InformatIcs

Knowledge managementPaul cooper

Abstractthe relationship between data, knowledge, wisdom and understanding

is explained in this article. there is a need to convert implicit knowledge

to explicit knowledge to support several projects within the nHs (and

elsewhere), to disseminate good practice, and to provide a sound basis

for the different levels of developing clinical decision support systems.

stimulated by increasing access to the Internet, there is a tension be-

tween traditional sources of knowledge (e.g. books, individuals recog-

nized as experts), and many different and varied sources of information

and knowledge (a wide range of online resources that often are freely

available).

Keywords data; decision support; explicit knowledge; implicit knowledge

Data, information and knowledge (Figure 1)

Data (or more correctly a datum) consist of a label and a value (e.g. systolic blood pressure (SBP) = 80 mm Hg or SBP= − 30 mm Hg). By itself data does not have meaning.

Information is data together with a context, so that it gains meaning (e.g. SBP = −30 mm Hg if the transducer is incorrectly calibrated). SBP = 70 mm Hg has a different meaning, depend­ing on whether the patient is a neonate or an adult. Information answers the ‘who’, ‘what’, ‘where’, and ‘when’ questions.

Knowledge is the result of processing and collecting informa­tion, sometimes from many sources. Knowledge can be gained by learning. Knowledge answers the ‘how’ questions.

Understanding is the process by which one can synthesize new knowledge from previously held knowledge. Understanding answers the ‘why’ questions.

Wisdom is an extrapolative process, which includes knowledge in an ethical or moral framework. Wisdom is the process by which we also discern between right and wrong, good and bad.

Paul Cooper, BSc (Hons), FRCA, is Consultant Anaesthetist at North Tyneside

Hospital, North Shields. He qualified from Charing Cross Hospital,

London, and trained in Canada, Sheffield and Newcastle. He is a

member of the Society for Computing and Technology in Anaesthesia

(SCATA), and is completing a degree in computer science at the Open

University.

anaEstHEsIa anD IntEnsIVE carE mEDIcInE 8:12 516

Sources of knowledge and information

Much effort goes into ‘knowledge harvesting’, converting tacit knowledge (experience and intuition) into explicit knowledge, which, once organized and codified, can be used in producing guidelines and protocols. This process has several advantages:• best practice can be quickly passed round (people share ex­

periences and learn from each other)• poor or non­standard practice can be identified• experience can be made widely available.

Sources of knowledge and information are also changing (Table 1). The burgeoning influence and accessibility of the Inter­net has threatened traditional sources of information. The Inter­net allows information and knowledge to be published cheaply and easily, bypassing traditional hierarchical routes.

Some traditional publishers have made their materials avail­able on the Internet (often adding interactive content) as free or paid services. However, there is a growing threat to these tradi­tional sources of information, facilitated by the ease, cheapness and rapidity of publication on the Internet.

Wikipedia (www.en.wikipedia.org), an online encyclopedia that can be edited and contributed to by users, allows access to more than 1.5 million articles covering a wide range of subjects. Despite the potential problems with such open access, Wikipedia seems to be no less of a source of information than the traditional sources. Other more specialized resources also exist (e.g. http://www.ganfyd.org).1

Search engines (programmes that rapidly search and catego­rize the web page content) have been shown to be useful in arriving at diagnoses.2 As ways of categorizing and labelling (meta­information: information about information) become more accurate and intuitive, specific information amongst the millions of likely targets may become more rapidly and easily found through the Internet compared with the traditional sources of information. It is not yet clear how traditional controllers and organizers of knowledge and information will respond to this new threat.

Relationship between data, knowledge and wisdom

Recognizing relations and context

Understanding patterns

Extracting principles

Information

Data DataData

Knowledge

Wisdom

Evidence baseGuidelinesProtocols

Ethics Moral values

Figure 1

© 2007 Elsevier Ltd. all rights reserved.

InformatIcs

The Internet technologies are increasingly finding local appli­cation, and many organizations have local networks (Intranets) of resources available.

Decision-support software

In the clinical setting decision­support software is an application of knowledge management. This is any method that takes input information about a clinical situation and produces inferences,

Traditional and new sources of knowledge and information

Traditional source of knowledge comments

Books • Expensive production and

distribution costs

• 12–18 months in production

• sometimes peer-reviewed

Journals • Expensive production and

distribution costs

• often peer-reviewed

asking colleagues • cheap and easy source

• recognized (local) authority

Lectures • time-consuming, may

necessitate travel

new sources of knowledge comments

Web pages • Easy to access

• often not quality-assured

• author may not be readily

identified

• may be difficult to find

relevant information

Email • Quick and easy

• not limited by geography or

time zones

• may not be applicable for

distributing images

• Issues over authenticity

mailing lists • often unmoderated

• time-consuming (some lists

can generate hundreds of

emails/day)

Discussion forums • often not moderated

• the most prominent opinion

may not necessarily be the

most informed

Distributed multimedia • cDs containing images,

speech and text may be

expensive to produce but

cheap to distribute

• allow personal use, not

dependent on a connection

to Internet

Table 1

anaEstHEsIa anD IntEnsIVE carE mEDIcInE 8:12 51

which can assist decision­making. Decision­support systems comprise a number of different component parts (e.g. user interface, database, decision­support algorithms and sources of information).

Decision support can operate at many levels, from a system displaying warnings or advice to something that is much more prescriptive and can indicate courses of action (e.g. when to refer or which investigations to perform).

There are various projects that attempt to codify knowledge and integrate it into clinical practice. The National Library of Health Clinical Knowledge Service (http://cks.library.nhs.uk/)3 focuses on primary care problems. The Map of Medicine (http://www.mapofmedicine.com/)4 is a project in conjunction with Connecting For Health to codify and make available clinical information relating to a wide range of clinical conditions. One key feature is that the information can be configured locally, and combined with local directory information (e.g. referral paths).

Further information

For more information, Wikipedia has an article on clinical deci­sion support systems (http://en.wikipedia.org/wiki/Clinical_decision_support_system) compiled over approximately 2 years by 16 authors identified by a username and 9 identified only by an IP address (i.e. an internet address for a computer). Clicking on the ‘history’ tab gives a list of changes and allows you to compare versions and changes. You have to use your judgement as to the veracity of the information contained in the Wikipedia article.

The future

Developments in categorizing Web­based content (e.g. OWL, Web Ontology Language; and XML, Extensible Markup Lan­guage) are likely to make searching Web content more intuitive and relevant, whilst perhaps not quite achieving the ‘Semantic Web’ vision of Tim Berners­Lee (the inventor of the Internet).

Web technologies have enabled greater participation in knowledge and information systems. There are likely to be on­going tensions between the traditional keepers and maintainers of knowledge and those who are enthusiastic to challenge the hierarchical structures where they exist. ◆

ReFeRenceS

1 http://www.ganfyd.org/ (accessed 1 september 2007).

2 tang H, Hwee Kwoon ng J. Googling for a diagnosis—use of Google

as a diagnostic aid: internet based study. Br Med J 2006; 333:

1143–5.

3 national Library for Health. clinical knowledge summaries.

http://cks.library.nhs.uk/ (accessed 1 september 2007).

4 map of medicine. http://www.mapofmedicine.com/ (accessed

1 september 2007).

FuRTheR ReADing

W3c (Worldwide Web consortium) frequently asked questions.

http://www.w3.org/2001/sw/sW-faQ (accessed 20 august 2007).

7 © 2007 Elsevier Ltd. all rights reserved.