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Does deprivation affect the demand for NHS Direct? Observational study of routine data from Wales
Julie Peconi1, Steven Macey2, Sarah E Rodgers3,4
1Medical School, Swansea University, Swansea, UK j.peconi@swansea.ac.uk.
Objective:
To estimate the effect of deprivation on the demand for calls to National Health Service Direct Wales (NHSDW) controlling for confounding factors.
Design:
Study of routine data on over 400 000 calls to NHSDW using multiple regression to analyse the logarithms of ward-specific call rates across Wales by characteristics of call, patient and ward, notably the Welsh Index of Multiple Deprivation.
Setting:
810 electoral wards with average population of 3300, defined by 1998 administrative boundaries.
Population:
All calls to NHSDW between January 2002 and June 2004.
Main Outcome Measures:
We used ward populations as denominators to calculate the rates of three categories of calls: calls seeking advice, calls seeking information and all calls combined.
Results:
Confounding variables explained 31% of variation in advice call rates, but only 14% of variation in information call rates and in all call rates (all significant at 0.1% level). However, deprivation was only a statistically significant predictor of information call rates. The proportion of the ward population categorised as 'white' was a highly significant predictor of all three call rates. For advice calls and combined calls, rates decreased highly significantly with the proportion of those who called the service for themselves. Information call rates were higher on weekdays and highest on Mondays, while advice call rates were highest on Sundays.
Conclusions:
Deprivation had no consistent effect on demand for the service and the relationship needs further exploration. While our data may have underestimated the 'need' of deprived patients, they yield no evidence that policy-makers should seek to improve demand from those patients. However, we found differences in the way callers use advice and information calls. Previously unexplored variables that help to predict ward-specific call rates include: ethnicity, day of the week and whether patients made the calls themselves.
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