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Big Data Drives New Research

Susan Bernstein  |  Issue: January 2019  |  December 12, 2018

“Many studies in rheumatology would qualify. We have data sharing, and people who want to archive data from their completed studies. We provide a way for them to do that through the Archive of Data on Disability to Enable Policy and Research (ADDEP),” he said. CLDR’s Visiting Scholars program supports investigators for up to six months to work with researchers who are experienced in using large data sets.

Function & Utilization Data
Soham Al Snih, MD, PhD, associate professor, Division of Rehabilitation Sciences, University of Texas Medical Branch, used large data sets from the Centers for Medicaid & Medicare Services (CMS) and the Hispanic Established Populations for the Epidemiological Study of the Elderly (H-EPESE) for a new analysis of patients with OA, rheumatoid arthritis (RA) and spondyloarthropathies (SpA).

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In a study supported by the NIH National Institute of Aging (NIA), she and her co-investigators compared self-reported arthritis data with data from CMS files for diagnosis sensitivity and specificity. They also examined sociodemographics, clinical characteristics and functional outcomes, provider types and level of healthcare use by different patient groups. The H-EPESE database includes archived patient questionnaire data collected from Mexican-Americans aged 65 years and older since 1993. They also analyzed CMS beneficiary summary file data, including ICD-9 billing codes and fee-for-service claims. Out of 3,952 original participants, 1,518 were used in their final sample.

“When we looked at sociodemographic characteristics by arthritis groups, we could see there were no differences by age” between those with self-reported arthritis and patients who met the CMS Chronic Case Warehouse definitions of arthritis, Dr. Al Snih said. “The group with no arthritis tended to [include mostly men], but the other groups with arthritis were more likely to [include married women and were] more likely to [include people under] financial strain compared with those who had no arthritis. When we looked at the distribution of clinical characteristics, we found that the groups with arthritis were more likely to report pain, their BMI was higher, they reported more depression and had more comorbidities using the Charlson index.”

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People with arthritis had higher healthcare use compared with those without the disease, including 97.4% with one or more outpatient visits in a year, she said.

When investigators analyzed data specific to the types of arthritis, they found patients with RA and SpA had more hospital admissions and emergency department visits than OA patients. Additionally, more than 80% of patients in each arthritis patient group reported at least one functional limitation according to the Instrumental Activities of Daily Living and Activities of Daily Living (IADL-ADL) index. In the study, 32.3% of RA patients had been treated by a rheumatologist, compared with 5.6% of the OA patients and none of the patients with SpA. Also, 47% of the SpA patients were treated by a physical or occupational therapist based on the claims data.

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Filed under:Research RheumTechnology Tagged with:big dataelectronic health record (EHR)Research

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