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State the Purpose Obtaining high‐quality samples to diagnose streptococcal pharyngitis in pediatric patients is challenging due to discomfort associated with traditional pharyngeal swabs. This may cause reluctance to go to the clinic, inaccurate diagnosis, or inappropriate treatment for children with sore throats. Here, we determined the efficacy of CandyCollect, a lollipop‐inspired open‐microfluidic pathogen collection device, to capture Group A Streptococcus (GAS) and compare user preference for CandyCollect, conventional pharyngeal swabs, or mouth swabs in children with pharyngitis and their caregivers. Results All child participants (30/30) were positive for GAS by qPCR on both the mouth swab and CandyCollect. Caregivers ranked CandyCollect as a good sampling method overall (27/30), and all caregivers (30/30) would recommend CandyCollect for children 5 years and older. Twenty‐three of 30 children “really like” the taste and 24/30 would prefer to use CandyCollect if a future test were needed. All caregivers (30/30) and most children (28/30) would be willing to use CandyCollect at home. Conclusion All participants tested positive for GAS on all three collection methods (pharyngeal swab, mouth swab, and CandyCollect). While both caregivers and children like CandyCollect, some caregivers would prefer a shorter collection time. Future work includes additional studies with larger cohorts presenting with pharyngitis of unknown etiology and shortening collection time while maintaining the attractive form of the device.

Cyclic vomiting syndrome (CVS) is an enigmatic and debilitating disorder of gut-brain interaction that is characterized by recurrent episodes of severe vomiting and nausea. It significantly impairs patients' quality of life and can lead to frequent medical visits and substantial health care costs. The diagnosis for CVS is often protracted and complex, primarily due to its exclusionary diagnosis nature and the lack of specific biomarkers. This typically leads to a considerable delay in accurate diagnosis, contributing to increased patient morbidity. Additionally, the absence of approved therapies for CVS worsens patient hardship and reflects the urgent need for innovative, patient-centric solutions to improve CVS management. We aim to develop a digital patient assistant (DPA) for patients with CVS to address their unique needs, and iteratively enhance the technical features and user experience on the initial DPA versions. The development of the DPA for CVS used a design thinking approach, prioritizing user needs. A literature review and Patient Advisory Board shaped the initial prototype, focusing on diagnostic support and symptom tracking. Iterative development, informed by the design thinking approach and feedback from patients with CVS and caregivers through interviews and smartphone testing, led to significant enhancements in user interaction and artificial intelligence integration. The final DPA's effectiveness was validated using the System Usability Scale and feedback questions, ensuring it met the specific needs of the CVS community. The DPA developed for CVS integrates an introductory bot, daily and weekly check-in bots, and a knowledge hub, all accessible via a patient dashboard. This multicomponent solution effectively addresses key unmet needs in CVS management: efficient symptom and impacts tracking, access to comprehensive disease information, and a digital health platform for disease management. Significant improvements, based on user feedback, include the implementation of artificial intelligence features like intent recognition and data syncing, enhancing the bot interaction and reducing the burden on patients. The inclusion of the knowledge hub provides educational resources, contributing to better disease understanding and management. The DPA achieved a System Usability Scale score of 80 out of 100, indicating high ease of use and relevance. Patient feedback highlighted the DPA's potential in disease management and suggested further applications, such as integration into health care provider recommendations for patients with suspected or confirmed CVS. This positive response underscores the DPA's role in enhancing patient engagement and disease management through a patient-centered digital solution. The development of this DPA for patients with CVS, via an iterative design thinking approach, offers a patient-centric solution for disease management. The DPA development framework may also serve to guide future patient digital support and research scenarios.

During the COVID-19 pandemic, there has been a significant increase in the use of internet resources for accessing medical care, resulting in the development and advancement of the Internet of Medical Things (IoMT). This technology utilizes a range of medical equipment and testing software to broadcast patient results over the internet, hence enabling the provision of remote healthcare services. Nevertheless, the preservation of privacy and security in the realm of online communication continues to provide a significant and pressing obstacle. Blockchain technology has shown the potential to mitigate security apprehensions across several sectors, such as the healthcare industry. Recent advancements in research have included intelligent agents in patient monitoring systems by integrating blockchain technology. However, the conventional network configuration of the agent and blockchain introduces a level of complexity. In order to address this disparity, we present a proposed architectural framework that combines software defined networking (SDN) with Blockchain technology. This framework is specially tailored for the purpose of facilitating remote patient monitoring systems within the context of a 5G environment. The architectural design contains a patient-centric agent (PCA) inside the SDN control plane for the purpose of managing user data on behalf of the patients. The appropriate handling of patient data is ensured by the PCA via the provision of essential instructions to the forwarding devices. The suggested model is assessed using hyperledger fabric on docker-engine, and its performance is compared to that of current models in fifth generation (5G) networks. The performance of our suggested model surpasses current methodologies, as shown by our extensive study including factors such as throughput, dependability, communication overhead, and packet error rate.

Integrating Artificial Intelligence (AI) in healthcare represents a transformative shift with substantial potential for enhancing patient care. This paper critically examines this integration, confronting significant ethical, legal, and technological challenges, particularly in patient privacy, decision-making autonomy, and data integrity. A structured exploration of these issues focuses on Differential Privacy as a critical method for preserving patient confidentiality in AI-driven healthcare systems. We analyze the balance between privacy preservation and the practical utility of healthcare data, emphasizing the effectiveness of encryption, Differential Privacy, and mixed-model approaches. The paper navigates the complex ethical and legal frameworks essential for AI integration in healthcare. We comprehensively examine patient rights and the nuances of informed consent, along with the challenges of harmonizing advanced technologies like blockchain with the General Data Protection Regulation (GDPR). The issue of algorithmic bias in healthcare is also explored, underscoring the urgent need for effective bias detection and mitigation strategies to build patient trust. The evolving roles of decentralized data sharing, regulatory frameworks, and patient agency are discussed in depth. Advocating for an interdisciplinary, multi-stakeholder approach and responsive governance, the paper aims to align healthcare AI with ethical principles, prioritize patient-centered outcomes, and steer AI towards responsible and equitable enhancements in patient care.

A paradigm shift is underway in the patient-clinician relationship, driven by irreversible changes in information access, yet the model under which clinicians are trained, care is conducted, and care delivery is designed has not changed significantly even though we call it “patient centered.” Humanity endured centuries in which even doctors had little idea what the patient’s problem really was. Science slowly solved that, and for a century, only doctors could know what was worth knowing. Today, the rise of the internet and digital health has led to the end of that era. We are already witnessing early signs of the era of participatory health: genuinely empowered people living their lives and managing their health according to their own priorities, in partnership and consultation with physicians as needed. This may feel like a threat to the physician’s sacred role, but it is no more so than when physicians adopted informed consent and then shared decision-making. In the 2010s, many pharmaceutical, medical, and health care companies started to use patient centricity as a mantra. We argue that to drive this paradigm change fully into existence, we need to shift “patient centricity” from a relatively passive process, driven by industry needs, into a far more active, collaborative process driven by both parties’ needs and preferences. To build this new world of practice and workflow, we simply must engage with patients as true partners. To achieve medicine’s new potential, it must be optimized around the wants and priorities of the ultimate stakeholder—the party that has the most at stake in how it all plays out: the patient. Patient design is the approach that can make it happen.

The world is facing multiple healthcare challenges because of the emergence of the COVID-19 (coronavirus) pandemic. The pandemic has exposed the limitations of handling public healthcare emergencies using existing digital healthcare technologies. Thus, the COVID-19 situation has forced research institutes and countries to rethink healthcare delivery solutions to ensure continuity of services while people stay at home and practice social distancing. Recently, several researchers have focused on disruptive technologies, such as blockchain and artificial intelligence (AI), to improve the digital healthcare workflow during COVID-19. Blockchain could combat pandemics by enabling decentralized healthcare data sharing, protecting users’ privacy, providing data empowerment, and ensuring reliable data management during outbreak tracking. In addition, AI provides intelligent computer-aided solutions by analyzing a patient’s medical images and symptoms caused by coronavirus for efficient treatments, future outbreak prediction, and drug manufacturing. Integrating both blockchain and AI could transform the existing healthcare ecosystem by democratizing and optimizing clinical workflows. In this article, we begin with an overview of digital healthcare services and problems that have arisen during the COVID-19 pandemic. Next, we conceptually propose a decentralized, patient-centric healthcare framework based on blockchain and AI to mitigate COVID-19 challenges. Then, we explore the significant applications of integrated blockchain and AI technologies to augment existing public healthcare strategies for tackling COVID-19. Finally, we highlight the challenges and implications for future research within a patient-centric paradigm.

Patient-centric resident conferences (PCRCs) provide meaningful time to connect with and learn from patients. This qualitative study explores themes of patients’ perioperative experiences from PCRCs through patient and resident perspectives. General Surgery residents participated in six PCRCs, which include condensed standard didactics to accommodate a patient panel regarding their perioperative experience. Panel transcripts and resident survey responses describing what they learned were coded using grounded theory methodology. Themes were evaluated and compared. 76 identified codes were grouped into major categories: “Medical/Surgical Knowledge,” “Patient Perspective,” “Patient-Physician Relationship,” and “Communication.” Themes from resident responses predominantly paralleled patient discussion, with common themes including “impact of disease and surgery on patient” and “compassion/empathy.” “Medical/surgical knowledge” was only present in resident responses while themes regarding quality of life were more frequent in patient transcripts. PCRCs are a valuable tool in resident education to understand patients’ perioperative experiences. Themes from patient panels complement, but do not replace, information covered in didactic lectures. •Patient-centric resident conferences are a valuable tool in resident education.•PCRCs help residents understand patients' perioperative experiences.•Patients value communication, quality of life, and the patient-physician relationship.•Residents do not emphasize the impact of the system on perioperative care.•Themes from PCRCs are complimentary to material covered in resident didactics.

Pharmaceutical compounding is an important component of pharmacy practice despite its low prevalence. Several therapeutic needs can be met by a compounded medicine such as dosing adjusted for pediatric patients, special drug combinations, medicines for patients allergic to a given excipient, and medicines for orphan drugs not provided by the pharmaceutical industry. Examples of such applications are provided in this review. Adherence to medication is a critical public health issue as nonadherence to pharmacotherapy has been associated with adverse outcomes and higher costs of patient care. Adherence to therapy represents a key factor in the reduction in morbidity and mortality and optimization of the use of financial resources. The role of pharmaceutical compounding in promoting medication adherence is underexploited. The customization might represent a positive reinforcement of the initiation of the treatment, while implementation and persistence might also be favored in a pharmacy setting. However, studies addressing the influence of compounding in adherence promotion are lacking in the literature. The results of such studies could support health policies including proper regulatory framework, pharmacist training, and information to health care practitioners.

Patient engagement in research is gaining traction as an international standard, and often requirement, of many health research funding agencies. Drivers of this increase include patient interest, increased attention to and recognition of the value of patients’ voices in research, and more patients leading or partnering in the conduct research. Patient engagement includes collaborating and providing insights into research question and study design, and may extend to the publication process. When patients contribute to publications, they can bring unique perspectives that may enhance the impact, reach, and utility of the research in real-world contexts. Currently, there is limited systematic guidance to support patient partners as they navigate this complex publication process. As a result, it can be difficult for patient partners to understand when and how they should be included as authors, how to collaborate in the writing process, and how to complete mandatory tasks during the submission process. In this paper, we review barriers and facilitators within existing publication practices and offer recommendations to ensure that the scientific publication process is more transparent and accessible for patient partners.

Protocol design complexity, and associated study volunteer burden, negatively impact patient recruitment and retention as well as overall research and development productivity. Complex protocols reduce the willingness of potential clinical trial participants to enroll and reduce retention rates. There have been few systematic assessments of protocol design characteristics to determine the burden placed on study volunteers, although such an assessment would offer a compelling opportunity to optimize trial designs and improve recruitment and retention performance. To be useful, an assessment would need to be patient-centric, and focused on the factors that influence participation throughout the clinical trial. Such an assessment would also need to accommodate the unique cost-value trade-off compared with current treatment patterns that each participant makes when choosing to participate and remain in a clinical trial. This article proposes a new methodology to quantify patient burden: the clinical trial patient friction coefficient (PFC). A case example is provided to illustrate the utility of the PFC. A number of applications for the PFC are envisioned: standardizing patient burden assessment to evaluate clinical trial design feasibility, shedding light on the impact of patient burden on clinical trial economics and performance, and conducting sensitivity analyses to identify factors that most reduce patient burden and improve the performance and efficiency of clinical trials.