Improving the quality of health services in the health sector is an important and necessary matter that must be taken care of and improved, and this study seeks to demonstrate the role of quality costs in improving the quality of health services and achieving a high level of quality to satisfy the beneficiaries and to provide health services of good quality, and the research concluded that the main point of service provision Good health is the costs of prevention and evaluation (costs of quality conformity) and attention to it, and that technical competition contributes greatly to the development of the level of quality, as well as the use of health and medical staff with competent expertise, and that the costs of internal failure and the costs of external failure (costs of quality mismatch) are closely related. With the components of continuity, safety, and justice for health services, the study recommends focusing on technical competition and attention to medical devices, setting adequate evaluation costs to avoid quality problems represented in the costs of internal and external failure, and focusing management's attention on redistributing internal and external quality costs to achieve a high level of quality health services.
The impact of quality costs in improving the quality of health services
quality
costs
quality costs
quality of health services
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
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