Do I need to exclude grouper concepts from clinical data entry?
Collection: Implementation dilemma
Summary: No, as general advice, excluding groupers from clinical data entry is not necessary. The effort of manually identifying groupers and maintaining the list updated over time is considerable, and a best practice search and data entry implementation effectively prevents the selection of general clinical terms.
Implementation dilemma
SNOMED hierarchies include grouper concepts that support the aggregation of clinical concepts in multiple ways, including analytics, reporting, and clinical decision-support use cases. At the moment of clinical data entry, some implementers wonder if these concepts should be excluded from the options that the clinician can select.
When creating small, manually curated sets of concepts for options in clinical data entry, implementers will always exclude any unnecessary concepts, and non-clinical groupers will never be selected to be included. However, the dilemma appears when the implementer designs a data entry set for a field with a large set of values, for example, "all clinical findings". In these cases, the identification of the non-clinical groupers to exclude becomes a challenge.
Advice
The first challenge for removing grouper from the search is identifying which concepts represent groupers with less clinical value. This will depend on the context and the clinical user. In some contexts, it is appropriate to record clinical content using more general concepts, like when recording old events where the patient does not have an exact recollection of the clinical details ("I had surgery for an abdominal infection") or when the final diagnosis is not yet confirmed. Still, the clinician wants to record a general idea of the probable one("metabolic disorder"). Also, the level of detail required will differ depending on the specialty; a nurse, a family physician, a surgeon, or an endocrinologist may have different views of the same clinical entities. The specialist requires very detailed concepts inside their specialty but very little detail for anything else outside it.
The lack of a universal definition of what a grouper is has resulted in the fact that groupers are not identified in SNOMED CT, so any effort to remove them from the search will require a manual curation of the concepts to create exclusions refsets or value sets (Figure 1). These exclusion lists would need to be constantly updated with new SNOMED releases.
Figure 1: Example of possible grouper concepts, depending on the context
The concern about the groupers is based on the idea that the clinician may have detailed clinical information that is not recorded because a more general grouper concept appears first in the search results. This highlights the importance of implementing effective search and sorting algorithms. Best practice recommendations, implemented in most common terminology servers, provide mechanisms to prevent that. The most relevant one may be the multi-prefix search strategy ("ac myo inf")1, which facilitates the inclusion of multiple words in the search string with only a few keystrokes. This refines the search, including detailed concepts in the results, when most groupers fail to match the search string.
As general advice, excluding groupers from clinical data entry is not necessary when using large search sets. The effort of manually identifying groupers and maintaining the list updated over time is considerable, and a best practice search and data entry implementation effectively prevents the selection of general clinical terms.
Tips for best results implementing data entry with SNOMED CT without restricting groupers
Focus on creating the best possible terminology bindings: use value sets or ECL (the Expressions Constraint Language)2 to ensure that only acceptable concepts are available for data entry.
Train clinical users on how the multiple prefixes, no order, string matching technique works.
Implement a program to monitor the quality of clinical data entry and provide continuous training opportunities for clinicians.
Provide benefits to clinicians based on the coded information, like facilitating the aggregation and navigation of the patient history. Clinicians will quickly notice any problems with the level of detail, which will have a positive reinforcement at the moment of coding.
References
Search and Data Entry Guide: Optimizing searches: https://confluence.ihtsdotools.org/x/pgb-AQ
Expression Constraints Language Guide: http://snomed.org/ecl
SNOMED Terminology Services: https://www.implementation.snomed.org/terminology-services
Learn More
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