USING A CLASSIFICATION SCHEME TO FACILITATE

OUTSOURCING OF RADIOLOGY SERVICES

Ulrik Schønnemann

MedWare

Blåbærvej 108, 5260 Odense S, Denmark

Uffe Kock Wiil

The Maersk Mc-Kinney Moller Institute, University of Southern Denmark

Campusvej 55, 5230 Odense M, Denmark

Keywords: Support for clinical decision-making, Knowledge management, Design and development of methodologies

for Healthcare IT, Classification scheme, Articulation work, Common information space.

Abstract: This paper deals with the issues involved in outsourcing radiology services. Based upon a field study of the

work practices at the radiology department at Svendborg Hospital in Denmark, a novel solution (including a

prototype of a computer supported reporting tool) that enables outsourcing of radiology services is

introduced. The solution is based upon development of a classification scheme of possible radiology

findings. Using predefined clinical findings for the radiology reports assure a high quality and enable

automatic translation of radiology reports.

1 INTRODUCTION

Many countries in Western Europe suffer from a

lack of radiologists, while some Eastern European

countries have available radiology resources.

According to the Danish National Board of Health

(www.sst.dk), Denmark had 102 unfilled radiology

positions in November 2007. Outsourcing of

radiology services is a potential solution to the

problem. However, important issues have to be

addressed before this solution becomes viable.

Outsourcing of radiology services demands a great

deal of trust to the providing organization. The

customer must trust that the provider delivers a

product which is at least as good as their own both

with regards to radiologic competence and linguistic

quality. The quality of the radiology service is

crucial, since patient treatment will be based upon

the radiologist’s report. The linguistic quality is an

issue when outsourcing, since a radiology report in

Denmark must be written in Danish. Having an

interpreter translate each report is very time

consuming and there are potential problems related

to decreased comprehensibility of the reports as well

as legal problems in case of mistreatment of a

patient due to a wrong translation of a correct

radiology report.

Based upon a field study of the work practices in

the radiology department at Svendborg Hospital in

Denmark, a novel solution (including a prototype of

a computer supported reporting tool) that enables

outsourcing of radiology services is introduced. The

solution is based upon development of a

classification scheme of possible radiology findings.

Using predefined clinical findings for the radiology

reports assure a high quality and enable automatic

translation of radiology reports.

2 FIELD STUDY AT SVENDBORG

HOSPITAL

The field study presents the current work practices

of the radiology department at Svendborg Hospital

in Denmark focusing on the lifecycle of an

examination.

149

Schønnemann U. and Kock Wiil U. (2009).

USING A CLASSIFICATION SCHEME TO FACILITATE OUTSOURCING OF RADIOLOGY SERVICES.

In Proceedings of the International Conference on Health Informatics, pages 149-154

DOI: 10.5220/0001510101490154

 SciTePress

2.1 The Radiology Department

An examination starts with a referral from either a

general practitioner or from another department

within the hospital. The referral contains the identity

of the patient and some text explaining what the

radiology department should investigate. The

referral is either received in paper or electronic form.

In both cases the referral is added to the Radiology

Information System (RIS), which is used for

governing the workflow around examinations within

the radiology department.

At a daily conference, the radiologists prioritize

the new examinations based on how crucial the

referral is and they decide which images to take. If a

patient complains about pain in the knee and the

general practitioner expects osteoarthritis, which is a

very slow progressing disease, the patient will

receive a low priority. On the other hand, if cancer is

expected, the patient will get a high priority. After

the examinations have been prioritized, a secretary

will send notification letters to the patients. Acute

patients are of course handled as fast as possible.

When the patient arrives at the department, a

secretary guides the patient to the relevant x-ray

room, where a radiographer takes the images

requested by the radiologists. Images are stored in

the Picture Archiving and Communication System

(PACS). The patient is done and leaves the

department again. The RIS is updated, enabling the

radiologists to see that the images have been taken.

A radiologist can now describe the images. If the

images contain findings that the radiologist is unsure

about, a second opinion from a colleague will be

requested. The description is entered into the RIS

and then electronically transmitted back to the

doctor who requested it in the first place.

2.2 The Radiologist

When describing an examination, the radiologist

typically follows a workflow that contains five steps:

(1) investigate the patient’s medical background, (2)

investigate what is requested to be examined, (3)

examine the images and create a mental diagnosis,

(4) report what is actually examined, and (5) report

what is found starting with most critical and finish

with a conclusion. Some of the steps (1, 2 and 4) in

the workflow can be omitted, but the quality of the

report will as a consequence be lowered. The

radiologist can obviously in some cases iterate back

and forth over the steps. The above approach of

reporting is problem oriented, meaning that the

radiologist searches for an answer to a specific

problem. This approach is optimal for swiftly

finding the source for the given problem, but there is

a risk that the radiologist will not discover secondary

findings.

When reporting, the radiologist compiles a more

or less complete mental overview of the diagnosis

before writing the report. Compilation of the mental

overview is based upon a search for findings in the

images and then concluding with a diagnosis. Thus,

the radiologist knows both the diagnosis and the

findings before the report is written.

2.3 Relevant Observations

A radiology department (fully digitalized or not)

with multiple collaborating actors requires

articulation work “to manage the distributed nature

of cooperative work” (Schmidt and Bannon 1992).

The cooperative work arrangement is supported by a

common information space (CIS) (Bannon and

Bødker 1997), which in this case encompass daily

conferences among actors and a powerful shared

artifact (the RIS). Bossen’s framework for analyzing

CIS is used to briefly characterize the CIS of the

radiology department through its parameters (Bossen

2002).

The CIS is characterized by being distributed

both in time and space – but mainly in time. There is

a high need for precision – primarily in the

descriptions made by the radiologists. There is a

high degree of common knowledge – the

descriptions are distributed among doctors who have

a very long identical education. The multiplicity of

the CIS is limited to speech and reading/writing and

the intensity is quite low due to the RIS. The

diversity of artifacts is low since it is mainly the RIS

which is used. Articulation work is also limited since

the department has very well defined work patterns.

There are three main states in the lifecycle of an

examination that requires articulation work:

prioritizing the examination, selecting the

radiographer, and selecting the radiologist. This

coordination of the actors is carried out in

conferences and is based on factors like: who is at

work, what are their qualifications, and are there

other tasks they must attend to.

There is one primary artifact used at the

radiology department (the RIS) which helps the

actors keep track of the progress of examinations

and provides the information at decentralized

locations. A radiographer does not have to leave the

x-ray room in order to know which patient is coming

and what image should be taken. The RIS also helps

to assure that patients’ data are not mixed up.

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Finally, the RIS enforces a workflow that eases the

cooperation.

A radiology department also uses classification

schemes (Simone 2000) – some are formal and some

arises through daily practice. The most formal is

perhaps the classification of examination types,

which is a unified classification in Denmark. A less

formal classification scheme is the findings

described by the radiologists. A single radiologist

will tend to use standard terms and phrases for the

findings. The radiologists as a group will in time

develop a common set of terms and phrases. The

standardization helps the interpretation of the

descriptions. Currently, there exists no single

classification scheme for radiologic findings.

3 ISSUES IN OUTSOURCING

RADIOLOGY SERVICES

The above field study focus on the current work

practice where radiology services are handled in-

house. Outsourcing requires changes to the

cooperative work arrangement.

The articulation work will change significantly.

The management in a traditional radiology

department has to deal with quality of services,

coordination, motivation, and so on. In a department

which utilizes outsourcing, business also becomes an

important issue. The articulation work suddenly also

constitutes price determination, creation of business

relations, and negotiation with the providers.

The CIS is primarily affected in two ways. The

CIS will become distributed in space also, since part

of the workflow will be handled at a different

hospital. The CIS will also become multilingual,

since outsourcing is expected to take place in

different countries with different native languages.

The language issue changes the daily workflow.

Translation will introduce a new task. Both the

referrals and the reports must be translated.

One of the basic criteria that must be met in

order for outsourcing to be successful is that the

impact on the workflow when outsourcing should

not be much different from the impact of hiring

more radiologists. The achievement of that criterion

relies heavily on computer support and therefore

new artifacts. A number of new artifacts can be

introduced to minimize the overhead of outsourcing

radiology services:

 Business relations. A new artifact can be

introduced enabling the management to set up

business relations with providers of radiology

services.

 CIS distribution in space. A new artifact can

be introduced enabling the RIS to send images

and referrals to and receive reports from the

providers.

 CIS language issues. A new artifact can be

introduced enabling automatic translation of

referrals and reports.

In the following, we will primarily focus on

addressing the language issues, which we believe is

by far the most complex of the issues involved in

outsourcing radiology services.

4 TOWARDS A SOLUTION

The approach taken aims at “expanding” the CIS

that currently encompass the work in the radiology

department at Svendborg Hospital to also include the

radiologists at the outsourced locations. More

precisely, we wish to develop a “common language”

shared by radiologists at Svendborg together with

radiologists at the outsourced locations. As

mentioned in the field study, a group of radiologists

that work together will over time develop a common

set of terms and phrases used for the description of

findings. This can be viewed as an informal

classification scheme.

The work to turn the informal classification

scheme into a formal one shared across distributed

locations involves radiologists at Svendborg

Hospital as well as East Tallinn Central Hospital in

Estonia. The work is based on the SNOMED CT

health care terminology and involves the Danish

National Board of Health. SNOMED CT is owned

and managed by the International Health

Terminology Standards Development Organization

(IHTSDO) (http://www.ihtsdo.org/). The novel

classification scheme of clinical findings is

organized as depicted in Figure 1.

Modality

Anatomic Region

Diagnosis

Finding

Figure 1: Classification of clinical findings.

USING A CLASSIFICATION SCHEME TO FACILITATE OUTSOURCING OF RADIOLOGY SERVICES

151

Modality is one of {x-ray, CT, MRI, US},

anatomic region is a part of the human body (i.e., a

knee), diagnosis is a suspected medical problem

(i.e., osteoarthritis) and a finding is supporting

medical evidence (i.e., subchondral sclerosis of the

medial femoral condyle).

Using predefined clinical findings for creating

the radiology reports, makes it possible to once and

for all translate the findings into multiple languages.

This solution has a number of benefits and allows

for a number of features that goes way beyond the

issues of language and translation that were the

initiating problems (see next section).

5 THE COMPUTER SUPPORTED

REPORTING TOOL

A prototype of a Computer Supported Reporting

(CSR) tool has been developed. CSR is a new

artifact in the CIS based on the novel classification

scheme of predefined clinical findings. CSR is

shown in Figure 2. The clinical finding on the screen

covers osteoarthritis in a knee.

Figure 2: The Computer Supported Reporting Tool.

The workflow for a radiologist using CSR

contains the following steps:

1. Select modality,

2. Select anatomic region,

3. Select diagnosis,

4. Add diagnosis to report conclusion, and

5. Add findings to report.

The modality and anatomical region will typically be

available from the RIS or PACS system. If they are

not, the radiologist will have to select them. As

described in the field study, the radiologist has a

mental overview of the diagnosis and the findings

that supports the diagnosis when writing the report.

Findings are typically related to a single diagnosis,

and it is therefore appropriate to have a tree structure

where the radiologist starts with selecting the desired

diagnosis and then the associated findings. If there

are enough indicators for the diagnosis, the

radiologist can choose to select this diagnosis for the

conclusion.

A diagnosis will typically have many associated

findings, which makes the list from which the

radiologist selects from very long. Therefore, CSR

provides a method for filtering the findings and a

method for compressing the findings.

1. Anatomic Filtering. For the selected

anatomic region an image of that region is

shown. Each finding is defined within an

area of that image. CSR enables the

radiologist to select an area of interest within

the shown image and thereby filter the

available findings to only those defined

within the area of interest.

2. Compressed Content. Some findings are

compressed into one statement where part of

the content is changeable, since some

findings are mutually exclusive, which

makes it appropriate only to be able to select

one of them; severity of the finding is an

example. Some findings can be found in

only two locations (A, B) which induces

three options (A, B, A and B). These options

can be made selectable instead of having

two separate findings.

The clinical findings supported by CSR can be

presented in different languages. The desired

language can be selected by clicking at an icon

depicting the nationality. Currently, Danish,

Estonian, and English are supported. Clinical

findings which are not currently predefined can be

typed in as free text. Such findings will naturally

have to be translated by an interpreter. However, the

solution supports that such findings can be assessed

later and added to the predefined set if eligible.

The use of a classification scheme for predefined

clinical findings combined with the features of the

CSR tool enables a number of advanced features:

Automated Translation between Languages. The

fact that each predefined clinical finding is translated

into numerous languages makes automated

translation of reports possible. Translation opens for

the possibility of cross border outsourcing of

radiology services. Foreign radiologists working at a

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hospital can also benefit from automated translation

since they can report in their native language.

Clinical Guidance. CSR offers clinical guidance for

the radiologist. Each clinical finding is documented

by a reference image and some descriptive

background knowledge. The reference image aids

the radiologist in selecting the correct clinical

finding especially when the finding contains

severity.

Higher Comprehensibility of Reports. Reports

made with CSR will have a higher comprehensibility

than traditional reports due to the fact that linguistics

is independent of the radiologist who made the

report. A lot of effort is put into making good

descriptions and translations of the predefined

clinical findings. The receiver of a report can benefit

from the descriptive background knowledge for each

clinical finding in case of uncertainties.

Faster Reporting. Efficiency for the radiologists is

one of the primary objectives for CSR. The goal is to

have the radiologist use less time for reporting and

more time for using their radiologic knowledge.

Faster reporting is achieved by organizing the

clinical findings in a way which enables the

radiologist to rapidly find it.

Automated Translation to Patients. Countries

where patients are granted access to their own

medical records will suffer from the problem that

reports are almost impossible to understand due to

the difficult medical terminology. The automated

translation feature of CSR can remedy this by

translating the findings into an understandable

terminology.

Easy and Automatic Testing. CSR can assists in

testing radiologists. A group of experts describes a

number of examinations and thereby making the

“correct” answer for the test. When a radiologist has

described the examinations, the reports and the

correct answers are compared in an objective and

automated manner. The radiologist can either be

aware or unaware of the testing depending on the

purpose of the test.

6 SYSTEM OVERVIEW

The system architecture is optimized to support the

CSR tool, which is the central component used for

the actual reporting by the radiologists as described

in Section 5. The clinical content will continuously

be under development and undergo a lot changes.

The CSR tool will be used by numerous radiologists.

The overall architecture should insure efficient

updating of the clinical content. It is therefore

desirable to separate the clinical content and the

CSR tool as depicted in Figure 3.

Clinical

Content

Database

Clinical

Content

Server

Examination

Server

Administration

Tool

CSR

Tool

RIS

SOAP

HTML

Examination

Tool

HTML

Figure 3: The overall system architecture.

The clinical content is stored in the clinical

content database, which is accessible via the clinical

content server. The roles of the clinical content

server are to protect the database by validating the

data before it is stored in the database and to publish

an easy accessible SOAP interface for fetching the

clinical content. The clinical content server also

provides a web interface for the administration tool,

which is used to create and manage the clinical

content. The reports created with the CSR tool are

stored in the examination server, which in a real

world scenario needs to be connected to the RIS.

The examination tool is used by the local hospital to

manage users (radiologists) at the remote hospitals

and to add new tasks to be handled by the remote

hospitals. The examination tool is used by the

radiologist at the remote hospitals to login into the

system, to find their tasks, and to create radiology

reports (by opening and using the CSR tool).

Additional details about the CSR tool and the

overall system can be found in (Schønnemann

2008).

7 RELATED WORK

The presented work is inspired by previous work on

the structured reporting tool developed as part of the

Baltic eHealth project (www.baltic-ehealth.org).

Dixon and Fitzgerald (2008) discuss potential

benefits and risks of outsourcing radiology services.

They outline language, terminology, and accuracy

issues as risks. They propose that outsourced reports

should be in the same style as the usual reports from

the outsourcing hospital. CSR and the radiology

classification scheme handle these issues by

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153

introducing a common language used for radiology

reports.

Some hospitals already have experiences with

outsourcing of radiology services (i.e., Esbjerg

Hospital in Denmark (Rasmussen 2007)). They use a

Danish radiologist who was formerly employed at

Esbjerg Hospital. Therefore, they do not have to deal

with language, terminology, and accuracy issues.

To our knowledge, this work is the first attempt

to develop a classification scheme of radiology

findings with the degree of precision and structure

needed to allow computer tools to automatically

manipulate the clinical content.

8 CURRENT STATUS

The classification scheme currently only provides

clinical findings regarding one anatomical region

(the knee) and using one modality (x-ray). Future

work will focus on expanding the classification

scheme with additional modalities, anatomical

regions, and languages.

The CSR (with its limited clinical content added

using the administration tool) has been used in a test

scenario involving radiologists in Denmark and

Estonia. A senior radiologist at Svendborg Hospital

in Denmark provided images for the tests. The tasks

were added to the examination server using the

examination tool. The images were examined by a

senior radiologist and three medical students from

East Tallinn Central Hospital in Estonia using the

examination tool and the CSR tool.

The users found the system quite easy to use and

clinically relevant. They concluded that the system

could be useful to structure reporting methods inside

their own radiology department. More importantly,

they also concluded that the system would have even

more value for outsourcing radiology reports.

The users also commented on a few minor issues

relating to the layout of the features in the main

window of the CSR tool. These issues are relatively

easy to fix and did not hinder the use of the CSR

tool.

9 CONCLUSIONS

The primary contribution of this work is the

development of a classification scheme of clinical

findings and a set of tools for computer supported

reporting. Together, they provide a novel solution

allowing radiology services to be outsourced. We

have demonstrated that is it possible to introduce

classification into a limited medical domain and that

doing so enable automation of many tasks.

The tests of our solution were very promising

and encouraging. We envision that such systems for

outsourcing medical services will find their way into

hospitals within few years.

One could imagine that an internet based world

wide market place for outsourcing medical services

would appear some time in the future to fulfill the

needs of hospitals that find it difficult to recruit

certain medical specialist.

The approach of outsourcing medical services is

appealing compared to the alternative of enticing

medical specialist from less resourceful countries to

move to more resourceful countries. Such an

approach would, of course, eliminate the problems

in Denmark, but it would create new problems in

other less resourceful countries.

ACKNOWLEDGEMENTS

We wish to thank Dr. Leslie Christensen, Svendborg

Hospital, Denmark and Dr. Peeter Ross, East Tallinn

Central Hospital, Estonia for their collaboration and

participation in this project.

REFERENCES

Bannon, L., Bødker, S. 1997. Constructing Common

Information Spaces. In Proc. of ECSCW 1997.

Kluwer, pp. 81-96

Bossen, C. 2002. The Parameters of Common Information

Spaces: the Heterogeneity of Cooperative Work at a

Hospital Ward. In Proc. of CSCW 2002. (Nov., New

Orleans, LA). ACM Press, pp. 176-185.

Dixon, A. K., Fitzgerald, R. 2008. Outsourcing and

Teleradiology: Potential Benefits, Risks and Solutions

From a UK/European Perspective. Journal of the

American College of Radiology, 5, 1, 12-18.

Rasmussen, J. 2007. Barcelona hjælper sygehus

(Barcelona helps hospital). JydskeVestkysten (Danish

newspaper), November 29, 2007.

Schmidt, K., Bannon, L. 1992. Taking CSCW Seriously:

Supporting Articulation Work. Computer Supported

Cooperative Work, 1, 1-2, 7-40.

Schønnemann, U. 2008. IT Support of Radiology

Outsourcing. Master’s Thesis, The Maersk Mc-Kinney

Moller Institute, University of Southern Denmark.

Simone, C. 2000. Making Classification Schemes a first

class notion in CSCW. 1st CISCPH workshop on

Cooperative Organization of Common Information

Spaces. http://www.itu.dk/~schmidt/ciscph.html.

(Aug., Copenhagen, Denmark).

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