Search

We examined the importance of understanding and incorporating cultural context within Aotearoa/New Zealand when engaging in clinical research and practice. This paper reports on the qualitative findings of a mixed methods study aimed at determining what effect a cardiac risk reduction exercise and lifestyle management programme, embedded within a kaupapa Māori methodological approach, had on Māori participants. This methodology saw participants able to redevelop a western model cardiac risk reduction programme by introducing a Māori worldview. Our study revealed how the kaupapa Māori approach empowered participants to examine and evaluate not only their own health and lifestyle choices, but those of family and the wider community. Combining biomedical and kaupapa Māori components into the programme was found to benefit participants' mental, physical, spiritual and family well-being. [ABSTRACT FROM AUTHOR]

Distributed networks of health-care data sources are increasingly being utilized to conduct pharmacoepidemio-logic database studies. Such networks may contain data that are not physically pooled but instead are distributed horizontally (separate patients within each data source) or vertically (separate measures within each data source) in order to preserve patient privacy. While multivariable methods for the analysis of horizontally distributed data are frequently employed, few practical approaches have been put forth to deal with vertically distributed healthcare databases. In this paper, we propose 2 propensity score-based approaches to vertically distributed data analysis and test their performance using 5 example studies. We found that these approaches produced point estimates close to what could be achieved without partitioning. We further found a performance benefit (i.e., lower mean squared error) for sequentially passing a propensity score through each data domain (called the "sequential approach") as compared with fitting separate domain-specific propensity scores (called the "parallel approach"). These results were validated in a small simulation study. This proof-of-concept study suggests a new multivariable analysis approach to vertically distributed health-care databases that is practical, preserves patient privacy, and warrants further investigation for use in clinical research applications that rely on health-care databases. [ABSTRACT FROM AUTHOR]