Summary
This study investigated the expressiveness of SNOMED CT in the domain of chronic wounds. It presents a mapping of a documentation standard for chronic wounds, the NKDUC, which is a nationally consented collection of items relevant for leg wound care, to SNOMED CT. Based on the NKDUC, the developed information model revealed 268 items to be mapped. Conducted by three health care professionals, the mapping had “moderate” reliability (K = 0.512). The coverage rate of SNOMED CT was 67.2% (symmetric match) overall and 64.3% specifically for wounds.
Coverage Rate
The achieved coverage rate can be regarded as “satisfactory” as there is a direct, symmetric match in SNOMED CT for two-thirds of all the mapped items (67.2%). An additional 14.6% of the mapped items found an asymmetric match, which adds to a total of 81.8% coverage. Regarding wound specific information, wound assessment ranked first (75%) and wound diagnostics last (57.1%).
In comparison, the overall coverage rates based on pre-coordinated concepts in other clinical domains, e.g. emergency medicine (89%) [19], were higher, but could also be as low as 30% in case of the Human Phenotype Ontology [31], which allows these results to be classified.
Considering the NKDUC sections, heterogeneous coverage rates became apparent. At the end of both extremes, the section “general medical condition” - with over 80% coverage for the first both degrees - had the highest, and the section “patient demographics” had the lowest coverage with 50% combing degree 1 and 2 only. “General medical condition” mainly contains a list of ulcer-relevant conditions also found in the ICD-10 classification. Past ICD-10 mappings with SNOMED CT showed that SNOMED CT covers those items generally well [32], which explains the high coverage rate of this section.
Although the wound specific sections (i.e. “wound status”, “wound assessment”, “diagnostics” and “therapy”) showed a fair to reasonable coverage rate, the mappings thereof remained incomplete. In particular, only a bit more than 55% of the items in the “diagnostics” sections could be mapped literally to the same term or a synonym.
The section “patient demographics” contains items specific to the German system: Its contents include the educational, marital, professional and health insurance status for whose items few identical concepts were identified in SNOMED CT. The reduced coverage rate of this section reflects the fact that the mapping was performed using the international SNOMED CT version for German specific items. Our findings support the need to fill these gaps for a national German SNOMED CT version.
There are no comparable studies in the wound domain to validate our findings. However, an attempt to link a small nursing-specific data set for chronic wound care with SNOMED CT concepts yielded a value to be used as a hint. This value of 50.8% [13] was smaller than the 67.2% in our study.
In any case, our investigation revealed a gap of expressing information specific for chronic wound care in SNOMED CT. Clinical, interdisciplinary datasets that are based on the literature and consented by medical experts, such as the NKDUC, provide valuable insights to identify and fill these gaps.
One approach to doing so is post-coordination to express meaning by composing the existing concepts following SNOMED CT’s compositional grammar. Post-coordination seems especially promising when the target concepts had a broader meaning (degree 4) and the meaning can possibly be narrowed down using post-coordination. Even for missing matches (degree 5), post-coordination can offer a solution. For example, post-coordination would lead to a SNOMED CT expression to code a “leg ulcer smear procedure ”
(16314007 |Microbial smear examination (procedure)|: {363700003 |Direct morphology (attribute)| = 56208002 |Ulcer (morphologic abnormality)|, 363704007 |Procedure site (attribute)| = 416077002 |Skin and/or subcutaneous tissue structure of lower limb (body structure)|}).
In addition, post-coordination requires a consensus building process to be established, as there are various solutions to post-coordinate expressions.
However, if post-coordination fails, missing concepts should be added to SNOMED CT. In this context, the wound-specific sections “diagnostics” and “wound status” may benefit the most because they showed the lowest coverage rates. New concepts to describe the progress of epithelisation and granulation to record wound healing would be good examples to illustrate this need.
Both of the approaches, post-coordination and adding missing concepts, promise to close the semantic gaps identified in SNOMED CT and would allow NKDUC, and probably other documentation standards in wound care, to reach semantic interoperability.
In summary, the findings show that SNOMED CT is not fully ready to be used for wound care documentation and, therefore, further measures need to be taken.
Reliability
The strength of these findings highly depends on the reliability of the mapping. The overall reliability of K = 0.512 is what the reference literature describes as a “moderate” agreement between the mappers. Thus, the findings of the mapping stand on solid ground. However, in this mapping process, rather than selecting items from a small set of options, the raters had to choose from a vast range of SNOMED CT concepts, as it provides over 350,000 pre-coordinated concepts. This circumstance makes it generally harder to find consensus. This conclusion is supported by the fact that the Kappa statistic tends to decrease as the number of categories grow [33].
Comparing NKDUC sections, they showed heterogeneous reliability values. For example, mappers were more discordant for concepts concerning “diagnostics” compared to “general medical condition”. This situation may imply that sections showing low reliability are challenging to map, either because there are many similar SNOMED CT concepts, the NKDUC items are ambiguous or both cases hold true. Reliability values and coverages rates seem to not be uncorrelated as the lower Kappa values for wound status (0.366), diagnostics (0.280) and therapy (0.367) tend to correspond with lower coverages rates of 64.9%, 57.1% and 61.6%, respectively. Alike, higher reliability values for general medical condition (0.754) and wound assessment (0.568) vary with higher coverage rates of 83.3% and 75%. Therefore, in either case, the mapped SNOMED CT concepts in the sections with lower reliability have to be validated carefully prior to its use in clinical practice.
Information Model
Although the information model that was derived from the NKDUC served primarily as a source for identifying the items to be mapped, it also allows statements to be made about the general validity of NKDUC by comparing this information model with others. For example, the openEHR templates “wound assessment panel” and “wound presence assertions” [34], which partly represent wound phenomena, embrace similar content as the corresponding parts of the NKDUC information model. This overlap hints at the validity of this information model as well as the mapping and implications for SNOMED CT. Furthermore, it seems promising to integrate the identified SNOMED CT concepts into wound-specific openEHR archetypes and templates to enhance interoperability in the domain of chronic wound care [35].
Limitations
There are some limitations to be considered when interpreting the results. Most importantly, as mentioned herein above, this study did not make use of post-coordination, which most likely limited a higher coverage rate, as post-coordination usually extends the content of SNOMED CT through compositional expressions [36]. However, this study was conducted to investigate the predefined content and its coverage rate in the ulcer care domain using the NKDUC as an example of a national consented collection of ulcer-relevant items. We plan to implement post-coordination for an upcoming mapping of the NKDUC to SNOMED CT to further fill semantic gaps and to improve the coverage rate, which is required for actual implementation in systems used in clinical care. Furthermore, as the NKDUC focuses on cardiovascular leg wounds, the coverage rate for items of further wound types, e.g. pressure ulcers, have to be investigated.
Another limitation of this study is the absence of a German SNOMED CT version resulting in the necessity of a translation by each mapper, which may have introduced bias. However, while a national licence is unavailable, at least until 2021, an upcoming German translation is unlikely, especially as German-speaking countries with a SNOMED CT licence, i.e. Austria and Switzerland, do not plan to release a German SNOMED CT version soon [37]. Thus, a translation of the German terms and items was required in this initiative and will remain so in the upcoming German mapping initiatives. In turn, those initiatives may guide and support the future development of a German SNOMED CT version.