This section provides a general introduction to the terminology service requirements related to EHR data entry. It outlines the rationale for the following sections on data entry design and practical data entry.
Background Reading
Readers of this section of the guide are advised to read the following sections of the SNOMED CT Search and Data Entry Guide.
- 4. Optimizing Searches - describes effective ways to optimize SNOMED CT searches.
- 5. Optimize Display of Search Results - provides guidance on ordering and structuring lists of search results.
- 6. Data Entry - describes a range of techniques that facilitate the effective recording of SNOMED CT concepts or expressions in health records.
Data Entry Context
Entry of data into an Electronic Health Record (EHR) requires access to services that enable the user to rapidly locate and select the concepts and terms that need to recorded. There are a wide range of different EHR data entry scenarios determined by the type of healthcare encounter and the reason for that encounter. A typical data entry scenario involves recording data in different data entry contexts. The data entry contexts are typically distinguished by section headings (e.g. "Surgical History"), individual data item labels (e.g. "Initial Diagnosis") and in some case by specific questions with a limited range of answers (e.g. "Family history of heart disease?" with values "Yes", "No" or "Unknown").
Data entry design needs to take account of data entry context for two reasons.
- The range of concepts that can rationally be entered is determined by the data entry context.
- Table 3.2.1-1 illustrates this point with examples of three data entry contexts. In each of these contexts, there are constraints on the range of SNOMED CT concepts that it is rational to enter.
- The interpretation of concepts or other data entered may be affected by the data entry context.
- Table 3.2.1-1 provides examples of ways in which the data entry context can affect the interpretation of recorded data. To ensure appropriate interpretation, relevant information about the data entry context must be stored with or linked to the data entered.
Data Entry Context | Constraints on Values | Interpretation of Recorded Data |
Initial diagnosis on an encounter or admission form | A concept recorded in this data entry context should be a subtype of 64572001 | Disease (disorder)| . | The fact that this is an "Initial diagnosis" data entry context needs to be captured so that the record can be appropriately interpreted. |
Surgical history as part of past medical history | A concept recorded in this data entry context could either be:
| The "Past History" data entry context needs to be captured so that the record can be appropriately interpreted. It must be possible to distinguish a past history record of a procedure from a contemporaneous record of the same procedure. |
Symptom check list with yes or no options for each symptom | Each question should be bound to a concept that represents the relevant symptom. These concepts should be subtypes of 404684003 | Clinical finding| . The simplest way to represent the "yes" and "no" answers to a question like this is to record the relevant finding concept if the answer is "yes" and not to create a record if the answer is "no". However, where the answer "no" has clinical significance, alternative approaches discussed in the next column may be preferable. | The simple approach suggested in the previous column does not explicitly record negative answers. However, in many cases, a negative response has its own significance and does need to be recorded.
Similarly, there may be questions that have 3 alternative answers (e.g. "yes", "no", "don't know"). In these cases, an approach is needed to distinguish between the available responses. |
Terminology Binding
Table 3.2.1-1 highlights the significance of the relationship between the SNOMED CT terminology and EHR structured data and data entry contexts. Formal representations of these relationships are referred to as terminology bindings.
- A terminology binding is a link between a terminology component and an information model artifact.
There are two distinct types of terminology binding:
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A value set binding is
a terminology binding that represents the set of permitted values that can be used to populate a coded data item.
- This type of binding is used to represent search constraints applicable to a particular data entry context.
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A meaning binding is
a terminology binding that represents the clinical meaning of a data item or collection of data items.
- This type of binding is used to represent aspects of the meaning of the entered data that are derived from the data entry context.
Footnotes
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