2020 Fiscal Year Annual Research Report
Concept Design and Implementation of Personalized Triage to Reduce Healthcare Data Errors in Human Assisted Remote Healthcare Systems
| Project/Area Number |
18K11529
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| Research Institution | Kyushu University |
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Principal Investigator |
Ashir Ahmed 九州大学, システム情報科学研究院, 准教授 (30457444)
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| Co-Investigator(Kenkyū-buntansha) |
久住 憲嗣 九州大学, システムLSI研究センター, 准教授 (10380685)
イスラム ラフィクル 九州大学, 大学病院, 学術研究員 (20815906)
横田 文彦 九州大学, 持続可能な社会のための決断科学センター, 講師 (50760451)
福田 晃 九州大学, システム情報科学研究院, 教授 (80165282) [Withdrawn]
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | Healthcare data / data error / triage / acceptance range / portable health clinic |
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| Outline of Annual Research Achievements |
The objective of this research is to identify the root cause of remote healthcare data errors and propose a software solution to detect and reduce them to improve the efficiency of remote healthcare systems.
The study carried out field research in Bangladesh to find out the source and root causes of remote healthcare data errors. Among the data error sources, it was found that more than 82% of the errors occurred during the data digitization process. An extensive training program can help reduce such input errors.
The study proposed three different statistical approaches to determine acceptance ranges: (1) Human Acceptance Range (2) Group Acceptance Range and Personalized Acceptance Range.
The detected ranges were installed in the software system and applied over the same population group in Bangladesh in five phases. We observed the number of out-of-range data was gradually decreased. Initially, the unusual data was 5.86% without any intervention, then gradually decreased to 1.62%, 1.00%, 1.00%, and 1.63%. The fourth phase had new members. The out-of-range data were rechecked, but no errors were found. It means these are simply unusual.
In summary, this research showed its effectiveness quantitatively by using the Grameen-Kyushu University joint portable health clinic research platform in Bangladesh. The results will contribute to the advancement of next-generation remote healthcare systems in developing countries.
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