OBJECTIVE: To determine the influence of population, hospital and general practice characteristics on practice admission rates for asthma and chronic obstructive pulmonary disease (COPD) in England. METHODS: Cross sectional study using Hospital Episode Statistics (HES), routine population data and primary care data. Admissions for all general practices in England during 2005-06, adjusted for age and sex composition of practice population. Univariable analysis of population, practice and hospital care provision variables, including prevalence and quality data. Significant factors included in multiple regression Poisson model. RESULTS: Admissions from 8169 practices were included. Risk of admission for each condition increased with deprivation, prevalence and smoking. Admission rates were higher in urban than rural practices. Hospital bed availability and distance to the nearest emergency department were also significantly associated with risk of admission. The associations with practice factors including practice size and quality markers varied across conditions. CONCLUSIONS: Practice population, geographic and hospital supply factors are consistently associated with asthma and COPD admissions. Higher smoking rates among such patients in a practice are associated with higher admission rates. There is little evidence from this study that other modifiable general practice factors are important in influencing admission rates.
OBJECTIVE: To determine the influence of population, hospital and general practice characteristics on practice admission rates for asthma and chronic obstructive pulmonary disease (COPD) in England. METHODS: Cross sectional study using Hospital Episode Statistics (HES), routine population data and primary care data. Admissions for all general practices in England during 2005-06, adjusted for age and sex composition of practice population. Univariable analysis of population, practice and hospital care provision variables, including prevalence and quality data. Significant factors included in multiple regression Poisson model. RESULTS: Admissions from 8169 practices were included. Risk of admission for each condition increased with deprivation, prevalence and smoking. Admission rates were higher in urban than rural practices. Hospital bed availability and distance to the nearest emergency department were also significantly associated with risk of admission. The associations with practice factors including practice size and quality markers varied across conditions. CONCLUSIONS: Practice population, geographic and hospital supply factors are consistently associated with asthma and COPD admissions. Higher smoking rates among such patients in a practice are associated with higher admission rates. There is little evidence from this study that other modifiable general practice factors are important in influencing admission rates.
Authors: Julie Langan Martin; Richard Lowrie; Alex McConnachie; Gary McLean; Frances Mair; Stewart W Mercer; Daniel J Smith Journal: Br J Gen Pract Date: 2014-10 Impact factor: 5.386
Authors: Robert Fleetcroft; Michael Noble; Aidan Martin; Emma Coombes; John Ford; Nicholas Steel Journal: Br J Gen Pract Date: 2016-06-20 Impact factor: 5.386
Authors: Suzanne M M Verstappen; Mark Lunt; Robert N Luben; Jackie Chipping; Tarnya Marshall; Kay-Tee Khaw; Nick Wareham; William G Dixon; Ian N Bruce; Deborah P M Symmons Journal: Ann Rheum Dis Date: 2012-10-13 Impact factor: 19.103