A life table approach to small area health need profiling Export

@article{congdon_2002, abstract = {Recent developments in health outcome models for small areas have found benefits from pooling information over areas to produce smoothed estimates of mortality and morbidity rates. Such indices serve as proxies for the need for health care and are often used in allocating health care resources. The present paper adopts a full life table approach to such outcomes, which includes the joint modelling of mortality and health variation between small areas. A further feature of the approach here is random effects modelling of age-specific death and wellness rates, so pooling strength in estimating life table parameters for areas, such as healthy and total life expectancies, which may be based on small event counts. The basic model involves exchangeable random effects for age and area. However, structured forms of variation considered include correlations between mortality and health, spatial correlation in these outcomes, and interrelatedness in age effects. A case study illustration uses deaths and long-term illness data to develop small area life tables for two London boroughs, and includes a temporal perspective on deaths. It then considers the utility of area life table measures in predicting health activity, providing a form of validation in addition to formal statistical cross-validation. 10.1191/1471082x02st026oa}, author = {Congdon, Peter}, citeulike-article-id = {3403057}, citeulike-linkout-0 = {http://smj.sagepub.com/cgi/content/abstract/2/1/63}, comment = {Discusses the utility of life expectancy and healthy life expectancy as small-area indicators for informing health policy (in this case need and resourcing). Incorporates Bayesian smoothing using a hierarchical approach. }, day = {1}, journal = {Statistical Modelling}, keywords = {bayesian, healthy-life-expectancy, life-expectancy, modelling, small-area}, month = {April}, number = {1}, pages = {63--88}, posted-at = {2008-10-14 02:03:52}, priority = {0}, title = {A life table approach to small area health need profiling}, url = {http://smj.sagepub.com/cgi/content/abstract/2/1/63}, volume = {2}, year = {2002} }

TY - JOUR ID - congdon_2002 L3 - citeulike-article-id:3403057 N2 - Recent developments in health outcome models for small areas have found benefits from pooling information over areas to produce smoothed estimates of mortality and morbidity rates. Such indices serve as proxies for the need for health care and are often used in allocating health care resources. The present paper adopts a full life table approach to such outcomes, which includes the joint modelling of mortality and health variation between small areas. A further feature of the approach here is random effects modelling of age-specific death and wellness rates, so pooling strength in estimating life table parameters for areas, such as healthy and total life expectancies, which may be based on small event counts. The basic model involves exchangeable random effects for age and area. However, structured forms of variation considered include correlations between mortality and health, spatial correlation in these outcomes, and interrelatedness in age effects. A case study illustration uses deaths and long-term illness data to develop small area life tables for two London boroughs, and includes a temporal perspective on deaths. It then considers the utility of area life table measures in predicting health activity, providing a form of validation in addition to formal statistical cross-validation. 10.1191/1471082x02st026oa IS - 1 JF - Statistical Modelling EP - 88 TI - A life table approach to small area health need profiling VL - 2 SP - 63 KW - bayesian KW - healthy-life-expectancy KW - life-expectancy KW - modelling KW - small-area N1 - Discusses the utility of life expectancy and healthy life expectancy as small-area indicators for informing health policy (in this case need and resourcing). Incorporates Bayesian smoothing using a hierarchical approach. AU - Congdon, Peter PY - 2002/04/01/ UR - http://smj.sagepub.com/cgi/content/abstract/2/1/63 ER -