title: Employment of mid-level providers in primary care and control of diabetes.
abstract: OBJECTIVE
  Examine potential associations between inclusion of mid-level providers in United States Veterans Affairs (VA) primary care programs and diabetes control.
  
  
  METHODS
  We established a cohort of diabetes patients (alive October 1, 1999) using the VA Diabetes Registry and VA corporate databases. 1999 VA Survey of Primary Care Practices data were combined with individual-patient information. We used a two-level hierarchical model to determine the relationship between staffing characteristics and hemoglobin A1c (HbA1c), among 88,682 patients from 198 clinics.
  
  
  RESULTS
  Inclusion of nurse practitioners (NPs) at relatively limited levels (% of all providers who are NPs) in the primary care program was significantly associated with HbA1c lower by 0.31 percentage points (95% CI, -0.50% to -0.12%) compared to programs that did not include NPs. Having some level of NP staffing vs. no NP staffing was associated HbA1c lower by 0.25%. Inclusion of physician assistants (PAs) in primary care programs was generally not associated with a statistically significant difference in HbA1c. The exception is that moderate levels of PA staffing were associated with slightly higher HbA1c [0.18%, 95% CI, 0.02-0.34)].
  
  
  CONCLUSIONS
  Diabetes control among primary care patients appeared to benefit from inclusion of NPs, while an analogous association was not found for PAs.
authors.affiliation: Center for Health Services Research in Primary Care, Veterans Affairs Medical Center, Durham, NC 27705, USA. george.l.jackson@duke.edu
authors.forename: George L
authors.initials: GL
authors.lastname: Jackson
authors.forename: Shoou-Yih Daniel
authors.initials: SY
authors.lastname: Lee
authors.forename: David
authors.initials: D
authors.lastname: Edelman
authors.forename: Morris
authors.initials: M
authors.lastname: Weinberger
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Yano
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D016000:Cluster Analysis; D003920:Diabetes Mellitus / Q000097:blood / Q000451:nursing / Q000628:therapy*; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D019538:Health Care Surveys; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009722:Nurse Practitioners / Q000706:statistics & numerical data*; D010823:Physician Assistants / Q000706:statistics & numerical data*; D011320:Primary Health Care; D012042:Registries; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States; D014493:United States Department of Veterans Affairs; D000078329:Workforce
chemical_list: D015415:Biomarkers; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human