Drug inventory prediction system and method based on big data

A technology of inventory forecasting and big data, applied in forecasting, data processing applications, medical care resources or facilities, etc., can solve problems such as discrepancies, insufficient drug inventory, and insufficiently objective and accurate forecast results, so as to reduce the weakening of drug efficacy, The effect of reducing drug inventory and facilitating control

Pending Publication Date: 2020-06-19
重庆亚德科技股份有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for hospitals, it is not enough to only grasp the inventory of medicines, and it is also necessary to predict the purchase volume of medicines, and the existing forecasting methods are mostly experienced medicine management personnel, based on experience, and the forecast results Not objective and accurate enough
At the same time, due to the uncertainty of the development of the disease, there is a difference between the experience of drug managers and the demand for drugs in the current situation.

Method used

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  • Drug inventory prediction system and method based on big data

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] Drug inventory forecasting system based on big data, as attached figure 1 As shown, it includes a database, a medication statistics subsystem, an inventory statistics subsystem, a management terminal, and the management terminal is used by drug management personnel. The database stores a purchase time record form, a prescription record form, and a medicine withdrawal record form.

[0037] Medication statistics subsystem, including:

[0038] The purchase time setting module is used to obtain several purchase times, and record the purchase times in the purchase time record table of the database in chronological order. Purchasing time is the time for purchasing medicines agreed upon by the hospital and the drug supplier. In this embodiment, the first day of each month is defined as the purchasing time, and several purchasing times are all purchasing times within a year, that is, the purchasing time record table There are 12 purchase times recorded in it.

[0039] The hi...

Embodiment 2

[0051] The difference between this embodiment and the first embodiment lies in that the big data-based drug inventory forecasting system also includes a procurement statistics subsystem.

[0052] The time calculation module is also used to obtain the current time when receiving the purchase signal, and obtain the next purchase time from the purchase time record table according to the current time, and send the current time as the start time and the next purchase time as the end time to the history development Drug statistics module. The historical prescription information generated by the historical prescription statistics module according to the current time and the next purchase time is used as the historical prescription information B, and the historical prescription information B is sent to the predicted drug sales statistics module. The predicted drug sales statistics module generates predicted drug sales information b according to the historical prescription information ...

Embodiment 3

[0059] Drugs are usually stacked in full boxes in the drug storehouse. When medical personnel need them, they take out the full box of medicines from the drug storehouse and distribute them to the pharmacy or nurse station. Since the medicines are stored in a stacked manner, it is not standardized to take the medicines. Behavior makes the stability of medicine stacking weakened, subject to slight vibration, prone to falling of the medicine box. In hospitals, some medicines are still packaged in glass, and bumps can easily cause the glass packaging to break, and the medicine bottle will be damaged if the medicine box falls, which will cause the medicine to fall, and the medicine box will usually bring a series of problems. Chain reactions, such as collisions with other medicine boxes, resulting in a large number of medicines falling, and the falling of many medicines cannot be recognized at all, and the dropped medicines can only be discarded. Therefore, in order to avoid the wa...

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Abstract

The invention relates to the technical field of medicine management, in particular to a medicine inventory prediction system and method based on big data, and the system comprises a medicine use statistics subsystem which is used for obtaining historical purchasing time, obtaining historical medicine opening information A from historical current time to purchasing time according to the historicalpurchasing time, and carrying out the statistics of the historical medicine opening information A to generate predicted medicine selling information a; and the inventory statistics subsystem is used for acquiring the current inventory information and generating predicted inventory information according to the predicted medicine selling information a and the current inventory information. By adopting the scheme, the sales volume of the medicines can be accurately predicted according to the historical medicine opening information of doctors, so that the inventory of the medicine library at the purchasing time is obtained, a hospital is assisted in determining the medicine purchasing volume, and the inventory of the medicines in the medicine library is reduced.

Description

technical field [0001] The invention relates to the technical field of drug management, in particular to a big data-based drug inventory prediction system and method. Background technique [0002] With the continuous deepening of informatization construction, the information management platform has completed the functional transformation from informatization construction to data accumulation. In the fields of communication, finance, and large-scale manufacturing, the urgency of the storage and analysis of massive data has become increasingly obvious. Taking mobile communication operators as an example, the demand for data services has increased sharply, and the traffic has increased sharply. Operators need to coordinate the development of different networks (WLAN, LTE, 3G, 2G), centralize management, maintain network problems in real time, and deal with network failures in a timely manner. . It is against this background that the big data forecasting system came into being....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/08G16H40/20
CPCG06Q10/04G06Q10/0875G16H40/20
Inventor 刘震冯永季科张建贞杨文武寇晓明钟新莉
Owner 重庆亚德科技股份有限公司
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