Validating Type 2 Diabetes Diagnoses Across the Madrid Hospital Network: Evidence for Secondary Use of the CMBD in the European Health Data Space

Background/Objectives: Hospital discharge data are increasingly reused for research and within health data spaces, but their value depends on accurate diagnostic coding. The validity of type 2 diabetes mellitus (T2DM) coding in the Spanish hospital discharge database (CMBD) had not been assessed across a whole regional network. We aimed to quantify the precision and completeness of E11 coding across the public hospital network of the Region of Madrid. Methods: We conducted a retrospective validation study in the public hospitals of the Region of Madrid (2016–2025). In each of four hospital complexity groups, we selected admissions with and without an ICD-10-ES E11 code, matched by age and sex (787 and 781 analysed). The reference standard was the American Diabetes Association criteria, checked in health records. Predictive values were estimated directly; sensitivity, specificity and prevalence were reconstructed for the whole population, adjusting for sex and age. Results: Of 4,707,924 discharges, 918,797 (19.5%) had a T2DM code. The positive predictive value was 94.2% (95% CI: 92.1–96.0), the negative predictive value 94.0% (91.3–96.3), specificity 98.5% (98.0–99.0) and sensitivity 79.3% (72.4–86.2), a lower bound. The estimated prevalence of T2DM among discharges was 23.2%, against 19.5% coded; about 226,000 admissions with T2DM had no code. Only the positive predictive value differed between hospital groups (p = 0.006). Conclusions: The E11 code is highly precise but incomplete: it is reliable for building cohorts, whereas counts based on it underestimate the number of cases by about one in five.

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Journal
Journal of Clinical Medicine
Published
2026-10-07
DOI
https://doi.org/10.3390/jcm15197717
Primary Topic
Medical Coding and Health Information
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article
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article

Validating Type 2 Diabetes Diagnoses Across the Madrid Hospital Network: Evidence for Secondary Use of the CMBD in the European Health Data Space

Daniala L. Weir, Ana López‐de‐Andrés, Miguel Ángel Salinero-Fort, Carmen de Burgos‐Lunar et al.
Journal of Clinical Medicine
Medical Coding and Health Information
article

Validating Type 2 Diabetes Diagnoses Across the Madrid Hospital Network: Evidence for Secondary Use of the CMBD in the European Health Data Space

Daniala L. Weir, Ana López‐de‐Andrés, Miguel Ángel Salinero-Fort, Carmen de Burgos‐Lunar, Ana Chacón-García, Rafael Gómez-Coronado-Martín
article en

Abstract

Background/Objectives: Hospital discharge data are increasingly reused for research and within health data spaces, but their value depends on accurate diagnostic coding. The validity of type 2 diabetes mellitus (T2DM) coding in the Spanish hospital discharge database (CMBD) had not been assessed across a whole regional network. We aimed to quantify the precision and completeness of E11 coding across the public hospital network of the Region of Madrid. Methods: We conducted a retrospective validation study in the public hospitals of the Region of Madrid (2016–2025). In each of four hospital complexity groups, we selected admissions with and without an ICD-10-ES E11 code, matched by age and sex (787 and 781 analysed). The reference standard was the American Diabetes Association criteria, checked in health records. Predictive values were estimated directly; sensitivity, specificity and prevalence were reconstructed for the whole population, adjusting for sex and age. Results: Of 4,707,924 discharges, 918,797 (19.5%) had a T2DM code. The positive predictive value was 94.2% (95% CI: 92.1–96.0), the negative predictive value 94.0% (91.3–96.3), specificity 98.5% (98.0–99.0) and sensitivity 79.3% (72.4–86.2), a lower bound. The estimated prevalence of T2DM among discharges was 23.2%, against 19.5% coded; about 226,000 admissions with T2DM had no code. Only the positive predictive value differed between hospital groups (p = 0.006). Conclusions: The E11 code is highly precise but incomplete: it is reliable for building cohorts, whereas counts based on it underestimate the number of cases by about one in five.

Journal of Clinical MedicineVol. 15(19)
Universidad Complutense de Madrid (ES), Utrecht University (NL), Instituto de Salud Carlos III (ES), Hospital Clínico San Carlos (ES), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (ES), Hospital La Paz Institute for Health Research (ES), Universidad Alfonso X el Sabio (ES), Research Network (United States) (US)
Openalex Percentile: Top 7%
Medical Coding and Health Information
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