![](bg7.png)
the instance’s current state in terms of rule composition and the status of its rules at
that time or interval. The query illustrated in Fig. 9. provides information on what
tests were ordered with respect to the specified patient during the given time interval.
The term order in the query can be generalised to rule-action so that one can obtain
information on rule actions that have been performed during the specified time
interval. In this case study, the use of the highly intuitive UML state chart brings easy
communication with domain experts during CPG knowledge elicitation, capture and
specification. Subsequent extraction of the relevant ECA rules is also made easier
since the state chart naturally supports the ECA rule paradigm [22] and is also easily
understood by domain experts. The database offered a uniform and flexible way to
access, manipulate and query all information from specification, to executing process
state, to data in the patient record. The generation of SQL trigger code implementing
ECA rules of the MAP was automatically supported by TOPS and required minimal
intervention. This makes it easy for application domain experts to use TOPS with no
knowledge of the SQL trigger specification language. However, domain experts still
needed to be familiar with the specification language, PLAN, which is closer to their
domain language than the SQL. The execution of the rule actions was subject to the
availability of the appropriate software module that implements the action. Thus, rule
actions in the microalbuminuria CPG needed to be predefined and any new action
requires that the module to implement such an action be developed. However, rule
actions were designed to be generic and re-usable by other rules in other CPGs. Using
the database permits operations and queries on various aspects of the MAP through an
SQL-based manipulation language. It was shown that the MAP can be modeled and
specified by using the ECA rule paradigm guided by the state chart. This case study
demonstrated the applicability of the SpEM framework and the active database in
enabling the support for the management of the MAP for diabetes patients.
6 Summary and Conclusion
This paper has presented a unified CPG management framework, SpEM, for
computerized CPG management. The paper also presented a generic method with a
case study to harness the ECA rule paradigm and active databases to provide
computerized CPG support, by following the SpEM. Active databases combine the
ECA rule paradigm with data management to present a promising environment for
TOPS:\> query
QUERY:\> --->SELECT PLAN FROM SNAPSHOT WHERE TARGET:2005-7-19
01:55:02,2005-7-19 01:55:58; SOURCE:PATIENT_ID=25
processing query ...
…
PLAN [ PL$25$1$ ] SNAPSHOT @[2005-07-19 22:30:26.91]
[rule 1]--->[ 72, PL$25$1$AUS2, DYNAMIC, READY ]
[rule 2]--->[ 73, PL$25$1$AUS3, DYNAMIC, READY ]
[rule 3]--->[ 74, PL$25$1$OIS2, DYNAMIC, READY ]
[rule 4]--->[ 75, PL$25$1$OIS3, DYNAMIC, READY ]
[rule 5]--->[ 76, PL$25$1$OIS4, DYNAMIC, READY ]
…
[rule 19]--->[ 90, PL$25$1$CMA4a, DYNAMIC, READY ]
[rule 20]--->[ 91, PL$25$1$CMA4b, DYNAMIC, READY ]
[rule 21]--->[ 92, PL$25$1$NPH1, DYNAMIC, READY ]
[rule 22]--->[ 93, PL$25$1$main$AUS1, STATIC, EXECUTING ]
END SNAPSHOT FOR PLAN PL$25$1$.
QUERY:\> --->exit
TOPS:\>
TOPS:\> query
QUERY:\> --->SELECT ORDER FOR PATIENT WHERE TARGET:2005-7-16 17:48:30,2005-
7-16 17:51:25; SOURCE:PATIENT_ID=61
processing query ...
launching specialised query handler ...
processing ORDER query [ 2005-7-16 17:48:30,2005-7-16 17:51:25 ] for [ PATIENT ]
...
Tests ordered for [PATIENT_ID=61] during time interval [2005-7-16 17:48:30,2005-7-16
17:51:25]
Dip_stick_urine Profile, DSU, 2005-07-16 17:49:28.0
Urinary_Tract_Infection Profile, UTI, 2005-07-16 17:50:06.0
Urinary_Tract_Infection Profile, UTI, 2005-07-16 17:50:06.0
-------------------
End test listing.
QUERY:\> --->EXIT
TOPS:\>
Fig. 8. A query for a snapshot of the com-
position of a CPG instance in TOPS.
Fig. 9. A query to find out what clinical tes
orders where made during the specified time
interval.
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