dr. robert vanderslice dr. peter simon nancy sutton rhode island department of health health...
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DR. ROBERT VANDERSLICEDR. PETER SIMONNANCY SUTTONRHODE ISLAND DEPARTMENT OF HEALTH
Health Partnerships for Healthy Housing
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
NANCY SUTTONRHODE ISLAND DEPARTMENT OF HEALTH
Asthma Insurance Claims Project
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