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Digital Health Technology Infrastructure Challenges to Support Health Equity in the United States: Scoping Review

Background: Even though Digital Health Technology (DHT) is widely utilized in the United States (U.S.) at both hospital provider and individual levels, it is beset with several challenges that have contributed to inequities in the health service delivery. Previous studies have shown that health inequities observed may be amplified many by DHT requirements. Objective: The objectives of this scoping review are aimed at synthesizing information on DHT inequities by exploring evidence that describes DHT infrastructure needs focused on promoting health equity in the U.S. and identifying key challenges at both the individual/patient level and at the health service provider's level. Methods: We adapted Arksey and O'Malley's scoping review guidelines in our review. We searched PubMed, Web of Science, CINAHL, and PsycINFO were searched. We also conducted supplementary searches on Google Scholar. The inclusion criteria were peer-reviewed publications that broadly conceptualize or analyze DHT infrastructure from a health equity perspective and the challenges of DHT requirements between 2020 and 2024. Following a full-text screening using eligibility criteria such as studies were included if they examined DHT infrastructure in the U.S. from a health equity perspective, discussed health disparities resulting from DHT interventions, or investigated the variables influencing health inequities connected to DHT. Two researchers evaluated each citation’s individually at the title and abstract levels. Thematic approach and qualitative analysis determined this scoping review’s outcome. Results: Of the 628 research articles from the search, 27 were included in the analysis based on the inclusion criteria. In this review, we discussed factors such as elderly population, education, race, ethnicity, and socioeconomic status leading to health inequities in DHT. Patients and Service providers challenges that exist in health inequities related to DHT. The most common challenges for service providers were infrastructure and technical issues such as inadequate integration with existing workflows, user-unfriendly health information exchange (HIE) interfaces, and lack of skilled staff, while for individuals or patients, this included limited broadband internet access, cultural or linguistic appropriateness, and access to digital tools. Conclusions: The study identified that in the U.S., DHT is an essential part of the delivery of health services, yet it is saddled with key challenges leading to health inequities. Finding pragmatic solutions to these challenges can improve health equity in DHT.

Prompt Engineering in Clinical Practice: Tutorial for Clinicians

Large language models (LLMs), such as OpenAI’s GPT series and Google’s PaLM, are transforming healthcare by improving clinical decision-making, enhancing patient communication, and simplifying administrative tasks. However, their performance relies heavily on prompt design, where small changes in wording or structure can greatly impact output quality. This poses a challenge for clinicians who are not experts in natural language processing (NLP). This tutorial combines prompt engineering techniques tailored for clinical use, covering methods like zero-shot, few-shot, chain-of-thought, and meta-prompting. We examine four critical dimensions (accuracy, bias mitigation, privacy protection, and workflow integration) through clinical case studies grounded in real-world practice. We provide actionable guidance on defining objectives, applying core principles, iteratively refining prompts, and integrating them into interoperable electronic health record (EHR) systems. This framework helps clinicians leverage LLMs to improve decision-making, streamline documentation, and enhance patient communication while maintaining ethical standards and ensuring patient safety.
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  • Hugging Face Releases FinePDFs: a 3-Trillion-Token Dataset Built from PDFs Robert Krzaczyński
    Hugging Face has unveiled FinePDFs, the largest publicly available corpus built entirely from PDFs. The dataset spans 475 million documents in 1,733 languages, totaling roughly 3 trillion tokens. At 3.65 terabytes in size, FinePDFs introduces a new dimension to open training datasets by tapping into a resource long considered too complex and expensive to process. By Robert Krzaczyński
     

Hugging Face Releases FinePDFs: a 3-Trillion-Token Dataset Built from PDFs

15 September 2025 at 16:55

Hugging Face has unveiled FinePDFs, the largest publicly available corpus built entirely from PDFs. The dataset spans 475 million documents in 1,733 languages, totaling roughly 3 trillion tokens. At 3.65 terabytes in size, FinePDFs introduces a new dimension to open training datasets by tapping into a resource long considered too complex and expensive to process.

By Robert Krzaczyński

Do startups still need Silicon Valley? Leaders at SignalFire, Lago, and Revolution debate at TechCrunch Disrupt 2025

24 September 2025 at 01:15
Does Silicon Valley still give founders an edge? At TechCrunch Disrupt 2025, Anh-Tho Chuong (Lago), David Hall (Revolution), and Tawni Nazario-Cranz (SignalFire) debate whether location still drives startup success.

Primary care detection of Alzheimer’s disease using a self-administered digital cognitive test and blood biomarkers

Nature Medicine, Published online: 15 September 2025; doi:10.1038/s41591-025-03965-4

A brief, self-administered digital cognitive test, in combination with a blood test, accurately detects clinical Alzheimer’s disease in primary care.
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