Annual night visiting rates in 129 general practices in one family health services authority: association with patient and general practice characteristics

Abstract

Background: Rates of night visiting by general practitioners have increased steadily over the last 30 years and vary widely between general practices.

Aim: An ecological study was carried out to examine night visiting rates by general practices in one family health services authority, and to determine the extent to which differences in night visiting rates between practices could be explained by patient and practice characteristics.

Method: The study examined the variation in annual night visiting rates, based on night visit fees claimed between April 1993 and March 1994, among 129 general practices in Merton, Sutton and Wandsworth Family Health Services Authority, London.

Results: Practices' annual night visiting rates varied from three per 1000 to 75 per 1000 patients. The percentages of the practice population aged under five years and aged five to 14 years were both positively correlated with night visiting rates (r = 0.38 and r = 0.35, respectively), as were variables associated with social deprivation such as the estimated percentage of the practice population living in one-parent households (r = 0.24) and in households where the head of household was classified as unskilled (r = 0.20). The percentage of the practice population reporting chronic illness was also positively associated with night visiting rates (r = 0.26). The percentages of the practice population aged 35 to 44 years and 45 to 54 years were both negatively associated with night visiting rates (r = -0.34 and r = -0.31, respectively) as was the estimated list inflation for a practice (r = -0.31). There was no significant correlation between night visiting rates and the distance of the main practice surgery from the nearest hospital accident and emergency department. There was also no association between night visiting rates and permission to use a deputizing service. In a stepwise multiple regression model, the multiple correlation coefficient was 0.56 with four factors (percentage of the practice population aged under five years, percentage aged 35-44 years, percentage who were chronically ill and estimated list inflation) explaining 32% of the variation in night visiting rates.

Conclusion: Only about one third of the variation in night visiting rates between practices could be explained by patient and practice variables derived from routine data. Population-based research using data collected on individual patients and practices is required to improve current understanding of the patient and practice characteristics that influence the demand for night visits and of why night visiting rates vary so widely between practices.