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Factors Contributing to Incomplete Reporting of Patient Risk Factor Information on HIV/AIDS Case Report Forms in the State of Georgia

Bautista, Greg (2013)
Master's Thesis (101 pages)
Committee Chair / Thesis Adviser: Sullivan, Patrick S
Committee Members: Whiteside, Yohance (CDC - DHAP);
Research Fields: Health Sciences, Epidemiology; Health Sciences, Public Health
Partnering Agencies: Does not apply (no collaborating organization)
Keywords: HIV/AIDS; transmission category algorithm; notifiable disease reporting; public health; stigma; No Identified Risk (NIR); No Risk Reported (NRR); presumed heterosexual; behavioral survey; patient risk history
Program: Rollins School of Public Health, Career Masters of Public Health (Prevention Science)
Permanent url: http://pid.emory.edu/ark:/25593/d6sf0

Abstract

Implemented in all fifty states, HIV/AIDS case surveillance includes required reporting of patient demographics, laboratory data, treatment and a brief behavioral survey. An algorithm developed in the 1980's by the Centers for Disease Control and Prevention (CDC) assigns each case a transmission category based on this behavioral survey. The three categories which comprise the vast majority of cases are male sexual contact with another male (MSM); heterosexual contact with a person known to have HIV infection or at least with a person at increased risk of HIV infection; and "injection drug use" (IDU). Unfortunately, many cases are reported with little or no risk history information and thus do not meet the criteria for any of the CDC-defined transmission categories. According to the Georgia Department of Public Health (DPH), each year a significant percentage of HIV/AIDS cases diagnosed in Georgia lack complete patient risk history information. For example, in 2011 70% of HIV cases diagnosed among males (n=2,002) and 92% of HIV cases diagnosed among females (n=787) were in the category of "no identified risk" (NIR). This is a growing problem of public health significance as health departments depend on the completeness of surveillance data to monitor changes in HIV/AIDS incidence, track the burden of disease, plan programs and services, allocate limited resources for HIV care, and develop strategies for targeting prevention interventions to populations most at risk of infection. A literature review was conducted to identify factors that have been shown to be associated with incomplete reporting of patient information as well as strategies with demonstrated effectiveness for addressing this challenge. Also, a logistic regression analysis was conducted of 25,022 adult AIDS cases in the CDC AIDS Public Information Dataset (APIDS). This analysis identified the following variables as significantly associated with the binary outcome of having or not having sufficient risk information for transmission category classification: patient age at diagnosis, race/ethnicity, residence in a large metropolitan area, birth in the United States and sex at birth.

Table of Contents

TABLE OF CONTENTS -- Section 1: Background (p. 1) -- --1.1: Introduction (p. 1) -- --1.2: Problem statement and context (p. 2) -- --1.3: Purpose statement (p. 5) -- --1.4: Significance statement (p. 6) -- --1.5: Definition of terms (p. 6) -- Section 2: Review of the literature (p. 12) -- Section 3: Key informant interviews (p. 32) -- Section 4: Methodology (p. 38) -- --4.1: Introduction (p. 38) -- --4.2: Population and sample (p. 38) -- --4.3: Data analysis procedures (p. 39) -- --4.4: Limitations and delimitations (p. 41) -- Section 5: Results (p. 42) -- --5.1: Findings (p. 42) -- --5.2: Discussion (p. 51) -- Section 6: Conclusions and recommendations (p. 54) -- References (p. 56) -- LIST OF FIGURES -- Figure 1: Number of AIDS cases diagnosed from 1981 to 2002 among adults and adolescents and percentage classified as "No Identified Risk" (NIR), adjusted for reporting delays (APIDS dataset) -- Figure 2: Number of AIDS cases diagnosed from 1981 to 2002 among adults and adolescents in the Atlanta MSA and percentage classified as "No Identified Risk" (NIR), adjusted for reporting delays (APIDS dataset) -- Figure 3: List of recommendations to improve reliability and validity of HIV-related sexual behaviors reported by patients. (Weinhardt 1998) -- Figure 4: Simplified illustration of CDC algorithm for determining "transmission category" for adult HIV/AIDS cases -- Figure 5: Proposed alternative layout for "Patient Risk History" section of the Georgia HIV/AIDS case report form. -- Figure 6: Among adult and adolescent AIDS cases diagnosed in 2002: Percentage classified as "No Identified Risk" (NIR), by age group (APIDS dataset) -- LIST OF TABLES -- Table 1: Number of HIV cases diagnosed and reported in 2010 in Georgia by exposure category: Comparison of two data presentation options -- Table 2: Number of HIV cases diagnosed and reported in 2011 in Georgia by exposure category: Comparison of two data presentation options -- Table 3: Number of AIDS cases diagnosed in 2002 among adults and adolescents and percentage classified as "No Identified Risk" (NIR), by selected characteristics (APIDS dataset) -- Table 4: Logistic regression analysis of the association between various sociodemographic characteristics and classification as "No Identified Risk" (NIR): AIDS cases reported in 2002 among adults and adolescents (APIDS dataset) -- Table 5: Evaluation of logistic regression model for the association between various sociodemographic characteristics and classification as "No Identified Risk" (NIR): AIDS cases reported in 2002 among adults and adolescents (APIDS dataset) -- Table 6: Observed and predicted frequencies for classification as "No Identified Risk" (NIR) in a logistic regression model with a 0.50 prediction cuttoff: AIDS cases reported in 2002 among adults and adolescents (APIDS dataset) -- Table 7: Cumulative predicted probability of being classified as "No Identified Risk" (NIR) by logistic regression for hypothetical case examples: AIDS cases reported in 2002 among adults and adolescents (APIDS dataset) -- LIST OF ATTACHMENTS -- Attachment #1: Key informant interview guide -- Attachment #2: Georgia confidential HIV/AIDS case report form (2 pages) -- Attachment #3: CDC 2011 Adult HIV Confidential Case Report Form (4 pages) -- Attachment #4: Codebook for the APIDS public access database -- Attachment #5: Exempt study approval letter (Emory IRB) -- Attachment #6: Code for logistic regression model in SAS 9.2 -- Attachment #7: SAS output
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