Optimization And Analysis Of Screening Strategy Of Chronic Disease

Chronic disease not only threatens individual health, but also exertsgreat economic burden to the overall society which makes scientificmanagement of chronic disease significantly important. Since its chronicity,early detection of chronic disease can effectively improve cure rate andprolong life expectancy. And health screening as the most reliable methodto detect a chronic disease at an early stage needs to be scientificallyarranged.Traditional screening strategy usually schedules annual or semi-annualhealth screening without consideration of the different characteristics ofindividuals among risk groups of chronic disease. Chronic disease notonly includes pathological characteristics， but would also be influencedby non-pathological characteristics (abbr. NPC). Based on the fundamentalhealth state reflected by the three NPCs, which are gender, and obesityspecifically, classify the risk group of people and calculate the respectiveincidence rate of chronic disease using decision tree method with SPSS.Based on the incidence rate calculated according to the three NPCs,extract the formula of expected lead time of screening and analyze theeffectiveness of health screening using quantitative methods. Setnon-linear programming to determine an optimal dynamic strategy whichtargets to cut down the expected lead time with limited overall screenings.Then solve the programming model with KT conditions and dynamicprogramming respectively and compare the solutions obtained from thesetwo methods. Perform empirical comparative studies to demonstrate theefficacy of the dynamic screening strategy and model. Since regular screening service is always performed against more thanone disease, it makes sense to study the collaborative screening strategy oftwo diseases. Therefore，set multi-objective decision model which aims toshorten the expected lead time both of the two diseases to find the optimalstrategy of collaborative screening and then discuss the rationalityconditions of collaborative screenings for theses two diseases fromeconomic perspective.