title: Variations in 30-day hospital readmission rates across primary care clinics within a tertiary referral center.
abstract: BACKGROUND
  Reducing hospital readmissions is a national healthcare priority. Little is known about how readmission rates vary across unique primary care practices.
  
  
  OBJECTIVE
  To calculate all-cause 30-day hospital readmission rates at the level of individual primary care practices and identify factors associated with variations in these rates.
  
  
  METHODS
  Retrospective analysis
  
  
  METHODS
  Seven primary care clinics affiliated with the University of California, San Francisco (UCSF).
  
  
  METHODS
  Adults ≥18 years old with a primary care provider (PCP) at UCSF MEASUREMENTS: All-cause 30-day readmission rates were calculated for primary care clinics for discharges between July 1, 2009 and June 30, 2012. We built a model to identify demographic, clinical, and hospital factors associated with variation in rates.
  
  
  RESULTS
  There were 12,564 discharges for patients belonging to the 7 clinics, with 8685 index discharges and 1032 readmissions. Readmission rates varied across practices, from 14.9% in Human Immunodeficiency Virus primary care and 7.7% in women's health. In multivariable analyses, factors associated with variation in readmission rates included: male gender (odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.05-1.40), Medicare insurance (OR: 1.31, 95% CI: 1.05, 1.64; Ref = private), Medicare-Medicaid dual eligible (OR: 1.26, 95% CI: 1.01-1.56), multiple comorbidities, and admitting services. Patients with a departed PCP awaiting transfer assignment to a new PCP had an OR of 1.59 (95% CI: 1.16-2.17) compared with having a current faculty PCP.
  
  
  CONCLUSIONS
  Primary care practices are important partners in improving care transitions and reducing hospital readmissions, and this study introduces a new way to view readmission rates. PCP turnover may be an important risk factor for hospital readmissions.
authors.affiliation: Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California.
authors.forename: Ning
authors.initials: N
authors.lastname: Tang
authors.forename: Judith H
authors.initials: JH
authors.lastname: Maselli
authors.forename: Ralph
authors.initials: R
authors.lastname: Gonzales
mesh_terms: D000046:Academic Medical Centers / Q000191:economics / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D005260:Female; D006801:Humans; D008297:Male; D008484:Medicaid / Q000191:economics / Q000706:statistics & numerical data; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data; D008875:Middle Aged; D008962:Models, Theoretical; D015999:Multivariate Analysis; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data*; D011320:Primary Health Care / Q000191:economics / Q000706:statistics & numerical data*; D012017:Referral and Consultation / Q000191:economics / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012495:San Francisco; D017678:Sex Distribution; D012959:Socioeconomic Factors; D062606:Tertiary Care Centers / Q000191:economics / Q000706:statistics & numerical data*; D014481:United States; D055815:Young Adult