OBJECTIVES: to enhance identification of older nursing and residential home residents in a national sample and describe their chronic disease prevalence. DESIGN: cross-sectional analysis of an established primary care database (The Health Improvement Network). SETTING: 326 English and Welsh general practices. SUBJECTS: 435,568 patients aged > or = 65. Care home residents were identified by either a Read code for care home residence or multiple care home residence markers (postcode linkage, household size identifier and location of consultation). COMPARISONS: nursing and residential home residents were compared with a community control group with no markers of care home residence using age and sex standardised chronic disease prevalence ratios. MAIN OUTCOME MEASURES: chronic disease prevalence using definitions from the national primary care contract. RESULTS: 11,547 (2.7%) older people were identified as care home residents, of whom only 4,403 (38.1%) were directly identified by their primary care record. Mean age for nursing and residential homes was 84.9 and 86.1 years compared to 74.7 for controls. Prevalence ratios for dementia were 14.8 (95% CI 13.4-16.4) for nursing and 13.5 (12.4-14.8) for residential homes compared to controls. Stroke and severe mental illness were commoner in nursing and residential homes but hypertension, respiratory and cancer diagnoses were slightly less common. Recorded disease prevalences in nursing and residential homes were similar. CONCLUSIONS: recording of care home residence is limited in primary care and this is a barrier to routine monitoring of this group. Higher dementia and stroke prevalence in care home residents confirms high clinical need, but the small differences in disease prevalence between nursing and residential homes have implications for delivering medical and nursing care to residential homes. Lower prevalence of some chronic diseases suggests incomplete recording or case finding. Routine flagging of care home residents in health care systems is a potential tool for improving monitoring and outcomes.
OBJECTIVES: to enhance identification of older nursing and residential home residents in a national sample and describe their chronic disease prevalence. DESIGN: cross-sectional analysis of an established primary care database (The Health Improvement Network). SETTING: 326 English and Welsh general practices. SUBJECTS: 435,568 patients aged > or = 65. Care home residents were identified by either a Read code for care home residence or multiple care home residence markers (postcode linkage, household size identifier and location of consultation). COMPARISONS: nursing and residential home residents were compared with a community control group with no markers of care home residence using age and sex standardised chronic disease prevalence ratios. MAIN OUTCOME MEASURES: chronic disease prevalence using definitions from the national primary care contract. RESULTS: 11,547 (2.7%) older people were identified as care home residents, of whom only 4,403 (38.1%) were directly identified by their primary care record. Mean age for nursing and residential homes was 84.9 and 86.1 years compared to 74.7 for controls. Prevalence ratios for dementia were 14.8 (95% CI 13.4-16.4) for nursing and 13.5 (12.4-14.8) for residential homes compared to controls. Stroke and severe mental illness were commoner in nursing and residential homes but hypertension, respiratory and cancer diagnoses were slightly less common. Recorded disease prevalences in nursing and residential homes were similar. CONCLUSIONS: recording of care home residence is limited in primary care and this is a barrier to routine monitoring of this group. Higher dementia and stroke prevalence in care home residents confirms high clinical need, but the small differences in disease prevalence between nursing and residential homes have implications for delivering medical and nursing care to residential homes. Lower prevalence of some chronic diseases suggests incomplete recording or case finding. Routine flagging of care home residents in health care systems is a potential tool for improving monitoring and outcomes.
Authors: Jinmyoung Cho; Peter Martin; Jennifer Margrett; Maurice MacDonald; Mary Ann Johnson; Leonard W Poon; S M Jazwinski; R C Green; M Gearing; J L Woodard; J S Tenover; I C Siegler; C Rott; W L Rodgers; D Hausman; J Arnold; A Davey Journal: Gerontology Date: 2011-11-15 Impact factor: 5.140
Authors: Sunil M Shah; Iain M Carey; Tess Harris; Stephen Dewilde; Christina R Victor; Derek G Cook Journal: Am J Public Health Date: 2013-04-18 Impact factor: 9.308
Authors: Sunil M Shah; Iain M Carey; Tess Harris; Stephen DeWilde; Christina R Victor; Derek G Cook Journal: Am J Epidemiol Date: 2012-10-09 Impact factor: 4.897
Authors: Anu Jain; Albert J van Hoek; Jemma L Walker; Rohini Mathur; Liam Smeeth; Sara L Thomas Journal: PLoS One Date: 2017-11-30 Impact factor: 3.240
Authors: Sunil M Shah; Iain M Carey; Tess Harris; Stephen DeWilde; Christina R Victor; Derek G Cook Journal: PLoS One Date: 2013-11-05 Impact factor: 3.240