Summary
Background: Routine implementation of instruments to capture patient-reported outcomes could guide clinical practice and facilitate health services research. Audio interviews facilitate self-interviews across literacy levels.
Objectives: To evaluate time burden for patients, and factors associated with response times for an audio computer-assisted self interview (ACASI) system integrated into the clinical workflow.
Methods: We developed an ACASI system, integrated with a research data warehouse. Instruments for symptom burden, self-reported health, depression screening, tobacco use, and patient satisfaction were administered through touch-screen monitors in the general medicine clinic at the Cook County Health & Hospitals System during April 8, 2011-July 27, 2012. We performed a cross-sectional study to evaluate the mean time burden per item and for each module of instruments; we evaluated factors associated with longer response latency.
Results: Among 1,670 interviews, the mean per-question response time was 18.4 [SD, 6.1] seconds. By multivariable analysis, age was most strongly associated with prolonged response time and increased per decade compared to < 50 years as follows (additional seconds per question; 95% CI): 50–59 years (1.4; 0.7 to 2.1 seconds); 60–69 (3.4; 2.6 to 4.1); 70–79 (5.1; 4.0 to 6.1); and 80–89 (5.5; 4.1 to 7.0). Response times also were longer for Spanish language (3.9; 2.9 to 4.9); no home computer use (3.3; 2.8 to 3.9); and, low mental self-reported health (0.6; 0.0 to 1.1). However, most interviews were completed within 10 minutes.
Conclusions: An ACASI software system can be included in a patient visit and adds minimal time burden. The burden was greatest for older patients, interviews in Spanish, and for those with less computer exposure. A patient’s self-reported health had minimal impact on response times.
Citation: Trick WE, Deamant C, Smith J, Garcia D, Angulo F. Implementation of an audio computer-assisted self-interview (ACASI) system in a general medicine clinic – patient response burden. Appl Clin Inf 2015; 6: 148–162
http://dx.doi.org/10.4338/ACI-2014-09-RA-0073
Keywords
Computers - software - quality of life - symptoms - patient-centered outcome research
