Creating a SNOMED CT reference set for common endocrine disorders based on routine clinic correspondence.

Autor: Yap SHA; JJR Macleod Centre for Diabetes & Endocrinology, Aberdeen Royal Infirmary, Aberdeen, UK., Philip S; JJR Macleod Centre for Diabetes & Endocrinology, Aberdeen Royal Infirmary, Aberdeen, UK., Graveling AJ; JJR Macleod Centre for Diabetes & Endocrinology, Aberdeen Royal Infirmary, Aberdeen, UK., Abraham P; JJR Macleod Centre for Diabetes & Endocrinology, Aberdeen Royal Infirmary, Aberdeen, UK., Downs D; National Services, Edinburgh, Scotland, UK.
Jazyk: angličtina
Zdroj: Clinical endocrinology [Clin Endocrinol (Oxf)] 2024 Apr; Vol. 100 (4), pp. 343-349. Date of Electronic Publication: 2023 Aug 09.
DOI: 10.1111/cen.14951
Abstrakt: Background: Routine clinical coding of clinical outcomes in outpatient consultations still lags behind the coding of episodes of inpatient care. Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) offers an opportunity for standardised coding of key clinical information. Identifying the most commonly required SNOMED terms and grouping these into a reference set will aid future adoption in routine clinical care.
Objective: To create a common endocrinology reference set to standardise the coding for outcomes of outpatient endocrine consultations, using a semi-automated extraction of information from existing clinical correspondence.
Methods: Retrospective review of data from an adult tertiary outpatient endocrine clinic between 2018 and 2019. A total of 1870 patients from postcodes within two regional areas of NHS Grampian (Aberdeen City and Aberdeenshire) attended the clinic. Following consultation, an automated script extracted each problem statement which was manually coded using the 'disorder' concepts from SNOMED CT (UK edition).
Results: The review identified 298 relevant endocrine diagnoses, 99 findings and 142 procedures. There were a total of 88 (29.5%) commonly seen endocrine conditions (e.g., Graves' disease, anterior hypopituitarism and Addison's disease) and 210 (70.5%) less commonly seen endocrine conditions. Subsequently, consultant endocrinologists completed a survey regarding the common endocrine conditions; 28 conditions have 100% agreement, 25 have 90%-99% agreement, 31 have 50%-89% agreement and 4 have less than 59% agreement (which were excluded).
Conclusion: Automated text parsing of structured endocrine correspondence allowed the creation of a SNOMED CT reference set for common endocrine disorders. This will facilitate funding and planning of service provision in endocrinology by allowing more accurate characterisation of the patient cohorts needing specialist endocrine care.
(© 2023 The Authors. Clinical Endocrinology published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
Externí odkaz: