Dementia and Parkinson’s disease diagnoses in electronic health records vs. Medicare claims data: a study of 101,980 linked patients

Abstract

Abstract Background Medicare claims and electronic health record data are both commonly used for research and clinical practice improvement; however, it is not known how concordant diagnoses of neurodegenerative diseases (NDD, comprising dementia and Parkinson’s disease) are in these data types. Therefore, our objective was to determine the sensitivity and specificity of neurodegenerative disease (NDD) diagnoses contained in structured electronic health record (EHR) data compared to Medicare claims data. Methods This was a retrospective cohort study of 101,980 unique patients seen at a large North Carolina health system between 2013–2017, which were linked to 100% North and South Carolina Medicare claims data, to evaluate the accuracy of diagnoses of neurodegenerative diseases in EHRs compared to Medicare claims data. Patients age > 50 who were enrolled in fee-for-service Medicare were included in the study. Patients were classified as having or not having NDD based on the presence of validated ICD-CM-9 or ICD-CM-10 codes associated with NDD or claims for prescription drugs used to treat NDD. EHR diagnoses were compared to Medicare claims diagnoses. Results The specificity of any EHR diagnosis of NDD was 99.0%; sensitivity was 61.3%. Positive predictive value and negative predictive value were 90.8% and 94.1% respectively. Specificity of an EHR diagnosis of dementia was 99.0%, and sensitivity was 56.1%. Specificity of an EHR diagnosis of PD was 99.7%, while sensitivity was 76.1%. Conclusions More research is needed to investigate under-documentation of NDD in electronic health records relative to Medicare claims data, which has major implications for clinical practice (particularly patient safety) and research using real-world data.