ORCID Profile
0000-0002-6213-9708
Current Organisations
Charles Darwin University
,
University of Nusa Cendana
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Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 08-1999
Publisher: Elsevier BV
Date: 12-2012
DOI: 10.1016/J.MIDW.2011.09.005
Abstract: to describe the system of health reporting by village midwives and two rural clinics in eastern Indonesia and solve some of the problems in this system through consultation. participatory action research model where problems are identified by those most affected and solutions sought. Clinic staff were observed and interviewed regarding their work roles and reporting duties. Allocation of work time to various tasks was recorded by all clinic staff before and after the implementation of a new health recording system. Several information sessions and focus group discussions were held with village midwives and other health staff to identify and address problems. Indonesia initiated a programme in 1989, aiming to place a midwife in every village, in response to high maternal mortality rates and low rates of births attended by trained birth assistants. Remote rural villages in eastern Indonesia have difficulty recruiting and retaining village midwives. These midwives play a crucial role in health reporting. During 2010 a new system of recording and reporting by clinics was implemented. village and clinic health staff in two rural subdistricts in eastern Indonesia. there was incomplete coverage by village midwives in the two subdistricts studied 28% of villages had a resident midwife, 48% had a visiting midwife and 24% had only monthly visits by a mobile clinic. Village midwives performed duties additional to their official duties and training. Village midwives had problems associated with the reporting system including inconsistency in reporting, poor access to in idual patient histories and poor access to clinics. These problems resulted in incompleteness and poor timeliness of data transfer. midwives in remote villages felt compelled to provide services for which they were not trained. Poor quality of data reporting resulted from inconsistent reporting methods. Local staff can successfully change and manage reporting systems if given appropriate support and training. socialisation of health reporting systems among all staff involved can lead to improved data consistency and completeness. Effective systems for data transfer and reporting may reduce time spent on these tasks by some staff. Improvements to accuracy of data and availability of in idual patient histories have the potential to contribute to improved health care. Quality of health care by village midwives should be addressed by adequate training and improved transport.
Publisher: Public Library of Science (PLoS)
Date: 09-06-2021
DOI: 10.1371/JOURNAL.PONE.0251869
Abstract: The rate of maternal deaths in remote areas in eastern Indonesia–where geographic conditions are difficult and the standard of infrastructure is poor–is high. Long travel times needed to reach emergency obstetric care (EMOC) is one cause of maternal death. District governments in eastern Indonesia need effective planning to improve access to EMOC. The aim of this study was to develop a scenario modelling tool to be used in planning to improve access to EMOC in eastern Indonesia. The scenario model was developed using the geographic information system tool in NetLogo. This model has two inputs: the location of the EMOC facility ( PONED ) and the travel cost of moving across geographical features in the rainy and dry seasons. We added a cost-benefit analysis to the model: cost is the budget for building the infrastructure benefit is the number of people who can travel to the EMOC in less than 1 hour if the planned infrastructure is built. We introduced the tool to representative midwives from all districts of Nusa Tenggara Timur province and to staff of Kupang district planning agency. We found that the tool can model accessibility to EMOC based on weather conditions compare alternative infrastructure planning scenarios based on cost-benefit analysis enable users to identify and mark poor infrastructure and model travel across the ocean. Lay people can easily use the tool through interactive scenario modelling: midwives can use it for evidence to support planning proposals to improve access to EMOC in their district district planning agencies can use it to choose the best plan to improve access to EMOC. Scenario modelling has potential for use in evidence-based planning to improve access to EMOC in low-income and lower-middle-income countries with poor infrastructure, difficult geography conditions, limited budgets and lack of trained personnel.
Publisher: World Scientific Pub Co Pte Lt
Date: 06-2010
DOI: 10.1142/S1793962310000158
Abstract: We propose a method of s ling regular and irregular-grid volume data for visualization. The method is based on the Metropolis algorithm that is a type of Monte Carlo technique. Our method enables "importance s ling" of local regions of interest in the visualization by generating s le points intensively in regions where a user-specified transfer function takes the peak values. The generated s le-point distribution is independent of the grid structure of the given volume data. Therefore, our method is applicable to irregular grids as well as regular grids. We demonstrate the effectiveness of our method by applying it to regular cubic grids and irregular tetrahedral grids with adaptive cell sizes. We visualize volume data by projecting the generated s le points onto the 2D image plane. We tested our s ling with three rendering models: an X-ray model, a simple illuminant particle model, and an illuminant particle model with light-attenuation effects. The grid-independency and the efficiency in the parallel processing mean that our method is suitable for visualizing large-scale volume data. The former means that the required number of s le points is proportional to the number of 2D pixels, not the number of 3D voxels. The latter means that our method can be easily accelerated on the multiple-CPU and/or GPU platforms. We also show that our method can work with adaptive space partitioning of volume data, which also enables us to treat large-scale/complex volume data easily.
Publisher: Springer Science and Business Media LLC
Date: 22-01-2014
No related grants have been discovered for Frederika Rambu Ngana.