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					Health Partnerships for Healthy Housing

DR. ROBERT VANDERSLICE
DR. PETER SIMON
NANCY SUTTON
RHODE ISLAND DEPARTMENT OF HEALTH
             Healthy Housing
• Two biggest issues: Lead and Asthma
• Preventable +-
• Older and poorly maintained housing
• Concentrated in urban core, but not just an
  urban problem
• Lead as proxy for other issues
• Two kinds of data: Case-Making and
  Operational
Higher Lead Exposure = More Chronic Absence
Higher Lead Exposure = More Grade Repetition
Higher Lead Exposure = Lower Achievement
             Policy Implications
School performance improvement without a
comprehensive, coordinated investment in social and
environmental determinants of health will continue to
produce unimpressive results. This is work that Public
Schools cannot do alone.
• Changes in early intervention system: need
  more attention for 5-20 mcg/dl (more research!)
   – Not just Part C, more broad
• Changes in prevention system: targeted,
  proactive enforcement
Operational Data: Healthy Housing Mapper
Asthma Insurance Claims Project

NANCY SUTTON
RHODE ISLAND DEPARTMENT OF HEALTH
                   Asthma

• Traditionally tracked 15 datasets, sizable
  portion of Asthma Program budget
• These are necessary but not sufficient
• Much more precise data needed for case-
  making, operations
• Enter… Insurance Data
  RI Insurance Claims Data Project
• RI Health Plan Data
   – NHPRI
   – BCBSRI
   – UHC of New England

• Purpose:
   – Map clustering of children w/asthma
   – Identify high risk homes, neighborhoods, communities
   – Document geographic clustering of asthma cases,
     hospitalizations, and ED visits
RI Insurance Claims Data Project

• Providence Plan - RI Data Hub
• Explore relationships between asthma and:
   – academic performance
   – school absenteeism
   – age of housing
   – poverty
   – public v. private insurance
              Claims Data
• Address, Name, DOB

• # of Asthma Cases

• # of Asthma ED Visits

• # of Asthma inpatient admissions

• One Data Request = 3 insurers, 5 different
  datasets!
First Run: Basic maps

Address data allow much
more accurate mapping
than ED/Discharge data
from hospitals

Name and DOB will allow
HUB linkage
         Next Steps for Asthma

• Combine with lead hotspots for HH Mapper

  – ID least healthy housing in city

• DataHUB Link to students, schools

  – Confirm link to attendance, performance

  – ID disproportionate asthma in schools
Imagine this analysis for Asthma
                 Policy Implications
• TARGETING LIMITED RESOURCES (e.g., Asthma Control Program)
   – Identify schools, health centers, communities with greatest need for
     intervention
   – Strengthens integration efforts
• HEALTH CENTERS/PRIMARY CARE PROVIDERS
   – integrate asthma into QI/Patient-Centered Medical Home models
• COMMUNITY PLANNING & DEVELOPMENT
   – provides evidence of association between poor housing/communities
     & health
   – sidewalks, bike routes/paths, public transit, traffic routes, open space
               Policy Implications
• SCHOOLS & PUBLIC/SUBSIDIZED HOUSING
  –   Proximity to highways, Diesel
  –   IPM/pest management
  –   Cleaning supplies/practices
  –   mold/moisture
  –   smoke-free
• HOUSING
  – smoke free private housing rentals
  – code enforcement

				
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posted:3/8/2013
language:English
pages:23