University of Birmingham

NIHR204871

Improving primary healthcare for patients with non-communicable diseases during severe flooding in India

The study is currently not prepared for registration, as the intervention component has yet to be developed. This development will occur during the initial phase of the project, following the completion of two foundational activities: the situational analysis and the formulation of the theory of change. These preliminary steps are critical, as they will provide the necessary insights to guide the design, structure, and content of the intervention. The situational analysis will help identify key contextual factors, needs, and challenges, while the theory of change will articulate the pathways through which the intervention is expected to produce its intended outcomes. Only after these components are thoroughly completed and the intervention is clearly conceptualized and defined will the study proceed to registration. At that point, it will be registered in accordance with all applicable regulatory and ethical requirements to ensure compliance and transparency. The study registration will be completed before the recruitment of the first participant (likely to be in August-October 2025).

Methods - Mixed methods

Dr. Semira Manaseki-Holland (0000-0001-5827-8855)

Dr. Jeemon Panniyammakal (0000-0003-4172-4307)

Dr. Tanvir Ahmed, Project Manager, University of Birmingham

We will follow the Digital Personal Data Protection Act, 2023 (Government of India). https://www.meity.gov.in/static/uploads/2024/06/2bf1f0e9f04e6fb4f8fef35e82c42aa5.pdf The Digital Personal Data Protection Act, 2023 is India’s first comprehensive legislation aimed at regulating the processing of digital personal data to protect individuals’ privacy while enabling lawful data use. The Act emphasizes consent-based data processing, outlining key rights for individuals such as access, correction, erasure, and grievance redressal. It places significant obligations on Data Fiduciaries, requiring them to implement safeguards. To ensure the security of data, the Act requires Data Fiduciaries to implement reasonable safeguards to prevent personal data breaches, including encryption, access controls, periodic risk assessments, and timely breach notifications. Overall, the DPDP Act marks a critical step towards a structured data governance framework in India.

The study will be conducted in community-based settings located in the flood-prone regions of the state of Bihar, India, where seasonal flooding poses recurring challenges to public health infrastructure and service delivery. These settings encompass both rural and semi-urban areas that are particularly vulnerable due to geographic and socio-economic factors. Within these regions, the study will focus on block level institutions (community health centres) and primary healthcare facilities—such as Primary Health Centres (PHCs) and Sub-Centres—and their surrounding catchment areas, which serve as the primary access points for health services for the local population. The selected sites will include communities that vary in population density, accessibility, and exposure to health risks intensified by frequent flooding events. These communities often experience disruptions in healthcare delivery, and communication infrastructure during floods, making them critical areas for targeted intervention. The study will engage with local health workers, community leaders, and residents to understand health system resilience, service utilization patterns, and the socio-environmental context influencing non-communicable disease related health outcomes in these flood-affected settings. This diverse and challenging landscape provides a relevant backdrop for testing context-sensitive, community-informed health interventions aimed at improving preparedness, continuity of care, and health system responsiveness during climate-induced emergencies.

New data will be systematically collected using structured electronic Case Report Forms (eCRFs), which will be specifically developed and managed within the REDCap (Research Electronic Data Capture) platform. The REDCap system will be securely hosted at one of the partner institutions and will serves as the designated Data Centre for the study, ensuring compliance with data governance and security standards. Data collection will take place in selected flood-prone communities across Bihar and will involve a combination of face-to-face interviews, physical health assessments, and longitudinal follow-up of patients living with non-communicable diseases (NCDs) over a six-month period. Trained field investigators will visit households and primary healthcare facilities to engage participants, obtain informed consent, and conduct structured interviews. These interviews will capture a range of information, including demographic details (age, sex, socioeconomic status), clinical parameters (diagnosis, comorbidities, current treatment regimens), health service utilization (frequency of visits, type of services accessed, barriers to access), and treatment burden (e.g., medication adherence, self-care demands, out-of-pocket costs, and caregiving responsibilities). To ensure cultural and linguistic appropriateness, all study instruments—including consent forms, interview guides, and eCRFs—will be translated into local languages, primarily Hindi and relevant regional dialects spoken in the target communities. These translations will undergo forward and backward translation, followed by pre-testing in the field to confirm clarity, accuracy, and contextual relevance. Standardized tools and validated instruments will be embedded within the eCRFs to ensure consistency and quality of data. Health assessments may include measurements such as blood pressure, weight, and blood glucose levels, conducted using portable diagnostic devices where applicable. Field teams equipped with tablets or laptops will enter data directly into the REDCap platform in real time or upload data in batches when internet connectivity is limited. Data entry will be monitored remotely, with automated validation checks and regular quality assurance reviews to ensure completeness and accuracy. The longitudinal design of the study, with follow-ups at six months, will enable the capture of changes in health status, service use, and treatment experiences over time, contributing valuable insights into the management of NCDs in disaster-prone, resource-constrained settings. Strong data security protocols will be maintained throughout the study. Data transmission from the field to the central server will be encrypted, and all devices used for data collection will be password-protected. Access to the REDCap platform will be restricted to authorized personnel through role-based user permissions, and all activities will be logged for audit purposes. Personal identifiers will be stored separately from analytical datasets, and de-identified data will be used for analysis to maintain participant confidentiality. Regular data backups, security audits, and compliance with institutional and national data protection guidelines—including those outlined in the Digital Personal Data Protection Act, 2023—will be strictly enforced.

The study will generate both quantitative and qualitative data to evaluate the impact of an intervention aimed at strengthening primary healthcare for patients with non-communicable diseases (NCDs) during and after flooding events. Quantitative data will include demographic characteristics (such as age, gender, education, and socioeconomic status), clinical information (including type and duration of NCDs, current treatments, and comorbidities), and data on healthcare service utilisation during and after floods. The study will also collect information related to key domains such as mental wellbeing, quality of life, medication adherence, respiratory symptom burden, and the impact of flooding on access to care and disease management. In addition, qualitative data will be collected through interviews and focus group discussions with patients, healthcare providers, and community members. These will explore personal experiences with healthcare access, the challenges encountered during flooding, and the ways in which individuals and communities respond to such disruptions. Quantitative data will be entered directly into REDCap using structured electronic Case Report Forms (eCRFs) and will be exportable in commonly used formats such as CSV, Excel, or statistical software files. Qualitative data will be recorded as audio files and transcribed into text documents. We estimate collecting data from around 2,000 participants across 20 clusters, generating approximately 300–400 MB of quantitative data and 2–5 GB of qualitative data throughout the study period.

A range of data quality control measures will be implemented to ensure the accuracy, completeness, and reliability of both quantitative and qualitative data collected in the study. A comprehensive, multi-layered strategy will be adopted, including both field-level procedures and central oversight mechanisms. For quantitative data, electronic data capture will be conducted using REDCap with built-in validation rules such as range checks, logical consistency, skip patterns, and mandatory response fields to minimise data entry errors. The electronic case report forms (eCRFs) will be pre-tested and refined during a piloting phase to ensure usability, clarity, and internal logic. Field investigators will receive structured training in study protocols, ethics, informed consent procedures, and device use. Regular field monitoring visits will be conducted by supervisors to ensure adherence to protocols and to verify a subset of entries. At least 2% of all CRF pages will be independently reviewed for completeness and accuracy. Central statistical monitoring will include automated and manual checks for missing data, inconsistencies, unusual response patterns, and outliers. Weekly data quality reports will be generated to flag anomalies, and corrective actions will be implemented promptly. Internal review meetings will be held regularly with data collectors, supervisors, and investigators to ensure continuous quality improvement. For qualitative data, interviews and focus group discussions will be audio-recorded with participant consent and transcribed verbatim. Transcripts will be reviewed for accuracy against recordings. A coding framework will be developed and applied consistently by trained qualitative researchers. Inter-coder reliability will be maintained through double coding of a subset of transcripts and regular team discussions to resolve discrepancies. Data quality will also be ensured through structured training of field staff in qualitative methods and ethical practices.

All study data will be securely stored using institutional and project-specific data management systems of one the partners as per the regulation of the Department of Science and Technology, Government of India. Quantitative data will be collected electronically using REDCap, a secure, cloud-based data capture platform hosted on password-protected servers with restricted access. Data entered via handheld tablets will be synced daily to the central server, ensuring encryption both during transmission and at rest. Access to the REDCap system will be limited to authorised personnel only, with role-based permissions ensuring users can only access data relevant to their specific responsibilities. Regular automated backups of the database will be scheduled to ensure data integrity and recovery in case of system failures. Qualitative data, including audio recordings and transcripts, will be stored on encrypted institutional drives with password protection and version control. Transcripts and related documents will be de-identified before storage, with identifying details stored separately in a secure, access-restricted file. To further ensure data security and prevent loss, regular backup procedures will be followed. Backups will be conducted daily, with copies stored in a separate, secure location to protect against potential data corruption or hardware failure. All backups will be encrypted, and access will be restricted to authorised personnel only. Physical records and documents (such as consent forms) will be stored in a locked, secure location with limited access to study staff. Additionally, the data management team will conduct regular reviews of the backup procedures to ensure they are functioning correctly, and that data integrity is maintained throughout the study.

Data Encryption: All data, including quantitative and qualitative data, will be encrypted during transmission and at rest. For electronic data collected via REDCap, encrypted communication channels will be used to ensure that data is secure while being transmitted between devices and servers. Data stored on the central server will be encrypted and accessible only to authorised personnel. Access Control: Access to study data will be strictly controlled. Only authorised personnel will be granted access to the data, with role-based permissions in place to ensure users only access data pertinent to their responsibilities. Sensitive data will be further protected by limiting access to specific roles based on the principle of least privilege. Data Anonymisation and De-identification: All sensitive data, particularly personal identifying information, will be anonymised or de-identified before storage. For qualitative data (e.g. interviews, focus groups), transcripts will be stripped of any personally identifiable information (PII). Identifying details will be stored separately and securely, ensuring that individuals cannot be identified from the data. Secure Data Storage: Quantitative data will be stored in REDCap, which is a secure, cloud-based data capture platform. This platform is hosted on password-protected servers with encrypted storage. Qualitative data, including audio recordings and transcripts, will be stored on encrypted institutional drives with password protection and version control. Physical Security: Physical records, such as signed consent forms, will be stored in a locked and secure location with restricted access to study personnel. All hard copies of sensitive data will be kept in a secure, monitored environment to prevent unauthorized access. Regular Audits and Monitoring: Continuous monitoring of data access logs will be carried out to detect any unauthorized access or suspicious activities. The data management team will conduct periodic security audits to ensure that all data security protocols are being followed and that there are no vulnerabilities in the system. Training and Awareness: All study staff involved in data collection, entry, and analysis will undergo training on data protection and security measures, including best practices for handling sensitive data. This ensures that everyone involved in the study is aware of their responsibilities and the importance of maintaining confidentiality.

Data will be shared after the publication of study findings, in accordance with institutional policies and ethical approvals. Anonymised transcripts and relevant datasets may be made available upon reasonable request to the lead investigator (Dr. Semira Manaseki-Holland) or the joint lead investigator (Dr. Jeemon Panniyammakal). Each request will be reviewed by the study’s publication committee to assess its scientific merit, ethical compliance, and alignment with the study’s data sharing policy. These considerations will be managed on a case-by-case basis to ensure ethical and responsible sharing of data. Data will be shared in a de-identified format to ensure participant confidentiality. Any personal identifiers will be removed prior to sharing. Data sharing agreements may be required depending on the nature of the request and the legal requirements of the collaborating institutions. Legal guidance will be sought from both the University of Birmingham and SCTIMST to determine whether such agreements are necessary.

At the end of the study, data that support published findings, have potential for reuse, or are required to meet institutional or funder obligations will be selected for long-term preservation. All personal identifiers will be stored separately from research data and linked only via participant IDs, with access restricted to relevant study staff. Preserved data will be retained at the University of Birmingham for a minimum of 10 years following final publication, in accordance with the University’s data retention and archiving policies. Appropriate repositories, such as the University of Birmingham’s Institutional Research Archive (UBIRA), will be used to ensure secure, long-term storage, with procedures guided by institutional and legal requirements to uphold confidentiality and enable future reuse.

Quantitative data will be stored in a widely used statistical format (.dta), and qualitative data such as interview transcripts will be provided in accessible text-based formats (e.g. .docx or .txt). To enable appropriate interpretation and analysis, supporting documentation such as codebooks, data dictionaries, and metadata will also be shared in standard formats (e.g. .pdf or .csv). These files can be accessed using commonly available tools suitable for statistical and textual analysis, ensuring that future users can work with the data effectively without requiring specialised software.

The responsibility for data management will rest with the designated data manager under the oversight of the joint lead investigator, Dr. Jeemon Panniyammakal. The data manager will coordinate day-to-day data handling, including storage, quality assurance, and access control, in line with institutional policies and ethical requirements. The overall data stewardship, including long-term preservation, compliance, and data sharing decisions, will be jointly overseen by Dr. Semira Manaseki-Holland (University of Birmingham) and Dr. Jeemon Panniyammakal (SCTIMST).

Adequate financial and human resources will be allocated throughout the study to ensure robust data management and compliance with FAIR (Findable, Accessible, Interoperable and Re-usable) principles. Dedicated personnel, including a full-time data manager, trained field staff, and supervisors, will be responsible for quality data collection, entry, validation, and documentation. Time will be allocated for staff training in data protocols, ongoing data quality monitoring, and maintaining comprehensive metadata and documentation to support interoperability and long-term reusability. As both collaborating institutions already have the necessary data infrastructure in place, including secure storage and access systems, no additional costs for software licences or cloud storage are anticipated.