Blado Reject Analysis SCAR 2002

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Is Reject Analysis Necessary after Converting toComputed Radiography?

Article in Journal of Digital Imaging · February 2002

Impact Factor: 1.19 · DOI: 10.1007/s10278-002-5028-7 · Source: PubMed

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Maria Elissa Blado

Texas Children's Hospital

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Title: Is Reject Analysis Necessary after Converting to Computed Radiography?

Primary Author: Rosemary Honea A.R.R.T., A.R.D.M.S.,

Secondary Author: Maria Elissa Blado

Secondary Author: Yinlin Ma

Affiliation: Edward L. Singleton Diagnostic Imaging Services


Address: Edward L. Singleton Diagnostic Imaging Services


6621 Fannin MC 2-2521

Houston, Texas 77030-2399

Phone: (832) 824-5563 voice

(832) 825-5370 facsimile

Internet Addresses: [email protected] (Rosemary Honea)

[email protected] (Maria Elissa Blado)

[email protected] (Yinlin Ma)

Topic 1. Modality Image Acquisition (Detectors, Imaging Physics, Quality Assurance)

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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ABSTRACT

Reject Analysis is an accepted standard of practice for Quality Assurance (QA) in conventional

radiology. The needs for Reject Analysis has been challenged by the introduction of Computed

Radiography (CR) because of low reported reject rates and because criteria for improperly exposed

image were lacking. Most CR systems include Quality Control (QC) workstations that are capable

of modifying the appearance of images before release, and also of deleting bad images before

being analyzed. Texas Children‟s Hospital has been practicing Computed Radiography since

October 1995, and now conducts essentially filmless imaging operations using a large-scale

Picture Archival and Communications (PACS) with fourteen CR units. In our hospital, the QC

workstation is a key element in our CR QC operation, however, the extensive software tools of the

workstation are limited in terms of avoiding repeated examinations. Neither the QC Workstation

nor the PACS itself are designed to support Reject Analysis, so our task was to design a system

that accommodates identification, isolation, and archiving of repeated examinations making use of

our electronic imaging systems. We had already developed transcription codes for our

radiologist‟s examination critique, so we adopted these as codes for rejected images. The

technologist at the QC workstation appends the critique code to patient demographic information,

and modifies other fields to indicate that the image is a reject, and archives as usual. Modified

routing tables prevent the release of rejected images, but ensure they are available for review. Our

frequency and reasons for repeated examinations are comparable to other reports of Reject

Analysis in the literature. The most frequent cause of a repeated examination is mis-positioning.

Developing the method for capturing repeat, collecting the data, and analyzing it is only one-half

of the battle. In order to achieve an improvement in services, it is necessary to feedback the results

to management and staff and to implement training as indicated. It is our intent to share our results

with PACS and CR vendors in the hope that they will incorporate some mechanisms for Reject

Analysis into the design of their systems.


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INTRODUCTION

Reject Analysis (RA), a.k.a. Repeat Analysis, is an accepted standard practice for Quality

Assurance (QA) in conventional radiography. Analysis of rejected images yields information

about the efficiency of the department and is the basis for Quality Control (QC) and the education

of the individual technologist1. While no one would question the value of performing Reject

Analysis, a.k.a. Repeat Analysis, in a conventional radiology department, the advent of Computed

Radiography (CR) has prompted some to challenge its relevance to electronic radiology

operations. This skepticism developed partly because of reports by early adopters of extremely

low reject rates using CR. The usual appearance of the CR image differs somewhat from a

conventional image and its contrast and density is automatically adjusted to improve appearance,

so criteria for improperly exposed images were slow to be recognized by practitioners. CR

systems almost universally include QC workstations that have the capability of modifying images

before release, as well as deleting unacceptable images. Even after more than a decade of

widespread clinical practice of CR, systems to support Reject Analysis are absent from standalone

CR systems as well as those incorporated into large-scale Picture Archiving and Communications

Systems (PACS). Our challenge was to utilize our electronic image acquisition and distribution

systems to develop a system for identifying, capturing, isolating, and archiving rejected images.

MATERIALS AND METHODS

Texas Children‟s Hospital operates a large-scale Agfa (Agfa Medical Systems, Ridgefield Park,

NJ) IMPAX Version 3.5 PACS. This system includes fourteen CR units with all Agfa Diagnostic

Center (ADC) production versions represented, namely the ADC70, ADC Compact, and ADC

Solo. Patient demographics and examination information are retrieved from the IDXRad Version


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9.7 Radiology Information System (RIS) and supplied to the ADC by Identification Stations

augmented by bar code scanners as described previously2. DICOM Modality Worklist

Management has been tested but is currently not practical for clinical operations. The Diagnostic

Imaging Service performed 141,321 examinations in calendar year 2001 (IDXRad), of which

93,386 are CR (Oracle version 7.0), consisting of 1.72 images per examination on the average.

Virtually all the primary interpretation is conducted using softcopy review stations: routine

printing and archiving of hardcopy images ceased on October 31, 2000.

The Processing Station. The ADC image is transmitted to one of eleven Processing Stations (PS,

a.k.a. VIPS) before being released for distribution in the PACS system. This QC workstation is a

key component in our imaging operation: a technologist inspects each image at the PS and

determines whether it was appropriately acquired and properly identified. If all views are

complete and acceptable, they are transmitted to the PACS system, the examination is “completed”

in the RIS, and the patient is released. In the event of errors, the PS has some sophisticated

features for modifying the image. As shown in Table I, some of these features are useful in

recovering images that would otherwise be rejected, such as by annotating the image when the

Left/Right marker is obscured, correcting incorrect demographic information, or reprocessing an

image with the appropriate examination menu selection. Technologists are discouraged from

making drastic adjustments to the image at the workstation3. The PS display is not designed for

primary interpretation: the image is down-sampled for display and the monitor luminance is not

strictly controlled. Technologists are trained to recognize anatomy, not pathology, and are as

likely to obscure important clinical features as to enhance them, especially when the display does

not match the appearance on diagnostic workstations. The operator of the PS also has the ability to

make bad CR images disappear without a trace.


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Reasons for Repeated Examinations. Table II shows reasons why an examination might need to

be repeated in a conventional department4. Each of these can occur with CR, although the

categories of “under -“ and “over -exposure”, and “lost film” require further elaboration. Even

though the CR system acts to adjust the density of the image to compensate for inappropriate

radiographic technique, a CR image that is under-exposed will appear “grainy” and a CR image

that is over-exposed subjects the patient to more radiation dose than necessary for the

examination5. In conventional radiography, the exposure level is evident from the optical density

(OD) of the film. Because density of CR is adjustable, the exposure level is revealed by numerical

analysis of pixel values in the digital image. An acceptable range of values was established for

this exposure indicator, called “lgM” or the “logarithm of the Median of the grayscale histogram”.

The range of acceptable values allows a factor of two under- or over-exposure around the target

value. Contrary to claims by some PACS proponents, electronic images can also be lost, either by

operator deletion or by equipment malfunctions resulting in corrupt image data files that cannot be

transferred.

Reject Codes. We previously reported a system of dictation codes for documenting radiologist

examination critiques6. Technologists team leaders used the dictation codes, shown in Table III to

classify the reason for repeating an image. The appropriate critique code, a delimiter (/), and the

responsible technologist‟s identification number are inserted before the contents of the Patient

Name field at the PS.

Segregating Rejected Images. A rejected image sent to PACS from the PS normally would join

the diagnostic images in the patient‟s examination folder. A procedure was developed to modify

specific fields to indicate that the examination is a reject. The text string “NONE” is inserted in

front of the contents of the Patient Name, Medical Record Number, and Accession Number fields.


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When these modified images are sent to PACS, they fail validation by the RIS interface and are

sequestered from public view by PACS users.

Releasing the Rejected Images for Archiving and Review. A PACS Analyst with

Administrative privileges retrieves the sequestered rejected images, modifies the Examination

Description field by inserting the text string “NONE-“, and forces the image into the public area.

(It is unfortunate that on the PS, the user is not allowed to edit the Examination Description field.

If this field was editable, the technologist will be able to enter the text „NONE‟ to its contents.

Once it is archived, there will be no need to manually modify this field by the PACS Analyst and it

will automatically route to its destinations.)

At this point the rejected image is disseminated according to rules established in the IMPAX

Routing Tables (Table IV). To avoid widespread dissemination of rejected images to clients

throughout the PACS network, the Routing Tables were extensively modified to send Rejects only

to the Archive Servers, where they would be automatically recorded on Magneto-Optical Disk

(MOD) and tape media7. Modification of Routing Tables that were appropriate for clinical

imaging operations was a major effort, and warrants further explanation in the discussion that

follows.

If we did not have reject images sent from the acquisition station, the specialty field in the Routing

Pattern table will indicate “Don‟t Care” (it does not matter what specialty the image is coming

from that station), as shown in Table IV. A new specialty called NONE is created and the routing

tables assign any examination procedure that has the text „NONE‟ with this specialty. It is quite

unfortunate that the routing pattern of our PACS system does not allow exclusive routing by

specialty. It will allow a specific specialty to route to a certain destination; for example, route


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ONLY FLUORO cases to a specific review station. But the design of configuring our routing

tables do not allow all specialties EXCEPT a specific specialty (in our case, the NONE specialty)

to route to a destination – unless we create an entry for EACH specialty.

As an example, on Table IV the CR modality has 14 different specialties. An entry for each

specialty was created to route to the NICU review station (patient location „NEO‟). The „NONE‟

specialty was not included so that the NICU physician will not be able to view the rejected image.

If there were more than one patient location to an area, i.e., ER and EMC for the Emergency

Room, then 14 entries for EACH patient location will be created on the routing pattern, in this case

a total of 28 entries for just one destination, as demonstrated in Table V.

The growth of the routing tables, in order to accommodate the rejected images into our archive

servers, was exponential and dependent on the number of each criteria: specialty, referring

physician, and patient location. The more specialties there are, the more the entries will be created

on the routing table for each referring physician and / or patient location.

Analysis of Rejected Images. Once a system was in place for documenting and preserving

rejected images, tools were needed to interrogate the image database to collect meaningful data for

Performance Improvement of imaging operations.

A script, using Standard Query Language (SQL) queries, was written to query the IMPAX image

database and to generate a report of all the archived NONE files in a month. This monthly report

is then imported to an Access database, which includes the following fields:

date of examination

time of examination

modality


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technologist number

accession number

examination procedure

number of images

and reject code.

All the data for these fields are retrieved from the IMPAX image database.

RESULTS AND DISCUSSION

Various statistical reports, using the information from NONE Access database, were generated.

These include:

Number of rejected CR images for the year 2001 and its percentage over the total number of

images in the archive (Table VI)

Number of rejected CR images broken down by reject code (Table VII).

Number of rejected CR images per shift and its percentage over the total number of images in

the archive per shift (Table VIII).

Number of rejected CR images by technologist number (Table IX).

Number of rejected CR images by examination description (Table X).

Table VI shows the number of rejected CR images for the year 2001 and its percentage over the

total number of images archived in a month. The data yields a yearly overall reject rate of 4.07%

of CR rejects for the year 2001. The average change in the monthly rates is 0.53% with the

maximum of 1.13% between August and September. Figure 1 is the chart representation of Table

VI.


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Table VII reports the number of rejected CR images broken down by reject reason code for the

year 2001. The codes listed are based on Table III, the Radiologist Examination Critique List. A

code for OTHER (code number 45) and NOT INDICATED (code number 46) were added to this

list. According to this data, the most common reason for rejecting an image is mis-positioning, at

62% compared with the total number of rejects. Inadequate inspiration comes in second at

8.73% and not enough contrast at 6.74%, while 5.7% of the rejects were not labeled with a reject

code. Two separate studies conducted at other institutions within the past 5 years also reported

positioning as the top reason for their repeated examinations, one at 57.19%4 and the other at

46.9%6.

Table VIII is a sample report on the number of rejects by shift. Figure 2 is the chart representation

of the percentages on Table VIII. These reports show that the weekend shift consistently has the

most number of rejects for the whole year.

Table IX shows a portion of the report listing the technologists‟ numbers and the number of

rejected images they archived over a period of time. This information is further broken down by

reject codes. The report consistently shows MISPOSITIONING as being the most common reason

for rejecting an image among the technologists. The number of rejected images by a technologist

will be compared with the number of images in the examinations a technologist actually performed

during this same period. The latter piece of information still needs to be entered in the NONE

database in order to get this ratio.

The under-reporting of rejected images, the toleration of unacceptable images, and the inconsistent

following of the procedure for sending rejected images to the archive could contribute to the

inaccuracy of the statistics. On the processing station, the technologist may send an image


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directly to the trashcan. Once that trashcan is emptied, the image will be deleted for good. This is

one example of under-reporting of rejected images.

Table X shows that CHEST examinations have the most number of repeats at 51.66% while

ABDOMEN procedures are at 9.97%. 9.69% of the rejects have not been indicated with an

examination description by the technologists (NOT INDICATED).

The list in Table III has been modified by the area supervisors to meet the technologists‟ needs in

being more specific and descriptive with their reasons for rejecting images. A number of the

reasons were broken down in more detail by indicating more specifics of various scenarios or

possibilities for doing repeats. This modified reject code list will assist the technologists with

consistency as well. Other reasons for repeats that have been discovered are:

„double exposure‟ (as opposed to „duplicate images‟),

„wrong marker‟ (as opposed to „no marker‟),

„patient mispositioned‟ and „cassette mispositioned‟,

equipment malfunction,

high / low lgM (instead of too much contrast or not enough contrast),

breaking down „artifacts‟ to „patient‟, „cassette‟, or „equipment‟,

radiologist request to reject,

and test images.

The categories of „Availability‟, „Identification‟, „Appropriateness of Exam‟, and „Diagnostic‟

have been modified by omitting reasons that are not used for rejecting an image. Table XI is the

modified reject code list that will be used beginning this year.


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There is more work to be done. There are a couple of pieces of information that may be added in

the Access database of NONE files. The first is the area where the examination was performed

(i.e., portable, main radiology/fluoroscopy, outpatient, etc.) which will be useful for the

supervisors of these areas. The second is the lgM value of every rejected CR image, which can be

extracted from its DICOM header file. From this, the distribution of the lgM values can be

reported and analyzed. The automation of data transfer from the IMPAX database to the Access

database of NONE files will also be explored. The PACS team will continue to extract the data

into the NONE Access database, from which the management of Diagnostic Imaging may generate

their statistical reports for their own use. The procedure for labeling the rejected images with

„NONE‟ will also be clarified for consistency as well as to eliminate the possibility of having any

more records recorded as „NOT INDICATED‟. Changes are expected as we evolve through this

electronic process of accommodating rejected images.

These preliminary statistical reports were presented to Diagnostic Imaging‟s management and staff

and a number of them have viewed the rejected images. These reports, being a source for Quality

Improvement (QI), will be analyzed to investigate the causes of rejects and find ways to eliminate

them. Retraining of staff and other corrective actions may have to be implemented and

documented.

The next focus of our department‟s QI efforts in Reject Analysis is expanding this process to the

areas or modalities that involve some form of radiation, such as Computed Tomography (CT),

Nuclear Medicine (NM) and scout images of Fluoroscopy examinations (not all the fluoroscopy

images are archived). How the technologists of these areas will be sending there reject images will

have to be reviewed and documented. This includes finding out where in their imaging chain do


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we accommodate the reject analyses. Their data will be placed in the same database as the reject

data for CR. Reports will also be generated and shared with the supervisors of these areas.

Of course, all these accommodations for reject analyses have been based on current versions of the

software of the acquisition stations, processing stations, and the PACS archive. They may not

work on the next version of IMPAX or processing stations. As we upgrade to the next versions of

each system, we would have to review the versions to assure that we can continue to do the

procedure we have developed for reject analyses.

We also intend to share our results with our vendors. They may be able to assist us in

accommodating reject images electronically, hopefully through a user-friendly mechanism, if not

in the current versions, maybe in future versions of their systems. Vendors play a vital role in the

world of reject analysis8. A few suggestions are one that allows specific fields to be edited to

include „NONE-„ labels, allows automatic r outing of rejected images, and will not allow deletion

of such images on the processing or quality control station.

The Diagnostic Imaging service formed a team to lower the reject rate. This team consists of all

Team Leaders from Nuclear Medicine, Ultrasound, Cat Scan, Portable X-ray, Outpatient,

Magnetic Resonance (MR), Main Radiology, and the PACS team. The lists of rejects (NONE

files) included discarded images from each modality. Team leaders were surprised to find that

some MR Technologists routinely acquire additional series, rather than following the appropriate

clinical protocol. When these Technologists determine which Radiologist is to interpret the

examination, they were having the PACS Analyst split away the images not in excess of the

protocol of the individual Radiologist protocol. The Team leader commented that this practice

contributed to extended patient scan times for a service already suffering from a substantial


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backlog as well as wasting PACS Analysts time and PACS archive space. This finding reinforced

the idea that reject analysis is valuable even for modalities that do not involve ionizing radiation.

CONCLUSIONS

Reject Analysis must be conducted routinely regardless of using conventional film/screen or CR

radiography. Attention to the sources and frequency of rejects can dramatically improve routine

image quality, provide a basis for in-service training of the individual technologist, resulting in

better patient care. The results of our reject analysis led our department to modify our entry

training program for new Technologists to emphasize averting the most common mis-positioning

errors. This is also included in evaluating job competency at 90 days post employment. The

efforts of the PACS Analysts in compiling reject reports from the image database are wasted

unless administrators are willing to implement methods of addressing the causes of rejects. Team

leaders are also key to this method: they are the ones who assure that rejects are properly reported

and they are the ones who determine whether an individual technologist or a group of technologists

need additional training.

The purpose, methodology, and importance of reject analysis must be emphasized with PACS

vendors so they can incorporate this in their software.


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REFERENCES

1. S.Peer, R. Peer, M. Walcher, M.Pohl, W. Jaschke: Comparative reject analysis in

conventional film-screen and digital storage phosphor radiography Eur. Radiol.9, 1693-1696

(1999)

2. Shook, K.A. O‟Neall, D., and Honea, R. Challenges in the integra tion of PACS and RIS

databases. Journal of Digital Imaging Vol 11 No. 3 Suppl 1 (August) 1998: pp. 75-79.

3. Willis, C.E., Parker, B.R., Orand, M., and Wagner, M.L.: Challenges for pediatric radiology

using computed radiography. Journal of Digital Imaging. Vol. 11 No. 3 Suppl 1 (August) 1998

pp156-158.

4. Willis, C.E., Mercier, J., and Patel, M.: Modification of conventional quality assurance

procedures to accommodate computed radiography. 13th Conference on Computer

Applications in Radiology. Denver, Colorado. June 7, 1996. pp. 275-281.

5. Willis, C.E.: Computed radiographic imaging and artifacts. Chapter 7. in Filmless Radiology.

New York: Springer-Verlag. pp. 137-154. 1999.

6. Willis, C.E. Computed Radiography: QA/QC in Practical Digital Imaging and PACS.

Medical Physics Monograph No. 28. Madison: Medical Physics Publishing pp 157-175. 1999.

7. Willis, C. E.; McCluggage, C.W.; Orand, M.R., and Parker, B.R. Puncture Proof Picture

Archiving and Communications Systems. Journal of Digital Imaging Vol 14 No 2 Suppl 1

(June) 2001: pp 66-71.

8. Barnes, Eric. IN DIGITAL RADIOLOGY, QA MEANS NEVER HAVING TO SAY

YOU‟RE SORRY; September 19, 2000, http://www.auntminnie.com/index.asp?sec=sea&sub=res

http://www.auntminnie.com/index.asp?sec=sea&sub=reshttp://www.auntminnie.com/index.asp?sec=sea&sub=reshttp://www.auntminnie.com/index.asp?sec=sea&sub=reshttp://www.auntminnie.com/index.asp?sec=sea&sub=res


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Table I. Agfa Processing Station Features

Demographic EditingImage modifications

– Reorientation

– Annotation

– Window and level

CollimationExposure field mask or removal

– Examination menu selectionMeasuring distance

Invert

Orientation change

– Sensitometry curve selection

Image processing (MUSICA -MultiScale Image Contrast Amplification)

)

Table II. Reason for Repeated Examinations in Conventional Department

Artifacts

Mis-positioningOver-collimation

Patient motion

Double exposure

Inadequate inspirationOverexposed - too dark

Underexposed - too light

Marker missing or wrongWrong examination

Wrong patientFilm lost in processor


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Table III: Radiologist Examination Critique List

RADIOLOGIST EXAM CRITIQUE

Media Comment Category Fault Specification Dictat ion Code

F =Film Availability Current Exam Not Local 1

S =Soft Copy Not on System or Cache 2

Prior Exam Not Local 3

Not on System 4

Number of Images Missing Images 5

Duplicate Images 6

Image Sequence Wrong Sequence 7

Combined Exam 8

Identification Patient Identification Wrong MRN 9

Wrong Patient 10

Wrong Name 11

Wrong DOB 12

Exam Information Wrong Accession Number 13

Wrong Exam Procedure 14

Annotation Incorrect Orientation 15

Improper Placement of Marker 16

No Marker 17

Appropriateness of Exam Wrong Diagnosis 18

Wrong Exam Performed 19

Inappropriate Exam 20

No History Provided 21

Technical Mis-positioned 22

Inadequate Inspiration 23

Motion 24

Collimation Not Enough 25

Too Much 26

No Collimation 27

Shielding Image Artifacts (Holding) 28

Inappropriate Shielding 29

No Shielding 30

Quality Density Too Dark 31

Too Light 32

Blurred Monitor 33

Image 34

Contrast Too Much Contrast35

Not Enough Contrast 36

Noisy 37

Image Size Magnified 38

Minified 39

Artifact (Note: Please Specify) 40

Diagnostic Repeat: Non Diagnostic 41

Save For Teaching File 42

Save for Green Dot 43


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Table IV: Routing Pattern, not allowing the routing of a rejected image to the user, but only

to the archive servers.

Table V: An entry for each specialty with each patient location or referring physician for

each destination is created on the routing table, giving an exponential growth to the table.


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Table VI: Number of Rejected Images reported for the year 2001.

Month Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec TOTAL AVERAGE

Modality Computed Radiology

(CR)# of NONE

Images559 617 541 573 456 493 446 458 622 611 542 613 6531 544

# of TotalImages inArchive

13028 12931 13388 12966 13336 12074 12520 12842 13235 15206 14428 14667 160621 13385

% 4.29 4.77 4.04 4.42 3.42 4.08 3.56 3.57 4.7 4.02 3.76 4.18 4.07 4.07

Figure 1: Monthly CR rejects for the year 2001 versus the total number of image archived.

Monthly Distribution of Rejects

4.29

4.77

4.04

4.42

3.42

4.08

3.56 3.57

4.70

4.023.76

4.18

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

Month

% o f R e j e c t e d I m a

g e s t o T o t a l

A r c h i v e d I m

a g e s


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Table VII: Number of Images per Reject Code for 2001.

Sum of Reject Reason (CR, By Image)

Reject Code Reject Description Number ofImages

Percentage toTotal # of Rejects

%

22 MISPOSITIONED 4035 61.7823 INADEQUATE INSPIRATION 570 8.73

36 CONTRAST--NOT ENOUGH CONTRAST 440 6.74

46 NOT INDICATED 372 5.70

40 ARTIFACT 286 4.38

35 CONTRAST--TOO MUCH CONTRAST 139 2.13

24 MOTION 131 2.01

41 REPEAT: DIAGNOSTIC 83 1.27

6 # OF IMAGES--DUPLICATE IMAGE 74 1.13

32 DENSITY--TOO LIGHT 69 1.06

16 ANNOTATION--IMPROPER PLACEMENT 75 1.15

17 ANNOTATION--NO MARKER 54 0.83

34 BLURRED--IMAGE 28 0.4326 COLLIMATION--TOO MUCH 23 0.35

19 WRONG EXAM PERFORMED 24 0.37

28 SHIELDING--IMAGE ARTIFACTS 21 0.32

31 DENSITY--TOO DARK 13 0.20

15 ANNOTATION--INCORRECT ORIENTATION 13 0.20

33 BLURRED--MONITOR 11 0.17

5 # OF IMAGES--MISSING IMAGES 10 0.15

14 EXAM INFORMATION -WRONG EXAM PROCEDURE 8 0.12

29 SHIELDING--INAPPROPRIATE SHIELDING 7 0.11

10 PATIENT ID--WRONG PATIENT 7 0.11

43 DUPLICATE 7 0.11

21 NO HISTORY PROVIDED 5 0.08

25 COLLIMATION-NOT ENOUGH 5 0.08

11 PATIENT ID--WRONG NAME 4 0.06

45 OTHER 3 0.05

20 INAPPROPRIATE EXAM 3 0.05

2 CURRENT EXAM NOT ON SYSTEM OR CACHE 2 0.03

7 IMAGE SEQUENCE - WRONG SEQUENCE 2 0.03

13 EXAM INFORMATION - WRONG ACCESSION NUMBER 2 0.03

38 IMAGE SIZE--MAGNIFIED 1 0.02

8 COMBINED EXAM 1 0.02

42 SAVE FOR TEACHING FILE 1 0.02

27 COLLIMATION--NO COLLIMATION 1 0.024 PRIOR EXAM NOT ON SYSTEM 1 0.02

TOTAL 6531


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2

Table VIII: CR Rejected compared with # of Archived Images by SHIFT for the year 2001.

2001 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL AVERA

Shift 17 a - 3 pm

# of NONE Images 227 274 175 195 199 205 161 177 224 240 233 269 2579 215

Total # of Images in PACS Archive

5254 4986 5174 5122 5425 5014 4908 5494 4833 6178 5662 5298 63348 5279

% (NONE vs Total Images) 4.32 5.50 3.38 3.81 3.67 4.09 3.28 3.22 4.63 3.88 4.12 5.08 4.07 4.0

Shift 23 - 11 pm

# of NONE Images 142 143 142 180 102 107 96 137 188 165 136 151 1689 141


4021 4012 3974 3857 4004 3351 3724 3816 4144 4638 4180 4109 47830 3986


Shift 311 pm - 7

am

# of NONE Images 48 52 90 73 50 63 55 55 63 64 61 56 730 61


1732 1754 1809 1724 1824 1537 1608 1515 1607 1991 2039 1936 21076 1756


Weekends # of NONE Images 142 148 134 125 105 118 134 89 147 142 112 137 1533 128


2021 2179 2431 2263 2083 2172 2280 2017 2651 2399 2539 3324 28359 2363


TOTAL # of NONE Images 559 617 541 573 456 493 446 458 622 611 542 613 6531 544


13028 12931 13388 12966 13336 12074 12520 12842 13235 15206 14420 14667 160613 1338


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Figure 2: CR Rejected Images by Shift for 2001

% of CR Rejects by SHIFTs

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

J a n

F e b

M a r c h

A p r i l

M a y

J u n e

J u l y

A u g

S e p t O c

t N o

v D e

c

Month

% o f C R R e j e c t s o v e r T o t a l A r c h i v e d I m a g e s b y

S h i f t

SHIFT 1

SHIFT 2

SHIFT 3

WEEKEND


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Table IX: A portion of the report showing the Number of Rejects broken down by

Technologist Number and Reject Codes.

Technologist Number Reject Code Number of Studies Number of Images

6 6 4 4

11 22 3 3

40 1 1

12 6 4 4

17 3 322 15 15

23 1 1

35 1 1

40 1 1

16 16 1 1

21 34 1 1

22 22 7 7

23 6 1 1

7 2 2

16 1 1

22 101 102

23 18 18

29 1 1

31 2 2

40 9 941 2 2


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Table X: CR Rejects by Exam Description

Exam Description Number of Rejected Images %

Chest 3374 51.66

Abdomen 651 9.97

NOT INDICATED 633 9.69

Spine 496 7.59Upper_Ext 426 6.52

Head 412 6.31

Lower_Ext 397 6.08

Pelvis 106 1.62

Body 18 0.28

Abdomen/KUB 7 0.11

Renal 6 0.09

Bone 3 0.05

Neck 2 0.03

TOTAL 6531


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Table XI: Reject Code List

REJECT CODE LIST

Comment Category Fault Specification Dictat ionCode

Images Number of Images Missing Images 1

Duplicate Images 2

Image Sequence Wrong Sequence 3

Combined Exam 4

Identification Patient Identification Wrong Patient 5

Exam Information Wrong Exam Procedure 6

Annotation Incorrect Orientation 7

Improper Placement of Marker 8

No Marker 9

Wrong Marker 10

Appropriateness of Exam Wrong Exam Performed 11

Technical Mis-positioned Patient 12

Cassette 13

Inadequate Inspiration 14

Motion 15

Collimation Not Enough 16

Too Much 17

No Collimation 18

Shielding Image Artifacts (Holding) 19

Inappropriate Shielding 20

No Shielding 21

Double Exposure 22

Equipment Malfunction23

Quality Density Too Dark 24

Too Light 25

Blurred Monitor 26

Image 27

Contrast High LGM 28

Low LGM 29

Noisy 30

Image Size Magnified 31

Minified 32

Artifact Patient 33

Cassette 34

Equipment 35

Diagnostic Radiologist's Request to Reject 36

Save for Green Dot/Teaching File 37

Test 38

Other 39

Blado Reject Analysis SCAR 2002

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