Using an automated recruitment process to generate an unbiased study sample of multiple sclerosis patients

Telemed J E Health. 2010 Jan-Feb;16(1):63-8. doi: 10.1089/tmj.2009.0078.

Abstract

The objective of this study was to test the efficiency of an automated recruitment methodology developed as a component of a practical controlled trial to assess the benefits of a Web-based personal health site to guide self-management of multiple sclerosis symptoms called Mellen Center Care On-line. We describe the study's automated recruitment methodology using clinical and administrative databases and assess the comparability between subjects who completed informed consent (IC) forms, and individuals who were invited to participate but did not reply, designated as patient nonresponders (PNR). The IC and PNR groups were compared on demographics, number of physician or advanced practice nurse/physician assistant visits during the 12 months prior to the initial invitation, and level of disability as measured by the Charlson Comorbidity Index (CCI). Out of a total dynamic potential pool of 2,421 patients, 2,041 had been invited to participate, 309 had become ineligible to participate during the study, and 71 individuals remained in the pool at the end of recruitment. The IC group had a slightly greater proportion of females. Both groups were predominantly white with comparable marital status. The groups had comparable mean household income, education level, and commercial insurance. The computed mean CCI was similar between the groups. The only significant difference was that the PNR group had fewer clinic visits in the preceding 12 months. The subjects were highly representative of the target population, indicating that there was little bias in our selection process despite a constantly changing pool of eligible individuals.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Consent Forms / statistics & numerical data
  • Female
  • Humans
  • Internet*
  • Male
  • Medical Records Systems, Computerized / statistics & numerical data
  • Middle Aged
  • Multiple Sclerosis*
  • Patient Selection*
  • Randomized Controlled Trials as Topic
  • Research Design*
  • Socioeconomic Factors
  • Telemedicine*