China Hypertension and Diabetes Care Cascade Study

Brief Summary

Detailed Description

Hypertension and type 2 diabetes present substantial challenges to the Chinese health system. A nationwide survey revealed a hypertension prevalence of 37.2% among Chinese adults over 35, with only 44.7% aware of their diagnosis and a mere 30.1% receiving antihypertensive treatment, resulting in an overall control rate of 7.2% \[1\]. Similarly, diabetes prevalence in 2018 stood at 12.9%, with awareness and treatment rates of 37% and 33%, respectively \[2\]. Achieving hypertension and diabetes control is conditional on successful progression through screening, diagnosis, management, and control-a continuum demanding care continuity. The care cascade analysis, originally devised for communicable diseases (i.e., HIV and tuberculosis), offers a systematic approach that dissects disease management into a series of interconnected service delivery stages \[3, 4\]. This method evaluates patient progression, unveiling critical drop-offs between each stage. Despite existing population-based surveys detailing the awareness, prevalence and treatment of hypertension and diabetes in China, few studies provide a systematic diagnosis of what happens between stages and devise interventions tailored to each stage of the care cascade. This implementation study aims to identify priorities and formulate strategies to overcome health service delivery bottlenecks associated with hypertension and diabetes in rural China. Leveraging implementation frameworks, the study seeks to unravel the complexities embedded within the care cascade, paving the way for targeted interventions. Addressing the nuanced dynamics of the care cascade, this research will provide indispensable insights for optimising healthcare delivery in resource-limited settings, ultimately informing global perspectives on chronic disease management. The overall aim of this study is to enhance the control of hypertension and diabetes in rural China through a systematic assessment and improvement of the care cascade, specifically: 1. To describe the cascade gap and identify barriers and facilitators at each cascade stage. 2. To develop practical interventions through stakeholder co-design. 3. To assess the effectiveness of developed interventions and evaluate implementation strategies. This is a hybrid design implementation study using mixed methods and integrates diverse implementation theories, models, and frameworks. The theoretical model synthesises the process model, determinant framework, and evaluation framework under the theory of implementation science (Figure 1). The Consolidated Framework for Implementation Research (CFIR) framework identifies multilevel factors influencing implementation. The chronic care model (CCM) is used to inform intervention development. The RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework is used to assess interventions across multiple dimensions. Normalisation Process Theory (NPT) is applied to measure elements critical for successful implementation and integration into routine work. The study will be conducted in Gongyi, Wugang and Weifang counties of China. Study sites are selected by the study team on the basis of their willingness to participate and their proximity to the research team. This study comprises three phases: 1) context analysis and need assessment, 2) intervention development; and 3) implementation and evaluation. In phase one, we will conduct qualitative interviews with policymakers, physicians, primary care health providers and patients. This exploration distill the current state of hypertension and diabetes care in selected counties, identifying determinants within health delivery functions. The Consolidated Framework for Implementation Research (CFIR) framework will guide the assessment, allowing for a nuanced understanding of the intricacies influencing care cascades. Phase two will employ stakeholder-based participatory research to craft targeted interventions. Systematic assessments of barriers identified in phase one will inform this process, facilitated by the CFIR-ERIC tool for mapping potential strategies. The resultant priority actions and interventions will be collaboratively co-designed with local service providers, health administrators, and decision-makers, ensuring a tailored and contextually relevant approach. In phase three, a rigorously designed cluster-randomized controlled trial will be implemented to discern longitudinal changes in hypertension and diabetes care. Forty-eight villages will undergo randomisation into intervention and control groups, employing a 1:1 allocation ratio. Intervention villages will enact strategies developed in phase two, while control villages maintain usual care. The intervention period spans one year. To assess study outcomes at the population level, we will draw two independent random samples comprising 150 participants aged 35 to 74 from each village before and after the intervention. Outcomes measured include patient-level clinical outcomes (i.e., between-group differences in SBP, HbA1c), system-level service outcomes (i.e., successful progression through steps of cascade), and implementation outcomes (i.e., reach, adoption, feasibility, fidelity). Baseline surveys, conducted prior to randomization, aim to blind study staff from intervention allocation. The follow-up survey, performed one year after intervention initiation, will involve participants identified in the baseline survey, supplemented by the recruitment of an additional random sample. Qualitative interviews with stakeholders will be conducted to discern barriers and facilitators encountered during intervention implementation. Furthermore, an economic evaluation from the health services perspective is planned to provide a comprehensive understanding of the intervention's impact on healthcare resource utilisation and cost-effectiveness.

Primary Outcomes

Secondary Outcomes

• Treatment rate at baseline and at 12 month(Baseline and at 12 month)
• Screening rate at baseline and at 12 month(Baseline and at 12 month)
• Diagnosis rate at baseline and at 12 month(Baseline and at 12 month)