BACKGROUND: Clinical trials conducted in rural resource-poor settings face special challenges in ensuring quality of data collection and handling. The variable nature of these challenges, ways to overcome them, and the resulting data quality are rarely reported in the literature. PURPOSE: To provide a detailed example of establishing local data handling capacity for a clinical trial conducted in a rural area, highlight challenges and solutions in establishing such capacity, and to report the data quality obtained by the trial. METHODS: We provide a descriptive case study of a data system for biological samples and questionnaire data, and the problems encountered during its implementation. To determine the quality of data we analyzed test-retest studies using Kappa statistics of inter- and intra-observer agreement on categorical data. We calculated Technical Errors of Measurement of anthropometric measurements, audit trail analysis was done to assess error correction rates, and residual error rates were calculated by database-to-source document comparison. RESULTS: Initial difficulties included the unavailability of experienced research nurses, programmers and data managers in this rural area and the difficulty of designing new software tools and a complex database while making them error-free. National and international collaboration and external monitoring helped ensure good data handling and implementation of good clinical practice. Data collection, fieldwork supervision and query handling depended on streamlined transport over large distances. The involvement of a community advisory board was helpful in addressing cultural issues and establishing community acceptability of data collection methods. Data accessibility for safety monitoring required special attention. Kappa values and Technical Errors of Measurement showed acceptable values. Residual error rates in key variables were low. LIMITATIONS: The article describes the experience of a single-site trial and does not address challenges particular to multi-site trials. CONCLUSIONS: Obtaining and maintaining data integrity in rural clinical trials is feasible, can result in acceptable data quality and can be used to develop capacity in developing country sites. It does, however, involve special challenges and requirements.
RCT Entities:
BACKGROUND: Clinical trials conducted in rural resource-poor settings face special challenges in ensuring quality of data collection and handling. The variable nature of these challenges, ways to overcome them, and the resulting data quality are rarely reported in the literature. PURPOSE: To provide a detailed example of establishing local data handling capacity for a clinical trial conducted in a rural area, highlight challenges and solutions in establishing such capacity, and to report the data quality obtained by the trial. METHODS: We provide a descriptive case study of a data system for biological samples and questionnaire data, and the problems encountered during its implementation. To determine the quality of data we analyzed test-retest studies using Kappa statistics of inter- and intra-observer agreement on categorical data. We calculated Technical Errors of Measurement of anthropometric measurements, audit trail analysis was done to assess error correction rates, and residual error rates were calculated by database-to-source document comparison. RESULTS: Initial difficulties included the unavailability of experienced research nurses, programmers and data managers in this rural area and the difficulty of designing new software tools and a complex database while making them error-free. National and international collaboration and external monitoring helped ensure good data handling and implementation of good clinical practice. Data collection, fieldwork supervision and query handling depended on streamlined transport over large distances. The involvement of a community advisory board was helpful in addressing cultural issues and establishing community acceptability of data collection methods. Data accessibility for safety monitoring required special attention. Kappa values and Technical Errors of Measurement showed acceptable values. Residual error rates in key variables were low. LIMITATIONS: The article describes the experience of a single-site trial and does not address challenges particular to multi-site trials. CONCLUSIONS: Obtaining and maintaining data integrity in rural clinical trials is feasible, can result in acceptable data quality and can be used to develop capacity in developing country sites. It does, however, involve special challenges and requirements.
Authors: Meera K Chhagan; Jan Van den Broeck; Kany-Kany A Luabeya; Nontobeko Mpontshane; Andrew Tomkins; Michael L Bennish Journal: BMC Public Health Date: 2010-03-18 Impact factor: 3.295
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