This qualitative study was conducted to explore health-seeking behaviour for sexually transmitted infections (STIs) and HIV testing among female sex workers (FSWs) in the cities of Hanoi and Da Nang, Vietnam. Data were gathered from in-depth interviews, focus groups and participant observation. Results suggest that women's decision to seek STI treatment and HIV testing is influenced by the complex interplay of personal risk perceptions, social relationships and community discourse. The women exhibited adequate knowledge of HIV while their knowledge of STIs was limited. They demonstrated high-risk perceptions of HIV, but they showed little concern for STIs. Most women sought treatment at pharmacies when they noticed symptoms of the genital tract. Their decision to seek care in health facilities and HIV testing was hampered by the high costs of treatment, judgmental attitudes of service providers, and a lack of information on testing services. Future interventions need to focus on strengthening knowledge of STIs and the STI-HIV association, and increasing awareness of HIV counselling and testing services. Training for STI service providers including pharmacies and private practitioners on sex-worker friendly and non-judgmental services and counselling skills should be emphasized to provide timely diagnosis and treatment of STIs, and to refer women to HIV testing.

BackgroundDiabetes case finding based on structured medical records does not fully identify diabetic patients whose medical histories related to diabetes are available in the form of free text. Manual chart reviews have been used but involve high labor costs and long latency.ObjectiveThis study developed and tested a Web-based diabetes case finding algorithm using both structured and unstructured electronic medical records (EMRs).MethodsThis study was based on the health information exchange (HIE) EMR database that covers almost all health facilities in the state of Maine, United States. Using narrative clinical notes, a Web-based natural language processing (NLP) case finding algorithm was retrospectively (July 1, 2012, to June 30, 2013) developed with a random subset of HIE-associated facilities, which was then blind tested with the remaining facilities. The NLP-based algorithm was subsequently integrated into the HIE database and validated prospectively (July 1, 2013, to June 30, 2014).ResultsOf the 935,891 patients in the prospective cohort, 64,168 diabetes cases were identified using diagnosis codes alone. Our NLP-based case finding algorithm prospectively found an additional 5756 uncodified cases (5756/64,168, 8.97% increase) with a positive predictive value of .90. Of the 21,720 diabetic patients identified by both methods, 6616 patients (6616/21,720, 30.46%) were identified by the NLP-based algorithm before a diabetes diagnosis was noted in the structured EMR (mean time difference = 48 days).ConclusionsThe online NLP algorithm was effective in identifying uncodified diabetes cases in real time, leading to a significant improvement in diabetes case finding. The successful integration of the NLP-based case finding algorithm into the Maine HIE database indicates a strong potential for application of this novel method to achieve a more complete ascertainment of diagnoses of diabetes mellitus.

Parental exposure to Agent Orange appears to be associated with an increased risk of birth defects.

BackgroundRoad traffic injuries (RTIs) are among the leading causes of mortality in Vietnam. However, mortality data collection systems in Vietnam in general and for RTIs in particular, remain inconsistent and incomplete. Underlying distributions of external causes and body injuries are not available from routine data collection systems or from studies till date. This paper presents characteristics, user type pattern, seasonal distribution, and causes of 1,061 deaths attributable to road crashes ascertained from a national sample mortality surveillance system in Vietnam over a two-year period (2008 and 2009).MethodsA sample mortality surveillance system was designed for Vietnam, comprising 192 communes in 16 provinces, accounting for approximately 3% of the Vietnamese population. Deaths were identified from commune level data sources, and followed up by verbal autopsy (VA) based ascertainment of cause of death. Age-standardised mortality rates from RTIs were computed. VA questionnaires were analysed in depth to derive descriptive characteristics of RTI deaths in the sample.ResultsThe age-standardized mortality rates from RTIs were 33.5 and 8.5 per 100,000 for males and females respectively. Majority of deaths were males (79%). Seventy three percent of all deaths were aged from 15 to 49 years and 58% were motorcycle users. As high as 80% of deaths occurred on the day of injury, 42% occurred prior to arrival at hospital, and a further 29% occurred on-site. Direct causes of death were identified for 446 deaths (42%) with head injuries being the most common cause attributable to road traffic injuries overall (79%) and to motorcycle crashes in particular (78%).ConclusionThe VA method can provide a useful data source to analyse RTI mortality. The observed considerable mortality from head injuries among motorcycle users highlights the need to evaluate current practice and effectiveness of motorcycle helmet use in Vietnam. The high number of deaths occurring on-site or prior to hospital admission indicates a need for effective pre-hospital first aid services and timely access to emergency facilities. In the absence of standardised death certification, sustained efforts are needed to strengthen mortality surveillance sites supplemented by VA to support evidence based monitoring and control of RTI mortality.