Exploring the impact of public services on quality of life indicators: the case of health

TY - CONF

T1 - Exploring the impact of public services on quality of life indicators

T2 - the case of health

AU - Castelli, A.

AU - Jacobs, R.

AU - Goddard, Maria Karen

AU - Smith, P.C.

PY - 2008/7

Y1 - 2008/7

N2 - The fundamental aim of public services is to improve the quality of life of citizens. Quality of life is a multi-dimensional concept, entailing aspects such as health and social well-being, economic well-being, education, the environment, access to transport, and security and safety. Indicators have been developed by the Audit Commission in England to capture these broad concepts of quality of life at a local authority level. This study investigates the contribution of public service organisations to quality of life of citizens at a local level. We separate out the effects and influences of specific policy measures administered at different policy levels on quality of life of neighbouring localities. We also explore the underlying relationships between performance indicators for different public sector organisations and various quality of life indicators. We focus in the first instance on variables which traditionally fall within the realm of the health sector, such as mortality rates and life expectancy, and examine the influence of both the health sector and other public service organisations on these outcomes. We generate a comprehensive hierarchical cross-sectional dataset of public sector performance in England, using quality of life indicators (as published by the Audit Commission), socio-economic factors (including the Index of Multiple Deprivation), and performance indicators of key public sector services. Data is measured at small area level or Lower Super Output Area (LSOA). LSOAs are a new geographic hierarchy, which pull together localities that are similar in terms of population size, social homogeneity, and mutual proximity. This is the most detailed dataset of its kind to present a snapshot of public services and quality of life at a small area level in England. We use multi-level modelling techniques to disentangle the extent of variability in quality of life indicators at different hierarchical levels through an analysis of the residual variances. This enables us to ascertain at which level the most influence can be exerted by policymakers or managers. We control for exogenous constraints (geographical factors, socio-demographic characteristics of the population) which can also play an important role in affecting quality of life of citizens. Our results suggest large variations at local level of mortality rates. The most influential level in our hierarchy of public sector organisations is the lowest level or LSOA. Further variations seem to become significant at local authority level. The results are significant in policy terms because they suggest the geographical and governmental level at which policies are most effective in improving quality of life of citizens. They also highlight the degree of attribution of, for example, mortality rates to beyond the boundaries of healthcare. These indications can be of great help in adapting policies to specific public sector organisations and specific administrative levels, to best improve local quality of life.

AB - The fundamental aim of public services is to improve the quality of life of citizens. Quality of life is a multi-dimensional concept, entailing aspects such as health and social well-being, economic well-being, education, the environment, access to transport, and security and safety. Indicators have been developed by the Audit Commission in England to capture these broad concepts of quality of life at a local authority level. This study investigates the contribution of public service organisations to quality of life of citizens at a local level. We separate out the effects and influences of specific policy measures administered at different policy levels on quality of life of neighbouring localities. We also explore the underlying relationships between performance indicators for different public sector organisations and various quality of life indicators. We focus in the first instance on variables which traditionally fall within the realm of the health sector, such as mortality rates and life expectancy, and examine the influence of both the health sector and other public service organisations on these outcomes. We generate a comprehensive hierarchical cross-sectional dataset of public sector performance in England, using quality of life indicators (as published by the Audit Commission), socio-economic factors (including the Index of Multiple Deprivation), and performance indicators of key public sector services. Data is measured at small area level or Lower Super Output Area (LSOA). LSOAs are a new geographic hierarchy, which pull together localities that are similar in terms of population size, social homogeneity, and mutual proximity. This is the most detailed dataset of its kind to present a snapshot of public services and quality of life at a small area level in England. We use multi-level modelling techniques to disentangle the extent of variability in quality of life indicators at different hierarchical levels through an analysis of the residual variances. This enables us to ascertain at which level the most influence can be exerted by policymakers or managers. We control for exogenous constraints (geographical factors, socio-demographic characteristics of the population) which can also play an important role in affecting quality of life of citizens. Our results suggest large variations at local level of mortality rates. The most influential level in our hierarchy of public sector organisations is the lowest level or LSOA. Further variations seem to become significant at local authority level. The results are significant in policy terms because they suggest the geographical and governmental level at which policies are most effective in improving quality of life of citizens. They also highlight the degree of attribution of, for example, mortality rates to beyond the boundaries of healthcare. These indications can be of great help in adapting policies to specific public sector organisations and specific administrative levels, to best improve local quality of life.

KW - Quality of life indicators, public sector organisations, performance indicators.

M3 - Other

ER -