Less Resources, More Outcomes
1. Summary
In this paper, we regard the health care system (HCS) as a system with input and output, representing total expenditure on
health and its goal attainment respectively. Our goal is to minimize the total expenditure on health to archive the same or maximize
the attainment under given expenditure.
First, five output metrics and six input metrics are specified. Output metrics are overall level of health, distribution of health
in the population,etc. Input metrics are physician density per 1000 population, private prepaid plans as % private expenditure on
health, etc.
Second, to evaluate the effectiveness of HCS, two evaluation systems are employed in this paper: Evaluation of Absolute Effectiveness(EAE) 原文请加辣.文^论,文'网QQ3249,114
This evaluation system only deals with the output of HCS，and we define Absolute Total Score (ATS) to quantify the
effectiveness. During the evaluation process, weighted average sum of the five output metrics is defined as ATS, and the
fuzzy theory is also employed to help assess HCS. Evaluation of Relative Effectiveness(ERE)
This evaluation system deals with the output as well as its input, and also we define Relative Total Score (RTS) to
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quantify the effectiveness. The measurement to ATS is units of output produced by unit of input.
Applying the two kinds of evaluation system to evaluate HCS of 34 countries (USA included), we can find some countries which
rank in a higher position in EAE get a relatively lower rank in ERE, such as Norway and USA, indicating that their HCS should have
been able to archive more under their current resources .
Therefore, taking USA into consideration, we try to explore how the input influences the output and archive the goal: less input,
more output. Then three models are constructed to our goal: Multiple Logistic Regression
We model the output as function of input by the logistic equation. In more detains, we model ATS (output) as the
function of total expenditure on health system. By curve fitting, we estimate the parameters in logistic equation, and
statistical test presents us a satisfactory result. Linear Optimization Model on minimizing the total expenditure on health
We try to minimize the total expenditure and at the same time archive the same, that is to get a ATS of 0.8116. We
employ software to solve the model, and by the analysis of the results. We cut it to 2023.2 billion dollars, compared to
the original data 2109.8 billion dollars. Linear Optimization Model on maximizing the attainment
. We try to maximize the attainment (absolute total score) under the same total expenditure in2007.And we optimize the
ATS to 0.8823, compared to the original data 0.8116.
Finally, we discuss strengths and weaknesses of our models and make necessary recommendations to the
policy-makers。
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