53 papers
Improving health systems means finding smarter ways to deliver care, reduce errors, and ensure patients receive the best possible treatment. This field explores how hospitals and clinics can function more effectively, focusing on the practical changes that lead to better outcomes for everyone involved. It is less about discovering new drugs and more about refining the everyday processes that keep our healthcare networks running smoothly.
At Gist.Science, we track every new preprint in this category from medRxiv to bring you the latest research immediately. Our team processes these papers to provide both detailed technical summaries for experts and clear, plain-language explanations for anyone interested in how healthcare can improve. We believe that understanding these systemic changes is vital for building a more resilient future.
Below are the latest studies and insights from the health systems and quality improvement community, sorted by their recent submission dates.
This cross-sectional study conducted in northwestern Tanzania reveals that 83.2% of sexually active youth utilize family planning methods, with gender and peer influence identified as significant factors associated with their usage.
This qualitative study of family medicine registrars at Kamuzu University of Health Sciences reveals that while they demonstrate strong clinical leadership and interpersonal skills, their effectiveness is hindered by unclear role boundaries, insufficient mentorship, and limited involvement in decision-making, highlighting the need for targeted improvements in their leadership training.
This study validates the Index of Myalgic Encephalomyelitis Symptoms (TIMES) as a valid, reliable, and sensitive assessment tool for measuring symptom severity in ME/CFS patients, demonstrating strong criterion-related and discriminant validity, excellent test-retest reliability, and a defined minimal detectable difference.
Through a two-round modified Delphi study involving 21 international healthcare experts, this research establishes a consensus-based framework defining the purposes, key functions, and feasibility of a global Patient Safety Learning System, while generating novel criteria for identifying incidents of international concern to guide future implementation by organizations like the WHO.
This paper demonstrates that algorithmic recourse in healthcare and administrative systems is hindered by synergistic, multi-stage barriers across data and institutional layers, where single interventions yield negligible improvements and effective reform requires coordinated, multi-layer strategies.
This paper warns that widely used clinical prediction models based on two popular Kaggle datasets lack verifiable data provenance and appear to be fabricated, leading to potentially unreliable research and clinical applications, and calls for mandatory data provenance reporting to safeguard patient care.
This retrospective cohort study of 393 patients in the Brazilian Amazon reveals that the high mortality rate (48.5%) from acute lymphoblastic leukemia is primarily driven by age-related vulnerability and structural health system barriers, such as the centralization of specialized services, rather than baseline sociodemographic characteristics.
A cross-sectional assessment of 332 public health facilities in India reveals a critical mismatch where diagnostic availability for most Neglected Tropical Diseases remains low and poorly aligned with local disease burden, particularly at peripheral primary care levels, despite high programmatic prioritization for malaria.
This study presents a topology-aware, graph-augmented retrieval framework that enhances digital evidence-based medical synthesis by integrating mechanistic axis decomposition and graph auditing to improve the precision, traceability, and causal coherence of biomedical narrative generation beyond traditional similarity-driven methods.
This study analyzes SDOH screening data from 1.8 million patients to demonstrate methods for identifying redundant questions and demographic biases, offering strategies to streamline clinical workflows and ensure more equitable data collection.