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Challenges and Recommendations for Electronic Health Records Data Extraction and Preparation for Dynamic Prediction Modeling in Hospitalized Patients: Practical Guide and Tutorial
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients
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Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care
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Assessment of Prediction Tasks and Time Window Selection in Temporal Modeling of Electronic Health Record Data: a Systematic Review
inferredcites →https://doi.org/10.1016/j.is.2022.102130openalex-snapshot
A data preparation framework for cleaning electronic health records and assessing cleaning outcomes for secondary analysis
inferredcites →https://doi.org/10.1016/j.jclinepi.2019.11.001openalex-snapshot
Changing predictor measurement procedures affected the performance of prediction models in clinical examples
inferredcites →https://doi.org/10.1016/j.jclinepi.2024.111342openalex-snapshot
Table 0; documenting the steps to go from clinical database to research dataset
inferredcites →https://doi.org/10.1016/j.jclinepi.2024.111373openalex-snapshot
Improved reporting of selection processes in clinical database research. Response to de Kok et al.
inferredcites →https://doi.org/10.1016/s2589-7500(22)00154-6openalex-snapshot
Leveraging electronic health records for data science: common pitfalls and how to avoid them
inferredcites →https://doi.org/10.1017/cts.2020.513openalex-snapshot
Lessons and tips for designing a machine learning study using EHR data
inferredcites →https://doi.org/10.1038/s41586-019-1390-1openalex-snapshot
A clinically applicable approach to continuous prediction of future acute kidney injury
inferredcites →https://doi.org/10.1038/s41591-022-01993-yopenalex-snapshot
The AI life cycle: a holistic approach to creating ethical AI for health decisions
inferredcites →https://doi.org/10.1038/s41596-021-00513-5openalex-snapshot
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
inferredcites →https://doi.org/10.1038/s41597-023-01945-2openalex-snapshot
Author Correction: MIMIC-IV, a freely accessible electronic health record dataset
inferredcites →https://doi.org/10.1038/s41597-023-02256-2openalex-snapshot
A guide to sharing open healthcare data under the General Data Protection Regulation
inferredcites →https://doi.org/10.1038/s41746-024-01196-4openalex-snapshot
The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review
inferredcites →https://doi.org/10.1038/sdata.2016.35openalex-snapshot
MIMIC-III, a freely accessible critical care database
inferredcites →https://doi.org/10.1038/sdata.2018.178openalex-snapshot
The eICU Collaborative Research Database, a freely available multi-center database for critical care research
inferredcites →https://doi.org/10.1055/s-0038-1634831openalex-snapshot
Use and Abuse of Computer-Stored Medical Records
inferredcites →https://doi.org/10.1056/nejmsr1809937openalex-snapshot
The “All of Us” Research Program
inferredcites →https://doi.org/10.1093/ije/dyv291openalex-snapshot
Data Resource Profile: the Dutch National Intensive Care Evaluation (NICE) Registry of Admissions to Adult Intensive Care Units
inferredcites →https://doi.org/10.1093/jamia/ocaa088openalex-snapshot
MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care
inferredcites →https://doi.org/10.1093/jamia/ocaa139openalex-snapshot
Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data
inferredcites →https://doi.org/10.1093/jamia/ocab132openalex-snapshot
Increasing trust in real-world evidence through evaluation of observational data quality
inferredcites →https://doi.org/10.1093/jamia/ocad120openalex-snapshot
Electronic health record data quality assessment and tools: a systematic review
inferredcites →https://doi.org/10.1097/ccm.0000000000004916openalex-snapshot
Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example*
inferredcites →https://doi.org/10.1109/bigdata.2015.7364060openalex-snapshot
Evaluation of data quality of multisite electronic health record data for secondary analysis
inferredcites →https://doi.org/10.1109/tbme.2019.2909027openalex-snapshot
Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data
inferredcites →https://doi.org/10.1111/j.1475-6773.2005.00444.xopenalex-snapshot
Measuring Diagnoses: ICD Code Accuracy
inferredcites →https://doi.org/10.1111/j.1541-0420.2007.00886.xopenalex-snapshot
Modeling Longitudinal Biomarker Data from Multiple Assays that Have Different Known Detection Limits
inferredcites →https://doi.org/10.1136/amiajnl-2011-000681openalex-snapshot
Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research
inferredcites →https://doi.org/10.1177/1740774520931211openalex-snapshot
Five analytic challenges in working with electronic health records data to support clinical trials with some solutions
inferredcites →https://doi.org/10.1186/s12911-021-01669-6openalex-snapshot
Assessing the suitability of general practice electronic health records for clinical prediction model development: a data quality assessment
inferredcites →https://doi.org/10.21203/rs.3.rs-4384973/v1openalex-snapshot
A comparison of regression models for static and dynamic prediction of a prognostic outcome during admission in electronic health care records
inferredcites →https://doi.org/10.21203/rs.3.rs-4527690/v1openalex-snapshot
Comparison of static and dynamic random forests models for EHR data in the presence of competing risks: predicting central line-associated bloodstream infection
inferredcites →https://doi.org/10.2196/38557openalex-snapshot
Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities
inferredcites →https://doi.org/10.3389/fdgth.2022.940330openalex-snapshot
Challenges and recommendations for high quality research using electronic health records
inferredcites →https://doi.org/10.3389/fepid.2022.871630openalex-snapshot
Developing Clinical Prediction Models Using Primary Care Electronic Health Record Data: The Impact of Data Preparation Choices on Model Performance
inferredcites →https://doi.org/10.3390/informatics7030025openalex-snapshot
Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review
inferredcites →https://doi.org/10.4338/aci-2016-03-soa-0035openalex-snapshot
Preprocessing structured clinical data for predictive modeling and decision support
inferredcites →https://doi.org/10.4338/aci-2017-03-cr-0046openalex-snapshot
Barriers to Achieving Economies of Scale in Analysis of EHR Data
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1055/a-2943-7750openalex-snapshot
Beyond Accuracy: Why Replacing Traditional Scores with AI in Thrombosis Care Creates New Ethical and Regulatory Obligations
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Predicting radiology no-shows with machine learning: Methodological pitfalls and practical considerations
inferred← citeshttps://doi.org/10.1186/s41512-025-00199-3openalex-snapshot
A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models
inferred← citeshttps://doi.org/10.1200/cci-25-00389openalex-snapshot
Machine Learning Risk Stratification Approach Using Patient-Reported Outcomes for Forecasting Unplanned Health Care Use and Symptom Burden in Cancer Survivors
inferred← citeshttps://doi.org/10.2196/preprints.108851openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fdgth.2026.1747227openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/ph19081292openalex-snapshot
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From Algorithm Development to Clinical Implementation: A Systematic Review of Artificial Intelligence in Cardiovascular Medicine
inferred← citeshttps://doi.org/10.59395/ijadis.v7i2.1485openalex-snapshot
An Integrated Data Cleaning and Anomaly Detection Pipeline for Improving Clinical Data Quality in Primary Healthcare
inferred← citeshttps://doi.org/10.64898/2025.12.17.25342509openalex-snapshot
From free text to SOFA score: automated reconstruction of sepsis severity from unstructured clinical notes
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