Performance and Resource Requirements of In-Person, Voice Call, and Automated Telephone-Based Socioeconomic Data Collection Modalities for Community-Based Health Programs

Abstract

Gathering data on socioeconomic status (SES) is a prerequisite for health programs that aim to improve equity. There is a lack of evidence on which approaches offer the best combination of reliability, cost, and acceptability. To compare the performance of different approaches to gathering data on SES in community health programs. A search of the Cochrane Library, MEDLINE, Embase, Global Health, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform, and OpenGrey from 1999 to June 29, 2021, was conducted, with no language limits. Google Scholar was also searched and the reference lists of included articles were checked to identify further studies. The search was performed on June 29, 2021. Any empirical study design was eligible if it compared 2 or more modalities to elicit SES data from the following 3 categories: in-person, voice call, or automated telephone-based systems. Two reviewers independently screened titles, abstracts, and full-text articles and extracted data. They also assessed the risk of bias using Cochrane tools and assessed the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation approach. Findings were synthesized thematically without meta-analysis. Response rate, equivalence, time, costs, and acceptability to patients and health care professionals. The searches returned 3943 records. The 11 included studies reported data on 14 036 individuals from 7 countries, collecting data on 11 socioeconomic domains using 2 or more of the following modes: in-person surveys, computer-assisted telephone interviews (CATIs), and 2 types of automated data collection: interactive voice response calls (IVRs) and web surveys. Response rates were greater than 80% for all modes except IVRs. Equivalence was high across all modes (Cohen κ > 0.5). There were insufficient data to make robust time and cost comparisons. Patients reported high levels of acceptability providing data via IVRs, web surveys, and CATIs. Selecting an appropriate and cost-effective modality to elicit SES data is an important first step toward advancing equitable effective service coverage. This systematic review did not identify evidence that remote and automated data collection modes differed from human-led and in-person approaches in terms of reliability, cost, or acceptability.