The effect of number of healthcare visits on study sample selection in electronic health record data

Details

• Alternative Title:
  Int J Popul Data Sci
• Personal Author:
  Rasmussen-Torvik, Laura J. ; Furmanchuk, Al’ona ; Stoddard, Alexander J. ; Osinski, Kristen I. ; Meurer, John R. ; Smith, Nicholas ; Chrischilles, Elizabeth ; Black, Bernard S. ; Kho, Abel
• Description:
  Introduction
  
  Few studies have addressed how to select a study sample when using electronic health record (EHR) data.
  
  Objective
  
  To examine how changing criterion for number of visits in EHR data required for inclusion in a study sample would impact one basic epidemiologic measure: estimates of disease period prevalence.
  
  Methods
  
  Year 2016 EHR data from three Midwestern health systems (Northwestern Medicine in Illinois, University of Iowa Health Care, and Froedtert & the Medical College of Wisconsin, all regional tertiary health care systems including hospitals and clinics) was used to examine how alternate definitions of the study sample, based on number of healthcare visits in one year, affected measures of disease period prevalence. In 2016, each of these health systems saw between 160,000 and 420,000 unique patients. Curated collections of ICD-9, ICD-10, and SNOMED codes (from CMS-approved electronic clinical quality measures) were used to define three diseases: acute myocardial infarction, asthma, and diabetic nephropathy).
  
  Results
  
  Across all health systems, increasing the minimum required number of visits to be included in the study sample monotonically increased crude period prevalence estimates. The rate at which prevalence estimates increased with number of visits varied across sites and across diseases.
  
  Conclusions
  
  In addition to providing thorough descriptions of case definitions, when using EHR data authors must carefully describe how a study sample is identified and report data for a range of sample definitions, including minimum number of visits, so that others can assess the sensitivity of reported results to sample definition in EHR data.
  
  
• Keywords:
  Electronic Health Records Methods Prevalence Sampling Studies
• Source:
  Int J Popul Data Sci. 5(1)
• Pubmed ID:
  32864475
• Pubmed Central ID:
  PMC7448749
• Document Type:
  Journal Article
• Funding:
  U18 DP006120/DP/NCCDPHP CDC HHSUnited States/ ; U18DP006120/ACL/ACL HHSUnited States/ ; UL1 TR001436/TR/NCATS NIH HHSUnited States/ ; UL1 TR002537/TR/NCATS NIH HHSUnited States/
• Volume:
  5
• Issue:
  1
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:54633c791a7b2486ba29c387e6cec6fdf4a62709b9f00a7d23c9e481bc974d01
• Download URL:
  https://stacks.cdc.gov/view/cdc/93151/cdc_93151_DS1.pdf
• File Type:
  [PDF - 513.39 KB ]