Impact of methodological "shortcuts" in conducting public health surveys: results from a vaccination coverage survey

• Published in: BMC public health Vol. 8; no. 1; p. 99
• Main Authors: Luman, Elizabeth T, Sablan, Mariana, Stokley, Shannon, McCauley, Mary M, Shaw, Kate M
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27-03-2008; BioMed Central; BMC
• Subjects: Child; Child, Preschool; Health Care Surveys - methods; Humans; Infant; Public health; Public Health - statistics & numerical data; Surveys; Vaccination; Vaccination - utilization; United States
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/1471-2458-8-99

Lack of methodological rigor can cause survey error, leading to biased results and suboptimal public health response. This study focused on the potential impact of 3 methodological "shortcuts" pertaining to field surveys: relying on a single source for critical data, failing to repeatedly visit households to improve response rates, and excluding remote areas.
In a vaccination coverage survey of young children conducted in the Commonwealth of the Northern Mariana Islands in July 2005, 3 sources of vaccination information were used, multiple follow-up visits were made, and all inhabited areas were included in the sampling frame. Results are calculated with and without these strategies.
Most children had at least 2 sources of data; vaccination coverage estimated from any single source was substantially lower than from all sources combined. Eligibility was ascertained for 79% of households after the initial visit and for 94% of households after follow-up visits; vaccination coverage rates were similar with and without follow-up. Coverage among children on remote islands differed substantially from that of their counterparts on the main island indicating a programmatic need for locality-specific information; excluding remote islands from the survey would have had little effect on overall estimates due to small populations and divergent results.
Strategies to reduce sources of survey error should be maximized in public health surveys. The impact of the 3 strategies illustrated here will vary depending on the primary outcomes of interest and local situations. Survey limitations such as potential for error should be well-documented, and the likely direction and magnitude of bias should be considered.