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Randomized Controlled Trial
. 2017 Sep 7;18(1):418.
doi: 10.1186/s13063-017-2159-1.

Implementation and results of an integrated data quality assurance protocol in a randomized controlled trial in Uttar Pradesh, India

Jonathon D Gass Jr  1 , Anamika Misra  2 , Mahendra Nath Singh Yadav  2 , Fatima Sana  2 , Chetna Singh  2 , Anup Mankar  3 , Brandon J Neal  3 , Jennifer Fisher-Bowman  3 , Jenny Maisonneuve  3 , Megan Marx Delaney  3 , Krishan Kumar  2 , Vinay Pratap Singh  2 , Narender Sharma  2 , Atul Gawande  3 , Katherine Semrau  3 , Lisa R Hirschhorn  4
Affiliations
Randomized Controlled Trial

Implementation and results of an integrated data quality assurance protocol in a randomized controlled trial in Uttar Pradesh, India

Jonathon D Gass Jr et al. Trials. .

Abstract

Background: There are few published standards or methodological guidelines for integrating Data Quality Assurance (DQA) protocols into large-scale health systems research trials, especially in resource-limited settings. The BetterBirth Trial is a matched-pair, cluster-randomized controlled trial (RCT) of the BetterBirth Program, which seeks to improve quality of facility-based deliveries and reduce 7-day maternal and neonatal mortality and maternal morbidity in Uttar Pradesh, India. In the trial, over 6300 deliveries were observed and over 153,000 mother-baby pairs across 120 study sites were followed to assess health outcomes. We designed and implemented a robust and integrated DQA system to sustain high-quality data throughout the trial.

Methods: We designed the Data Quality Monitoring and Improvement System (DQMIS) to reinforce six dimensions of data quality: accuracy, reliability, timeliness, completeness, precision, and integrity. The DQMIS was comprised of five functional components: 1) a monitoring and evaluation team to support the system; 2) a DQA protocol, including data collection audits and targets, rapid data feedback, and supportive supervision; 3) training; 4) standard operating procedures for data collection; and 5) an electronic data collection and reporting system. Routine audits by supervisors included double data entry, simultaneous delivery observations, and review of recorded calls to patients. Data feedback reports identified errors automatically, facilitating supportive supervision through a continuous quality improvement model.

Results: The five functional components of the DQMIS successfully reinforced data reliability, timeliness, completeness, precision, and integrity. The DQMIS also resulted in 98.33% accuracy across all data collection activities in the trial. All data collection activities demonstrated improvement in accuracy throughout implementation. Data collectors demonstrated a statistically significant (p = 0.0004) increase in accuracy throughout consecutive audits. The DQMIS was successful, despite an increase from 20 to 130 data collectors.

Conclusions: In the absence of widely disseminated data quality methods and standards for large RCT interventions in limited-resource settings, we developed an integrated DQA system, combining auditing, rapid data feedback, and supportive supervision, which ensured high-quality data and could serve as a model for future health systems research trials. Future efforts should focus on standardization of DQA processes for health systems research.

Trial registration: ClinicalTrials.gov identifier, NCT02148952 . Registered on 13 February 2014.

Keywords: Data Quality Assurance (DQA); Data accuracy; Data feedback; India; Maternal and perinatal mortality; Maternal morbidity; Patient-reported outcomes; Randomized control trial (RCT); Safe Childbirth Checklist (SCC); Supportive supervision; Uttar Pradesh.

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Conflict of interest statement

Ethics approval and consent to participate

Women presenting for childbirth at study facilities and their newborns were enrolled and provided written consent for follow-up prior to their discharge. The call center reconfirmed consent verbally prior to initiating the outcomes questionnaire. The BetterBirth Trial study protocol has been approved by all participating institutions: Community Empowerment Lab (CEL) Ethics Review Committee (Ref no: 2014006) formerly Lucknow Ethics Committee (Ref no: 13/LEC/12), Jawaharlal Nehru Medical College Ethical Review Committee (Ref no: MDC/IECHSR/2015-16/A-53), Institutional Review Board of the Harvard T.H. Chan School of Public Health (Protocol 21975-102), Population Services International Research Ethics Board (Protocol ID: 47.2012), and the Ethical Review Committee of the World Health Organization (Protocol ID: RPC 501). The Indian Council of Medical Research also approved the study (Ref no: 5/7/858/12-RHN). The trial is registered at ClinicalTrials.gov (identifier: NCT02148952).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Data quality accuracy report for patient-reported outcomes
Fig. 2
Fig. 2
Accuracy rate and trend of each data collection activity by month (7 Nov 2014 to 6 Sept 2016). OP observation point
See this image and copyright information in PMC

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