Abstract
Samples of outpatient visits often must be used to identify users of a health facility with a given chronic condition. Such samples can lead to biases, however, because patients with more frequent visits are overrepresented. These biases can be avoided by a weighting procedure in which each sampled visit is weighted inversely to the number of clinic visits made by that patient during the sample period. This procedure proved critical in estimating the number and characteristics of hypertensive patients seen in the medical clinic of a teaching hospital. The unweighted estimate of the number of hypertensives was 7,373 patients, more than three times the weighted estimate of 2,250. Similarly,, the number of visits per year by these patients would be overestimated by almost 50 per cent without weighting. The estimated proportion of hypertensives still under treatment after 18 months was 68 per cent without weighting, compared to 51 per cent with weighting. Thus biases from failure to weight may be substantial. Analogous biases and solutions apply to other sampling problems in health services research.