Search is an important part of the clinical information life-cycle. Effective search must make it quick and easy for users to accurately select the relevant content for data entry. The selected Concept or Description may need to be stored in ways that represent information consistently and allow it to be processed effectively.
An EHR system must also have a user interface that makes search easy in terms of the time and effort required to find suitable Concepts to enter into the clinical record. Improving the usability of search can help increase the utility of SNOMED CT for data entry, and hence, the overall adoption of clinical systems. Increasing the utility and the added value of clinical systems depends on improving the tradeoff between time taken to code, and the quality of the coded content produced. This is true whichever terminology is chosen to be implemented 'front of house'.
Leveraging SNOMED CT advanced design and implementing it properly is specifically intended to give better leverage in this tradeoff than we could ever have on other coding systems. However, if badly implemented, SNOMED CT will make an already bad situation worse. On the other hand, a multitude of different but generally poor designs is equally dangerous. There is a minimum level of functionality that should be universal, and implementers need to be more prescriptive when designing the search functionality.
Approaches to search embedded in clinical systems need to be tailored to the way different groups of clinicians work and think. While this guide identifies useful techniques to support searching, the ways in which these are applied may need to vary to match the working practices of a clinical specialty or the priorities of a particular health provider organization.
For effective data entry, the interface needs to be designed to meet the requirements for subsequent display and retrieval. Data entered and stored in the clinical record, needs to be displayed in ways that can be easily read and understood. The data should also be retrievable to enable reporting analysis, decision support and appropriate communication to other systems and other users.
Search is the process by which a user finds a Concept or Description to represent a clinical idea for a specific purpose.
The way a search is carried out depends on the setting in which it is performed. A simple search may involve typing a word or phrase in a search box, getting a list of matching terms and viewing the list to identify the appropriate Concept. This Guide considers a range of enhancements to SNOMED CT searches which can make it quicker and easier for users to find the appropriate Concept.
The logical model of SNOMED CT is able to the support development of search techniques which can support effective and efficient Concept and Description retrieval.
It is however important to be aware that different techniques apply to different types of searches in order to avoid unconstrained searches which can make browsing SNOMED CT like navigating a jungle. This section presents some features of SNOMED CT which can help support effective and efficient searches.
The | is a | hierarchies in SNOMED CT support searches to be constrained by type, e.g. searches for Concepts which are contained in one of the top-level hierarchies such as | clinical finding | , | body structure | and | procedure | (see Constrain Searches by Supertype Ancestors).
This type of search limits the number of search candidates significantly, as it excludes all Concepts of types other than those specified by the chosen subtype hierarchy. More granular Concepts than the top-level Concepts can be used as the basis for this type of search. For instance, searching for subtypes of | Cardiovascular finding | will further concentrate the type and number of candidate results.
SNOMED CT supports the definition of Reference Sets. Reference Sets are important as they can be used to constrain search and data entry or support SNOMED CT navigation. Hence, searching within a Reference Set will limit the number of search results and ensure that the result set will be relevant for the desired context (see ).
Moreover, Reference Sets can also be used to exclude Concepts as possible result candidates. For example, as SNOMED CT contains both animal and human Concepts, for human medicine it is likely that Concepts in the non-human Reference Set needs to be excluded from all searches.
It is a benefit that SNOMED CT supports development of Language Reference Sets, as this supports searches by Descriptions that are limited to a specific language or dialect (see ). A Language Reference Set identifies the Descriptions which are considered to be preferred designation for and acceptable as alternatives for SNOMED CT Concepts in the context of a given language and, optionally, dialect.
