2.7M+ Longitudinal EHR Records Scanned PDF Dataset
Patient Health Records & Digital Health
Tags and Keywords
£560,800
About
2.7M+ Longitudinal EHR Records Scanned PDF Dataset
Description
The 2.7M+ Longitudinal EHR Records Scanned PDF Dataset is a collection of 2.7M+ longitudinal Electronic Health Record (EHR) documents in scanned PDF format of 28K+ anonymized patients, designed to support healthcare AI, machine learning, medical document analysis, and healthcare analytics. The dataset provides longitudinal patient record documentation that can help researchers and AI developers study clinical information across healthcare encounters and develop solutions for medical document understanding, OCR, clinical NLP, information extraction, and EHR analysis.
By connecting healthcare information across multiple time points, the dataset can support longitudinal patient analysis, clinical data mining, predictive modeling, healthcare AI, clinical NLP, disease progression research, and healthcare analytics. It is intended for data scientists, AI developers, healthcare technology organizations, and academic institutions working with structured clinical and patient-level healthcare data.
Note: The listed price applies to the specified initial batch of 500,000 records. Pricing for larger batches or the complete dataset library varies depending on several factors, including the number of EHR records, data volume, number and type of documents, metadata availability, level of clinical detail, scanned PDF quality and page count, file format, licensing terms, and customization needs. The final price will be determined based on the specific dataset requirements and selected package.
Data Product Features
| Feature | Description |
|---|---|
| Scanned PDF Documents | EHR records provided as scanned PDF documents for document processing and analysis. |
| Patient ID | De-identified patient identifier. |
| Medical History | Historical clinical information documented within the EHR records. |
| Diagnosis | Diagnoses and clinical conditions documented in the records, where available. |
| Medical Notes | Clinical notes and other textual information contained in the EHR documentation. |
| Medications | Medication-related information documented within the records, where available. |
| Investigations | Laboratory tests, diagnostic investigations, or related clinical information where available. |
| Document Structure | Scanned clinical documents that can be used for document understanding, OCR, and healthcare information extraction. |
Distribution
- Data Volume: 2.7M+ Longitudinal EHR Records
- Format: Scanned PDF
- Data Type: Healthcare / Electronic Health Records (EHR)
- Structure: Individual scanned PDF documents containing longitudinal clinical record information.
- Record Type: Longitudinal patient healthcare records.
- Dataset Size: Dataset size may vary depending on the selected dataset package, available records, document pages, metadata, and specific requirements.
Usage
This data product is ideal for a variety of applications:
- Healthcare AI & Machine Learning: Training and evaluating AI/ML systems for healthcare document understanding.
- OCR & Document Processing: Developing and evaluating OCR systems for scanned medical documents.
- Clinical NLP: Extracting diagnoses, medications, procedures, and other clinical information from medical documents.
- EHR Information Extraction: Converting unstructured or scanned EHR documentation into structured healthcare data.
- Medical Document Understanding: Building models capable of interpreting and classifying clinical documents.
- Clinical Research: Supporting research involving longitudinal patient records and healthcare documentation.
- Healthcare Analytics: Analyzing clinical documentation and healthcare information across patient encounters.
- AI Model Evaluation: Benchmarking healthcare AI, document intelligence, and medical NLP models.
Coverage
- Geographic Coverage: USA
- Clinical Scope: Longitudinal healthcare documentation may include patient history, diagnoses, medications, investigations, clinical notes, and other EHR information where available.
License
CC BY 4.0 (Creative Commons Attribution 4.0 International)
AI Training Rights
InfoBay.AI ensures that all datasets are sourced, curated, and managed with proper ownership verification, licensing documentation, and data provenance records. We hold the necessary rights to license and sublicense the datasets we provide through formal agreements with our data vendors, which grant us the required permissions for commercial licensing and AI training use cases. To ensure transparency and compliance, we maintain relevant documentation and have previously shared redacted agreements for selected datasets as evidence of our data rights and licensing authority.
Data Dictionary
| Column Name | Data Type | Description | Possible Values/Notes |
|---|---|---|---|
patient_id | STRING | Identifier associated with the patient record, where available. | De-identified patient identifier |
document_date | DATE | Date associated with the EHR document, where available. | Dataset-specific |
visit_date | DATE | Date of the healthcare encounter, where available. | Dataset-specific |
document_type | STRING | Type or category of the scanned EHR document. | Dataset-specific |
medical_history | TEXT | Historical medical information contained in the document. | Free-text clinical content |
diagnosis | TEXT | Diagnoses or clinical conditions documented in the record. | Free-text clinical content |
medical_note | TEXT | Clinical notes and other narrative medical information. | Scanned/document text |
medication | TEXT | Medication information documented in the record. | Drug/medication names where available |
investigation_name | TEXT | Investigation, laboratory test, or diagnostic test information. | Dataset-specific |
age | INTEGER | Patient age, where available. | Dataset-specific |
gender | STRING | Patient gender/sex information, where available. | Dataset-specific |
file_format | STRING | Format of the source document. | |
page_count | INTEGER | Number of pages in the scanned PDF, where available. | Non-negative integer |
Considerations
This dataset is provided for research and educational purposes only. It contains only sample data.
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£560,800
Download Dataset in DOCUMENTS Format
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