Literature DB >> 20703580

Apply influence diagrams for utility analysis of paying the weight-reducing expenses: a case study in taiwan.

Fan Wu1, Pei-Ran Sun, Chi-Chang Chang.   

Abstract

To effectively control the growth of medical expenditure, Bureau of National Health Insurance (NHI) of Taiwan has taken many measures, including the Reasonable Number of Outpatient Services, Ceiling Price, Global Budgets, Strategic Analysis and the Excellence Plan; however, these measures can only scratch the surface. Due to the change of life style and the deteriorating condition of over-nutrition and obesity, people now have a higher risk of diabetes, hypertension, hyperlipidemia, cardiovascular disease, gallbladder disease, cancer, gout, arthritis, and so on, which leads to higher medical expenditure. Therefore, good civil preventive health care is regarded as the solution of surging medical expenditure. According to NHI's statistics, the annual medical expenditure of diabetes is about 13 billion NT dollars. Among these diabetics, over 95% are affected by type 2 diabetes mellitus; at least two-thirds--over 80% according to some researches--are overweight or obese. The research says, losing 5% to 10% of the original body weight can lower the risk of chronic diseases effectively; also, giving early therapy for obesity can reduce the complication probability, thus for avoiding the waste of medical resources. By applying influence diagrams of Bayesian Network and Utility Expect of statistics, this paper evaluates the medical expenditure of Taiwan's NHI under the circumstances of providing and not providing benefit for weight-loss outpatient services. The result of this research is that the cost of not providing benefit for weight-loss outpatient services is 3.4 times of the contrary. Therefore, if Taiwan's NHI provides reasonable benefit for weight-loss outpatient services, not only the risk of people suffering from diabetes, hypertension, hyperlipidemia, cardiovascular disease, gallbladder disease, cancer, gout, arthritis, etc. will go down; but also the medical expenditure can be effectively reduced.

Entities:  

Mesh:

Year:  2009        PMID: 20703580     DOI: 10.1007/s10916-009-9346-x

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  14 in total

Review 1.  Obesity as a medical problem.

Authors:  P G Kopelman
Journal:  Nature       Date:  2000-04-06       Impact factor: 49.962

2.  Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.

Authors:  Ali H Mokdad; Earl S Ford; Barbara A Bowman; William H Dietz; Frank Vinicor; Virginia S Bales; James S Marks
Journal:  JAMA       Date:  2003-01-01       Impact factor: 56.272

Review 3.  Weight management through lifestyle modification for the prevention and management of type 2 diabetes: rationale and strategies: a statement of the American Diabetes Association, the North American Association for the Study of Obesity, and the American Society for Clinical Nutrition.

Authors:  Samuel Klein; Nancy F Sheard; Xavier Pi-Sunyer; Anne Daly; Judith Wylie-Rosett; Karmeen Kulkarni; Nathaniel G Clark
Journal:  Diabetes Care       Date:  2004-08       Impact factor: 19.112

4.  Uncertainty and decisions in medical informatics.

Authors:  P Szolovits
Journal:  Methods Inf Med       Date:  1995-03       Impact factor: 2.176

5.  Prevalence and risk factors for micro- and macroalbuminuria in an Italian population-based cohort of NIDDM subjects.

Authors:  G Bruno; P Cavallo-Perin; G Bargero; M Borra; V Calvi; N D'Errico; P Deambrogio; G Pagano
Journal:  Diabetes Care       Date:  1996-01       Impact factor: 19.112

6.  Meta-analysis: surgical treatment of obesity.

Authors:  Melinda A Maggard; Lisa R Shugarman; Marika Suttorp; Margaret Maglione; Harvey J Sugerman; Harvey J Sugarman; Edward H Livingston; Ninh T Nguyen; Zhaoping Li; Walter A Mojica; Lara Hilton; Shannon Rhodes; Sally C Morton; Paul G Shekelle
Journal:  Ann Intern Med       Date:  2005-04-05       Impact factor: 25.391

7.  Excess deaths associated with underweight, overweight, and obesity.

Authors:  Katherine M Flegal; Barry I Graubard; David F Williamson; Mitchell H Gail
Journal:  JAMA       Date:  2005-04-20       Impact factor: 56.272

Review 8.  Obesity and its surgical management.

Authors:  Edward H Livingston
Journal:  Am J Surg       Date:  2002-08       Impact factor: 2.565

9.  Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections.

Authors:  H King; R E Aubert; W H Herman
Journal:  Diabetes Care       Date:  1998-09       Impact factor: 19.112

10.  High prevalence of diabetic retinopathy and nephropathy in Polynesians of Western Samoa.

Authors:  V R Collins; G K Dowse; W E Plehwe; T T Imo; P M Toelupe; H R Taylor; P Z Zimmet
Journal:  Diabetes Care       Date:  1995-08       Impact factor: 19.112

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.