriate empirical treatment for ICU patients with nosocomial infection. Data gathered between 2007 and 2016 were retrospectively studied to compare susceptibility information from antibiograms of microorganisms isolated in blood cultures, lower respiratory tract samples, and urine samples from all ICU patients meeting clinical criteria for infection with the susceptibility mapped by LRMs for these bacterial species. Susceptibility described by LRMs was concordant with in vitro study results in 73.9% of cases. The LRM-predicted outcome agreed with the antibiogram result in >90% of cases infected with the bacteria for which GERH^® offers data on susceptibility to daptomycin, vancomycin, teicoplanin, linezolid, and rifampicin. Full adherence to LRM recommendations would have improved the percentage adequacy of empirical prescriptions by 2.2% for lower respiratory tract infections (p = 0.018), 3.1% for bacteremia (p = 0.07), and 5.3% for urinary tract infections (p = 0.142). LRMs may moderately improve the adequacy of empirical antibiotic therapy, especially for lower respiratory tract infections. LRMs recommend appropriate prescriptions in approximately 50% of cases but are less useful in patients with bacteremia or urinary tract infection.

Stewardship-Hospitalist Collaboration

Hospitalists represent a rapidly emerging specialty group that treats a large proportion of hospitalized patients with infections. Antimicrobial stewardship programs and hospitalist groups that focus on building a collaborative approach have been extremely successful in optimizing antimicrobial prescribing and improving patient outcomes. We discuss the tools needed to build collaborative relationships, summarize published examples of successful stewardship-hospitalist collaboration, and provide guidance on developing collaborative interventions.

Clinical Decision Support Systems and Their Role in Antibiotic Stewardship: a Systematic Review

PURPOSE OF REVIEW

The purpose of this article is to perform a systematic review over the past 5 years on the role and effectiveness of clinical decision support systems (CDSSs) on antibiotic stewardship.

RECENT FINDINGS

CDDS interventions found a significant impact on multiple outcomes relevant to antibiotic stewardship. There are various types of CDSS implementations, both active and passive (provider initiated). Passive interventions were associated with more significant outcomes; however, both interventions appeared effective. In the reviewed literature, CDSSs were consistently associated with decreasing antibiotic consumption and narrowing the spectrum of antibiotic usage. Generally, guideline adherence was improved with CDSS, although this was not universal. The effect on other outcomes, such as mortality, Clostridiodes difficile infections, length of stay, and cost, inconsistently showed a significant difference. Overall, CDDS implementation has effectively decreased antibiotic consumption and improved guideline adherence across the various types of CDSS. Other positive outcomes were noted in certain settings, but were not universal. When creating a new intervention, it is important to identify the optimal structure and deployment of a CDSS for a specific setting.

Rapid Analysis of Diagnostic and Antimicrobial Patterns in R (RadaR): Interactive Open-Source Software App for Infection Management and Antimicrobial Stewardship

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.