Sequence diagrams for visualising healthcare processes

Malcolm Pradhan, Michael Edmonds

from Pradhan, M., Edmonds., M., Runciman, W. ( 2001 ) Quality in Healthcare: Process. Best Practice & Research Clinical Anaesthesiology. 2001; 15 ( 4 ): 555 - 571

A model is a simplification of reality that enables communication and should improve our understanding of the problem area; it is perilous to assume that any model represents reality accurately. The purpose of a model is to gain shared insight into a problem, and to assist in decision-making; a good model is one that is useful in solving a problem, and a single model may not be useful in multiple problem areas without modification. We simplify reality by making assumptions, and in any modelling procedure all assumptions should be explicit so those using the results of the analysis understand its limitations and its strengths. It is important to note that making the correct assumptions, and testing them, requires skill and practice.

We promote graphical representations of our models so they are easier to communicate and therefore easier for people to understand what assumptions have gone into the creation of the model. While most of the technical work in modelling is often done in a spreadsheet, our experience has been that a clear graphical representation of our models engages clinical staff and administrators alike in a way that a spreadsheets cannot. More significantly, we are able to engage a wider pool of expertise to improve and refine our models through graphical methods before dwelling on the mathematics. To demonstrate practical techniques for modelling and improving healthcare processes we will use an example of a pre-operative screening clinic.

Example: Pre-operative screening clinic

Many large hospitals run a pre-operative screening clinic to assess a patient's fitness for day surgery, to reduce the risk of preventable error. The clinic workflow is quite complicated and demonstrates many features that exist in other areas of inpatient and outpatient care. The patient is interviewed by the clinic clerk, nurses, the surgical team and anaesthetists, and further information is requested and chased up from specialist consults, general practitioners, radiology departments and the biochemistry laboratories. The collation of this information is time-limited by the interval until the day of surgery, and is dependent on a complex information flow and inter-professional dynamics. This process has many steps that are open to error, and is often held together by two or three dedicated team members coordinating the patient and information flow so no information is lost.

Using sequence diagrams for modelling healthcare processes

We have been using sequence diagrams to model the process and information flow between all of the stakeholders involved in the healthcare of a patient. From the workflow sequence model it is possible to identify high-risk processes, and therefore where interventions can be most beneficial to reduce risk and improve patient safety. Importantly, the workflow sequence diagram is a good communication tool that highlights the interplay between different stakeholders in an episode of patient care (Figure 1).

Figure 1. Sequence diagam of a pre-operative workflow.

The workflow sequence diagram is derived from the Unified Modelling Language [1], a set of diagrams and semantics used in software engineering. Software engineers discovered that while an organisational structure represents the position of software entities in a hierarchy, it does not provide insight into the way the entities interact to fulfil a task. Similarly in business, the organisational structure of a hospital or unit does not provide us with how units and individuals interact to deliver patient care. Sequence diagrams are one of the graphical representations developed to demonstrate dynamic interaction of messages between entities in complex systems. Numerous other diagram formats exist but we have found the sequence diagram to be a good trade-off between accuracy and clarity.

In sequence diagrams entities that play a role in the process being modelled are represented along the top of the diagram. In healthcare processes we usually model units, individuals, or even organisations. For the episode of care being modelled, we represent an active participant in the process using a hollow rectangle. If a unit is involved in an episodic manner, then there may be several smaller rectangles, which can quickly identify problems with continuity of care. In the case of the pre-operative screening clinic, the episodic activity of the anaesthetist demonstrates clearly that there may be several different anaesthetists involved in the care of the patient over time. Each horizontal arrow represents a message. In workflow sequence diagrams we use solid arrows to represent requests for information or services, and dashed arrows to represent new information being returned or delivered.

The following patterns in workflow sequence diagrams represent workflow that may have a higher than expected risk:

• Long vertical gaps between information request and information delivery signal time lapses that will make the information easier to overlook or forget in the absence of a reminder or alerting system.
• The entity requesting the information is different to the entity receiving the information. This makes overlooking results much more likely.
• The information request is to an entity outside of the unit/organisational boundaries. For example, in a pre-operative clinic the anaesthetist may be required to contact a general practitioner or a specialist for patient information. If this information is not returned immediately, then the likelihood of information being lost or mis-transcribed increases.

Figure 1 shows an example of complicated workflow that is open to risk and error at each of the points above. The pathway that blood test and other investigation requests follow from the requesting doctor, in this case the anaesthetist is complex and inefficient. There is a long vertical gap, or time lapse, the person receiving the information may not be the same that requested it, and it depends on an entity outside the unit. In this part of the workflow process the anaesthetist makes the request, and passes the paper form onto the nurse. The nurse takes a blood sample at the end of the patient's pre-operative screening session, and, every so often, all of the samples are sent to the laboratory. The laboratory sends the results of the test back to the pre-operative clinic clerk, who files them with the patient's case notes. The nurse then checks these notes, and passes on any significant findings to the anaesthetist, who will report their interpretation of these to the case notes. This process has risk in its many steps and over the long period it unfolds. Some pre-operative screening clinics have a mechanism in place to ensure results get back to the anaesthetist by using "show me" orders which require all results for that patient to be reviewed by the anaesthetist. These orders are normally only attached to high risk patients or those where the results may change the decision to go ahead with surgery, but this does not account for all important test results. These orders are an example of an attempt at creating an 'urgent' channel, but won't cover all potentially risky situations.

From our analysis of a large pre-operative screening clinic we observed that the complicated workflow is largely unsupported by alerts and decision support. This lack of support places large demands on individual anaesthetists and nurses; the clinic has a reputation of a challenging place in which to work. We have found that the prevention of errors relies on the dedication of a few individuals to assiduously follow up results and to remember specific patient problems. The effectiveness of the clinic is therefore at considerable risk if staff changes or staff illness occur. Points for intervention may include increased automation, the ability for anaesthetists to highlight certain patients as important for follow up, the ability to mark certain patients as 'rule-in' meaning that the operation is on hold unless certain criteria are met with respect to their health state. All of these interventions require investment, but unfortunately the benefits accrued by the hospital through decreased length of stay due to effective pre-operative screening are not re-invested into improving the infrastructure of the clinic - it is not uncommon for healthcare organisations to have a 'silo' approach to funding that hinders the improvement of quality in healthcare delivery.

References

1. Booch G, Jacobson I, Rumbaugh J, Rumbaugh J. The Unified Modeling Language User Guide. New York: Addison-Wesley; 1998.

Home > Topics > Clinical Workflow

© 2004 The University of Adelaide Last Modified Wednesday, 28-Jun-2006 11:32:06 CST  Health Informatics	Copyright | Privacy | Disclaimer