Does Deprivation Affect the Demand for NHS Direct? Observational Study of Routine Data from Wales

Overview

Journal BMJ Open

Specialty General Medicine

Date 2019 Oct 13

PMID 31604783

Citations 2

Authors

Julie Peconi

Steven Macey

Sarah E Rodgers

Ian T Russell

Helen Snooks

Alan Watkins

Affiliations

Soon will be listed here.

Abstract

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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References

Burt J, Hooper R, Jessopp L . The relationship between use of NHS Direct and deprivation in southeast London: an ecological analysis. J Public Health Med. 2003; 25(2):174-6. DOI: 10.1093/pubmed/fdg038. View

Ring F, Jones M . NHS Direct usage in a GP population of children under 5 years: is NHS Direct used by people with the greatest health need?. Br J Gen Pract. 2004; 54(500):211-3. PMC: 1314833. View

Peconi J, Macey S, Rodgers S, Russell I, Snooks H, Watkins A . Advice given by NHS Direct in Wales: do deprived patients get more urgent decisions? Study of routine data. J Epidemiol Community Health. 2017; . PMC: 5561357. DOI: 10.1136/jech-2017-208978. View

Lyons R, Jones K, John G, Brooks C, Verplancke J, Ford D . The SAIL databank: linking multiple health and social care datasets. BMC Med Inform Decis Mak. 2009; 9:3. PMC: 2648953. DOI: 10.1186/1472-6947-9-3. View

Hsu W, Bath P, Large S, Williams S . The association of geographical location and neighbourhood deprivation with older people's use of NHS Direct: a population-based study. Age Ageing. 2012; 42(1):57-62. DOI: 10.1093/ageing/afs120. View

Dixon-Woods M, Cavers D, Agarwal S, Annandale E, Arthur A, Harvey J . Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups. BMC Med Res Methodol. 2006; 6:35. PMC: 1559637. DOI: 10.1186/1471-2288-6-35. View

Knowles E, Munro J, OCathain A, Nicholl J . Equity of access to health care. Evidence from NHS Direct in the UK. J Telemed Telecare. 2006; 12(5):262-5. DOI: 10.1258/135763306777889091. View

Judge A, Welton N, Sandhu J, Ben-Shlomo Y . Equity in access to total joint replacement of the hip and knee in England: cross sectional study. BMJ. 2010; 341:c4092. PMC: 2920379. DOI: 10.1136/bmj.c4092. View

Cooper D, Arnold E, Smith G, Hollyoak V, Chinemana F, Baker M . The effect of deprivation, age and sex on NHS Direct call rates. Br J Gen Pract. 2005; 55(513):287-91. PMC: 1463131. View

10.

Morgenstern H . Uses of ecologic analysis in epidemiologic research. Am J Public Health. 1982; 72(12):1336-44. PMC: 1650553. DOI: 10.2105/ajph.72.12.1336. View

11.

George S . NHS Direct audited. BMJ. 2002; 324(7337):558-9. PMC: 1122495. DOI: 10.1136/bmj.324.7337.558. View

12.

Turnbull J, Pope C, Martin D, Lattimer V . Do telephones overcome geographical barriers to general practice out-of-hours services? Mixed-methods study of parents with young children. J Health Serv Res Policy. 2009; 15(1):21-7. DOI: 10.1258/jhsrp.2009.009023. View

13.

OReilly D, Stevenson M, Mccay C, Jamison J . General practice out-of-hours service, variations in use and equality in access to a doctor: a cross-sectional study. Br J Gen Pract. 2001; 51(469):625-9. PMC: 1314071. View

14.

Turnbull J, Martin D, Lattimer V, Pope C, Culliford D . Does distance matter? Geographical variation in GP out-of-hours service use: an observational study. Br J Gen Pract. 2008; 58(552):471-7. PMC: 2441507. DOI: 10.3399/bjgp08X319431. View

15.

Cook E, Randhawa G, Large S, Guppy A, Chater A . A U.K. case study of who uses NHS direct: investigating the impact of age, gender, and deprivation on the utilization of NHS direct. Telemed J E Health. 2012; 18(9):693-8. DOI: 10.1089/tmj.2011.0256. View

16.

Victora C, VAUGHAN J, Barros F, Silva A, Tomasi E . Explaining trends in inequities: evidence from Brazilian child health studies. Lancet. 2000; 356(9235):1093-8. DOI: 10.1016/S0140-6736(00)02741-0. View

17.

Hanigan I, Hall G, Dear K . A comparison of methods for calculating population exposure estimates of daily weather for health research. Int J Health Geogr. 2006; 5:38. PMC: 1592542. DOI: 10.1186/1476-072X-5-38. View

18.

Shah S, Cook D . Socio-economic determinants of casualty and NHS Direct use. J Public Health (Oxf). 2008; 30(1):75-81. DOI: 10.1093/pubmed/fdn001. View

19.

Snooks H, Williams A, Griffiths L, Peconi J, Rance J, Snelgrove S . Real nursing? The development of telenursing. J Adv Nurs. 2008; 61(6):631-40. DOI: 10.1111/j.1365-2648.2007.04546.x. View