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The management of pediatric pain typically consists of individualized treatment plans and interventions that have not been systematically evaluated. There is an emerging need to create systems that can support the translation of clinical discoveries, facilitate the assessment of current interventions, and improve the collection of patient-centered data beyond routine clinical information. We present the development of the pediatric pain data repository, a custom-built system developed at Boston Children's Hospital [...]

Effective implementation of artificial intelligence in behavioral healthcare delivery depends on overcoming challenges that are pronounced in this domain. Self and social stigma contribute to under-reported symptoms, and under-coding worsens ascertainment. Health disparities contribute to algorithmic bias. Lack of reliable biological and clinical markers hinders model development, and model explainability challenges impede trust among users. In this perspective, we describe these challenges and discuss design and implementation recommendations to overcome [...]

Public engagement in health and biomedical research is being influenced by the paradigm of citizen science. However, conventional health and biomedical research relies on sophisticated research data management tools and methods. Considering these, what contribution can citizen science make in this field of research? How can it follow research protocols and produce reliable results?

Comorbidity network analysis (CNA) is a graph-theoretic approach to systems medicine based on associations revealed from disease co-occurrence data. Researchers have used CNA to explore epidemiological patterns, differentiate populations, characterize disorders, and more; but these techniques have not been comprehensively evaluated. Our objectives were to assess the stability of common CNA techniques.

The growing prevalence of chronic conditions requiring changes in lifestyle and at-home self-management has increased interest in and need for supplementing clinic visits with data generated by patients outside the clinic. Patient-generated health data (PGHD) support the ability to diagnose and manage chronic conditions, to improve health outcomes, and have the potential to facilitate more "connected health" between patients and their care teams; however, health systems have been slow to [...]

Institutions cite managing the modification in infrastructure, technical support, and process change as substantial barriers to a successful electronic health record (EHR) implementation. In an effort to organize and centralize the complex scheduling, task completion and communication needs of a "big-bang" EHR go-live, we developed a unified communication system with the goal of improving implementation process efficiency. Our goal was to create a platform that would work across the medical [...]

To adapt and evaluate a deep learning language model for answering why-questions based on patient-specific clinical text.

There has been substantial growth in eHealth over the past decade, driven by expectations of improved healthcare system performance. Despite substantial eHealth investment, little is known about the monitoring and evaluation strategies for gauging progress in eHealth availability and use. This scoping review aims to map the existing literature and depict the predominant approaches and methodological recommendations to national and regional monitoring and evaluation of eHealth availability and use, to [...]

Opioid-based analgesia is routinely used in clinical practice for the management of pain and alleviation of suffering at the end of life. It is well-known that opioid-based medications can be highly addictive, promoting not only abuse but also life-threatening overdoses. The scope of opioid-related adverse events (AEs) beyond these well-known effects remains poorly described. This exploratory analysis investigates potential AEs from drug-drug interactions between opioid and nonopioid medications (ODIs).