BackgroundWhile adolescents’ access and utilization of health services is critical for ensuring their health, very few seek care, and if they do, it is primarily from family members, friends, or other non-formal sources of care. Examining the influence of the social context on adolescent health care seeking behaviors may provide us with a better understanding for how interventions can increase adolescents’ utilization of formal health care services.MethodsThe study is based on qualitative and quantitative data collected as part of the Well Being of Adolescents in Vulnerable Environments (WAVE) study, one of the first global studies to focus on very disadvantaged urban adolescents (aged 15–19 years) across five diverse sites, which include: Baltimore (USA), Ibadan (Nigeria), Johannesburg (South Africa), New Delhi (India), and Shanghai (China). Qualitative data was based on numerous methodologies, including key informant interviews, a Photovoice exercise, community mapping, focus groups and in-depth interviews. Quantitative data was gathered from a cross-sectional Audio Computer Assisted Self Interview (ACASI) survey that was administered to approximately 450–500 adolescents per site, yielding a total of 2,393 adolescents. Respondent-driven sampling was used to ensure the sample include out-of-school youth and unstably housed youth who are often underrepresented in school-based or household-based samples.ResultsWhile adolescents in Baltimore, New Delhi, and Johannesburg were more likely to seek health services if they felt illness symptoms, a fairly large proportion of adolescents indicated that even when they needed health care, they didn’t seek it. In Johannesburg, more than 30 % of adolescents did not seek care even when they knew it was needed. Similarly, nearly a quarter of adolescents in Baltimore and in Shanghai indicated not seeking care when needed. Qualitative data indicated that adolescents exhibited a general lack of trust in providers and often felt embarrassed or stigmatized for seeking services. Multivariate analysis revealed that perceived fear and exposure to community violence was associated with a decreased likelihood of seeking care, while adult support from the home increased adolescents’ likelihood to seek care in Baltimore and Johannesburg.ConclusionsAdolescent health care seeking patterns vary substantially by setting and gender. Neighborhood and family environments are important contexts in which health seeking behaviors are shaped. Efforts to connect adolescents to health care will need to target neighborhood safety as well as trust and support among adults outside of provider settings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-016-1597-x) contains supplementary material, which is available to authorized users.

Objectives: Achieving accurate, timely, and complete HIV surveillance data is complicated in the United States by migration and care seeking across jurisdictional boundaries. To address these issues, public health entities use the ATra Black Box—a secure, electronic, privacy-assuring system developed by Georgetown University—to identify and confirm potential duplicate case records, exchange data, and perform other analytics to improve the quality of data in the Enhanced HIV/AIDS Reporting System (eHARS). We aimed to evaluate the ability of 2 ATra software algorithms to identify potential duplicate case-pairs across 6 jurisdictions for people living with diagnosed HIV. Methods: We implemented 2 matching algorithms for identifying potential duplicate case-pairs in ATra software. The Single Name Matching Algorithm examines only 1 name for a person, whereas the All Names Matching Algorithm examines all names in eHARS for a person. Six public health jurisdictions used the algorithms. We compared outputs for the overall number of potential matches and changes in matching level. Results: The All Names Matching Algorithm found more matches than the Single Name Matching Algorithm and increased levels of match. The All Names Matching Algorithm identified 9070 (4.5%) more duplicate matches than the Single Name Matching Algorithm (n = 198 828) and increased the total number of matches at the exact through high levels by 15.4% (from 167 156 to 192 932; n = 25 776). Conclusions: HIV data quality across multiple jurisdictions can be improved by using all known first and last names of people living with diagnosed HIV that match with eHARS rather than using only 1 first and last name.

BACKGROUND HIV surveillance data are essential to monitoring disease trends and to ending the HIV epidemic. Due to strict policies around data security and confidentiality, identifiable HIV surveillance data are not routinely shared across United States (U.S.) public health jurisdictions, with the exceptions of a biannual case-by-case review process, the Routine Interstate Duplicate Review (RIDR) and a quinquennial process, the Comprehensive Interstate Duplicate Review (CIDR). Achieving accurate, timely, and complete HIV surveillance data is complicated in the U.S. by migration and care-seeking across geographic and public health boundaries. To address these issues in HIV surveillance data, a number of public health jurisdictions use the ATra Black Box—a secure, electronic, privacy-assuring system developed by Georgetown University—to identify and confirm potential duplicate case records, exchange data, and perform other data analytics. The goal of the ATra Black Box is to reduce jurisdiction burden in conducting the RIDR/CIDR processes and to improve the quality of data in each jurisdiction's Enhanced HIV/AIDS Reporting System (eHARS). OBJECTIVE This paper evaluates the ability of two software algorithms in the ATra Black Box to identify potential pairs of duplicate case records across multiple jurisdictions for persons living with diagnosed HIV (PWDH). We hypothesized that the algorithm which contains rules to examine all the known first names and last names of the PWDH case records would perform significantly better than the algorithm that examines only one first name and last name per PWDH case record. METHODS Two software algorithms for identifying potential duplicate pairs of case records (matching algorithms) were implemented in the ATra Black Box. For quality assurance precision testing, input files of test data were created for each jurisdiction. Each test file contained randomly generated values as well as a predetermined number of hand-crafted match pairs prepared by one of the authors (F. Kwon). Output reports were examined to verify that the hand-crafted input match pairs (matches) were identified correctly according to the rules of each matching algorithm. The two algorithms were then used by six public health jurisdictions to identify matches in their PWDH data files. Each jurisdiction compared the outputs to determine which algorithm yielded the greater number of duplicate case pairs. RESULTS The matching algorithm with rules to inspect all first and last names for a PWDH case record, including legal and all alias names, performed significantly better than the algorithm that inspected only one first name and last name. The All Names matching algorithm identified 9,070 (4.5%) more duplicate matches than the Single Name matching algorithm. CONCLUSIONS HIV data deduplication across multiple public health jurisdictions is more effective when all the known first and last names of PWDH are searched versus only one first and last name.