Adult Changes in Thought Study

Electronic Health Record & Utilization Data

Health Record Data.png Data Description

Because participants in the Adult Changes in Thought (ACT) Study are sampled from among Kaiser Permanente Washington (KPWA) members, the ACT Study provides the opportunity to leverage select clinical and claims data from participants’ health system utilization.

These data include elements such as enrollment information, diagnosis and procedures codes from clinical encounters, pharmacy fills, laboratory measures, vital signs (e.g., blood pressure, BMI), and other domains mapped to a common data model – the Virtual Data Warehouse (VDW) – developed by the Health Care Systems Research Network (HCSRN) to support research. Information on the VDW and its data specifications can be found on the HCSRN website.

While ACT participants are sampled from among KPWA members, continued health plan enrollment in KPWA during study follow-up is not a requirement for ACT participation. As such, proposed research leveraging VDW elements must consider that capture of claims and clinical utilization data for a participant is only possible during periods in which they were enrolled in the health plan. Further, the periods of potential availability of such clinical data from the VDW on ACT participants depends on the data domain:

  • Medications: 1977+
  • Labs: 1988+
  • Diagnoses/procedures: 1993+
  • Vital signs: ~2003+

Note: Only select elements from the VDW are included with ACT data freezes. Any requests for clinical data beyond the included elements will be subject to review to ascertain data availability, allowability, and programmatic resources needed to pull such data.

Key Publications

The following publications provide additional detail on the ACT electronic health record data elements. These may be helpful supporting citations when publishing analyses using these data.

  • Ross TR, Ng D, Brown JS, Pardee R, Hornbrook MC, Hart G, & Steiner JF. (2014). The HMO Research Network Virtual Data Warehouse: A Public Data Model to Support Collaboration. EGEMS (Washington, DC), 2(1), 1049. doi.org/10.13063/2327-9214.1049
  • Gray SL, Anderson ML, Dublin S, Hanlon JT, Hubbard R, Walker R, Yu O, Crane PK, Larson EB. (2015). Cumulative use of strong anticholinergics and incident dementia: a prospective cohort study. JAMA Internal Medicine, 175(3):401-7. doi.org/10.1001/jamainternmed.2014.7663. 
  • Gray SL, Walker RL, Dublin S, Yu O, Aiello Bowles EJ, Anderson ML, Crane PK, Larson EB. (2018). Proton Pump Inhibitor Use and Dementia Risk: Prospective Population-Based Study. Journal of the American Geriatrics Society, 66(2):247-253. doi.org/10.1111/jgs.15073. 
  • Barnes DE, Zhou J, Walker RL, Larson EB, Lee SJ, Boscardin WJ, Marcum ZA, Dublin S. (2020). Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia. Journal of the American Geriatrics Society, 68(1):103-111. doi.org/10.1111/jgs.16182.