Search results for: Darshani Premaratne

Authors: Darshani Premaratne, Afshin Kandampath Puthiyadath

Abstract:

The Government of Qatar is taking active steps in improving quality of health care industry in the state of Qatar. In this initiative development and market introduction of Clinical Information System and Electronic Health Record (EHR) system are proved to be a highly challenging process. Along with an organization specialized on EHR system development and with the blessing of Health Ministry of Qatar the process of introduction of EHR system in Qatar healthcare industry was undertaken. Initially a market survey was carried out to understand the requirements. Secondly, the available government regulations, needs and possible upcoming regulations were carefully studied before deployment of resources for software development. Sufficient flexibility was allowed to cater for both the changes in the market and the regulations. As the first initiative a system that enables integration of referral network where referral clinic and laboratory system for all single doctor (and small scale) clinics was developed. Setting of isolated single doctor clinics all over the state to bring in to an integrated referral network along with a referral hospital need a coherent steering force and a solid top down framework. This paper discusses about the lessons learned in developing, in obtaining approval of the health ministry and in introduction to the industry of the single doctor referral network along with an EHR system. It was concluded that development of this nature required continues balance between the market requirements and upcoming regulations. Further accelerating the development based on the emerging needs, implementation based on the end user needs while tallying with the regulations, diffusion, and uptake of demand-driven and evidence-based products, tools, strategies, and proper utilization of findings were equally found paramount in successful development of end product. Development of full scale Clinical Information System and EHR system are underway based on the lessons learned. The Government of Qatar is taking active steps in improving quality of health care industry in the state of Qatar. In this initiative development and market introduction of Clinical Information System and Electronic Health Record (EHR) system are proved to be a highly challenging process. Along with an organization specialized on EHR system development and with the blessing of Health Ministry of Qatar the process of introduction of EHR system in Qatar healthcare industry was undertaken. Initially a market survey was carried out to understand the requirements. Secondly the available government regulations, needs and possible upcoming regulations were carefully studied before deployment of resources for software development. Sufficient flexibility was allowed to cater for both the changes in the market and the regulations. As the first initiative a system that enables integration of referral network where referral clinic and laboratory system for all single doctor (and small scale) clinics was developed. Setting of isolated single doctor clinics all over the state to bring in to an integrated referral network along with a referral hospital need a coherent steering force and a solid top down framework. This paper discusses about the lessons learned in developing, in obtaining approval of the health ministry and in introduction to the industry of the single doctor referral network along with an EHR system. It was concluded that development of this nature required continues balance between the market requirements and upcoming regulations. Further accelerating the development based on the emerging needs, implementation based on the end user needs while tallying with the regulations, diffusion, and uptake of demand-driven and evidence-based products, tools, strategies, and proper utilization of findings were equally found paramount in successful development of end product. Development of full scale Clinical Information System and EHR system are underway based on the lessons learned.

Keywords: clinical information system, electronic health record, state regulations, integrated referral network of clinics

Procedia PDF Downloads 344

Authors: C. S. Subhashini, H. L. Premaratne

Abstract:

Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

Procedia PDF Downloads 361