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Principal Investigator: KELLY J HUNT
Organization: RALPH H JOHNSON VA MEDICAL CENTER
Fiscal Year: 2024
Funding agency: Veterans Affairs
Anticipated Impacts on Veterans Health Care: This project will put forth a comprehensive geospatial
framework to address the VA Blueprint for Excellence Strategy 3: Leverage information technologies,
analytics, and models of healthcare to optimize individual well-being and population health outcomes.
By creating a spatially referenced dataset incorporating health information, workforce productivity,
neighborhood deprivation, we will develop a comprehensive database to examine multiple dimensions of
diabetes care. Through the use of advanced GIS and spatiotemporal statistics, we will identify hotspots of high
disease risk, poor neighborhood resources, and low VA workforce capacity. This information will improve
access to care by helping VA policy makers better match resources to areas with poor outcomes. Finally, by
pinpointing areas with excessive health expenditures, the VA can develop cost-reduction measures to improve
Veterans’ health while containing costs.
Background: Diabetes is the seventh leading cause of death in the United States, can lead to serious
complications, and is associated with increased healthcare costs. Prevalence estimates for Veterans show a
disproportionate burden of disease, with estimates close to 25%, as compared to 8% of the general US
population. Evidence consistently shows racial minorities have a higher prevalence of diabetes, worse
outcomes, higher risk of complications, and higher mortality rate compared to non-Hispanic whites. This
disparity persists after controlling for patient-level factors such as education, income, knowledge, health
literacy, and self-efficacy; provider-level factors, such as bias, communication, and trust; and system-level
factors, such as access to care. Little attention has been given to differences that may be explained by regional
variation in patient-level resources, community-level resources, and health workforce resources.
Objectives: This study seeks to identify and explain spatial and temporal variation in health outcomes,
community resources, VA workforce capacity, and health disparities among patients with type 2 diabetes. Aim
1 will examine spatiotemporal trends in diabetes outcomes, including metabolic control, cost, and mortality.
Aim 2 will develop a new spatiotemporal neighborhood deprivation index and examine its association with
diabetes outcomes and racial disparities. Aim 3 will develop and validate a novel geographic workforce
deprivation index to examine its association with diabetes outcomes and racial disparities.
Methods: We will construct a cohort of veterans with type 2 diabetes receiving either inpatient or outpatient
care at the VA during the years 2000 through 2015 by linking multiple patient and administrative files from the
VHA National Patient Care and Pharmacy Benefits Management databases, using a previously validated VA
algorithm. Using advanced GIS and spatial statistical methods, we will examine spatiotemporal trends in
diabetes outcomes among Veterans with type 2 diabetes. In Aim 1, we will develop a flexible Bayesian
spatiotemporal model to identify hotspots of high prevalence of diabetes-related outcomes. In Aims 2 and 3,
we will use spatiotemporal latent factor models to develop novel neighborhood and workforce deprivation
indices, allowing us to investigate evolving patterns in community resource availability and VA workforce
capacity. Completion of these aims will enable the VA to identify individual, community, and institutional factors
associated with poor diabetes outcomes and to target community and system-level efforts to improve health in
low-resource areas.
Terms: <21+ years old><Access to Care><Address><Adult><Adult Human><Adult-Onset Diabetes Mellitus><Algorithms><Ambulatory Care><Amputation><Apoplexy><Area><Attention><Blood Pressure><Brain Vascular Accident><Cardiac Diseases><Cardiac Disorders><Caring><Cause of Death><Cerebral Stroke><Cerebrovascular Apoplexy><Cerebrovascular Stroke><Characteristics><Communication><Communities><Community Health><Community Health Care><Community Healthcare><Data Base Management><Data Base Management Systems><Data Bases><Data Set><Database Management Systems><Databases><Death Rate><Diabetes Mellitus><Dimensions><Disease><Disease Outcome><Disorder><Disparities><Disparity><Economic Income><Economical Income><Education><Educational aspects><Engineering><Equity><Ethnic Origin><Ethnicity><Geographic Area><Geographic Information Systems><Geographic Locations><Geographic Region><Geographical Location><Geography><Goals><Health><Health Care Costs><Health Care Providers><Health Care Systems><Health Costs><Health Expenditures><Health Personnel><Health Services Accessibility><Healthcare><Healthcare Costs><Healthcare Providers><Healthcare Systems><Healthcare worker><Heart Diseases><High Prevalence><Improve Access><Income><Individual><Information Technology><Institution><Intervention><Intervention Strategies><Ketosis-Resistant Diabetes Mellitus><Kidney Failure><Kidney Insufficiency><Knowledge><Link><Lipids><Low-resource area><Low-resource community><Low-resource environment><Low-resource region><Low-resource setting><Maturity-Onset Diabetes Mellitus><Measures><Metabolic Control><Methodology><Methods><Modeling><NIDDM><Neighborhoods><Non-Hispanic><Non-Insulin Dependent Diabetes><Non-Insulin-Dependent Diabetes Mellitus><Nonhispanic><Noninsulin Dependent Diabetes><Noninsulin Dependent Diabetes Mellitus><Not Hispanic or Latino><Outcome><Outpatient Care><Patient Care><Patient Care Delivery><Patients><Pattern><Personal Satisfaction><Physicians><Policies><Policy Maker><Population><Prevalence><Productivity><Race><Races><Renal Failure><Renal Insufficiency><Research><Research Resources><Resource-constrained area><Resource-constrained community><Resource-constrained environment><Resource-constrained region><Resource-constrained setting><Resource-limited area><Resource-limited community><Resource-limited environment><Resource-limited region><Resource-limited setting><Resource-poor area><Resource-poor community><Resource-poor environment><Resource-poor region><Resource-poor setting><Resources><Self Efficacy><Slow-Onset Diabetes Mellitus><Stable Diabetes Mellitus><Statistical Methods><Stroke><System><T2 DM><T2D><T2DM><Temporal trend><Time trend><Trends over time><Trust><Type 2 Diabetes Mellitus><Type 2 diabetes><Type II Diabetes Mellitus><Type II diabetes><United States><Variant><Variation><Veterans><Visualization><access to health care><access to health services><access to healthcare><access to services><access to treatment><accessibility of health care><accessibility to health care><accessibility to health services><accessibility to healthcare><adult onset diabetes><adulthood><availability of services><brain attack><burden of disease><burden of illness><care access><care for patients><care of patients><caring for patients><cerebral vascular accident><cerebrovascular accident><clinician factors><clinician-level factors><cohort><community care><community factor><community-based health><community-level factor><cost><data base><database management><database systems><deprivation><develop therapy><diabetes><disease burden><disease risk><disorder risk><disparate effect><disparate impact><disparate result><disparities in race><disparity due to race><disparity in health><flexibility><flexible><geographic disadvantage><geographic disparity><geographic inequality><geographic inequity><geographic location disparity><geographic site><geospatial information system><health care><health care access><health care availability><health care expenditure><health care model><health care personnel><health care service access><health care service availability><health care worker><health disparity><health literacy><health provider><health service access><health services availability><health workforce><healthcare access><healthcare accessibility><healthcare availability><healthcare expenditure><healthcare model><healthcare personnel><healthcare service access><healthcare service availability><heart disorder><high risk><improved><improved outcome><incomes><indexing><inequality due to race><inequitable effect><inequitable impact><inequitable outcome><inequity due to race><information system analysis><innovate><innovation><innovative><inpatient care><inpatient service><intervention development><interventional strategy><ketosis resistant diabetes><maturity onset diabetes><medical expenditure><medical personnel><mortality><mortality rate><mortality ratio><novel><outcome disparities><outcome inequality><outcome inequity><outpatient treatment><pharmacy benefit><physician factors><physician-level factors><population health><provider factors><provider-level factors><race based disparity><race based inequality><race based inequity><race disparity><race related disparity><race related inequality><race related inequity><racial><racial background><racial disparity><racial inequality><racial inequity><racial minority><racial origin><racially unequal><relational database management systems><service availability><spatiotemporal><statistic methods><statistics><stroked><strokes><therapy development><treatment access><treatment development><treatment provider><trend><type 2 DM><type II DM><type two diabetes><unequal effect><unequal impact><unequal outcome><well-being><wellbeing>