http://buycialisonlineworldwidestore.com/
https://jacup.com/

Description

Management information systems incorporating forecasting techniques have been successfully used in the context of operational research by many a profit organization and in versatile fields, such as business, commerce and industry. In all cases, they seem to facilitate managerial decisions, by giving an insight into the future. Because of the high costs involved in health care and the value and fragility of human health and life, such techniques should also be utilized by hospitals and their departments. Benefits can be identified in a great variety of scales and aspects. Our proposed system, Radiology Information & Forecasting Integrated System (RIFIS), will consist of two interacting subsystems: Radiology Information Subsystem (RIS) and Forecasting Information Subsystem (FIS).
RIS will help keep track of patient data, their medical status, stored items, equipment condition, etc, thus making information storage and flow through different sections of the departments and hospital more efficient. Structured information will aid report composition and help improve timelines and overall health care. Furthermore, accurate predictions, made in conjunction with FIS, can help supply orders meet demand patterns leading to more timely placed orders for all items, from drugs to expendable equipment parts. Less expiring products will end up wasted, which is beneficial in both economical and environmental sense, while amounts of items in stock will never be excessively large, keeping storing costs to a minimum. At the same time, however, a safety stock will always be available, so that patients can be treated in time, which is an obvious health benefit for each patient separately, but also concerning public health. Therefore, such a planning can help curtail supply expenditures, inventory upkeep cost and waste management procedures, delivering a relief on both where to buy viagra cheap hospital budgets and national economy, by decisively lowering health care expenditures.
A core module of statistical analysis and forecast estimation, FIS, will be well fitted in the general context of RIFIS. FIS is an innovative integrated business forecasting support system, which incorporates all available knowledge and experience in the field of forecasting, while, at the same time, it fully utilizes the up-to-date software and computer potential. This module will feed on collected data from the overall information system and produce forecasts and estimates, which can help managerial decisions. The aim of this system focuses on practicing managers (at the level of financial directors, product managers, production/inventory managers and planners/analysts) and its design and development are determined by the ideal of making the task of managerial forecasting as straightforward, user-friendly and practical as possible without compromising on the question of scientific vigor and statistical accuracy. The system will at the same time be useful for managers who have no forecasting technique and computing background.
Our expert system, RIFIS, will enable the management team of the organization to calculate the impact of special events (a disease breakout, etc) on the demand of medical items. This special feature is one of the key benefits of the software and its involvement in the forecasting process will lead to better arrangements and decisions concerning inventory control and an overall expenditure reduction. The monitoring and processing feature will calculate the errors made in long term forecasts, as soon as new data become available and let managers re-run the forecasting process in order to achieve better and more accurate forecasts. The system will automatically choose the best forecasting method for each inventory item and also highlight the most important items of the hospital department, features that contribute to an improvement of demand forecast accuracy and “safety stock” forecast accuracy. However, the statistically-skilled personnel will still be able to use custom methods in combination with expert judgment to improve decision making.

Language

Login Form