Using health administrative data to identify patients with pulmonary hypertension: A single center, proof of concept validation study in Ontario, Canada.
Don Thiwanka WijeratneAhmad HousinKatherine LajkoszM Diane LougheedPing Yu XiongDavid BarberKatharine M DolisznyStephen L ArcherPublished in: Pulmonary circulation (2022)
Real-world identification of pulmonary hypertension (PH) is largely based on the use of administrative databases identified by ICD codes. This approach has not been validated. The aim of this study was to validate a diagnosis of PH and its comorbidities using ICD 9/10 codes. Health records from Kingston Health Sciences Centre (2010 to 2012) were abstracted to identify a diagnosis of PH. Cohort 1 patients ( n = 300) were selected because they had attended a cardiology or respirology clinic without knowledge of PH status. Cohort 2 patients ( n = 200) were patients with a diagnosis of PH, identified using International Classification of Diseases (ICD) codes at the time of hospitalizations (CIHI-DAD) or emergency department (ED) visits (CIHI-NACRS). These cohorts were combined and reviewed to validate the diagnosis of PH. These data were securely transferred to the Institute of Clinical Evaluative Sciences (ICES). The diagnosis of PH from chart abstraction was used as the gold standard. The classification of PH into WHO groups, based on chart abstraction, was also compared to classification based on ICD code-defined comorbidities. Cohort 1 and Cohort 2 were merged to yield 449 unique patients in the combined cohort. In the combined cohort, 248 of 449 (55.2%) had a diagnosis of PH by ICD code criteria. The mean age of this PH group was 70 years, and the majority were females (65.5%). One hospitalization or ED visit resulting in a diagnostic code for PH had a sensitivity of 73% and a specificity of 99% for a confirmed PH diagnosis on chart abstraction. When WHO classification by chart abstraction and ICD codes for comorbidities were compared, there was 87% agreement. Identification of PH and its comorbidities using ICD codes is a valid approach, and this single-center study supports its application to identify PH.
Keyphrases
- emergency department
- end stage renal disease
- pulmonary hypertension
- healthcare
- machine learning
- public health
- newly diagnosed
- chronic kidney disease
- deep learning
- prognostic factors
- mental health
- mass spectrometry
- peritoneal dialysis
- cardiac surgery
- high resolution
- climate change
- pulmonary artery
- drug induced
- tandem mass spectrometry