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FUNCTIONS OF HEALTH INFORMATION MANAGER
1. they play a major role in the collection, analyzing ,maintenance of data that will be received by doctors ,nurses etc.
2. Provide accurate data when required.
3. They work in clinic.
4. They assess and manage information concerning patients so as to avoid passing
harmful information that will add insult to injury to their health.
5. They acts as interlink with the patients and other health professionals.
6. They indispensable to the running of health management as regards the integrity,
security , and protection of sensitive patients’ data.
COURSE RELATED TO HEALTH INFORMATION MANAGEMENT
2 .Health education certificate
3. Health science.
5. Public health
Health information management uses science information to collect ,store ,transmit ,update health care records of patients .They work with coded healthcare data, epidemiology ,demographic , and clinical to maintain effective service delivery, detect health information problem to boot.
SHORT HISTORY OF HEALTH INFORMATION MANAGEMENT
I t can be traced to the introduction of the American Health Information Management Association in 1928.In 1938, the American health information management was called American Association of Medical Record Librarian(AAMRL).As the development of the sector continues to grow in United States, the American Health Information Management Association was changed to Health Information Management.
According to American Health Management Association, there are four processes for documenting and managing quality data.
1. Analysis: the process of translating data into information.
2. Application: the purpose for which data are collected.
3. Warehousing: the processes, systems used to store and maintain data.
4. Collection: the process whereby data are accumulated .Each of these four keys is
analyzed with ten different characteristics.
1. Accuracy: the correctness of data
2. Accessibility: accessible and legal to collect.
3. Comprehensiveness; complete data collection and documentation.
4. Consistency: the same before and after translating data.
5. Currency updating data.
6. Granularity: attribute and value of data.
7. Definition: a clear meaning between the current and the future.
8. Precision: brief and clear of vale data
9. Relevancy: collected data should be important for application.
10. Timeliness: the usage and context of data.
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