title: Asthma coalition effects on vulnerable sub groups of children: the most frequent users of health care and the youngest.
abstract: OBJECTIVE
  To examine the impact of Allies Against Asthma, community-based coalitions working to improve asthma outcomes, on vulnerable children: those with the most urgent health care use and those of youngest age.
  
  
  METHODS
  Allies zip codes were matched with comparison communities on demographic factors. Five years of Medicaid data (n = 26,836) for significant health care events: hospitalizations, ED and urgent care facility visits, were analyzed. Longitudinal analyses using generalized estimating equations and proportional hazards models compared Allies and comparison group children.
  
  
  RESULTS
  In the two start-up years of Allies, odds of having a significant event were greater for Allies children than for comparison children (p < 0.05). During the third and fourth years when Allies activities were fully implemented, for frequent health care users at baseline, odds of an asthma event were the same for both Allies and comparison children, yet in the less frequent users, odds of an event were lower in Allies children (p < 0.0001). In the initial year of Allies efforts, among the youngest, the Allies children had greater odds than comparison children of an event (p < 0.01), but by the fourth year the Allies group had lower odds (p = 0.02) of an event. Hazard ratios over all years of the study for the youngest Allies children and most frequent baseline users of urgent care were lower than for comparison children (p = 0.01 and p = 0.0004).
  
  
  CONCLUSIONS
  Mobilizing a coalition of diverse stakeholders focused on policy and system change generated community-wide reductions over the long-term in health care use for vulnerable children.
authors.affiliation: Center for Managing Chronic Disease, University of Michigan , Ann Arbor. MI , USA .
authors.forename: Laurie
authors.initials: L
authors.lastname: Lachance
authors.forename: M Beth
authors.initials: MB
authors.lastname: Benedict
authors.forename: Linda Jo
authors.initials: LJ
authors.lastname: Doctor
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Gilmore
authors.forename: Cynthia
authors.initials: C
authors.lastname: Kelly
authors.forename: James
authors.initials: J
authors.lastname: Krieger
authors.forename: Marielena
authors.initials: M
authors.lastname: Lara
authors.forename: John
authors.initials: J
authors.lastname: Meurer
authors.forename: Amy
authors.initials: A
authors.lastname: Friedman Milanovich
authors.forename: Elisa
authors.initials: E
authors.lastname: Nicholas
authors.forename: Michael
authors.initials: M
authors.lastname: Rosenthal
authors.forename: Peter X K
authors.initials: PX
authors.lastname: Song
authors.forename: Shelley C
authors.initials: SC
authors.lastname: Stoll
authors.forename: Daniel F
authors.initials: DF
authors.lastname: Awad
authors.forename: Margaret K
authors.initials: MK
authors.lastname: Wilkin
authors.forename: Noreen M
authors.initials: NM
authors.lastname: Clark
mesh_terms: D000367:Age Factors; D000553:Ambulatory Care / Q000706:statistics & numerical data*; D001249:Asthma / Q000628:therapy*; D002648:Child; D002675:Child, Preschool; D003153:Community Health Services / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D011203:Poverty; D035862:Vulnerable Populations
keywords: Management/control; morbidity and mortality; pediatrics; prevention; quality of life