Spread Care

Careflow Management System


The SPREAD CARE is a project founded by the Italian Ministry of Health and required to provide about 27 Neurological Departments with a decision support system, based on “The Italian guidelines for stroke prevention and management”, delivered by the SPREAD association.

Our decision support system is based on workflow technology. The workflow logic is based on the rules provided by the SPREAD guidelines (GLs) for stroke management. The already existing clinical chart has been transformed into an evidence-based, real-time decision support system, meanwhile maintaining the same look the users were familiar with. Since the final aim of the Project was to improve evidence-based behavior and detect possible organizational bottlenecks, non-compliance to the clinical prac-tice guidelines, before and after the system introduction, have been analyzed, as well as the accuracy of the clinical chart compilation, some care process variables, and system usability. Results show that the system enhances the clinical practice without boring users.

Description of the work

Evidence-based clinical practice guidelines have been widely promoted as a way of improving health outcomes. In current healthcare systems, however, scientific knowledge about best care is not applied systematically or expeditiously to clinical practice. GLs usually capture both literature-based and practice-based evidence into a textual format, which can be easily diffused but uneasily used in daily work. Thus there is a great effort to disseminate them in computer-interpretable representations, more suitable for individual clinical decision support. Contemporary, there is increasing need of smooth integration of GLs into the existing hospital information systems.

The current workflow technology seems to offer a convenient solution to build a cooperative system in which the activities of a care providers’ team can be coordinated within a process properly designed on the basis of available best medical knowledge. This projectb presents an approach to the design, implementation and evaluation of an evidence-based Careflow management system (CfMS).
As borrowed from the Workflow Management Coalition, a CfMS is a system that defines, create and manages the execution of careflows (Cfs) through the use of software, running on one or more Cfs engines, which are able to interpret the care process definitions, interact with Cfs participants and invoke the use of ICT tools and applications. Careflow indicates the automation of a care process, in whole or in part, during which information, documents or tasks are passed from one participant to another for action, according to a process definition. Cfs are case-based, i.e., every piece of work is executed for a specific patient. One can think of a patient care process as a Cf instance. A Cf process definition specifies which medical tasks needs to be executed and in what order. A CfMS may also contribure to solve the communication problem within the health care organizations since it is able to manage automatically a great amount of communication acts among organizational agents involved in patient care.

The Neurological Departments, involved in the Project, were already equipped with a Computerized Clinical Chart (CCC) implemented with the commercial tool WINCARE® (by TSD Projects).  To add the decision-support funcionalities reengineering of both structure and interface of the electronic patient record (EPR) was performed. A deep analysis of the SPREAD GL, the existing EPR, and its interface, allowed to determine the minimum data set required for implementing all the GL reccomendations, to check where these data were or not already managed by WINCARE®, and whether they were in the oppurtune format. Thus, the data model has been updated both by increasing information and by changing the nature of the existing information, mainly shifting from free text to encoding. To meet physicans' needs to quickly produce printed reports in natural language we developed a module for Generation of Inferable Free Text (GIFT). The idea was to create a generic module able to produce textual reports starting from a set of encoded data in whichever WINCARE® form.

After the data model analysis, and its consequent update, we implemented the GL recommendations through CfMS using Oracle Workflow™. The Cf model is described on the basis of the SPREAD GL, with some site-specifications decided by the involved neurologists. All the GL recommendations were implemented, regardless of their scientific evidence level (SPREAD uses four levels, from A to D). The CfMS needs patient data in order to feed the workflow engine and to interpret GL rules, then it must be able to communicate the patient-specific recommendations to the users, or Cf participants, through messages and to-do-lists. Our choice was to integrate all the needed functionalities within the existing end-user application, making it more “dynamic”, according to the CfMS execution, without creating a new specific interface. A middleware layer has been developed to keep the systems independent, while granting communication. It is composed by a supporting database (Oracle DB) and an Interpreter written in PL/SQL.

In implementing and integrating the decision support system attention has been put in maintaining the end-user interface as much as possible unchanged, so that users perceive the new system just as an update of the clinical chart, with some new functionalities, that are:

  • the sections of the clinical chart waiting for new data are listed runtime in an “intelligent”, patient-specific, dynamic way, i.e. accounting for the most useful data for that patient in that moment ;
  • data relevant for interpretation of the guideline rules appear as yellow-coloured fields, in order to facilitate a complete record filling ;
  • according to the urgency of the recommendation, the related message is shown directly on the screen or made accessible through a communication box;
  • at the patient discharge a module, called RoMA (Reasoning on Medical Actions) is actived and the list of non-compliances is shown and physicians may provide motivations.

The test-bed for the proposed methodologica and techonological solutions is the Stroke Unit in Pavia. The decision support system has been installed in April 2006, but the data model of the EPR is the same from January 1st 2005. Since that time to mid January 2007, about 400 ischemic stroke patients have been admitted to the SU. In a recent work we compared data collected in the two periods April /December 2005 and April/December 2006 in order to check the impact of the CfMS on the clinical routine. Preliminary results are encouraging: the system has been accepted by healthcare personnel and entered the daily practice; completeness of encoded data input is increasing for the most part of the data forms useful for guideline interpretation and also compliance is in general improved.


  • Oracle WorkflowTM
  • DBMS OracleTM
  • Pl/SQL
  • Visual Basic