Flexible guideline-based patient careflow systems.
Workflow Management Systems integrate domain and organisational knowledge to support business processes. When applied to the medical environment, they can be termed "Careflow Management Systems", and may be used to manage care delivery by enhancing co-operation among healthcare professionals. This paper focuses on care delivery based on clinical practice guidelines. Healthcare organisations are very different from industrial or commercial companies: their main goal is not profit, but maintaining and improving the health of the public. Therefore, outcomes are difficult to measure. Firstly, physicians, while playing a variety of roles, are quite independent decision-makers; secondly, the object of the process, i.e. the patient, may be involved in choosing treatment options, and may be treated by different institutions. For these reasons, the standard functionality of typical Workflow Management Systems must be strongly enhanced in order to cope with healthcare delivery needs. A major issue is accounting for exceptions. In most non-clinical settings this is not a problem because processes are very well defined and can often be easily controlled by some higher authority. As explained above, this does not happen in healthcare organisations. Responsibilities are widely shared, and health care professionals may be non-compliant with guidelines for a variety of reasons. The paper presents a classification of possible exceptions, and shows how the sequence of tasks described by a guideline may be altered, at the implementation level, in order to meet actual user needs, while maintaining guideline intentions as much as possible. A terminology server is also exploited towards this end. This work illustrates a prototype of a Careflow Management System based on an international guideline for ischemic stroke treatment, developed by the American Heart Association.
Quaglini
S
S
Dipartimento di Informatica e Sistemistica, Università di Pavia, Via Ferrata 1, I-27100, Pavia, Italy. silvana.quaglini@unipv.it
Stefanelli
M
M
Lanzola
G
G
Caporusso
V
V
Panzarasa
S
S
D001185:Artificial Intelligence; D002545:Brain Ischemia / Q000628:therapy; D020000:Decision Support Systems, Clinical; D006284:Health Plan Implementation; D006801:Humans; D010346:Patient Care Management / Q000379:methods; D017410:Practice Guidelines as Topic; D020521:Stroke / Q000628:therapy