Obesity is a growing global health concern, associated with various major diseases such as diabetes, cardiovascular issues, cancer, and premature death. Hospital diagnosis codes for overweight and obesity, based on the International Classification of Diseases, 10th Revision (ICD-10), offer a potential source for valuable epidemiological research. However, the validity of these codes in a population-based healthcare system has not been thoroughly assessed.
Materials and Methods
To address this knowledge gap, a study was conducted using data from the Danish National Patient Registry (DNPR) and the Central Denmark Region Clinical Information System (CDRCIS). The positive predictive value (PPV) of ICD-10 diagnoses of overweight and obesity was examined by comparing them with BMI measurements as the reference. Additionally, the completeness of overweight/obesity diagnosis coding was analyzed.
Health Registries: The Danish National Patient Registry (DNPR) provided comprehensive information on non-psychiatric hospital contacts in Denmark since 1977, including inpatient admissions, outpatient clinic visits, and emergency room visits, with details on diagnoses and admission types.
Overweight and Obesity Diagnosis Codes: Researchers identified individuals with overweight or obesity diagnosis codes in the Central Denmark Region between 2012 and 2015. Different subcategories of overweight and obesity were classified based on BMI ranges.
Validation of Diagnoses by BMI
Individual-level diagnosis data from the DNPR were linked with height, weight, and BMI data from the CDRCIS. A BMI value of ≥25 kg/m was considered the gold standard for overweight or obesity.
Completeness of Overweight/Obesity Coding: Starting with patients having a BMI measurement of ≥25 kg/m, researchers cross-referenced overweight/obesity diagnosis codes with DNPR data to assess the completeness of coding.
The study identified a total of 19,672 patients with overweight or obesity diagnosis codes. The overall PPV for overweight or obesity was 87.6% based on recorded BMI values. Specifically, BMI measurements within 1 year of diagnosis yielded a PPV of 79.8% for overweight or obesity. The PPV was higher among men (93.6%) compared to women (85.9%).
Furthermore, the study found that primary diagnosis codes of overweight/obesity had a higher PPV (94.1%) than secondary diagnosis codes (86.1%). Additionally, the PPV increased with higher patient age, indicating a stronger accuracy of diagnoses in older individuals.
Completeness of coding was found to be low, with only 10.9% of patients recorded with BMI ≥25 kg/m having an overweight/obesity diagnosis code.
Discussion and Implications
The study provides valuable insights into the validity of ICD-10 codes for overweight and obesity diagnoses in a general hospital-based setting in Denmark. The high PPV, especially for primary diagnosis codes and in older patients, indicates the reliability of these codes in accurately identifying overweight and obese individuals.
However, the low completeness of coding highlights potential underreporting of overweight/obesity diagnoses in hospital records. Researchers and healthcare professionals should be cautious when relying solely on hospital discharge registries for epidemiological research on obesity, as this may not capture the entire scope of the issue.
The study contributes to the growing understanding of the validity of ICD-10 codes for overweight and obesity diagnoses in a population-based healthcare system. Although the codes show a high PPV, there is room for improvement in the completeness of coding. Future research should continue to explore different factors affecting diagnosis coding accuracy and investigate strategies to enhance data quality in hospital records. As obesity continues to be a significant health concern, robust and accurate data collection methods are crucial for developing effective interventions and policies to address this global epidemic.