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Advances and Applications in Statistics

Advances and Applications in Statistics
Volume 6, Issue 3, Pages 335 - 351 (December 2006)

MODELLING HOSPITAL ACTIVITY: ACCOUNTING FOR SMALL AREA AND PRIMARY CARE PRACTICE VARIATION Peter Congdon (United Kingdom) Received May 23, 2006 References:
[1] R. Andrews, G. Boyne and R. Walker, Deprivation and Local Authority Performance: the Implications for CPA, Centre for Local and Regional Government Research, Cardiff University (CLRGR Discussion Paper No. 10), 2004. [2] J. Besag, J. York and A. Mollie, Bayesian image restoration with two applications in spatial statistics, Ann. Inst. Statist. Math. 43 (1991), 1-59. [3] R. Carr-Hill, G. Hardman, S. Martin, S. Peacock, T. Sheldon and P. Smith, A formula for distributing NHS revenues based on small area use of hospital beds, Centre for Health Economics, University of York, Occasional Paper 22, 1994. [4] V. Carstairs, Deprivation indices: their interpretation and use in relation to health, J. Epidemiol Community Health 49 (Suppl) (1995), S3-8. [5] P. Congdon and N. Best, Small area variation in hospital admission rates: adjusting for referral and provider variation, J. Roy. Statist. Soc. Ser. C 49 (2000), 207-226. [6] E. Dreassi and A. Biggeri, Incorporating gravity model principles into disease mapping, Biom. J. 45 (2003), 207-217. [7] J. Furler, E. Harris, P. Chondros, P. Powell Davies, M. Harris and D. Young, The inverse care law revisited: impact of disadvantaged location on accessing longer GP consultation times, Med. J. Aust. 177 (2002), 78-79. [8] A. Gelfand, S. Sahu and B. Carlin, Efficient parameterizations for normal linear mixed models, Biometrika 82 (1995), 479-488. [9] A. Gelman, J. Carlin, H. Stern and D. Rubin, Bayesian Data Analysis, 2nd ed., CRC Press, 2003. [10] M. Guagliardo, Spatial accessibility of primary care: concepts, methods and challenges, Internat. J. Health Geographics 3 (2004), 1-13. [11] M. Gulliford, Availability of primary care doctors and population health in England: is there an association?, J. Public Health Medicine 24 (2002), 252-254. [12] L. Knorr-Held, Bayesian modelling of inseparable space-time variation in disease risk, Statistics in Medicine 19 (2000), 2555-2567. [13] I. Langford, A. Leyland, J. Rasbash and H. Goldstein, Multilevel modelling of the geographical distributions of diseases, J. Roy. Statist. Soc. Ser. C 48 (1999), 253-268. [14] G. Lin, D. Allan and M. Penning, Examining distance effects on hospitalizations using GIS: a study of three health regions in British Columbia, Canada, Environment and Planning A 34 (2002), 2037-2053. [15] P. McCullagh and J. Nelder, Generalized Linear Models, Chapman & Hall/CRC, 1989. [16] M. Noble, G. Smith, B. Penhale, G. Wright, C. Dibben and M. Lloyd, Measuring Multiple Deprivation at the Small Area Level: The Indices of Deprivation 2000, Dept. of Environment, Transport & Regions, Regeneration Series Reports, December 2000. [17] C. Phibbs and H. Luft, Correlation of travel time on roads versus straight line distance, Medical Care Research and Review 52 (1995), 532-542. [18] D. Spiegelhalter, N. Best, B. Carlin, A. van der Linde, Bayesian measures of model complexity and fit, J. Roy. Statist. Soc. Ser. B 64 (2002), 583-639. [19] S. Vines, W. Gilks and P. Wild, Fitting Bayesian multiple random effects models, Stat. Comput. 6 (1996), 337-346. [20] F. Wang and M. Wall, Generalized common spatial factor model, Biostatistics 4 (2003), 569-582. [21] J. Weissman, C. Gatsonis and A. Epstein, Rates of avoidable hospitalization by insurance status in Massachusetts and Maryland, J. American Medical Association 268 (1992), 2388-2394. [22] R. Wolpert and K. Ickstadt, Poisson/gamma random fields models for spatial statistics, Biometrika 85 (1998), 251-267.

Keywords and phrases: geographic access, primary care, random effects, spatial effects, practice variation.

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ISSN: 0972-3617

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