title: Clinical Operations Variables are Associated With Blood Pressure Outcomes.
abstract: BACKGROUND
  Uncontrolled blood pressure (BP), among patients diagnosed and treated for the condition, remains an important clinical challenge; aspects of clinical operations could potentially be adjusted if they were associated with better outcomes.
  
  
  OBJECTIVE
  To assess clinical operations factors' effects on normalization of uncontrolled BP.
  
  
  METHODS
  Observational cohort study.
  
  
  METHODS
  Patients diagnosed with hypertension from a large urban clinical practice (2005-2009).
  
  
  METHODS
  We obtained clinical data on BP, organized by person-month, and administrative data on primary care provider (PCP) staffing. We assessed the resolution of an episode of uncontrolled BP as a function of time-varying covariates including practice-level appointment volume, individual clinicians' appointment volume, overall practice-level PCP staffing, and number of unique PCPs.
  
  
  RESULTS
  Among the 7409 unique patients representing 50,403 person-months, normalization was less likely for the patients in whom the episode starts during months when the number of unique PCPs were high [the top quintile of unique PCPs was associated with a 9 percentage point lower probability of normalization (P<0.01) than the lowest quintile]. Practice appointment volume negatively affected the likelihood of normalization [episodes starting in months with the most appointments were associated with a 6 percentage point reduction in the probability of normalization (P=0.01)]. Neither clinician appointment volume nor practice clinician staffing levels were significantly associated with the probability of normalization.
  
  
  CONCLUSIONS
  Findings suggest that clinical operations factors can affect clinical outcomes like BP normalization, and point to the importance of considering outcome effects when organizing clinical care.
authors.affiliation: *VA Boston Healthcare System †Section of General Internal Medicine, Boston University School of Medicine, Boston, MA ‡Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA §Department of Pediatrics, Boston University School of Medicine ∥Northeastern University School of Pharmacy, Boston, MA.
authors.forename: Nancy R
authors.initials: NR
authors.lastname: Kressin
authors.forename: Karen E
authors.initials: KE
authors.lastname: Lasser
authors.forename: Michael
authors.initials: M
authors.lastname: Paasche-Orlow
authors.forename: Jeroan
authors.initials: J
authors.lastname: Allison
authors.forename: Arlene S
authors.initials: AS
authors.lastname: Ash
authors.forename: William G
authors.initials: WG
authors.lastname: Adams
authors.forename: Christopher W
authors.initials: CW
authors.lastname: Shanahan
authors.forename: Aaron
authors.initials: A
authors.lastname: Legler
authors.forename: Steven D
authors.initials: SD
authors.lastname: Pizer
mesh_terms: D000368:Aged; D001071:Appointments and Schedules; D001794:Blood Pressure; D015331:Cohort Studies; D015897:Comorbidity; D005260:Female; D006801:Humans; D006973:Hypertension / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D010561:Personnel Staffing and Scheduling / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000458:organization & administration* / Q000706:statistics & numerical data*