Development and validation of algorithms to build an electronic health record based cohort of patients with systemic sclerosis

Abstract

Objectives To evaluate methods of identifying patients with systemic sclerosis (SSc) using International Classification of Diseases, Tenth Revision (ICD-10) codes (M34*), electronic health record (EHR) databases and organ involvement keywords, that result in a validated cohort comprised of true cases with high disease burden. Methods We retrospectively studied patients in a healthcare system likely to have SSc. Using structured EHR data from January 2016 to June 2021, we identified 955 adult patients with M34* documented 2 or more times during the study period. A random subset of 100 patients was selected to validate the ICD-10 code for its positive predictive value (PPV). The dataset was then divided into a training and validation sets for unstructured text processing (UTP) search algorithms, two of which were created using keywords for Raynaud’s syndrome, and esophageal involvement/symptoms. Results Among 955 patients, the average age was 60. Most patients (84%) were female; 75% of patients were White, and 5.2% were Black. There were approximately 175 patients per year with the code newly documented, overall 24% had an ICD-10 code for esophageal disease, and 13.4% for pulmonary hypertension. The baseline PPV was 78%, which improved to 84% with UTP, identifying 788 patients likely to have SSc. After the ICD-10 code was placed, 63% of patients had a rheumatology office visit. Patients identified by the UTP search algorithm were more likely to have increased healthcare utilization (ICD-10 codes 4 or more times 84.1% vs 61.7%, p < .001), organ involvement (pulmonary hypertension 12.7% vs 6% p = .011) and medication use (mycophenolate use 28.7% vs 11.4%, p < .001) than those identified by the ICD codes alone. Conclusion EHRs can be used to identify patients with SSc. Using unstructured text processing keyword searches for SSc clinical manifestations improved the PPV of ICD-10 codes alone and identified a group of patients most likely to have SSc and increased healthcare needs.

Racial and ethnic associations with interstitial lung disease and healthcare utilization in patients with systemic sclerosis

“…The cohort of 788 patients with SSc was created using a previously published algorithm in which patients with >=2 SSc International Classification of Diseases, Tenth Revision (ICD-10) codes were identified from January 1, 2016 through June 30, 2021. 22 We identified patients with ILD using >=1 ILD ICD-10 codes (Table E1), sourced from encounters, billing, and the problem list. The first instance that the code was documented during the study period was considered the index date for SSc, and first ever code for ILD (specifically the earliest date as it could occur prior to SSc).…”

“…To test these hypotheses, we assessed an electronic health record (EHR) based cohort of patients with SSc from Mass General Brigham (MGB), an integrated multi-hospital healthcare system. 22…”