Structured and unstructured data play crucial roles in providing a comprehensive view of a patient’s medical history. Structured data in EHRs refers to information that is organized and formatted in a specific way, typically using predefined categories or fields. This data is highly organized and follows a consistent format, which makes it easy to search, retrieve, and analyze.
Examples of structured data in EHRs include:
- patient demographics (name, age, gender, contact information),
- vital signs (blood pressure, heart rate, temperature),
- lab results (numerical values of various tests),
- medication lists (name, dosage, frequency),
- allergies and adverse reactions,
- diagnosis codes (ICD-10 codes),
- procedures performed (CPT codes)
Unstructured data, on the other hand, is information that does not conform to a specific format or predefined structure. It is often in the form of free-text narratives, clinical notes, scanned images, handwritten notes, and other types of content that don’t fit neatly into structured fields. Unstructured data is more challenging to process and analyze using traditional methods due to its lack of consistent structure.
Examples of unstructured data in EHRs include:
- physician’s clinical notes and observations,
- radiology and pathology reports,
- consultation reports from specialists,
- patient history narratives,
- progress notes,
- handwritten notes or annotations.
