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My Heal Record System Project Vision Document

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You Need to Create a Project Vision Document Which Contains:






Project Vision Document

In order to support the project approval through providing the input, the project vision document has been created. This vision document consists of the information like issues, capabilities, functions, benefits of the system.

The Title of the Project:

The title of the project is "Implementation of My Health Record for Commonwealth Government of Australia”.

Description of the Project:

The project owner is The Commonwealth Government of Australia. The organisation wants to build a system that will be connected to every clinical system of Australia. The system will collect data from the clinical system database and provide it to the users.


  1. Developing a system that will be installed in the clinical system
  2. Developing cloud based database
  3. Developing MY Health Record


The main functionalities of the system are such as following.

  1. Connecting database of the clinical systems with the cloud database
  2. Allowing access to the data to the user
  3. Authorising the user


Potential technologies to be used in the project are as following.

  1., HTML, CSS
  2. Big Data              
  3. Cloud Architecture
  1. Data Mining
  2. Java Platform
  3. JavaScript
  4. Encryption

Target Audiences:

The users of the system will the patents of the country and the doctors.


The Information and Communication Technology are inclined to issues. This may bring about because of deficient information of the representative or absence of support of the partner. The underneath is a portion of the issues that can emerge in this venture.


Inappropriate Functionality:
The framework will be coordinated into all the clinical frameworks in the Australia. It should be viewed as that not every one of the frameworks keeps running on a similar stage and have a similar kind of database. The venture framework examiner and the administrator must figure out how to plan the framework so it can speak with every one of the frameworks. This will make the issue of wrong usefulness for a few frameworks where some will work fine. 

Malfunction: As the complexity of the system is very high, it is highly possible that the system will malfunction in its lifetime.


Speedy Data Access: The framework will different look calculations for encouraging the information to get to time. The framework will utilise enormous information for taking care of the information related exercises. The huge information will permit the framework to hold tremendous information in one area, and the information procedure will be a great deal more proficient.

Remote access to information: The framework will store the information in the cloud. The cloud is the virtual innovation that permits clients to get to capacities and information on the web. This infers the client using the site or application can get to the framework from anyplace and at whatever time.


Improved Treatment: The framework will hold all the record of the patient. Taken for instance, if the patient went to check up for fever two months back and cannot recall that, it is not a major issue any longer. It is because of the framework will remember everything for the patient. The specialists can get all the patient treatment-related exercises precisely. This will open more approaches to better treatment.

The other benefits of the system are less amount of treatment cost, effective checkup and more.



Hripcsak, G., & Albers, D. J. (2013). Next-generation phenotyping of electronic health records. Journal of the American Medical Informatics Association, 20(1), 117-121.

Hripcsak, G., & Albers, D. J. (2013). Next-generation phenotyping of electronic health records. Journal of the American Medical Informatics Association, 20(1), 117-121.

Simpson, K. R. (2015). Electronic health records. MCN: The American Journal of Maternal/Child Nursing, 40(1), 68.

Urech, T. H., Woodard, L. D., Virani, S. S., Dudley, R. A., Lutschg, M. Z., & Petersen, L. A. (2015). Calculations of financial incentives for providers in a pay-for-performance program: manual review versus data from structured fields in electronic health records. Medical care, 53(10), 901-907.

Zhou, S. M., Fernandez-Gutierrez, F., Kennedy, J., Cooksey, R., Atkinson, M., Denaxas, S., ... & Sudlow, C. (2016). Defining disease phenotypes in primary care electronic health records by a machine learning approach: a case study in identifying rheumatoid arthritis. PloS one, 11(5), e0154515.

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