Creating a model of how patients and staff use and provide services at a health clinic can help that clinic operate more efficiently.

Dargaville Medical Centre (DMC) is a large General Practice in Northland with 12 doctors and about 14,500 patients. As well as its weekday clinics, the centre operates a 24/7 acute service for people with urgent health needs. It also runs phone appointments, where people can call to talk to a doctor or nurse for free instead of coming to the clinic.

With anonymised data from the practice’s management system, Lucy McSweeney modelled the clinic using hierarchical control conceptual modelling (HCCM). This is the first time this type of model has been applied to a primary healthcare facility. HCCM is more realistic than simple models such as a first-in-first-out queue.

For example, a simple model might be that the first patient to arrive at a clinic is the first to be seen by a doctor, and the first to leave. This is not how it works in real life. Patients book appointments in advance, and a patient who is very early to an appointment will still be seen after other patients who arrive later. In the acute clinic, patients with urgent needs are seen before those with less serious conditions, regardless of wait time.

HCCM gives the modeller control over logic and decisions and can create a much more complex model considering people’s needs and differing behaviours. Each step along the way represents a logic decision that must be made. A patient’s journey through the system might look like this:

Call to talk to doctor on the phone; book an appointment. Arrive at reception; wait for doctor. See doctor for 15 minutes. Return to reception to pay; leave the clinic.

The model shows how doctor appointments, the acute clinic, phone appointments, and reception are used. It does not include nurses, outreach clinics or special clinics (such as optometry appointments).

The completed model can be used to make accurate decisions based on data – giving staff information so they can make decisions around rostering and appointments. Having the right staff available at the right times allows the centre to operate efficiently and better serve its patients, while giving doctors a better-balanced workload.

It can also be tweaked to see how changes will affect the clinic. Would two doctors being on leave at the same time increase wait times? How much will population growth affect demand? If more patients use the phone service for minor problems, will demand for the acute clinic decrease?

Modelling these changes allows DMC to plan for the future, test different ways of providing care and look for ways to solve existing problems.

Lucy hopes this type of model can be improved by considering nurse activities and other events, applied to different clinics, and made available to staff and Primary Health Organisations for planning.

Lucy McSweeney is one of 10 students who took part in the Summer of Research programme funded by Precision Driven Health. The research is at an early “proof of concept” stage. The projects offer fresh insights into what healthcare will look like when precision medicine is widely used.