2019 Fiscal Year Research-status 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)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | Remote Healthcare / Error Detection / Personalized Triage |
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| Outline of Annual Research Achievements |
The objective of this project has been to introduce the concept of Personalized Triage to reduce Healthcare Data Errors in Human Assisted Remote Healthcare Systems. At the first step, we investigated anthropometric growth patterns of adults (> 20 years of age). Over forty thousands health records were randomly collected by using our portable health clinic system. Incomplete records, uninterested records (young patients, age <20 years) were removed. Finally N=25,447 (male: N=13,069 and female: N=12,378) records were considered. The resulting plots comprise a series of percentile (5th, 10th, 25th, 50th, 75th, 90th, and 95th) curves that illustrate the distribution by height, weight, BMI, waist, and hip. The obtained curves were smoothened by Local Polynomial Regression (LPR). For height, there is no sharp change until the age of 49, but after the age of 50, we observe a slight decline of height and a sharp decline after the age of 80. Weight grows until the age of 49 and decline after that. Waist and Hip show similar growth characteristics with weight. A very small samples were available from old people (>80 years old). The obtained growth patterns at this age level are not representative. The study will continue to collect more samples, find growth pattern for females and compare with those of males. Once the range for age based anthropometric data is known, it will be much easier to predict measurement errors of the patients for remote healthcare systems. significant clinical growth patterns over age.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
As per the plan, we designed the concept of personalized triage. There are three steps for the final implementation of the concept: (1) Human Acceptance Range (2) Group Acceptance Range (3) Personal Acceptance Range. At the first step, we completed the previously recorded data analysis to find the human acceptance range and also part of the group acceptance range.
In addition, we investigated the influence of clinical factors (Blood glucose, Blood Uric acid, BMI etc) in determining the health status of a person.
We have already submitted 4 journal papers. 2 are accepted and rest 2 are in review process. The progress is according to the plan.
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| Strategy for Future Research Activity |
We are almost done with the personalized triage for NCDs. Now we are working on new triage to estimate health status for COVID-19 patients. We are redesigning our PHC for two modes- (1) regular mode and (2) emergency mode. The emergency mode has multiple advantages. New triage is developed. We will deploy this new triage to check the accuracy.
The emergency mode will eliminate the risk of transmission among frontline healthcare staff and contribute significantly towards reducing pressure on healthcare services and resources.
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| Causes of Carryover |
The total expenditure was executed almost according to the initial plan. Only 84,566 yen left for next year. We will use this amount for students remuneration (shakin) for data analysis.
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