📄 Category

health informatics

225 papers

Health informatics sits at the vibrant intersection of medicine, data science, and technology, transforming how we store, analyze, and utilize health information. This rapidly evolving field empowers clinicians and researchers to uncover patterns in patient data, improve diagnostic accuracy, and personalize treatment plans without getting lost in complex databases. By turning raw medical records into actionable insights, these innovations are reshaping the future of healthcare delivery and population health management.

At Gist.Science, we bridge the gap between cutting-edge research and public understanding by curating the latest preprints from medRxiv specifically within this domain. Our team processes every new submission in this category, providing both accessible plain-language explanations and detailed technical summaries to ensure the science is clear for everyone, from policymakers to curious readers. Below are the latest papers in health informatics, freshly distilled and ready for you to explore.

📄 health informatics

Is Lower Limb Movement Enough? Quantifying Overground Arm Swing Kinematics and Coordination to Assess Ageing Decline in Older Adults

This study validates a wearable sensor algorithm for quantifying overground arm swing kinematics and coordination in older adults, revealing that arm-leg coordination is a distinct and sensitive dimension of gait stability that declines with frailty and neurological impairment, thereby offering a scalable method to detect early mobility instability beyond traditional walking speed metrics.

Tan, K. Z., Pai, S., Kim, Y. K., Frautschi, A., Gwerder, M., Tan, K. Y., Koh, V. J. W., Ravi, D., Taylor, W. R., Malhotr (…)2026-08-05
📄 health informatics

Digital Health Adoption, eHealth Literacy, and Trust in AI Among Generation Z University Students in Sri Lanka: An Empirical Study

This study reveals that while Generation Z university students in Sri Lanka possess high eHealth literacy and increasingly rely on AI for health information, their adoption of digital health services remains constrained by significant privacy concerns and a persistent preference for traditional face-to-face consultations.

Athukorala, S. C.2026-07-28✓ Author reviewed ⓘ
📄 health informatics

Development and formative application of the Health Data Readiness Level framework for federated health-data services.

This paper presents the development and formative application of the Health Data Readiness Level (HDRL) framework, a multidimensional tool designed to assess organizational and system readiness for federated health-data services across three UK ecosystems, while cautioning that it remains a planning instrument rather than a validated accreditation standard.

Seymour, D., Halliday, R., Smart, J., Burns, F.2026-07-27
📄 health informatics

Sex and menstrual cycle differences in the mood-activity association should inform cycle-aware digital phenotyping

This study demonstrates that the relationship between physical activity and mood varies significantly by sex and menstrual cycle phase, particularly in women, indicating that digital phenotyping models must account for these biological factors to avoid biased predictions and enable personalized mental health insights.

Delray, K., Zeitler, J. K., Hayes, J. F., Kandola, A., Keay, N., Evans, R. J.2026-07-27
📄 health informatics

Selective prediction as a triage gate for primary-care depression screening: quantifying and mitigating selection bias in CHARLS-2011

This study demonstrates that cumulative selection bias in primary-care depression screening inflates machine-learning metrics while distorting epidemiological associations, and proposes a decoupled selective prediction framework using a four-variable CART rule to safely triage only the most reliable 20% of patients for algorithmic scoring while routing the remainder to human evaluation.

Wang, Z., liu, y.2026-07-22
📄 health informatics

Behavioural readiness, not demographics, predicts wearable adoption and digital medicine integration in a diverse multinational population: a cross-sectional study of 3,004 adults in Qatar

This cross-sectional study of 3,004 adults in Qatar demonstrates that behavioural readiness, particularly daily exercise and willingness to share data, is a stronger predictor of wearable adoption and digital medicine integration than traditional demographic factors like education, highlighting the need to prioritize behavioural engagement over demographic targeting for equitable digital health implementation.

Zaghloul, H., Arabi, B., Al-Ani, M., Abdullah, A., El-Masri, R., AboMuslim, O., Al-Ahdab, F., Rizwan, M. R. M., Tag, Z. (…)2026-07-20
📄 health informatics

Assessing electronic health record potential for adaptive learning in multimorbidity care in Sub-Saharan Africa: a mixed-methods study of Zimbabwe's Impilo system

This mixed-methods study of Zimbabwe's Impilo EHR system reveals that while frontline health workers generate adaptive learning for multimorbidity care through a hybrid of digital and paper-based tools, the lack of socio-technical arrangements to stabilize and institutionalize this learning prevents the system from evolving into a true Learning Health System capable of driving broader care adaptation.

Dhodho, E., Choga, K., Mundoga, F., Chimberengwa, P. T., Gongora, R. T., Webb, K., Chinyanga, T. T., Banda, F., Masiye (…)2026-07-19
📄 health informatics

Chart review and genetic validation of electronic medical record dementia diagnoses in VA: The impact of CMS data

This study evaluates the impact of incorporating CMS data on electronic medical record algorithms for Alzheimer's disease and related dementias within the VA system, finding that while CMS data increases case detection and sensitivity, a broad algorithm without CMS data is optimal for epidemiology, whereas a strict algorithm with CMS data yields the strongest genetic associations for late-onset AD.

Logue, M., Lee, S. O., Gillis, M., Zhang, R., Lee, M., Marra, D., Lopez, F. V., Lynch, J., Panizzon, M. S., Tsuang, D. W (…)2026-07-17