Use of a cross-sectional survey to estimate outcome of health care: the example of anxiety and depression

Abstract

Our study proposes that a population-based cross-sectional survey can be used to estimate the outcome of health care by linking general practice morbidity records to the survey. Using the example of anxiety and depression to test this idea, we conducted a survey of an adult population registered with one general practice in the UK. The Hospital Anxiety and Depression (HAD) questionnaire was used to identify cases and controls. After mailing to a randomly selected adult population of 4002, there was an adjusted response rate of 66% (n = 2,606), with 416 (16%) high-score cases, 506 (19%) medium-score cases, and 1684 (65%) low-score controls. All cases were compared with a sample of controls (n = 450). In the 12 months before the survey, the high-score case group had experienced significantly higher GP contacts (n = 377 [91%] versus 354 [79%]), diagnoses for anxiety or depression (119 [29%] versus 21 [5%]), and related drug treatments (111 [27%] versus 22 [5%]) compared with the control sample. Most of the diagnoses and drug treatments had been initiated at least 9 months before the survey. The linkage between the survey and the clinical records suggested that the health outcome of previously identified anxious and depressed patients was poor, with an estimated two-thirds who will not have fully recovered within an average of 9 months. This study demonstrates the potential for using cross-sectional population surveys to estimate not only the need for health care but also the outcome of health care.