Http://healthcybermap.semanticweb.org MIM Centre A Dynamic Problem-Knowledge Coupling Semantic Web...

http://healthcybermap.semanticweb.orghttp://healthcybermap.semanticweb.orgMIM Centre

A Dynamic Problem-Knowledge Coupling Semantic Web Service

M.N.Kamel-Boulos, A.V.Roudsari, and E.R.CarsonCentre for Measurement and Information in Medicine

City University, London, UKE-mail: [email protected]@city.ac.uk


Background and Introduction - 1• Many information needs arise during everyday clinical practice,

including questions related to diagnosis, determining risks/prognosis, planning an optimum investigative or therapeutic strategy, disease prevention and patient education material, etc. The quality and outcomes of patient care will suffer if these information needs are unmet or are answered with inaccurate, non-current or misleading information.

• Contextual relevance is an important aspect of medical information quality that is frequently overlooked. It is essentially an information retrieval issue. An information resource that is excellent on its own merits can end up becoming mere distracting noise if it does not properly address the user’s specific knowledge needs, or does not fit the clinical context in which it was recalled.


Background and Introduction - 2• Problem-knowledge coupling (PKC) aims at providing contextually

appropriate medical knowledge in the right place and at the right time. This should be a major goal when designing the Electronic Patient Record (EPR).

• Appleyard and Malet (1997) were among the first to mention that “the incorporation of nomenclatures such as UMLS into meta-tags will allow the linking of Web-based knowledge sources into electronic medical record systems.” The ideal online medical library should act as a “contextual medical knowledge provider” within a Clinical Information System, coupling problem-specific knowledge with real patient data (EPR). This can assist in decision making, improve patient care and educate the student, professional and patient.


Background and Introduction - 3• HealthCyberMap (HCM - http://healthcybermap.semanticweb.orghttp://healthcybermap.semanticweb.org)

aims at mapping medical Web resources in unique and novel ways to deliver a semantically superior experience to its users. This is achieved through intelligent categorisation and interactive hypermedia visualisation of the medical cyberspace using metadata, clinical codes (a terminology or classification) and GIS (Geographic Information Systems) technologies.

• A clinical terminology/classification is a kind of ontology by definition as it preserves and “understands” the relationships between the 1,000s of terms in it or else it would become a mere dictionary/thesaurus. By tagging a medical Web resource (or a metadata record of it) with clinical codes, we are automatically establishing the relationships (as defined by the coding scheme in use) between this resource and other related (tagged) resources, and also similarly coded EPRs. This is the basis of PKC.


Background and Introduction - 4• The Semantic Web initiative (http://semanticweb.orghttp://semanticweb.org) aims at creating a

Web where information semantics are represented in a form “understandable” by machines as well as by humans. In the case of medical information, this can be achieved using clinical codes. This will pave the way to more “intelligent” machine-to-machine communication (e.g., between an EPR system and a digital medical library), and ultimately empower humans.

• Hendler (2001) provides an extensive discussion of Semantic Web Services. He mentions a service advertise/ discover mechanism. Microsoft has already implemented closely related ideas in its .NET/ Web Services framework.

• In the case of HCM, we thought of a very useful Semantic Web Service, namely a PKC Service to be consumed by EPR clients. Coupling is possible as both the EPR and HCM will be using the same clinical coding system or two different schemes with reliable cross mapping.


Materials and Methods - 1• HCM relies on stand-alone metadata (in a central database—cf.

peripheral metadata embedded in the Web resources themselves) based on the Dublin Core (DC) metadata set (http://dublincore.orghttp://dublincore.org).

• Clinical codes are used to populate the DC subject field in HCM database. The current HCM Web implementation uses ICD-9-CM, a hierarchical classification with no support for multiple parentage, as some of HCM hypermaps rely on a GIS extension that only understands ICD-9.


Materials and Methods - 2

• Candidate resources are hand-selected. Their attributes, including ICD codes representing their subjects (using code locators, e.g., http://eICD.comhttp://eICD.com) are manually compiled in HCM database.

• Manual indexing ensures the quality of selected resources and the precision of their topic indexing. HCM currently allows three DC subject fields (for topic indexing) per resource record.

• The database is registered on HCM server (a Windows 2000 Server) as an ODBC Data Source. ASP Server Pages are used to query the database and present the results on the Web.


Materials and Methods - 3

HealthCyberMap resource metadata entry form in Microsoft® Access 97.


Results - 1

• In our Web Demo, we assumed an EPR that codes diagnoses in ICD-9-CM, and since HCM crisply describes the subjects of the Web resources stored in its database using the same codes, a link between the two systems in the form of: http://healthcybermap.org/icd.asp?SearchText=http://healthcybermap.org/icd.asp?SearchText=PUT_SINGLE_ICD-9-CM_CODE_HEREPUT_SINGLE_ICD-9-CM_CODE_HERE

will be all what we need to perform the coupling query and dynamically link the EPR to contextually relevant knowledge and guidelines.

• The ICD code from the EPR is passed as an SQL query argument to HCM. Only resources with a DC subject field containing the argument are retrieved.


Results - 2Screenshot of HealthCyberMap’s Problem-Knowledge Coupling Demonstrator (http://healthcybermap.semanticweb.orghttp://healthcybermap.semanticweb.org/pk.htm/pk.htm).


Discussion - 1

• The service can be also implemented as a .NET Service (giving clients more control over presentation of query results), or according to any other Semantic Web Service standard when available.

• The philosophy behind Semantic Web Services including Microsoft’s implementation is that systems should be able to talk to each other instantly and reliably without the “headache” of developing ad hoc information exchange protocols. Systems should advertise and provide their services in a reusable and flexible form to all disparate clients (service consumers) who might want to use these services and to integrate them in their interfaces.

One service and different clients/interfaces


Discussion - 2

• HCM should ideally be expanded to include more comprehensive clinical coding systems like SNOMED-CT (when released).

• Clinical codes provide a common backbone language (ontology) for communication between the EPR and systems like HCM. Combined with a suitable terminology server (Bechhofer, 1997), we can reason with these codes in more sophisticated semantic ways and support synonyms and related concepts (parents, siblings, children, cousins and uncles).

• To maximise contextual relevance, indexed resources should ideally be qualified using a mechanism similar to MeSH qualifiers or subheadings, which are used to better define a topic, narrow retrieval, or express a

certain aspect of a main heading (ICD has no similar support).

HCM

EPR


Discussion - 3

Using a terminology server to enhance DC subject queries in HealthCyberMap.


Discussion - 4

• Unlike other inflexible solutions with hard-coded knowledge like Dr. Weed’s Problem Knowledge Couplers (http://www.pkc.comhttp://www.pkc.com), HCM solution is flexible and dynamic. We can keep adding/ deleting resources to HCM and have all new changes instantly reflected on our output without modifying HCM architecture or code (or the client’s calling code).

• We can choose to call certain resource categories we need most, e.g., only official guidelines on a given topic, instead of all resource types on that topic, thanks to the HCM DC type field.


Conclusions - 1

• Our study shows the feasibility of EPR to HCM problem-knowledge coupling using ICD codes as crisp problem-knowledge couplers or hooks. Though ICD-9-CM codes are mainly used for EPR billing (US), we have successfully demonstrated another clever use of these codes using mainstream technology that most interested groups can easily adopt.


Conclusions - 2

• By minimising irrelevant leads (noise) and reducing the time needed to find relevant information (the right contextually relevant knowledge is coupled with real patient data in the EPR), the system is clearly beneficial.

• Empirical evidence also shows that well-informed physicians and patients are able to make better clinical decisions that positively affect healthcare outcomes. However, an evaluation study will be needed to accurately measure how the system is affecting clinical outcomes. The success of the system will depend on the quality and granularity of metadata it uses (including the clinical coding scheme(s) used for topical indexing) and the quality of resources it points to.

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