Information management system

Abstract

The invention discloses an information management system, and belongs to the field of informatization management systems. The system comprises a doctor workstation subsystem, a nurse workstation subsystem, a laboratory result subsystem, a consultation subsystem, a patient use subsystem, an information transfer docking management subsystem, a server, a medical institution statistics subsystem, a medicine management subsystem, a patient referral subsystem and an occupational exposure management subsystem. According to the invention, the information filling and processing efficiency is improved,and the previous mode of patient treatment-paper form filling-data entry reporting is changed into patient treatment full-process informatization. Repeated information is automatically called by the system, unnecessary repeated input is omitted, and laboratory data can be automatically filled by calling a hospital LIS or HIS system database, so that the working efficiency is remarkably improved, manual input errors are reduced, and the labor cost is remarkably reduced.

Description

technical field [0001] The invention relates to the field of information management systems, in particular to an information management system. Background technique [0002] Over the years, our district has realized the basic management of the AIDS antiretroviral treatment work in the whole district through the national system. But in fact, the annual tuberculosis screening of the patients under treatment, the HIV antibody detection of single-positive spouses, and the filling of case follow-up forms are mainly completed by designated hospitals for AIDS antiretroviral treatment, and the workload of designated hospitals has increased significantly. In addition, the designated hospitals are also responsible for the assessment and disposal of occupational exposure to AIDS. However, due to the suspension of the laboratory system in the national system for many years, the management of occupational exposure to AIDS is in a state of non-information management and disorder. With th...

AI Technical Summary

Problems solved by technology

Hospitals that treat a large number of people often need to arrange several full-time information entry personnel to work, and the manpower burden is heavy.

[0004] 2. There are many data contents filled in repeatedly in different workrooms, which wastes time and energy

Repeatedly filling in the same content distracts and wastes the time and energy of medical staff, which affects the quality of major tasks such as diagnosis and consultation

[0005] 3. The timeliness of data collection, reporting and statistical analysis of other related work other than antiviral treatment is low

For the treatment of AIDS patients, most treatment sites still stay at the level of relatively primitive working methods such as manual writing of medical records, prescriptions, manual filling of forms, and manual statistical data. Many, very inefficient

In addition, limited by the authority of the national system, hospitals cannot realize information management such as tuberculosis screening, spouse testing, and case follow-up through the national system. The original data of each treatment point still needs to be manually registered, classified, and counted before reporting. The accuracy is difficult to guarantee, and the efficiency of data reporting and statistical analysis is greatly restricted

[0006] 4. There are hidden dangers in the information exchange process

There are corresponding confidentiality requirements for AIDS treatment data. The treatment information of each treatment point (treatment list, number of people, referral approval, follow-up completion, summary analysis results, etc.) Security is difficult to guarantee, and there are security risks of data loss and leakage

[0007] 5. The monitoring of relevant medical indicators in antiviral treatment work, such as treatment failure, antiviral drug side effects and long-term complications, lacks quick guidance methods

In the past, the Guangxi AIDS Diagnosis and Treatment Quality Control Center downloaded historical cards from the national system, performed statistical analysis on relevant indicators, and then fed back to each treatment point after discovering problems. The processing data volume was large, time-consuming, and timeliness was not high.

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