Validating ICD coding algorithms for diabetes mellitus from administrative data

Abstract

Aim

To assess validity of diabetes International Classification of Disease (ICD) 9 and 10 coding algorithms from administrative data using physicians’ charts as the ‘gold standard’ across time periods and geographic regions.

Methods

From 48 urban and 16 rural general practitioners’ clinics in Alberta and British Columbia, Canada, we randomly selected 50 patient charts/clinic for those who visited the clinic in either 2001 or 2004. Reviewed chart data were linked with inpatient discharge abstract and physician claims administrative data. We identified patients with diabetes in the administrative databases using ICD-9 code 250.xx and ICD-10 codes E10.x–E14.x.

Results

The prevalence of diabetes was 8.1% among clinic charts. The coding algorithm of “2 physician claims within 2 years or 1 hospitalization with the relevant diabetes ICD codes” had higher validity than other 7 algorithms assessed (sensitivity 92.3%, specificity 96.9%, positive predictive value 77.2%, and negative predictive value 99.3%). After adjustment for age, sex, and comorbid conditions, sensitivity and positive predictive values were not significantly different between time periods and regions.

Conclusion

Diabetes could be accurately identified in administrative data using the following case definition “2 physician claims within 2 years or 1 hospital discharge abstract record with diagnosis codes 250.xx or E10.x–E14.x”.

Introduction

Diabetes prevalence has increased substantially in the past two decades, and is a major cause of morbidity and mortality [1], [2]. As a leading cause of blindness, end-stage renal disease and cardiovascular disease, diabetes poses a major challenge to the healthcare system, and weighs heavily on patients and their families [3], [4]. Therefore, diabetes has been widely studied for projecting population incidence, identifying high-risk groups and evaluating prevention and control initiatives for reducing the disease and its complications [5], [6].

In recent years administrative data have been widely used to conduct large-scale diabetes studies as the data are considerably less expensive and ready to access than conducting population based surveys. As the results derived from administrative data depend on the data quality, validity of administrative data in recording diabetes has been evaluated [7], [8], [9]. However, these validation studies have been mainly conducted in metropolitan areas, at a fixed time period, and from one diagnosis coding system, such as the International Classification of Disease (ICD) 9 database.

Completeness of administrative data depends on healthcare system utilization because the data records patients who have used the system. Health services utilization is determined by predisposing factors of demographic characteristics, enabling factors such as geographic location and health insurance and need factors such as the presence of chronic diseases [10]. Thus, the validity of diabetes ICD coding algorithms may vary by these factors. We conducted this study to investigate the validation of diabetes case definitions for ICD-9/ICD-10 administrative data across time periods and geographic areas after adjustment for patient demographic characteristics and chronic diseases.