title: Hospital admissions for asthma, diabetes and COPD: is there an association with practice nurse staffing? A cross sectional study using routinely collected data.
abstract: BACKGROUND
  Delivering good quality primary care for patients with chronic conditions has the potential to reduce non-elective hospital admissions. Practice nurse staffing levels in England have been linked to attainment of general practice performance targets for some chronic conditions. The aim of this study was to examine whether practice nurse staffing level is similarly associated with non-elective hospital admissions in three clinical areas: asthma, Chronic Obstructive Pulmonary Disease (COPD) and diabetes.
  
  
  METHODS
  This observational study used cross sectional analysis of routinely collected data. Hospital admissions data for the period 2005-2006 (for asthma, COPD and diabetes) were linked with a database of practice characteristics, nurse staffing data and data on population characteristics for the same period. Statistical modelling explored the relationship between non-elective hospital admission rates for the three conditions and the list size per full time equivalent (FTE) practice nurse.
  
  
  RESULTS
  Higher practice nurse staffing levels were significantly associated with lower rates of admission for asthma (p < 0.001) and COPD (p < 0.001). A similar association was seen for patients with two or more admissions (p < 0.05 for asthma and p < 0.001 for COPD). For diabetes, higher practice nurse staffing level was significantly associated with higher admission rates (p < 0.05), but this association was not significant in case of patients with two or more admissions. Across all models, increasing deprivation was associated with higher admission rates for all conditions.
  
  
  CONCLUSIONS
  The inconsistent relationship between nurse staffing and patient outcomes across the different conditions and the fact that for diabetes the relationship between staffing and outcomes was in a different direction from the association between staffing and care quality, highlights the need to avoid making a simple causal interpretation of these findings and reduces the possible confidence in such conclusions. There is a need for more research into the organisation and delivery of diabetes care services in general practice, preferably using patient level data; in order to better understand the impact of the different staffing configurations on patient outcomes.
authors.affiliation: King's College London, National Nursing Research Unit, 57 Waterloo Road, London, UK. peter.griffiths@kcl.ac.uk
authors.forename: Peter
authors.initials: P
authors.lastname: Griffiths
authors.forename: Trevor
authors.initials: T
authors.lastname: Murrells
authors.forename: Dalia
authors.initials: D
authors.lastname: Dawoud
authors.forename: Simon
authors.initials: S
authors.lastname: Jones
mesh_terms: D001249:Asthma / Q000175:diagnosis / Q000451:nursing; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000451:nursing; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D020380:Needs Assessment; D009722:Nurse Practitioners / Q000600:supply & distribution*; D009740:Nursing Staff / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data; D010561:Personnel Staffing and Scheduling; D011320:Primary Health Care / Q000592:standards / Q000639:trends; D011361:Professional Competence; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis / Q000451:nursing; D019984:Quality Indicators, Health Care; D012042:Registries; D018570:Risk Assessment; D012720:Severity of Illness Index; D006113:United Kingdom