Improving Complete Access To Data Within Collaborative Systems In Healthcare Domain
The problem of accessing complete data especially involving different sources had been a major concern in many fields. Due to the absence of data model that become the barrier to access and manage complete datasets, data providers within the collaborative environment may affect users to have fast an...
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| Format: | Thesis |
| Language: | English English |
| Published: |
UTeM
2016
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| Online Access: | http://eprints.utem.edu.my/id/eprint/18543/1/Improving%20Complete%20Access%20To%20Data%20Within%20Collaborative%20Systems%20In%20Healthcare%20Domain%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/18543/2/Improving%20Complete%20Access%20To%20Data%20Within%20Collaborative%20Systems%20In%20Healthcare%20Domain.pdf http://eprints.utem.edu.my/id/eprint/18543/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=100985 |
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| Summary: | The problem of accessing complete data especially involving different sources had been a major concern in many fields. Due to the absence of data model that become the barrier to access and manage complete datasets, data providers within the collaborative environment may affect users to have fast and seamless accessibility. There had been many data accessibility improvements methods such as: data replication, data sharing, cloud computing and much more. This dissertation had presented the critical review of these methods based on their criteria of accessibility. However, studies to measure complete access to data were limited. A data accessibility model has been proposed within a collaborative environment named as Collaborative Integrated Database System (COLLIDS), in order to overcome the issue to complete access to data. COLLIDS aims to improve complete access to data in multi-data provider‟s context in a case study. The highlighted feature in COLLIDS which is the completeness analyzer provides relative completeness analysis among data provider. Population-based Completeness (PBC) was applied in COLLIDS completeness analyzer to measure the completeness for the dimension of interest, among the population of data providers. It has been hypothesized that there will have an increment in the ratio of completeness of data accessible by data providers. Therefore, COLLIDS have been evaluated in terms of increment of data completeness for all data providers. Further analysis also has been conducted to compute the completeness cases of data providers. In this dissertation, healthcare domain has been chosen as the case study in order to explore the problem of accessing complete data seamlessly. Sample data have been collected from 106 healthcare providers called as „panel clinics‟. PBC have been used in this dissertation to measure the reference population which is the union of patient datasets collected from all the clinics. Two groups of datasets have been measured; „As-Is Completeness‟ and „ Completeness Increment‟ in normality test and Wilcoxon-Sign Rank test, in order to know the significance differences between both groups. The outcome of this dissertation will have to contribute towards understanding for the practical analysis and the evaluation of COLLIDS data model, in measuring complete access to data within multiple data providers‟ environments. |
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