A 2-1-1 research collaboration: participant accrual and service quality indicators

Am J Prev Med. 2012 Dec;43(6 Suppl 5):S483-9. doi: 10.1016/j.amepre.2012.09.007.

Abstract

Background: In times of crises, 2-1-1 serves as a lifeline in many ways. These crises often cause a spike in call volume that can challenge 2-1-1's ability to meet its service quality standards. For researchers gathering data through 2-1-1s, a sudden increase in call volume might reduce accrual as 2-1-1 has less time to administer study protocols. Research activities imbedded in 2-1-1 systems may affect directly 2-1-1 service quality indicators.

Purpose: Using data from a 2-1-1 research collaboration, this paper examines the impact of crises on call volume to 2-1-1, how call volume affects research participant accrual through 2-1-1, and how research recruitment efforts affect 2-1-1 service quality indicators.

Methods: t-tests were used to examine the effect of call volume on research participant accrual. Linear and logistic regressions were used to examine the effect of research participant accrual on 2-1-1 service quality indicators. Data were collected June 2010-December 2011; data were analyzed in 2012.

Results: Findings from this collaboration suggest that crises causing spikes in call volume adversely affect 2-1-1 service quality indicators as well as accrual of research participants. Administering a brief (2-3 minute) health risk assessment did not affect service quality negatively, but administering a longer (15-18 minute) survey had a modest adverse effect on these indicators.

Conclusions: In 2-1-1 research collaborations, both partners need to understand the dynamic relationship among call volume, research accrual, and service quality and adjust expectations accordingly. If research goals include administering a longer survey, increased staffing of 2-1-1 call centers may be needed to avoid compromising service quality.

Publication types

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

MeSH terms

  • Cooperative Behavior
  • Data Collection / methods
  • Disasters
  • Humans
  • Information Services / organization & administration*
  • Information Services / standards
  • Information Services / statistics & numerical data
  • Linear Models
  • Logistic Models
  • Patient Selection*
  • Quality Indicators, Health Care*
  • Research / organization & administration*
  • Risk Assessment / methods
  • Telephone
  • Time Factors