Health Information Management papers
Pofolia’s corpus holds 33 papers from Health Information Management (2024–2026), each with a short summary. Below, the 20 most-cited, then the most recently added.
At a glance
- Most cited: rdkit/rdkit: 2025_09_1 (Q3 2025) Release (2025, 457 citations).
- The 20 papers listed have 1,008 citations between them.
- 15 of the 18 with a known journal quartile appeared in a Q1 journal.
- 9 have a free full text (open access).
- Most frequent journals: BMC Health Services Research, Algorithms, Artificial Intelligence Review.
- Published between 2024 and 2026.
Most cited
Ranked by citation count. Because citations accumulate over time, this list naturally leans towards work published a few years ago; for where the field is now, see “recently added”. How to read the signals
rdkit/rdkit: 2025_09_1 (Q3 2025) Release
Open MIND · 2025 · 457 citations
The RDKit cheminformatics toolkit's 2025.09.1 release introduces new parsers for SCSR and CDXML/CDX file formats, alongside significant improvements to shape-based alignment and C++20 compatibility.
Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms
Journal Of Big Data · 2024 · Q1 · SJR 1.00 · FWCI 118.37 · 224 citations
Feature reduction techniques significantly improved machine learning model performance for hepatocellular carcinoma (HCC) prediction, with accuracies reaching up to 97.33% for Naive Bayes.
A systematic review of machine learning in heart disease prediction
TURKISH JOURNAL OF BIOLOGY · 2025 · Q2 · FWCI 12.74 · 52 citations · Open access
Machine learning models, particularly ensemble methods on structured data and deep learning on unstructured data (ECG, imaging), show high accuracy in heart disease prediction, but a significant gap hinders clinical translation due to lack of external validation, reliance on limited datasets, and model interpretability issues.
Leveraging XGBoost and explainable AI for accurate prediction of type 2 diabetes
BMC Public Health · 2025 · Q1 · SJR 1.00 · FWCI 65.80 · 46 citations · Open access
XGBoost achieved 96.07% accuracy and 99.29% AUC for type 2 diabetes prediction in an Iranian cohort, with SHAP identifying fasting blood sugar, fatty liver, and energy drink consumption as key predictors.
Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review
JMIR AI · 2025 · Q1 · SJR 1.00 · FWCI 63.09 · 44 citations
Six real-world studies show digital scribes using ambient listening and generative AI decrease self-reported clinician documentation time and improve engagement, though note length increases and physician burnout/productivity remain unchanged.
Changes in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence–Powered Scribes
JAMA · 2026 · FWCI 899.62 · 44 citations
Adoption of AI-powered scribes was associated with 13.4 fewer minutes of EHR time and 16.0 fewer minutes of documentation time per 8-hour day, and a 0.49 increase in weekly visits among 8,581 clinicians across 5 US academic health care institutions.
Fostering trust and interpretability: integrating explainable AI (XAI) with machine learning for enhanced disease prediction and decision transparency
Diagnostic Pathology · 2025 · Q1 · FWCI 60.08 · 42 citations · Open access
A novel hybrid framework integrating Machine Learning (ML) with Explainable AI (XAI) achieves 99.2% accuracy in predicting five diseases (Diabetes, Anaemia, Thalassemia, Heart Disease, Thrombocytopenia) while providing feature-based explanations for each prediction.
A dynamic weighted ensemble learning framework for cardiovascular risk prediction in type 2 diabetes: a comparative study with SHAP-based interpretability
Scientific Reports · 2025 · Q1 · FWCI 49.94 · 35 citations · Open access
A novel dynamic weighted ensemble model integrating Traditional Chinese Medicine (TCM) tongue diagnosis and modern biomarkers achieved 95.68% accuracy in predicting cardiovascular risk in Type 2 diabetes patients, outperforming traditional models.
Large Language Model Assistant for Emergency Department Discharge Documentation
JAMA Network Open · 2025 · Q1 · SJR 3.00 · FWCI 45.77 · 32 citations · Open access
An AI assistant fine-tuned on clinical data reduced emergency department (ED) discharge note completion time by over 50% (from a median of 69.5 to 32.0 seconds) while maintaining or improving documentation quality across completeness, correctness, conciseness, and clinical utility metrics.
XAI-HD: an explainable artificial intelligence framework for heart disease detection
Artificial Intelligence Review · 2025 · Q1 · SJR 3.00 · FWCI 46.12 · 32 citations · Open access
A new hybrid framework, XAI-HD, integrates machine learning, deep learning, and explainable AI to detect heart disease, reducing classification error rates by 20-25% compared to traditional models and enhancing interpretability.
Ambient artificial intelligence scribe implementation in inpatient setting
Journal of Hospital Medicine · 2026 · Q1 · Open access
Ambient AI scribes were utilized for only 3% of inpatient notes, with no change in physician time spent on documentation, indicating a need for workflow-specific development to increase adoption.
Healthcare professionals’ perceptions of a maternal and newborn electronic health record and the role of design in their experiences: a qualitative study
International Journal of Medical Informatics · 2026 · Q1 · SJR 1.00 · Open access
Maternal and newborn EHR design elements like templates and auto-population positively impacted healthcare professionals' (HCPs) performance and effort expectancy, while pop-up alerts and slow log-ins hindered them.
Implementation challenges and unintended financial consequences of e-prescribing in an integrated payer–provider health system: a qualitative study from Tehran, Iran
BMC Health Services Research · 2026 · Q1 · SJR 1.00
E-prescribing implementation in Iran's integrated payer-provider system led to workflow friction, fragmented care, and unexpected out-of-pocket costs for patients due to unreliable digital infrastructure and limited interoperability.
Interpretable Heart Disease Prediction: Optimizing Machine Learning Models via Metaheuristic Ivy Algorithm
Algorithms · 2026 · Q2
The Ivy Algorithm (IVYA) optimized machine learning models for heart disease prediction, with IVYA-LightGBM achieving 0.945 AUC and 0.907 accuracy, outperforming other optimizers and standard models on two datasets.
Electronic Medical Record System utilization and associated factors among health professionals in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia
BMC Health Services Research · 2026 · Q1 · SJR 1.00
EMRS utilization was high (88.0%) among 410 health professionals at Tikur Anbessa Specialized Hospital, with male sex, over two years of EMRS experience, and favorable attitudes being key drivers.
Barriers and Enablers Influencing Dietetic Practice in the Management of Polyendocrine Metabolic Ovarian Syndrome
Nutrients · 2026 · Q1 · SJR 1.00
Australian dietitians (n=86) report moderate knowledge (38.4%) and confidence (36.5%) in managing Polyendocrine Metabolic Ovarian Syndrome (PMOS), with key barriers including weight management support, interprofessional collaboration, and misinformation.
“Managing the Binder”: A Systematic Review of the Burdens Experienced by Patients and Carers in Managing Personal Health Information Across Fragmented Healthcare Systems
Healthcare · 2026 · Q1
A systematic review of 11 studies found that patients and carers experience significant burdens managing personal health information (PHI) across fragmented healthcare systems, with paper-based methods remaining common due to their visibility and portability.
Delayed EHR availability of vital signs is associated with nursing shift structure
npj Health Systems · 2026 · Q2 · Open access
Vital signs from 11.4 million measurements were delayed in EHRs, with median lags of 12-25 minutes, and one-third of abnormal values delayed over an hour, peaking around nursing shift changes.
Evaluation frameworks for digital health interventions in long-term care homes: a scoping review
BMC Health Services Research · 2026 · Q1 · SJR 1.00
A scoping review of 48 studies found that evaluation frameworks for digital health interventions (DHIs) in long-term care (LTC) homes are fragmented, with only 15 studies using formal frameworks, often relying on ad-hoc approaches.
Automated Case Logging for Surgical Residency Training Using the Electronic Health Record: A Pilot Study
Neurosurgery · 2026 · Q1 · SJR 1.00
An automated system extracted 94.8% accurate neurosurgery case logs from EHRs, reducing logging time by 66% (68.4s/case vs. 199.9s/case) and saving residents 58 hours over 5 years.
Recently added
An enhanced hierarchical Mamba-based cardiac segmentation network for cardiovascular analysis and disease diagnosis using multiple MRI datasets
Scientific Reports · 2026 · Q1
A new Mamba-based network, H-MayoMamba Net, achieves enhanced accuracy in segmenting critical cardiac structures (LV, RV, myocardium) from MRI, addressing limitations of current deep learning methods.
Running to Stand Still: EHR Efficiency and Workload Across Emergency Medicine Residency
AEM Education and Training · 2026 · Q2
Emergency medicine residents improve EHR efficiency by 51% from PGY-1 to PGY-4, but rising patient volume means total EHR time per shift increases.
Strategic entrepreneurship and SME growth in emerging economies: a multidimensional PLS-SEM study from Tamil Nadu
Cogent Business & Management · 2026 · Q2
Proactiveness and Risk Taking are the strongest predictors of SME growth in Tamil Nadu, India, followed by Innovation and Strategic Resource Management, according to a PLS-SEM study of 400 SMEs.
Optimizing population health outcomes: How IT manages chronic diseases
Health Systems · 2026 · Q2
Health Information Technology (HIT) yields the greatest value for chronic diseases with high avoidable costs, actionable biomarker data, and established clinical understanding (A-B-C framework), as demonstrated by greater savings for diabetes, breast cancer, and COPD in Vermont.
A health informatics in-depth evaluation study of the rural, across-distance implementation of a health information system: Implementing in the wild
Health Information Management Journal · 2026 · Q1 · SJR 1.00
Health Information Managers (HIMs) successfully implemented a Patient Administration System (PAS) across a vast rural Australian health district by collaboratively reordering technology, systems, policies, procedures, and workflows, despite challenges with Go-Live timing, design consultation, and system functionalities.
M3: Conversational LLMs simplify secure clinical data access, understanding, and analysis
PLOS Digital Health · 2026 · Q1 · SJR 1.00
M3, a new system, allows researchers to query the complex MIMIC-IV clinical database using natural language, achieving 93-94% accuracy with LLMs.
Deterministic and stochastic interventions in reducing drug–drug interactions in inappropriate prescribing: A systematic review
PLoS ONE · 2026 · Q1
A systematic review of 10 studies found that while newer stochastic and generative models show strong internal performance for predicting drug-drug interactions (DDIs), they suffer from high risk of bias due to limited external validation and unclear handling of overfitting, failing to demonstrate improved clinical safety over older deterministic systems.
Data capture, collection, management, and storage systems for clinical research: A scoping review protocol
PLoS ONE · 2026 · Q1
This protocol outlines a scoping review to map and synthesize literature on electronic systems for clinical research data capture, collection, management, and storage from 2000-2025.
Journals in this field
The journals that publish most of this field’s papers. Quartile (Q1–Q4), SJR and h-index are from SCImago Journal Rank; “in this field” is how many of the journal’s pooled papers belong here. What is a Q1 journal? · What is the h-index?
| Journal | Quartile | SJR | h-index | In this field | Summaries |
|---|---|---|---|---|---|
| BMC Health Services Research | Q1 | 1.00 | 172 | 3 | 16 |
| PLOS ONE | Q1 | — | 500 | 3 | 87 |
| Scientific Reports | Q1 | — | 382 | 2 | 170 |
| npj Digital Medicine | Q1 | 4.00 | 130 | 1 | 11 |
| Artificial Intelligence Review | Q1 | 3.00 | 169 | 1 | 3 |
| JAMA Network Open | Q1 | 3.00 | 178 | 1 | 20 |
| Neurosurgery | Q1 | 1.00 | 236 | 1 | 5 |
| BMC Public Health | Q1 | 1.00 | 225 | 1 | 24 |
Every journal in Health Information Management (Q1–Q4) →
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