STUDY OBJECTIVE: To demonstrate how Care Need Index (CNI), a social deprivation index, may be used to allocate total primary health care resources. DESIGN: Cross sectional survey and register data. The CNI was based on sociodemographic factors: elderly persons living alone, children under age 5, unemployed people, people with low educational status, single parents, high mobility, and foreign born people. The CNI weights were calculated from the ratings of Swedish GPs of the impact of these factors on their workload. The CNI scale was transformed into a positive scale to avoid negative values. CNI weights were calculated for each decile of the study population. The risk of poor self reported health in the CNI deciles was estimated by means of a hierarchical logistic regression in the age range 25-74 (n=27 346). The MigMed database comprising all people living in Sweden was used to calculate the CNI for Stockholm. PARTICIPANTS: The Swedish population and the population in Stockholm County. MAIN RESULTS: The means of the CNI for deciles ranged from 61 (most affluent neighbourhoods) to 140 (most deprived) in Stockholm County. The ratio between the tenth and the first decile was 1.66. There was an approximately 150% increased risk of poor self reported health for people living in the most disadvantaged neighbourhoods (OR=2.50) compared with those living in the most affluent ones (OR=1). CNI ratios for the deciles corresponded approximately to the odds ratios of poor self reported health status. CONCLUSIONS: The CNI can be used to allocate total primary health care resources.
STUDY OBJECTIVE: To demonstrate how Care Need Index (CNI), a social deprivation index, may be used to allocate total primary health care resources. DESIGN: Cross sectional survey and register data. The CNI was based on sociodemographic factors: elderly persons living alone, children under age 5, unemployed people, people with low educational status, single parents, high mobility, and foreign born people. The CNI weights were calculated from the ratings of Swedish GPs of the impact of these factors on their workload. The CNI scale was transformed into a positive scale to avoid negative values. CNI weights were calculated for each decile of the study population. The risk of poor self reported health in the CNI deciles was estimated by means of a hierarchical logistic regression in the age range 25-74 (n=27 346). The MigMed database comprising all people living in Sweden was used to calculate the CNI for Stockholm. PARTICIPANTS: The Swedish population and the population in Stockholm County. MAIN RESULTS: The means of the CNI for deciles ranged from 61 (most affluent neighbourhoods) to 140 (most deprived) in Stockholm County. The ratio between the tenth and the first decile was 1.66. There was an approximately 150% increased risk of poor self reported health for people living in the most disadvantaged neighbourhoods (OR=2.50) compared with those living in the most affluent ones (OR=1). CNI ratios for the deciles corresponded approximately to the odds ratios of poor self reported health status. CONCLUSIONS: The CNI can be used to allocate total primary health care resources.
Authors: Karin Nelson; Greg Schwartz; Susan Hernandez; Joseph Simonetti; Idamay Curtis; Stephan D Fihn Journal: J Gen Intern Med Date: 2016-11-04 Impact factor: 5.128
Authors: Amy J H Kind; Steve Jencks; Jane Brock; Menggang Yu; Christie Bartels; William Ehlenbach; Caprice Greenberg; Maureen Smith Journal: Ann Intern Med Date: 2014-12-02 Impact factor: 25.391
Authors: Louise Bennet; Sven-Erik Johansson; Carl-David Agardh; Leif Groop; Jan Sundquist; Lennart Råstam; Kristina Sundquist Journal: BMC Public Health Date: 2011-05-12 Impact factor: 3.295