Electronic Health Records and Context

Electronic Health Records (EHRs) use diverse data entry models to support various clinical use cases. Each model has specific terminology and information structure requirements. To ensure the captured information is interoperable and meaningful beyond its initial use, it is essential to design a comprehensive context representation model.

Clinical Data Entry Scenarios and Context Representation Challenges

Free Text Entry

Interpretation

• Accurate interpretation depends on how each sentence is phrased.

• Ignoring any part of the text may lead to misinterpretation.

• Computerized processing may be possible using Natural Language Processing (NLP), sometimes generating structured coded data for reporting and analysis.

Example: Admission Note

Acute 161972006 | central chest pain (finding)|.

No past history of 56265001 | heart disease (disorder)| or 50043002 | Disorder of respiratory system (disorder)|.

Hiatus hernia 84089009 | hiatus hernia| was diagnosed 5 years ago.

Treats 162031009 | indigestion (finding)| with 3402011000001103 | Generic Gaviscon 500mg chewable tablets sugar free (product)|.

Father died of myocardial infarction at age 57. 160274005 | No family history diabetes (situation)|.

Says their cousin has chest problems but is not sure if this is Asthma.

Working diagnosis: possible myocardial infarction but maybe reflux gastritis.

Note after investigation

Diagnosis of myocardial infarction.

Structured Form with Headed Sections

Interpretation

• Interpretation depends on section headings and terms/phrases under each heading.

• Computerized interpretation possible if section meanings and entries are coded.

Example Medical Case Summary

Presenting Symptoms

Acute central chest pain

Past Medical History

No known heart or lung disease
Hiatus hernia

Family History

Father: Myocardial infarction (died at 57)
No family history of diabetes mellitus
Uncertainty about family history of asthma

Differential Diagnosis (on admission)

Myocardial infarction
Reflux esophagitis

Final Diagnosis

Myocardial infarction

Structured Form with Headed Sections and Prompts

Interpretation

• Depends on section heading, question/data label, and values entered.

• Computerized interpretation is possible with appropriate codes and values.

Example

Past Medical History

Heart disease:                   Yes       No  
Lung disease:                    Yes       No  
Gastrointestinal disease:        Yes       No  
Hiatus hernia

Family History

Heart disease:                   Yes       No       Unknown  
Diabetes mellitus:               Yes       No       Unknown  
Chronic lung disease:            Yes       No       Unknown  

Vital Signs

Heart rate:                  85         /min  
Respiratory rate:            24         /min  
Temperature:                 37.2        °C  

Diagnosis (on admission)

Myocardial infarction:       Confirmed   Possible   Excluded  
Reflux esophagitis:          Confirmed   Possible   Excluded  

Diagnosis (after investigation)

Myocardial infarction:       Confirmed   Possible   Excluded  
Reflux esophagitis:          Confirmed   Possible   Excluded  

An EHR may emulate traditional paper-based structures for data entry and display. However, unlike paper records, electronic systems store data in a common logical structure, independent of UI format. This allows for flexible display, reporting, and analysis.

Different entry techniques suit different clinical situations—e.g., a checklist for common history items or a detailed form for a specific diagnosis. Paper records may differ structurally but contain similar information. In contrast, EHRs can map diverse UI formats to a unified structure, as illustrated in the diagram below.

Accurate interpretation of data from various input methods requires systems to capture and consistently apply context—e.g., differentiating between confirmed vs. possible diagnoses, or personal vs. family history.

Example of Mapping from Different User Interface Examples to a Common Data Structure