This study was the first of its kind to integrate several databases to understand HIV primary health care utilization over a period of years. Our findings reinforce the importance of CD4 and viral load values as indicators of utilization of HIV primary health care, particularly in the absence of other health data sets. The lack of available data and the way in which source data were available limited the study.
This study integrated healthcare information from multiple data sources to measure access to HIV primary care in the St. Louis, Missouri area between 1998-2002. We describe the process of creating the collective database and the degree to which each dataset contributed to the calculation of global variables such as evidence of HIV primary care. Descriptive analyses were used to measure evidence of HIV primary among the included data sources. This study was the first of its kind to study HIV primary healthcare access over a period of five years with integrated databases. Findings reinforce the importance of HIV laboratory values as indicators of access to HIV primary healthcare, particularly in the absence of other health data sets. Limitations to the study were posed by data availability and integration of data sources with varying purposes and sophistication.
A wide range in percent linked to HIV medical care was observed between residents of 18 urban areas in the United States with noted age and racial disparities. Routine testing and linkage efforts and intensified prevention efforts should be considered to increase access to primary HIV-related medical care.
Background:
Focused attention on Data to Care underlines the importance of high-quality HIV surveillance data. This study identified the number of total duplicate and exact duplicate HIV case records in 9 separate Enhanced HIV/AIDS Reporting System (eHARS) databases reported by 8 jurisdictions and compared this approach to traditional Routine Interstate Duplicate Review resolution.
Methods:
This study used the ATra Black Box System and 6 eHARS variables for matching case records across jurisdictions: last name, first name, date of birth, sex assigned at birth (birth sex), social security number, and race/ethnicity, plus 4 system-calculated values (first name Soundex, last name Soundex, partial date of birth, and partial social security number).
Results:
In approximately 11 hours, this study matched 290,482 cases from 799,326 uploaded records, including 55,460 exact case pairs. Top case pair overlaps were between NYC and NYS (51%), DC and MD (10%), and FL and NYC (6%), followed closely by FL and NYS (4%), FL and NC (3%), DC and VA (3%), and MD and VA (3%). Jurisdictions estimated that they realized a combined 135 labor hours in time efficiency by using this approach compared with manual methods previously used for interstate duplication resolution.
Discussion:
This approach discovered exact matches that were not previously identified. It also decreased time spent resolving duplicated case records across jurisdictions while improving accuracy and completeness of HIV surveillance data in support of public health program policies. Future uses of this approach should consider standardized protocols for postprocessing eHARS data.
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