Title:Human Health Management and Life/Disease Risk Assessment: A Review
VOLUME: 15 ISSUE: 1
Author(s):Hui-Zhong Li, Xiang-Dong Liu* and Xin Shi*
Affiliation:Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, Faculty of Business and Law, Manchester Metropolitan University, Manchester, M15 6BH
Keywords:Health management, life risk assessment, disease risk assessment, random filter model, medical statistical charts,
the delay time model, residual life prediction.
Abstract:Background: Modern medical researches show that the health of a population is closely
related to their behavior, environmental factors, social and economic conditions, aging and genetic
susceptibility. Therefore, it is very important to study the relationship between these factors and
health of a population.
Objective: This study reviews the latest research progress in population health management and
life/disease risk assessment, analyzes the existing problems in relevant researches, and proposes
some improvement plans to solve the problems.
Methods: It also introduces the general methods of human health management and life/disease risk
assessment, analyzes the defects in these methods in practical application, and then draws conclusions
regarding industrial system equipment health management and residual life prediction, and
puts forward some new ideas to solve the problems.
Results: In the study of health assessment, although self-assessment of health is a common method
of determining health variables, its subjectivity and inaccuracy are problems that cannot be ignored.
In life/disease risk assessment studies, medical effect and efficacy are mainly evaluated, and little
consideration is given to other factors, such as behaviour, environment, and socio-economic status.
In the construction of statistical graphs, great individual differences, internal symbiotic variables
and external impact variables are seldom considered.
Conclusion: This study helps to understand the basic ideas and methods of health management and
life/disease risk assessment, and proposes some future research programs based on the author's
knowledge.
