Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa

Poor adherence to prescribed treatment is a major factor contributing to tuberculosis patients developing drug resistance and failing treatment. Treatment adherence behaviour is influenced by diverse personal, cultural and socio-economic factors that vary between regions and communities. Decision network models can potentially be used to predict treatment adherence behaviour. However, determining the network structure (identifying the factors and their causal relations) and the conditional probabilities is a challenging task. To resolve the former we developed an ontology supported by current scientific literature to categorise and clarify the similarity and granularity of factors

First experiences in the implementation of biometric technology to link data from Health and Demographic Surveillance Systems with health facility data

BACKGROUND: In developing countries, Health and Demographic Surveillance Systems (HDSSs) provide a framework for tracking demographic and health dynamics over time in a defined geographical area. Many HDSSs co-exist with facility-based data sources in the form of Health Management Information Systems (HMIS). Integrating both data sources through reliable record linkage could provide both numerator and denominator populations to estimate disease prevalence and incidence rates in the population and enable determination of accurate health service coverage. OBJECTIVE: To measure the acceptability and performance of fingerprint biometrics to identify individuals in demographic surveillance populations and those attending health care facilities serving the surveillance populations. METHODOLOGY: Two HDSS sites used fingerprint biometrics for patient and/or surveillance population participant identification. The proportion of individuals for whom a fingerprint could be successfully enrolled were characterised in terms of age and sex. RESULTS: Adult (18-65 years) fingerprint enrolment rates varied between 94.1% (95% CI 93.6-94.5) for facility-based fingerprint data collection at the Africa Centre site to 96.7% (95% CI 95.9-97.6) for population-based fingerprint data collection at the Agincourt site. Fingerprint enrolment rates in children under 1 year old (Africa Centre site) were only 55.1% (95% CI 52.7-57.4). By age 5, child fingerprint enrolment rates were comparable to those of adults. CONCLUSION: This work demonstrates the feasibility of fingerprint-based individual identification for population-based research in developing countries. Record linkage between demographic surveillance population databases and health care facility data based on biometric identification systems would allow for a more comprehensive evaluation of population health, including the ability to study health service utilisation from a population perspective, rather than the more restrictive health service perspective

Application of handheld devices to field research among underserved construction worker populations: a workplace health assessment pilot study

This is the final version of the article. Available from BioMed Central via the DOI in this record.BACKGROUND: Novel low-cost approaches for conducting rapid health assessments and health promotion interventions among underserved worker groups are needed. Recruitment and participation of construction workers is particularly challenging due to their often transient periods of work at any one construction site, and their limited time during work to participate in such studies. In the present methodology report, we discuss the experience, advantages and disadvantages of using touch screen handheld devices for the collection of field data from a largely underserved worker population. METHODS: In March 2010, a workplace-centered pilot study to examine the feasibility of using a handheld personal device for the rapid health assessment of construction workers in two South Florida Construction sites was undertaken. A 45-item survey instrument, including health-related questions on tobacco exposure, workplace safety practices, musculoskeletal disorders and health symptoms, was programmed onto Apple iPod Touch® devices. Language sensitive (English and Spanish) recruitment scripts, verbal consent forms, and survey questions were all preloaded onto the handheld devices. The experience (time to survey administration and capital cost) of the handheld administration method was recorded and compared to approaches available in the extant literature. RESULTS: Construction workers were very receptive to the recruitment, interview and assessment processes conducted through the handheld devices. Some workers even welcomed the opportunity to complete the questionnaire themselves using the touch screen handheld device. A list of advantages and disadvantages emerged from this experience that may be useful in the rapid health assessment of underserved populations working in a variety of environmental and occupational health settings. CONCLUSIONS: Handheld devices, which are relatively inexpensive, minimize survey response error, and allow for easy storage of data. These technological research modalities are useful in the collection and assessment of environmental and occupational research data.This study was supported in part by the National Institute for Occupational Safety and Health (NIOSH)'s Deep South Educational Research Center at the University of Alabama (sub-contract: 288477-10) as a Graduate Student Pilot Grant Award; the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) grant F31AR057687 and the National Institute for Occupational Safety and Health (NIOSH) grant R01 OH003915

Implementing school malaria surveys in Kenya: towards a national surveillance system

OBJECTIVE: To design and implement surveys of malaria infection and coverage of malaria control interventions among school children in Kenya in order to contribute towards a nationwide assessment of malaria. METHODS: The country was stratified into distinct malaria transmission zones based on a malaria risk map and 480 schools were visited between October 2008 and March 2010. Surveys were conducted in two phases: an initial opportunistic phase whereby schools were selected for other research purposes; and a second phase whereby schools were purposively selected to provide adequate spatial representation across the country. Consent for participation was based on passive, opt-out consent rather than written, opt-in consent because of the routine, low-risk nature of the survey. All children were diagnosed for Plasmodium infection using rapid diagnostic tests, assessed for anaemia and were interviewed about mosquito net usage, recent history of illness, and socio-economic and household indicators. Children's responses were entered electronically in the school and data transmitted nightly to Nairobi using a mobile phone modem connection. RDT positive results were corrected by microscopy and all results were adjusted for clustering using random effect regression modelling. RESULTS: 49,975 children in 480 schools were sampled, at an estimated cost of US$ 1,116 per school. The overall prevalence of malaria and anaemia was 4.3% and 14.1%, respectively, and 19.0% of children reported using an insecticide-treated net (ITN). The prevalence of infection showed marked variation across the country, with prevalence being highest in Western and Nyanza provinces, and lowest in Central, North Eastern and Eastern provinces. Nationally, 2.3% of schools had reported ITN use >60%, and low reported ITN use was a particular problem in Western and Nyanza provinces. Few schools reported having malaria health education materials or ongoing malaria control activities. CONCLUSION: School malaria surveys provide a rapid, cheap and sustainable approach to malaria surveillance which can complement household surveys, and in Kenya, show that large areas of the country do not merit any direct school-based control, but school-based interventions, coupled with strengthened community-based strategies, are warranted in western and coastal Kenya. The results also provide detailed baseline data to inform evaluation of school-based malaria control in Kenya

An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa

Olukunle Ayodeji Ogundele,1 Deshendran Moodley,1 Anban W Pillay,1 Christopher J Seebregts1,2 1UKZN/CSIR Meraka Centre for Artificial Intelligence Research and Health Architecture Laboratory, School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, KwaZulu-Natal, 2Jembi Health Systems NPC, Cape Town, South Africa Purpose: Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA).Methods: An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. Conclusion: The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence. Keywords: tuberculosis, treatment adherence behavior, influencing factor, conceptual model, ontolog

Building Blocks for a Clinical Imaging Informatics Environment

Over the past 20 years, imaging informatics has been driven by the widespread adoption of radiology information and picture archiving and communication and speech recognition systems. These three clinical information systems are commonplace and are intuitive to most radiologists as they replicate familiar paper and film workflow. So what is next? There is a surge of innovation in imaging informatics around advanced workflow, search, electronic medical record aggregation, dashboarding, and analytics tools for quality measures (Nance et al., AJR Am J Roentgenol 200:1064–1070, 2013). The challenge lies in not having to rebuild the technological wheel for each of these new applications but instead attempt to share common components through open standards and modern development techniques. The next generation of applications will be built with moving parts that work together to satisfy advanced use cases without replicating databases and without requiring fragile, intense synchronization from clinical systems. The purpose of this paper is to identify building blocks that can position a practice to be able to quickly innovate when addressing clinical, educational, and research-related problems. This paper is the result of identifying common components in the construction of over two dozen clinical informatics projects developed at the University of Maryland Radiology Informatics Research Laboratory. The systems outlined are intended as a mere foundation rather than an exhaustive list of possible extensions