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regarding treatment customization. Once the treatment has been completed, the relevant artifact will be available for viewing.

1.3 Referral follow-up:

The system will allow the user to view information about all treatments the patient received, including treatments that were referred to a medical facility using an identical or compatible EMR system.

1.4 Prescribe preventative care:

The system will provide the user with general guidelines for relevant preventative care for a given diagnosis.

  • 2.

    Decision Support:

    • 2.1

      Confirm a clinical diagnosis:

The system will compare the signs, symptoms and risk factors the user has acquired based on a patient‟s symptoms and compare them against a database of symptoms for a given diagnosis. If the system finds the diagnosis to be inconsistent with symptoms, then the system will display a message to that effect as a warning to the user.

2.2 Suggest treatment plan processes:

The system, when given a diagnosis, will compare treatments the patient has already received to a list of possible treatments for that diagnosis. The system will then suggest the relevant treatment plan and call attention to elements of the plan that have not already been administered.

2.3 Promote the use of “best practices”:

The system, when presented with a diagnosis, will present a list of generally accepted treatments for the diagnosis. The list will be retrieved from a database that contains a list of best practice guidelines and is maintained by the system.

2.4 Customize treatment according to specific conditions:

The system will allow the user to enter any notes or special instructions (i.e., allergies, recent trauma, etc.) when scheduling a treatment. Any special instructions that a user adds will be viewable by any other user observing the patient's medical history.

    • 2.5

      Distinguish between various types of MRSA:

      • 2.5.1

        Determine if MRSA is Health-Care acquired (HA-MRSA)

Template based on IEEE Std 830-1998 for SRS. Modifications (content and ordering of information) have been made by Betty H.C. Cheng, Michigan State University (chengb at chengb.cse.msu.edu)


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