Who's engaged? Using health information exchange to identifypersons out of HIV care in Atlanta, GA Pubblico
Outlaw, Katrece Danielle (2015)
Abstract
New HIV transmission rates have remained stable in the United States for the last decade with an increasing burden of HIV diagnosis in the Southern states. A significant barrier to reducing HIV transmission rates is a failure to effectively engage persons living with HIV/AIDS (PLWHA) into HIV care. An emerging approach to address the lack of engagement in care is the development of HIV health information exchanges (HIE) between public health and health care providers. This study seeks to examine the utility of a HIE in identifying out of care patients who received non-HIV care at an Atlanta health center and to examine factors associated with the care engagement of the patients identified. Surveillance records from 8,350 PLWHA considered out of care by the Georgia Department of Public Health (GDPH) in 2014 were compared to 46,546 patient records from Saint Joseph's Mercy Care clinic (SJMC) from 2006 -2014. Patients were matched on the basis of name, date of birth and social security number. Bivariate and multivariable logistic regression analysis were used to examine demographic and clinical factors in this matched cohort associated with having never engaged in care or having at least one prior gap in care. Overall, 395 patients were identified as out of care who presented at SJMC. Of those, 109 (27.6%) had never engaged in care; of those who had engaged in care 219 (76.6%) had at least one gap in care. In multivariable analysis, patients who were homeless, aged 18-25 years or diagnosed for less than 10 years were more likely to have never engaged in care (PR= 1.63, 95% CI=1.21, 2.21; PR= 2.34, 95% CI=1.46, 3.77; PR= 3.17, 95% CI=1.95, 5.15). Bivariate analysis revealed that a diagnosis time of < 10 years and age 26-35 were associated with having a gap in care (PR= 0.87, 95% CI= 0.76-0.99; PR= 0.80, 95% CI= 0.65-0.98); however, no significant association was found in multivariable analysis (p=0.1647; p=0.0671). This study demonstrates that a HIE between the GDPH and SJMC could successfully identify patients out of care for HIV who present for other healthcare and provide opportunity for potential re-engagement.
Table of Contents
Chapter I: Background 1
Chapter II: Manuscript 9
INTRODUCTION 10
METHODS 12
RESULTS 16
DISCUSSION 18
REFERENCES 23
Chapter III: Summary, Implications and Future Directions 33
Appendix A: SAS Code Analysis 37
Appendix B: SAS Code Variable Descriptions 67
Appendix C: Full Multivariable Logistic Regression Models 70
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