Inpatient Non-Communicable Disease Patterns and Influencing Factors in New Zealand and China: A Mixed-Methods Study Protocol
Abstract
Aims To examine both similarities and differences in inpatient non-communicable disease (NCD) patient characteristics, disease patterns and hospitalisation indicators between New Zealand and China, and to explore multilevel factors influencing NCD care across different healthcare contexts from a nursing and health services perspective. Design An explanatory sequential mixed-methods study protocol guided by the Social Ecological Model (SEM). The study comprises two sequential phases: a retrospective quantitative analysis of hospital discharge data, followed by a qualitative phase informed by quantitative findings. Methods In the quantitative phase, de-identified discharge records of adult inpatients (≥16 years) with major non-communicable diseases will be extracted from Waikato Hospital (New Zealand) and the Third People’s Hospital of Yibin (China) for the period 2023–2025. Data will include patient demographics, clinical characteristics, comorbidities and hospital outcomes such as length of stay, in-hospital mortality and 30-day readmission. Comparative analyses and multivariable regression models will be conducted to identify shared patterns as well as context-specific variations in NCD profiles and outcomes across the two settings. In the qualitative phase, semi-structured interviews will be undertaken with nurses and other healthcare professionals involved in inpatient NCD care in both settings. Interviews will be informed by quantitative findings and structured around the five levels of the SEM. Qualitative data will be analysed thematically and integrated with quantitative results using joint displays to explain both convergent and divergent findings. Conclusions This mixed-methods protocol outlines a systematic approach to examining inpatient NCD care across two contrasting healthcare systems. By identifying common patterns alongside context-specific differences, the study aims to generate transferable insights while also accounting for local healthcare structures and practices.
Publication details
- Journal / source
- Open Science Framework
- Publication date
- 1 January 2026