This research will be done primarily in Jinan, China at Shandong University with Dr. Shixue Li, as an extension of NIH Grant # R01NR008226. Aging is a worldwide population and public health issue. China has the largest and one of the most rapidly growing elderly populations in the world. China's elder care has long depended upon acute care and family support, but with China's rapid economic development, the traditional multi-generational family has declined. As a result, nursing home care is now considered to be an option for the elderly who need institutionalized care, but who lack family support. However, nursing home care is in its infancy, and basic knowledge of nursing home needs, supply, and quality of care are lacking. Our research team believes that the research methods and findings developed in US nursing homes will benefit China. In return, we could learn from China's culture of family and community support of the elderly and family-oriented nursing homes. Based on our NIH R01 and other research by the team, this project examines whether our parent research results could be applied to China, and seeks to build nursing home research capacity in China.
The aims of this project are to: 1) investigate the perceived nursing home needs (type, magnitude, intensity and variability) of elder residents in both urban and rural areas;2) examine the potential gap between nursing home needs and supply;3) identify the effect of nurse staffing on nursing care quality, controlling the effects of institutional contextual and market factors;4) use focus groups to better understand the results of Aim 3 and determine the future development of nursing home care in China;5) establish a LTC research laboratory and train a research fellow at Shandong University, Jinan, China;and 6) disseminate study findings and provide recommendations on nursing home development for the Chinese government. In the long-run we wish to apply the knowledge we gain from this project to other regions in China and other developing countries. Specific research tasks are: 1) translate a community needs assessment (CNA) instrument into simplified Chinese;randomly choose 1,000 elderly in Jinan, administer the survey to this sample, evaluate the appropriateness of the adaptation of the CNA instrument, and conduct a needs assessment survey;2) collect nursing home supply data in Jinan and compare nursing home supply and resident needs;3) obtain administrative and resident data and examine the impact of nurse staffing on the quality of care, using two- level structural equation modeling;4) conduct focus groups with government officers, nursing home administrators, providers and residents to understand their perceptions of current nursing home services and preparedness for future nursing home care;5) provide policy recommendations to the Chinese government and disseminate major findings through reports, publications, and presentations. Capacity-building tasks are: 1) establish a LTC Research Laboratory in Shandong University. This laboratory will be the first LTC research laboratory in China;2) train the project fellow to develop a research agenda and capability in nursing home research;3) produce an adaptive protocol for establishing another LTC research laboratory with researchers in other provinces in China.
A better understanding of the nursing home industry in China, and adapting and learning from US nursing home experiences, will greatly benefit long term care systems in China and other developing countries. In return, developed countries, such as the U.S., can learn from China's culture of family and community support of the elderly and family-oriented nursing homes. This project will promote both of these goals.
| Wan, Thomas T H; Demachkie Masri, Maysoun; Ortiz, Judith et al. (2014) Willingness to participate in accountable care organizations: health care managers' perspective. Health Care Manag (Frederick) 33:64-74 |
| Wu, Min; Li, Shi Xue; Zhang, Ning Jackie et al. (2012) Nursing home research in Jinan, China: a focus group approach. Int J Public Pol 8:21-30 |
