Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project.
OBJECTIVE
Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis.


RESULTS
In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores.


CONCLUSIONS
Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.
Tolonen
Hanna
H
Department of Epidemiology and Health Promotion, National Public Health Institute, Helsinki, Finland. hanna.tolonen@ktl.fi
Dobson
Annette
A
Kulathinal
Sangita
S
D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D002784:Cholesterol / Q000097:blood; D003625:Data Collection / Q000379:methods / Q000592:standards*; D004812:Epidemiologic Methods; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D011786:Quality Control; D012189:Retrospective Studies; D012307:Risk Factors; D011795:Surveys and Questionnaires / Q000592:standards; D014944:World Health Organization
D002784:Cholesterol