Spatial Influences on Health Information Technology Benefits in Rural Colorado University of Colorado, Denver Anschutz Campus EHOH 6612, Final Project.

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Spatial Influences on Health Information Technology Benefits in Rural Colorado University of Colorado, Denver Anschutz Campus EHOH 6612, Final Project Lynne VanArsdale / July 22, 2011

Agenda Introduction and Background Problem Statement Previous Work Methodology Process map Discussion Planned Data Sources Initial Project Plan Expected Findings Limitations

San Luis Valley Dominant Social Characteristics: Long established Spanish families Highly innovative and collaborative

Sparsely Populated, Rural

Proposal to the Colorado Foundation Colorado Foundation Target Outcomes: – Healthy Living Increase the number of children and adults who engage in moderate or vigorous physical activity. Increase the number of children and adults who eat adequate amounts of fruits and vegetables daily. Increase the number of children who receive healthy meals at school and have access to healthy food and drinks in vending machines. Increase the number of underserved Coloradans who have convenient access to recreational exercise and fruits and vegetables. Increase the number of parents who are educated on child development, nutrition and preventive health care. Increase the number of Coloradans who are educated on chronic disease management. – Health Coverage Increase the number of children and adults who have adequate health coverage. Increase enrollment of eligible Coloradans in Medicaid and the Child Health Plan Plus (CHP+). – Health Care Increase the number of underserved Coloradans who receive integrated care. Increase the number of underserved Coloradans who regularly receive primary, mental and oral health care. Increase the number of health professionals who serve underserved Coloradans. Increase the number of patients who receive evidence-based care for chronic disease. Strategies: – Promote Healthy Communities – Develop Healthy Schools – Ensure Adequate and Affordable Coverage – Optimize Enrollment for Public Health Insurance Programs – Improve Health Care Delivery – Accelerate the Adoption of Health Information Technology – Build Health Care Professionals Workforce

Intro / Background HIT elements being introduced – EMR / standard order sets Valley Wide San Luis Valley Regional Medical Center – CORHIO connection

HIT and Health Outcomes in Rural Colorado How will spatial characteristics of rural Colorado affect the health outcomes targeted with HIT improvements (EMR, CORHIO) in the San Luis Valley? – Integration of care (including navigators) Metrics: 24 methods outlined in paper by Strandberg- Larsen, M. and Krasnik, A. – Receipt of evidence-based care for chronic disease Usage statistics on standard order sets from surveys of hospitals, clinics and primary care providers

HIT and Health Outcomes in Rural Colorado Investigative covariates: – Proximity / Access characteristics Patient distance to providers Provider internet access – Health professional training, proficiency and adoption Numbers of users/roles – Proficiency – Adoption Breadth of functions used – Community characteristics (patients) SES Education Race Age Disease / comorbidities

Literature Review Spatially-related challenges with rural health and HIT Metrics for integrated health care and EBM for chronic disease Covariates

Methodology / Process Map Center Line data with address data Look at results county-by-county Matching / validation databases – San Luis Valley Public Health databases – UC Denver Health Survey

Data sources and Potential Error Colorado state data Health Survey data CORHIO data Hospital and clinic data AHEC data

Timeline / Planned Schedule

Expected findings and contribution Improvements in the target outcomes – More prevalent closer to the hospitals – Higher rates of using EBM for chronic patients – Better integration of care Look at covariates for control – Identify confounders and effect modifiers – Recommend programs that uses those covariate parameters to enhance outcomes

Limitations One year timeframe Data availability (permissions) Data accuracy