Development and Validation of a Mobile Clinical Decision Support Tool for the Diagnosis of Drug Allergy in Adults: The Drug Allergy App

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

Introduction

Digital clinical decision support (CDS) tools are of growing importance in supporting healthcare professionals in understanding complex clinical problems and arriving at decisions that improve patient outcomes. CDS tools are also increasingly used to improve antimicrobial stewardship (AMS) practices in healthcare settings. However, far fewer CDS tools are available in lowerand middle-income countries (LMICs) and in animal health settings, where their use in improving diagnostic and treatment decision-making is likely to have the greatest impact. The aim of this study was to evaluate digital CDS tools designed as a direct aid to support diagnosis and/or treatment decisionmaking, by reviewing their scope, functions, methodologies, and quality. Recommendations for the development of veterinary CDS tools in LMICs are then provided.

Methods

The review considered studies and reports published between January 2017 and October 2023 in the English language in peer-reviewed and gray literature.

Results

A total of 41 studies and reports detailing CDS tools were included in the final review, with 35 CDS tools designed for human healthcare settings and six tools for animal healthcare settings. Of the tools reviewed, the majority were deployed in high-income countries (80.5%). Support for AMS programs was a feature in 12 (29.3%) of the tools, with 10 tools in human healthcare settings. The capabilities of the CDS tools varied when reviewed against the GUIDES checklist.

Discussion

We recommend a methodological approach for the development of veterinary CDS tools in LMICs predicated on securing sufficient and sustainable funding. Employing a multidisciplinary development team is an important first step. Developing standalone CDS tools using Bayesian algorithms based on local expert knowledge will provide users with rapid and reliable access to quality guidance on diagnoses and treatments. Such tools are likely to contribute to improved disease management on farms and reduce inappropriate antimicrobial use, thus supporting AMS practices in areas of high need.

Non-allergist healthcare workers views on delivering a penicillin allergy de-labelling inpatient pathway: identifying the barriers and enablers

Background

Non-allergist delivered PADL is supported by UK and World Health Organization guidelines but is not yet routine in UK hospitals. Understanding the views of healthcare workers (HCWs) on managing patients with penA records and exploring perspectives on delivering a PADL inpatient pathway are required to inform the development of non-allergist delivered PADL pathways.

Objective

To explore the perspectives of non-allergist HCWs working in medical specialties on managing patients with penA records, and to explore the enablers and barriers to embedding PADL as a standard of care for inpatients.

Methods

Semi-structured interviews with doctors, nurses, pharmacists and medicines optimization pharmacy technicians working in a district general hospital in the UK. Thematic analysis was used to analyse the data.

Results

The PADL pathway was considered a shared responsibility of the multidisciplinary team, which needed to be structured and supported by a framework. PADL aligns with HCW roles but time to deliver PADL was a barrier. Training for HCWs on the benefits of PADL and delivering PADL for those patients where a penicillin might be beneficial during the current episode of care would both motivate HCWs to deliver PADL.

Discussion and conclusion

The PADL pathway was acceptable to HCWs and aligned with their roles and current healthcare processes but their capacity to deliver PADL in a time pressured environment was a significant barrier.

Penicillin allergy de-labelling by non-allergists: a comparison of testing protocols

Optimizing penicillin allergy de-labelling (PADL) to ensure patients with an incorrect penicillin allergy record are de-labelled with minimal patient harm is important for antibiotic stewardship. The heterogeneity of inclusion and exclusion criteria in the published penicillin allergy testing protocols risks suboptimal delivery of PADL. We compared the similarities and the differences between non-allergist-delivered PADL testing protocols and make suggestions for harmonization. The observed variation in testing practice has two broad elements: (i) definitions and terminology; and (ii) differences in the acceptability of perceived risk. All direct drug provocation testing (DDPT) protocols included patients with benign delayed rash as eligible for testing, although the remoteness of the rash, and the terminology used to describe the rash, differed. Patients with features of potential IgE reactions were excluded from most DDPT protocols, but not all of them. There was differing advice on how to manage patients who had subsequently tolerated penicillin since the index reaction and differences in which patients were considered ineligible for DDPT due to acuity of illness, comorbidities and concomitant medications. Standardization of the terminology used in penicillin allergy testing protocols and consensus on inclusion and exclusion criteria are required for safe and efficient PADL delivery at scale by non-allergists.

Computer-Assisted Clinical Diagnosis and Treatment

PURPOSE OF REVIEW

Computer-assisted diagnosis and treatment (CAD/CAT) is a rapidly growing field of medicine that uses computer technology and telehealth to aid in the diagnosis and treatment of various diseases. The purpose of this paper is to provide a review on computer-assisted diagnosis and treatment. This technology gives providers access to diagnostic tools and treatment options so that they can make more informed decisions leading to improved patient outcomes.

RECENT FINDINGS

CAD/CAT has expanded in allergy and immunology in the form of digital tools that enable remote patient monitoring such as digital inhalers, pulmonary function tests, and E-diaries. By incorporating this information into electronic medical records (EMRs), providers can use this information to make the best, evidence-based diagnosis and to recommend treatment that is likely to be most effective. A major benefit of CAD/CAT is that by analyzing large amounts of data, tailored recommendations can be made to improve patient outcomes and reduce the risk of adverse events. Machine learning can assist with medical data acquisition, feature extraction, interpretation, and decision support. It is important to note that this technology is not meant to replace human professionals. Instead, it is designed to assist healthcare professionals to better diagnose and treat patients.

Standardizing In Vitro β-Lactam Antibiotic Allergy Testing with Synthetic IgE

The global prevalence of β-lactam allergy poses a major challenge in administering first-line antibiotics, such as penicillins, to a significant portion of the population. The lack of β-lactam IgE antibody pools with defined selectivity hampers the standardization and validation of in vitro assays for β-lactam allergy testing. To address this limitation, this study introduces a synthetic IgE specific to β-lactam antibiotics as a valuable tool for drug allergy research and diagnostic tests. Using phage display technology, we constructed a library of human single-chain antibody fragments (scFv) to target the primary determinant of amoxicillin, a widely used β-lactam antibiotic. Subsequently, we produced a complete human synthetic IgE molecule using the highly efficient baculovirus expression vector system. This synthetic IgE molecule served as a standard in an in vitro chemiluminescence immunoassay for β-lactam antibiotic allergy testing. Our results demonstrated a detection limit of 0.05 IU/mL (0.63 pM), excellent specificity (100%), and a four-fold higher clinical sensitivity (73%) compared to the in vitro reference assay when testing a cohort of 150 serum samples. These findings have significant implications for reliable interlaboratory comparison studies, accurate labeling of allergic patients, and combating the global public health threat of antimicrobial resistance. Furthermore, by serving as a valuable trueness control material, the synthetic IgE facilitates the standardization of diagnostic tests for β-lactam allergy and demonstrates the potential of utilizing this synthetic strategy as a promising approach for generating reference materials in drug allergy research and diagnostics.

Addressing the Challenges of Penicillin Allergy Delabeling With Electronic Health Records and Mobile Applications

Allergy labels are common, often incorrect, and potentially harmful. There are many opportunities for clinical decision support (CDS) tools integrated in the electronic health record (EHR) and mobile apps to address the challenges with drug allergy management, including penicillin allergy delabeling (PADL). Effective delabeling solutions must consider multidisciplinary clinical workflow and multistep processes, including documentation, assessment, plan (eg, allergy testing and referral), record update, drug allergy alert management, and allergy reconciliation over time. Developing a systematic infrastructure to manage allergies across the EHR is critical to improve the accuracy and completeness of a patient's allergy and avoid inadvertently relabeling. Improving the appropriateness and relevancy of drug allergy alerts is important to reduce alert fatigue. Using alerts to guide clinicians on appropriate antibiotic use may reduce unnecessary β-lactam avoidance. To date, EHR CDS tools have facilitated non-allergists to provide PADL at the point of care. A mobile app was shown to support PADL and provide specialist support and education. Future research is needed to standardize, integrate, and evaluate innovative CDS tools in the EHR to demonstrate patient safety and clinical utility and facilitate wider adoption.