Use of Technology to Improve Adherence in Allergy/Immunology.

The integration of technology into health care has shown significant promise in enhancing patient adherence, particularly in the field of allergy/immunology. This article explores the multifaceted approaches through which digital health interventions can be used to improve adherence rates among patients with allergic diseases and immunologic disorders. By reviewing recent advancements in telemedicine, mobile health applications, wearable devices, and digital reminders, as well as smart inhalers, we aim to provide a comprehensive overview of how these technologies can support patients in managing their conditions. The analysis highlights the role of personalized digital health plans, which, through the use of artificial intelligence and machine learning algorithms, can offer tailored advice, monitor symptoms, and adjust treatment protocols in real time. Moreover, the article discusses the impact of electronic health records and patient portals in fostering a collaborative patient-provider relationship, thereby enhancing communication and adherence. The integration of these technologies has been shown to not only improve clinical outcomes but also increase patient satisfaction and engagement.

Artificial intelligence and machine learning for anaphylaxis algorithms.

PURPOSE OF REVIEW: Anaphylaxis is a severe, potentially life-threatening allergic reaction that requires rapid identification and intervention. Current management includes early recognition, prompt administration of epinephrine, and immediate medical attention. However, challenges remain in accurate diagnosis, timely treatment, and personalized care. This article reviews the integration of artificial intelligence and machine learning in enhancing anaphylaxis management. RECENT FINDINGS: Artificial intelligence and machine learning can analyze vast datasets to identify patterns and predict anaphylactic episodes, improve diagnostic accuracy through image and biomarker analysis, and personalize treatment plans. Artificial intelligence-powered wearable devices and decision support systems can facilitate real-time monitoring and early intervention. The ethical considerations of artificial intelligence use, including data privacy, transparency, and bias mitigation, are also discussed. SUMMARY: Future directions include the development of predictive models, enhanced diagnostic tools, and artificial intelligence-driven educational resources. By leveraging artificial intelligence and machine learning, healthcare providers can improve the management of anaphylaxis, ensuring better patient outcomes and advancing personalized medicine.

Future Directions of Allergen Immunotherapy for Allergic Rhinitis: Experts' Perspective.

Allergen immunotherapy (AIT) is broadly used all over the world as the only available disease-modifying treatment option. The aim of this experts' perspective is to address 7 important unmet needs for the further direction of AIT and to provide the readership with the authors' positions on these topics. An international group of experts in the field of AIT have formulated 7 important aspects for the future position of AIT, performed a current literature review, and proposed a consented position on these topics. The aspects discussed and consented by the authors include: (1) alternative routes of allergen application in AIT, (2) potential of recombinant vaccines, (3) the role of allergy diagnosis based on component-resolved diagnosis for AIT composition, (4) the impact of COVID-19 vaccination for further innovations in AIT, (5) potential of combining biologics to AIT, (6) future innovations in high-risk children/adolescents, and (7) the future regulatory position on AIT. Important unmet needs and topics for AIT have been addressed in this expert review. The authors' views and personal position on these 7 aspects have also been elaborated.

Expert Consensus on SABA Use for Asthma Clinical Decision-Making: A Delphi Approach.

PURPOSE OF REVIEW: A modified Delphi process was undertaken to provide a US expert-led consensus to guide clinical action on short-acting beta2-agonist (SABA) use. This comprised an online survey (Phase 1), forum discussion and statement development (Phase 2), and statement adjudication (Phase 3). RECENT FINDINGS: In Phase 1 (n = 100 clinicians), 12% routinely provided patients with ≥4 SABA prescriptions/year, 73% solicited SABA use frequency at every patient visit, and 21% did not consult asthma guidelines/expert reports. Phase 3 experts (n = 8) reached consensus (median Likert score, interquartile range) that use of ≥3 SABA canisters/year is associated with increased risk of exacerbation and asthma-related death (5, 4.75-5); SABA use history should be solicited at every patient visit (5, 4.75-5); usage patterns over time, not absolute thresholds, should guide response to SABA overuse (5, 4.5-5). Future asthma guidelines should include clear recommendations regarding SABA usage, using expert-led thresholds for action.

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.

Telemedicine beyond the pandemic: challenges in the pediatric immunology clinic.

INTRODUCTION: Telemedicine and electronic medical records (EMRs) have revolutionized healthcare in recent years, offering numerous benefits that improve the delivery of care and the overall patient outcomes. AREAS COVERED: Telemedicine allows providers to diagnose and treat patients remotely, often eliminating the need for face-to-face visits. Its benefits include improved access to care, convenience for patients, and reduced costs both for patients and providers. When used with remote patient monitoring and remote therapeutic monitoring, continuous care becomes possible. EMRs allow providers to store, access, and share patient information more efficiently than paper charts. The benefits of EMRs include improved patient safety, increased efficiency, and reduced costs. EXPERT OPINION: The combination of telemedicine with EMRs makes it possible to envision the advent of computer-assisted diagnosis (CAD). This technology uses artificial intelligence and machine learning algorithms to analyze medical information including images, clinical and physiologic data, test results and remotely obtained information to support healthcare providers in making accurate diagnoses. By providing providers with what is essentially a second opinion, CAD systems can help prevent misdiagnoses and improve the quality of care. Such systems are not meant to replace healthcare providers, but rather to support them in making more informed and accurate diagnoses.

Real-world experience of pediatric patients treated with peanut (Arachis hypogaea) allergen powder-dnfp.

BACKGROUND: Peanut (Arachis hypogaea) allergen powder-dnfp (PTAH) is the first oral immunotherapy indicated for children aged 4 to 17 years with peanut allergy. There are limited real-world data on patients treated with PTAH. OBJECTIVE: To characterize pediatric patients treated with PTAH and associated treatment patterns in US clinical practice. METHODS: US-based physicians with allergy and immunology training treating patients with peanut allergy aged 4 to 17 years with PTAH were recruited from an existing physician panel and completed an online case report form (October to December 2021) with data abstracted from patient medical charts. Physician practice circumstances, patient characteristics, and PTAH treatment patterns were reported. Time to reach the 300-mg dose and treatment persistence were assessed using Kaplan-Meier analysis. RESULTS: A geographically balanced sample of 43 physicians contributed data for 118 demographically diverse pediatric patients. Patients had heterogeneous diagnostic test results, with a wide range of peanut-specific immunoglobulin E levels; 6.8% received an oral food challenge. During the updosing phase, there were no temporary interruptions and 5.1% of the patients required downdosing. Patients reached the 300-mg dose at a median of 21.3 weeks post-initiation. The rate of PTAH persistence at 24 weeks was 93.4%. Only 1 patient discontinued treatment because of treatment-related systemic allergic symptoms, and the remaining discontinuations were for reasons other than treatment-related symptoms. Prophylactic antihistamines were used by 33.9% of the patients to prevent PTAH adverse effects. CONCLUSION: PTAH was prescribed in demographically diverse patients with a wide range of peanut-specific immunoglobulin E levels. Treatment persistence with PTAH was high in this study population, with a small number of patients experiencing treatment modification.

Teleallergy: Where Have We Been and Where Are We Going?

Telemedicine uptake in allergy/immunology was slow before the coronavirus disease 2019 pandemic, but has accelerated since. This review examines where telemedicine has been in allergy/immunology and where it is headed in the future. Focus is placed on patient, physician, and health care professional satisfaction with telemedicine, capacity to expand access to allergy/immunology care, cost considerations, the regulatory environment, and future applications of telemedicine including adherence monitoring, wearable biosensors, artificial intelligence, and machine learning addressed.

The Regulatory Environment of Telemedicine After COVID-19.

The COVID-19 pandemic has created many barriers to providing health care, yet it also has created new opportunities. Although telemedicine was a nascent means of health care delivery before COVID-19, it now is one of the principal means for doing so today, and it is likely to remain so. Whether this will happen may depend in part on continued relaxation of regulations that hampered it before the pandemic. Whereas enforcement of compliance with Health Information Portability and Accountability Act will most likely resume, platform operators and providers have had an opportunity to prepare for this. State licensure requirements may also resume; however, the regulations were in the process of becoming more liberal before COVID-19 so that process might continue. There is no reason to anticipate that payment for telemedicine services including check-ins, remote physiologic and therapeutic monitoring, and relaxation of location and service requirements will end. For these reasons, telemedicine therefore is likely to continue as an important part of medical practice.

Pediatric subcutaneous allergen immunotherapy.

Subcutaneous immunotherapy (SCIT) is a widely used therapy for allergic rhinitis and asthma. It is a useful adjunct to standard medical management of these conditions that can lead to long-term benefits and possible resolution of symptoms. The benefits of SCIT, particularly for children, include avoiding prolonged use and side effects from medications, preventing new aeroallergen sensitizations, and reducing the risk of developing asthma. The primary risks of SCIT include local and systemic reactions. Standard schedules for SCIT include advancing through multiple doses usually in four vials (diluted to 1:1000) on a weekly basis; however, there are benefits of using accelerated schedules, especially for children who need to coordinate school and parent work schedules. Special considerations for pediatric patients include fear of needles, avoiding discomfort with injections, consent, optimal injection scheduling, and difficulty communicating about symptoms during reactions in very young children. Overall, SCIT can be a safe and beneficial therapy for children.

Eight tips for the implementation of the first licenced peanut allergy oral immunotherapy into clinical practice.

BACKGROUND: Shared learnings from the early use of novel therapies can aid in their optimization. The recent introduction of peanut oral immunotherapy (peanut OIT; Palforzia [Peanut (Arachis hypogaea) Allergen Powder-dnfp]) for peanut allergy addresses a significant unmet need but also highlights the requirement for consideration of several factors by both prescribers and patients. OBJECTIVE: To provide guidance for prescribers of licenced peanut OIT to facilitate treatment delivery and improve outcomes. METHODS: Clinicians with experience of licenced peanut OIT (United States n = 6, United Kingdom n = 1) participated in a series of interviews and group discussions designed to elicit tips for successful implementation. RESULTS: Clinicians identified 8 tips that were considered the most relevant, practical, and impactful for prescribers of Peanut (Arachis hypogaea) Allergen Powder-dnfp: (1) preparing to provide treatment, (2) assessing the medical indication for treatment and (3) shared decision making, (4) staff education, (5) establishing office processes, (6) managing patient expectations and using anticipatory guidance, (7) optimising adherence and (8) maintaining flexibility throughout the treatment process. In addition, a range of supporting materials (e.g., checklists and action plans) are provided. CONCLUSION: The introduction of a novel therapy often requires healthcare providers to modify or adopt practices to effectively employ the treatment. The provision of guidance based upon early real-world experiences of licenced peanut OIT may help inform clinical practice and improve treatment outcomes.

Patient and Clinician Attitudes Toward Telemedicine for Allergy and Immunology.

The use of telemedicine has increased in allergy/immunology, with rapid uptake of its use during the coronavirus disease 2019 pandemic. Existing data indicate an overall positive view of telemedicine by patients, particularly during the coronavirus disease 2019 pandemic. However, patients and clinicians prefer in-person visits for specific types of allergy/immunology encounters, such as those requiring a physical examination or diagnostic testing. The most data for telemedicine exist with asthma, and provide a model for treatment technique, therapeutic monitoring, and education in other allergic and immunologic conditions. Clinician satisfaction is also necessary for telemedicine to be an enduring option for patient/clinician interactions, and this is influenced by a multitude of factors, including technology quality, reimbursement, and maintenance of patient/clinician relationships. Areas of future research should include the need for more outcome data in additional disease states, which will likely help facilitate improved logistical policies around telemedicine that would facilitate its adoption.

Evolving Interpretation of Screening and Diagnostic Tests in Allergy.

Diagnostic tests for allergy usually are performed to confirm a diagnosis of an allergic disease. If a food allergy suspected, a test can help to determine whether it is present, to monitor its activity over time, and to determine whether the allergy is resolving. In this way, tests are used for diagnosis, monitoring, screening, and prognosis. There are 2 schools of thought for using tests: Frequentist and Bayesian approaches. The Frequentist approach defines probability in terms of the frequency of an event if it were to be repeated numerous times and uses parameters such as sensitivity, specificity, and predictive values to make a diagnosis. In contrast, the Bayesian approach defines probability as the degree of belief or disbelief regarding the diagnosis and asserts that only data are real and that test parameters are to be inferred from the data. There are strengths and limitations to each approach; however, the Bayesian approach provides an algorithm leading to a disease probability. To use the Bayesian approach, test results need to be expressed as a likelihood ratio. This helps to determine how much the result of a test changes the probability of a particular diagnosis. Once a probability of disease is determined, decision thresholds need to be defined so that a treatment decision can be made. Using this Bayesian approach, the concept of a false-positive or false-negative test result becomes obsolete.