title: Population health needs as predictors of variations in NHS practice payments: a cross-sectional study of English general practices in 2013-2014 and 2014-2015.
abstract: BACKGROUND
  NHS general practice payments in England include pay for performance elements and a weighted component designed to compensate for workload, but without measures of specific deprivation or ethnic groups.
  
  
  OBJECTIVE
  To determine whether population factors related to health needs predicted variations in NHS payments to individual general practices in England.
  
  
  METHODS
  Cross-sectional study of all practices in England, in financial years 2013-2014 and 2014-2015.
  
  
  METHODS
  Descriptive statistics, univariable analyses (examining correlations between payment and predictors), and multivariable analyses (undertaking multivariable linear regressions for each year, with logarithms of payments as the dependent variables, and with population, practice, and performance factors as independent variables) were undertaken.
  
  
  RESULTS
  Several population variables predicted variations in adjusted total payments, but inconsistently. Higher payments were associated with increases in deprivation, patients of older age, African Caribbean ethnic group, and asthma prevalence. Lower payments were associated with an increase in smoking prevalence. Long-term health conditions, South Asian ethnic group, and diabetes prevalence were not predictive. The adjusted R2values were 0.359 (2013-2014) and 0.374 (2014-2015). A slightly different set of variables predicted variations in the payment component designed to compensate for workload. Lower payments were associated with increases in deprivation, patients of older age, and diabetes prevalence. Smoking prevalence was not predictive. There was a geographical differential.
  
  
  CONCLUSIONS
  Population factors related to health needs were, overall, poor predictors of variations in adjusted total practice payments and in the payment component designed to compensate for workload. Revising the weighting formula and extending weighting to other payment components might better support practices to address these needs.
authors.affiliation: Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Centre for Medicine, Leicester.
authors.forename: Louis S
authors.initials: LS
authors.lastname: Levene
authors.affiliation: Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Centre for Medicine, Leicester.
authors.forename: Richard
authors.initials: R
authors.lastname: Baker
authors.affiliation: Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Centre for Medicine, Leicester.
authors.forename: Andrew
authors.initials: A
authors.lastname: Wilson
authors.affiliation: Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Centre for Medicine, Leicester.
authors.forename: Nicola
authors.initials: N
authors.lastname: Walker
authors.affiliation: Clinical Effectiveness Group, Centre for Primary Care and Public Health, Queen Mary University of London, London.
authors.forename: Kambiz
authors.initials: K
authors.lastname: Boomla
authors.affiliation: Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Centre for Medicine, Leicester.
authors.forename: M John G
authors.initials: MJ
authors.lastname: Bankart
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001208:Asia / Q000208:ethnology; D044466:Asian People; D001249:Asthma / Q000453:epidemiology*; D044383:Black People; D017691:Caribbean Region / Q000208:ethnology; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000453:epidemiology*; D004739:England / Q000453:epidemiology; D058006:General Practice / Q000191:economics*; D005102:Health Expenditures; D006301:Health Services Needs and Demand; D006333:Heart Failure / Q000453:epidemiology*; D006801:Humans; D016014:Linear Models; D008875:Middle Aged; D015999:Multivariate Analysis; D015995:Prevalence; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology*; D012052:Reimbursement, Incentive; D012907:Smoking / Q000453:epidemiology*; D013222:State Medicine; D016526:Workload
keywords: funding; health services needs; inequalities; populations, underserved; primary health care; workload