This report is on management strategies for a large multisite, multi-level study of a Community Health Nursing Model For Rural Hispanics funded by the Agency on Health Care Policy and Research.
Objective: The objective was to test three components of community health nursing in four rural communities on the outcomes of health status and health impact. The components were personalized preventive nursing (PPN), organized indigenous caregivers (OIC), and community empowerment (CE).
Design: Four rural communities were randomly assigned (without replacement) to the four treatments in this experimental design. The treatment protocols were to be maintained over time with appropriate modifications.
Population, Sample, Setting, Years: There were approximately 10,000 residents, 50% of whom were Hispanic and 50% non-Hispanic white. All subjects were in the sample for the treatment protocols. However, the outcome measure surveys were randomly assigned to different households, with a total 1,400 households across the communities. Three surveys were done over 5 years. These communities were in sparsely populated, underserved areas of Arizona. The communities were economically depressed and highly dependent upon copper mining. Local residents were employed for the intervention teams, local Public Health Department facilities were used and the Public Health Department was a subcontractor who hired and maintained the intervention staff. The study was conducted from 1990 to 1995 with an additional year for analysis, 1995-1996.
Concepts and Variables: Health care availability, accessibility, acceptability and affordability were concepts on which the treatment protocols were based. These protocols were to be implemented by teams of health care providers operating within the organization of the Public Health Department, which was a subcontractor on the grant. The length of the study and implementation protocols were to be carried out over 3 years in communities that were mostly Hispanic (50%) and white non-Hispanic (50%). Other ethnic groups were less than one percent.
Methods: Two major issues are the focus of the methods described. First, it was known that the multisite study would be difficult to manage given the distances were large and the teams and communities were disparate in their structure and health facilities. Thus, the team of researchers in Tucson was divided up in order to deal with specific components. These were the overall management, the intervention application and the data management. Second, it was known that the measures had to reflect the individual, the family and the community. This yielded a complex multi-level data set for management, analysis and interpretation.
Findings: While these issues known methods were developed to manage them, they did not nearly cover the problems faced over the course of the study. A flood caused damage to approximately ½ of one site with a loss of subjects from the site. The death of a key person in the Public Health Department, a geographic move of another and problems between one of the nurse team leaders and community members were only some of the problems. Constant change in the intervention, the communities and the context of data collection. Unique strategies for data management, each with its own time frame, had to developed and used.
Conclusions: Researchers must be aware of data management and interpretation issues and preplan a scheme to agregate data from one level to another over time, and in communities that experienced much change. The integrity of the data management and analysis was maintained but at a considerably high cost (personnel, time, and complexity) than planned. Thus, adequate budget, personnel and meetings to keep all informed of data management strategies must be planned. In addition, theoretical structure and current research must be used in order to interpret complex and at times conflicting data results.
Implications: The need for attention to these details, management of data, length of time to maintain knowledge of data management among all key personnel and the extent of required resources must be taken into account. Without adequate time, the investigators will quickly find themselves burdened and rapidly lose their understanding of the data. The investigators were, however, challenged and needed every bit theoretical and data management expertise to interpret the findings in this study.
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