Quality control: ConceptsTopic number: 1425414967389

Quality control is a process of aligning the patient order information with the images that come from different sources. It also includes reassigning or deleting studies for billing and cleanup purposes.

Quality control is an automated step in the unverified study workflow, but it can also be performed manually.

Note:

If you intend to delete the end results of a series of QC operations and then resend the original images from the modality, do not delete the results. Deleting and resending images does not work in Enterprise Imaging 8.1 and later. Enterprise Imaging will not accept the re-sent images.

Refer to “Troubleshooting: Cannot restore DICOM data after deleting the results of a series of QC operations” (topic number 1520961955077) in the Administrator Desktop Help.

Quality control in the unverified study workflow

When study images are taken without an existing order that includes patient data, the order is created afterward. For example, in the emergency department, patients are sometimes initially identified by means of a temporary patient ID, because their real identity is unknown.

Patient data associated with the study images and contained in the order must be the same. Creating an order for an already existing study triggers an automated verification process. It checks the following attributes:

  • Study UID
  • Patient ID
  • Accession number
  • Procedure code

If one of these attributes does not match, the study is marked as unverified. Manual quality control is required.

The automated QC workflow is defined by the administrator.

Manual quality control

Quality control tasks can be created as needed, for verified and unverified studies. For example, images from two different patients might be linked to one study because the technologist forgot to register the second patient after completing the study for the first. To resolve this, you can create a manual QC task—in this case, a split.

The main types of quality control tasks are:

  • Fixing studies—Re-identifying the study by patient name or fixing patient demographics when the modality information assigned to a study does not match the procedure information from the RIS. It involves moving unverified source study images into an empty order that contains the appropriate patient and order information.
  • Merging studies—Combining images from two studies into one.
  • Segmenting studies—Needed mostly for billing and reporting purposes, in cases when the number of studies ordered does not match the number performed. Segmenting involves redistributing images to other procedures for the same patient.
  • Splitting studies—Required when images for one patient are mistakenly included with another patient’s images. It involves dividing images between the two studies.
  • Deleting studies—When images are of poor quality, you can delete the study, then resend it from a modality.

Note:

When you perform quality control, all users viewing the corresponding studies and tasks are informed about what actions have been taken.

Lookup of target studies

The lookup of target studies during a quality control task uses the following default settings:

  • If the source study is for a verified patient, the following search fields are automatically filled with the source study values: patient ID, modality type, and patient date of birth.
  • If the source study is for an unverified patient, the following search fields are automatically filled with the source study values: patient first name, last name, and date of birth.

To allow for more flexibility in a multi-department setup, the lookup of target studies is configurable. Users can change the default settings and store them on system, desktop profile, and user levels.