Anban Pillay

2017

Ogundele, O., Moodley, D., Seebregts, C., & Pillay, A. (2017). Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa. In Software Engineering in Health Care, LNCS vol. 9062. Springer, Cham. http://doi.org/https://doi.org/10.1007/978-3-319-63194-3_6

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Ogundele-et-al-2017-FHIES-LNCS9062_1.pdf

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.

@inbook{250,
  author = {Olukunle Ogundele and Deshen Moodley and Chris Seebregts and Anban Pillay},
  title = {Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa},
  abstract = {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.},
  year = {2017},
  journal = {Software Engineering in Health Care, LNCS vol. 9062},
  pages = {81 - 95},
  publisher = {Springer, Cham},
  isbn = {978-3-319-63193-6},
  doi = {https://doi.org/10.1007/978-3-319-63194-3_6},
}

Seebregts, C., Pillay, A., Crichton, R., Singh, S., & Moodley, D. (2017). 14 Enterprise Architectures for Digital Health. Global Health Informatics: Principles of EHealth and MHealth to Improve Quality of Care. Retrieved from https://books.google.co.za/books?id=8p-rDgAAQBAJ&pg=PA173&lpg=PA173&dq=14+Enterprise+Architectures+for+Digital+Health&source=bl&ots=i6SQzaXiPp&sig=zDLJ6lIqt3Xox3Lt5LNCuMkUoJ4&hl=en&sa=X&ved=0ahUKEwivtK6jxPDYAhVkL8AKHXbNDY0Q6AEINDAB#v=onepage&q=14%20Enterp

Abstract BibTex Entry BibTeX Download

• Several different paradigms and standards exist for creating digital health architectures that are mostly complementary, but sometimes contradictory. • The potential benefits of using EA approaches and tools are that they help to ensure the appropriate use of standards for interoperability and data storage and exchange, and encourage the creation of reusable software components and metadata.

@article{162,
  author = {Chris Seebregts and Anban Pillay and Ryan Crichton and S. Singh and Deshen Moodley},
  title = {14 Enterprise Architectures for Digital Health},
  abstract = {• Several different paradigms and standards exist for creating digital health architectures that 
are mostly complementary, but sometimes contradictory.
• The potential benefits of using EA 
approaches and tools are that they help to ensure the appropriate use of standards for 
interoperability and data storage and exchange, and encourage the creation of reusable 
software components and metadata.},
  year = {2017},
  journal = {Global Health Informatics: Principles of eHealth and mHealth to Improve Quality of Care},
  pages = {173-182},
  publisher = {MIT Press},
  isbn = {978-0262533201},
  url = {https://books.google.co.za/books?id=8p-rDgAAQBAJ&amp;pg=PA173&amp;lpg=PA173&amp;dq=14+Enterprise+Architectures+for+Digital+Health&amp;source=bl&amp;ots=i6SQzaXiPp&amp;sig=zDLJ6lIqt3Xox3Lt5LNCuMkUoJ4&amp;hl=en&amp;sa=X&amp;ved=0ahUKEwivtK6jxPDYAhVkL8AKHXbNDY0Q6AEINDAB#v=onepage&amp;q=14%20Enterp},
}

2015

Crichton, R., Pillay, A., & Moodley, D. (2015). The Open Health Information Mediator: an Architecture for Enabling Interoperability in Low to Middle Income Countries.

Abstract BibTex Entry BibTeX Download PDF

thesis-ryan-11-03-2015-FINALv3_2.pdf

Interoperability and system integration are central problems that limit the effective use of health information systems to improve efficiency and effectiveness of health service delivery. There is currently no proven technology that provides a general solution in low and middle income countries where the challenges are especially acute. Engineering health information systems in low resource environments have several challenges that include poor infrastructure, skills shortages, fragmented and piecemeal applications deployed and managed by multiple organisations as well as low levels of resourcing. An important element of modern solutions to these problems is a health information exchange that enable disparate systems to share health information. It is a challenging task to develop systems as complex as health information exchanges that will have wide applicability in low and middle income countries. This work takes a case study approach and uses the development of a health information exchange in Rwanda as the case study. This research reports on the design, implementation and analysis of an architecture, the Health Information Mediator, that is a central component of a health information exchange. While such architectures have been used successfully in high income countries their efficacy has not been demonstrated in low and middle income countries. The Rwandan case study was used to understand and identify the challenges and requirements for health information exchange in low and middle income countries. These requirements were used to derive a set of key concerns for the architecture that were then used to drive its design. Novel features of the architecture include: the ability to mediate messages at both the service provider and service consumer interfaces; support for multiple internal representations of messages to facilitate the adoption of new and evolving standards; and the provision of a general method for mediating health information exchange transactions agnostic of the type of transactions. The architecture is shown to satisfy the key concerns and was validated by implementing and deploying a reference application, the OpenHIM, within the Rwandan health information exchange. The architecture is also analysed using the Architecture Trade-off Analysis Method. It has also been successfully implemented in other low and middle income countries with relatively minor configuration changes which demonstrates the architectures generalizability.

@phdthesis{110,
  author = {Ryan Crichton and Anban Pillay and Deshen Moodley},
  title = {The Open Health Information Mediator: an Architecture for Enabling Interoperability in Low to Middle Income Countries},
  abstract = {Interoperability and system integration are central problems that limit the effective use of health information systems to improve efficiency and effectiveness of health service delivery. There is currently no proven technology that provides a general solution in low and middle income countries where the challenges are especially acute. Engineering health information systems in low resource environments have several challenges that include poor infrastructure, skills shortages, fragmented and piecemeal applications deployed and managed by multiple organisations as well as low levels of resourcing. An important element of modern solutions to these problems is a health information exchange that enable disparate systems to share health information. 

It is a challenging task to develop systems as complex as health information exchanges that will have wide applicability in low and middle income countries. This work takes a case study approach and uses the development of a health information exchange in Rwanda as the case study. This research reports on the design, implementation and analysis of an architecture, the Health Information Mediator, that is a central component of a health information exchange. While such architectures have been used successfully in high income countries their efficacy has not been demonstrated in low and middle income countries. The Rwandan case study was used to understand and identify the challenges and requirements for health information exchange in low and middle income countries. These requirements were used to derive a set of key concerns for the architecture that were then used to drive its design. Novel features of the architecture include: the ability to mediate messages at both the service provider and service consumer interfaces; support for multiple internal representations of messages to facilitate the adoption of new and evolving standards; and the provision of a general method for mediating health information exchange transactions agnostic of the type of transactions.

The architecture is shown to satisfy the key concerns and was validated by implementing and deploying a reference application, the OpenHIM, within the Rwandan health information exchange. The architecture is also analysed using the Architecture Trade-off Analysis Method. It has also been successfully implemented in other low and middle income countries with relatively minor configuration changes which demonstrates the architectures generalizability.},
  year = {2015},
  volume = {MSc},
}

2014

Ogundele, O., Moodley, D., Seebregts, C., & Pillay, A. (2014). Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa. In 4th International Symposium (FHIES 2014) and 6th International Workshop (SEHC 2014).

Abstract BibTex Entry BibTeX Download PDF

Ogundele-et-al-2017-FHIES-LNCS9062.pdf

@{158,
  author = {Olukunle Ogundele and Deshen Moodley and Chris Seebregts and Anban Pillay},
  title = {Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa},
  abstract = {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},
  year = {2014},
  journal = {4th International Symposium (FHIES 2014) and 6th International Workshop (SEHC 2014)},
  pages = {81-95},
  month = {17/07-18/07},
}

Brandt, P., Moodley, D., Pillay, A., Seebregts, C., & de Oliveira, T. (2014). An Investigation of Classification Algorithms for Predicting HIV Drug Resistance Without Genotype Resistance Testing. In Third International Symposium on Foundations of Health Information Engineering and Systems. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-53956-5_16

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Pascal_FHIES13.pdf

The development of drug resistance is a major factor imped- ing the efficacy of antiretroviral treatment of South Africa’s HIV infected population. While genotype resistance testing is the standard method to determine resistance, access to these tests is limited in low-resource set- tings. In this paper we investigate machine learning techniques for drug resistance prediction from routine treatment and laboratory data to help clinicians select patients for confirmatory genotype testing. The tech- niques, including binary relevance, HOMER, MLkNN, predictive clus- tering trees (PCT), RAkEL and ensemble of classifier chains were tested on a dataset of 252 medical records of patients enrolled in an HIV treat- ment failure clinic in rural KwaZulu-Natal in South Africa. The PCT method performed best with a discriminant power of 1.56 for two drugs, above 1.0 for three others and a mean true positive rate of 0.68. These methods show potential for application where access to genotyping is limited.

@{97,
  author = {Pascal Brandt and Deshen Moodley and Anban Pillay and Chris Seebregts and T. de Oliveira},
  title = {An Investigation of Classification Algorithms for Predicting HIV Drug Resistance Without Genotype Resistance Testing},
  abstract = {The development of drug resistance is a major factor imped- ing the efficacy of antiretroviral treatment of South Africa’s HIV infected population. While genotype resistance testing is the standard method to determine resistance, access to these tests is limited in low-resource set- tings. In this paper we investigate machine learning techniques for drug resistance prediction from routine treatment and laboratory data to help clinicians select patients for confirmatory genotype testing. The tech- niques, including binary relevance, HOMER, MLkNN, predictive clus- tering trees (PCT), RAkEL and ensemble of classifier chains were tested on a dataset of 252 medical records of patients enrolled in an HIV treat- ment failure clinic in rural KwaZulu-Natal in South Africa. The PCT method performed best with a discriminant power of 1.56 for two drugs, above 1.0 for three others and a mean true positive rate of 0.68. These methods show potential for application where access to genotyping is limited.},
  year = {2014},
  journal = {Third International Symposium on Foundations of Health Information Engineering and Systems},
  pages = {236-253},
  month = {21/08-23/08},
  isbn = {978-3-642-53955-8},
  url = {http://link.springer.com/chapter/10.1007/978-3-642-53956-5_16},
}

Brandt, P., Moodley, D., & Pillay, A. (2014). An Investigation Of Multi-label Classification Techniques For Predicting Hiv Drug Resistance In Resource-limited Settings.

Abstract BibTex Entry BibTeX Download PDF

Pascal_Brandt_MSc_Dissertation_2014_FINAL.pdf

South Africa has one of the highest HIV infection rates in the world with more than 5.6 million infected people and consequently has the largest antiretroviral treatment program with more than 1.5 million people on treatment. The development of drug resistance is a major factor impeding the efficacy of antiretroviral treatment. While genotype resistance testing (GRT) is the standard method to determine resistance, access to these tests is limited in resource-limited settings. This research investigates the efficacy of multi-label machine learning techniques at predicting HIV drug resistance from routine treatment and laboratory data. Six techniques, namely, binary relevance, HOMER, MLkNN, predictive clustering trees (PCT), RAkEL and ensemble of classifier chains (ECC) have been tested and evaluated on data from medical records of patients enrolled in an HIV treatment failure clinic in rural KwaZulu-Natal in South Africa. The performance is measured using five scalar evaluation measures and receiver operating characteristic (ROC) curves. The techniques were found to provide useful predictive information in most cases. The PCT and ECC techniques perform best and have true positive prediction rates of 97% and 98% respectively for specific drugs. The ECC method also achieved an AUC value of 0.83, which is comparable to the current state of the art. All models have been validated using 10 fold cross validation and show increased performance when additional data is added. In order to make use of these techniques in the field, a tool is presented that may, with small modifications, be integrated into public HIV treatment programs in South Africa and could assist clinicians to identify patients with a high probability of drug resistance.

@phdthesis{93,
  author = {Pascal Brandt and Deshen Moodley and Anban Pillay},
  title = {An Investigation Of Multi-label Classification Techniques For Predicting Hiv Drug Resistance In Resource-limited Settings},
  abstract = {South Africa has one of the highest HIV infection rates in the world with more than 5.6 million infected people and consequently has the largest antiretroviral treatment program with more than 1.5 million people on treatment. The development of drug resistance is a major factor impeding the efficacy of antiretroviral treatment. While genotype resistance testing (GRT) is the standard method to determine resistance, access to these tests is limited in resource-limited settings. This research investigates the efficacy of multi-label machine learning techniques at predicting HIV drug resistance from routine treatment and laboratory data. Six techniques, namely, binary relevance, HOMER, MLkNN, predictive clustering trees (PCT), RAkEL and ensemble of classifier chains (ECC) have been tested and evaluated on data from medical records of patients enrolled in an HIV treatment failure clinic in rural KwaZulu-Natal in South Africa. The performance is measured using five scalar evaluation measures and receiver operating characteristic (ROC) curves. The techniques were found to provide useful predictive information in most cases. The PCT and ECC techniques perform best and have true positive prediction rates of 97% and 98% respectively for specific drugs. The ECC method also achieved an AUC value of 0.83, which is comparable to the current state of the art. All models have been validated using 10 fold cross validation and show increased performance when additional data is added. In order to make use of these techniques in the field, a tool is presented that may, with small modifications, be integrated into public HIV treatment programs in South Africa and could assist clinicians to identify patients with a high probability of drug resistance.},
  year = {2014},
  volume = {MSc},
}

Moodley, D., Seebregts, C., Pillay, A., & Meyer, T. (2014). An Ontology for Regulating eHealth Interoperability in Developing African Countries. In Foundations of Health Information Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7789.

Abstract BibTex Entry BibTeX Download PDF

Moodley_fhies_14_0.pdf

eHealth governance and regulation are necessary in low resource African countries to ensure effective and equitable use of health information technology and to realize national eHealth goals such as interoperability, adoption of standards and data integration. eHealth regulatory frameworks are under-developed in low resource settings, which hampers the progression towards coherent and effective national health information systems. Ontologies have the potential to clarify issues around interoperability and the effectiveness of different standards to deal with different aspects of interoperability. Ontologies can facilitate drafting, reusing, implementing and compliance testing of eHealth regulations. In this regard, we have developed an OWL ontology to capture key concepts and relations concerning interoperability and standards. The ontology includes an operational definition for interoperability and is an initial step towards the development of a knowledge representation modeling platform for eHealth regulation and governance.

@{92,
  author = {Deshen Moodley and Chris Seebregts and Anban Pillay and Tommie Meyer},
  title = {An Ontology for Regulating eHealth Interoperability in Developing African Countries},
  abstract = {eHealth governance and regulation are necessary in low resource African countries to ensure effective and equitable use of health information technology and to realize national eHealth goals such as interoperability, adoption of standards and data integration. eHealth regulatory frameworks are under-developed in low resource settings, which hampers the progression towards coherent and effective national health information systems. Ontologies have the potential to clarify issues around interoperability and the effectiveness of different standards to deal with different aspects of interoperability. Ontologies can facilitate drafting, reusing, implementing and compliance testing of eHealth regulations. In this regard, we have developed an OWL ontology to capture key concepts and relations concerning interoperability and standards. The ontology includes an operational definition for interoperability and is an initial step towards the development of a knowledge representation modeling platform for eHealth regulation and governance.},
  year = {2014},
  journal = {Foundations of Health Information Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7789},
  pages = {107-124},
  month = {15/09},
  isbn = {978-3-642-53955-8},
}

2013

Mudaly, T., Moodley, D., Pillay, A., & Seebregts, C. (2013). Architectural Frameworks for Developing National Health Information Systems in Low and Middle Income Countries. In Proceedings of the First IEEE International Conference on Enterprise Systems (ES 2013), Cape Town, South Africa.

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Mudaly_ES_2013.pdf

Consolidating currently fragmented health information systems in low and middle-income countries (LMIC) into a coherent national information system will increase operational efficiencies, improve decision-making and will lead to better health outcomes. However, engineering an enterprise information system of the scale and complexity of a national health information system (NHIS) pose unique and complex challenges in LMICs. In this paper, we review current approaches to NHIS development and discuss challenges faced by LMICs to develop their NHIS. Based on current LMIC systems we identify three stages of system evolution and propose that LMICs should follow an evolutionary, middle-out approach to NHIS development supported by appropriate architectural frameworks.

@{63,
  author = {Thinasagree Mudaly and Deshen Moodley and Anban Pillay and Chris Seebregts},
  title = {Architectural Frameworks for Developing National Health Information Systems in Low and Middle Income Countries},
  abstract = {Consolidating currently fragmented health information systems in low and middle-income countries (LMIC) into a coherent national information system will increase operational efficiencies, improve decision-making and will lead to better health outcomes. However, engineering an enterprise information system of the scale and complexity of a national health information system (NHIS) pose unique and complex challenges in LMICs. In this paper, we review current approaches to NHIS development and discuss challenges faced by LMICs to develop their NHIS. Based on current LMIC systems we identify three stages of system evolution and propose that LMICs should follow an evolutionary, middle-out approach to NHIS development supported by appropriate architectural frameworks.},
  year = {2013},
  journal = {Proceedings of the First IEEE International Conference on Enterprise Systems (ES 2013), Cape Town, South Africa},
  month = {07/11 - 08/11},
}

Crichton, R., Moodley, D., Pillay, A., & Seebregts, C. (2013). An Architecture and Reference Implementation of an Open Health Information Mediator: Enabling Interoperability in the Rwandan Health Information Exchange. In Foundations of Health Information Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7789. Springer Berlin Heidelberg. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-39088-3_6

Abstract BibTex Entry BibTeX Download PDF

paper-for-proof-before-publication_0.pdf

Rwanda, one of the smallest and most densely populated countries in Africa, has made rapid and substantial progress towards designing and deploying a national health information system. One of the more challenging aspects of the system is the design of an architecture to support: interoperability between existing health information systems already in use in the country; incremental extension into a fully integrated national health information system without substantial re-engineering; and scaling, from a single district in the initial phase, to national level without requiring a fundamental change in technology or design paradigm. This paper describes the key requirements and the design of the current architecture using the ISO/IEC/IEEE 42010 standard architecture descriptions. The architecture takes an Enterprise Service Bus approach. A partial implementation and preliminary analysis of the architecture is given. Since these challenges are experienced by other developing African countries, the next steps involves creating a generic architecture that can be reused for health information exchange in other developing African countries.

@inbook{51,
  author = {Ryan Crichton and Deshen Moodley and Anban Pillay and Chris Seebregts},
  title = {An Architecture and Reference Implementation of an Open Health Information Mediator: Enabling Interoperability in the Rwandan Health Information Exchange},
  abstract = {Rwanda, one of the smallest and most densely populated countries in Africa, has made rapid and substantial progress towards designing and deploying a national health information system. One of the more challenging aspects of the system is the design of an architecture to support: interoperability between existing health information systems already in use in the country; incremental extension into a fully integrated national health information system without substantial re-engineering; and scaling, from a single district in the initial phase, to national level without requiring a fundamental change in technology or design paradigm. This paper describes the key requirements and the design of the current architecture using the ISO/IEC/IEEE 42010 standard architecture descriptions. The architecture takes an Enterprise Service Bus approach. A partial implementation and preliminary analysis of the architecture is given. Since these challenges are experienced by other developing African countries, the next steps involves creating a generic architecture that can be reused for health information exchange in other developing African countries.},
  year = {2013},
  journal = {Foundations of Health Information Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7789},
  pages = {87-104},
  publisher = {Springer Berlin Heidelberg},
  isbn = {978-3-642-39087-6},
  url = {http://link.springer.com/chapter/10.1007/978-3-642-39088-3_6},
}

2012

Moodley, D., Pillay, A., & Seebregts, C. (2012). Position Paper: Researching and Developing Open Architectures for National Health Information Systems in Developing African Countries. In Foundations of Health Informatics Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7151. Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-32355-3_8

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paper_19.pdf

Most African countries have limited health information systems infrastructure. Some health information system components are implemented but often on an adhoc, piecemeal basis, by foreign software developers and designed to solve specific problems. Little attention is usually paid to how these components can fit into an integrated national health information system and interoperate with other components. The Health Enterprise Architecture Laboratory was recently established in the School of Computer Science at the University of KwaZulu-Natal in South Africa to undertake research and build capacity in open health architectures for developing African countries. Based on field experiences and requirements in South Africa, Mozambique and Rwanda, the laboratory is evolving a generic Health Enterprise Architecture Framework and Repository of Tools specifically for low resource settings. In this paper we describe these three initiatives and the expected impact on implementing health information systems in developing African countries.

@inbook{16,
  author = {Deshen Moodley and Anban Pillay and Chris Seebregts},
  title = {Position Paper: Researching and Developing Open Architectures for National Health Information Systems in Developing African Countries},
  abstract = {Most African countries have limited health information systems infrastructure. Some health information system components are implemented but often on an adhoc, piecemeal basis, by foreign software developers and designed to solve specific problems. Little attention is usually paid to how these components can fit into an integrated national health information system and interoperate with other components. The Health Enterprise Architecture Laboratory was recently established in the School of Computer Science at the University of KwaZulu-Natal in South Africa to undertake research and build capacity in open health architectures for developing African countries. Based on field experiences and requirements in South Africa, Mozambique and Rwanda, the laboratory is evolving a generic Health Enterprise Architecture Framework and Repository of Tools specifically for low resource settings. In this paper we describe these three initiatives and the expected impact on implementing health information systems in developing African countries.},
  year = {2012},
  journal = {Foundations of Health Informatics Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7151},
  pages = {129-139},
  publisher = {Springer},
  url = {http://link.springer.com/chapter/10.1007/978-3-642-32355-3_8},
}