Operationalizing independent oversight in large-scale public health cohorts: Monitoring protocol for the NIMHANS–NH–SKAN Stroke project

Background onitoring the implementation of observational studies are rare, unlike experimental studies. This article aims to describe the development and implementation of a monitoring plan and framework for a large-scale cohort and quasi-experimental study: the NIMHANS-NH-SKAN Stroke project. Methods The monitoring framework was developed through a systematic, stepwise process involving expert consultation workshops conducted by an Independent Monitoring Team in collaboration with the study team. A logical framework approach was used to identify key processes throughout the study implementation. These processes were then disaggregated into critical activities (sub-processes) to generate an initial list of monitoring items. These items were prioritized using the Vital–Essential–Desirable (VED) strategy through consensus building. The shortlisted items were further refined using SMART criteria (Specific, Measurable, Achievable, Relevant, and Time-bound) to finalize checklist components. Key Performance Indicators were subsequently derived from the finalized checklist items. The framework emphasized usability, feasibility, and relevance to implementation, enabling systematic monitoring of critical study processes. Results A total of 89 activities were identified and consolidated into 10 checklists, from which 16 Key Performance Indicators (KPIs) were derived. The monitoring framework primarily emphasized indicator-based assessment of project outputs and outcomes while ensuring adherence to key processes and quality standards. KPIs were expressed as proportions to facilitate standardized performance assessment across sites and time periods. The checklists comprised a combination of in-person observations and record reviews. Monitoring findings were synthesized into periodic reports based on KPI proportions, enabling objective evaluation of implementation performance and identification of areas requiring corrective action. Conclusions Timely and systematic monitoring is critical to ensure rigor in large-scale projects, and the approach described in this study provides a replicable framework for the development of robust monitoring systems in similar community-based large-scale observational studies in India and similar countries.