Dynamic Modelling to improve Renal Services

Solution

• Dynamic Modelling to improve Renal Services
• Solution
• Outcome

SOLUTION
The Approach

A commonly held view is that the rise in prevalence of chronic kidney failure, combined with the ageing population will require more in-centre facilities to be built to meet this demand. Before accepting this view we developed a better understanding of demand. To do this we used System Dynamics modelling to develop a clear picture of the dynamics involved in chronic kidney disease, the decline into chronic kidney failure and the impact of service design on both.

Synergia worked with the renal clinicians, staff from the planning section and business analysts who had access to the renal service’s clinical and financial data, to build this model. The aim was to develop a clear, robust picture of the renal service and how it was likely to evolve under current policies and practices. We began with a qualitative model that described the key factors involved in driving renal demand within the DHB. This included the obvious impact of age and deprivation levels but also highlighted the importance of managing renal disease, along with the aggravating factors, as these have a significant impact upon the dependency levels of patients arriving at the service. This in turn has a major impact upon the treatment, or modality options, available. As patients arrive sick and dependent the numbers requiring supported in-centre service grew proportionally.

With this background a detailed quantitative model was developed utilising data from the local service, the ANZDATA database – the major renal database in Australasia - and international literature. The first model ran scenarios based on a continuation of current policies and practices. The results were not good; demand would continue to rise, albeit starting to rise at a slower rate over the next 10 years, and in-centre facilities would have to be expanded to cope. However, the modelling did provide some hope, highlighting a number of other plausible futures with different patient and service outcomes. The modelling clearly showed that the need for in-centre facilities, as opposed to other options such as home dialysis or peritoneal dialysis, which were less expensive and, for most patients, clinically superior, was driven as much by the nature of the service as by the demographics of the population. This meant that something could be done. Even if the overall demand was out of the DHBs control, at least in the short to medium term, they could choose how to respond to that demand and in doing so drastically alter the future clinical and financial future of the service.

What became clear in this work was that patients were being treated in-centre because there were limited resources being applied elsewhere. The resources needed to support the training required for home and community options were being absorbed by the response to the rising in-centre demand. Links with the primary sector were far from optimal and patients were being seen by the renal service far later than was needed. As a result they were sicker than they should be and the dialysis options were limited. When a patient is sick, frightened and having to go on dialysis at short notice it is not a good time to talk about training and having dialysis at home. Furthermore, dialysis patients require minor surgery to provide access for the dialysis machine to circulate their blood. As patients were arriving late and access was hard to get on a timely basis a large number of them were being given temporary and even emergency access. Not a good start to a process that you were going to have to put up with for around five hours, three days a week for the rest of your life. It was great to have it all done for you. Thinking about having to do this at home, and being trained to do so was, for many patients far too difficult. Having the process all done by the nurse is a lot easier. Once patients start on fully supported in-centre care it is difficult to encourage them to change – even though it can be much better for them.

So, the more the service ran to keep up, the more the service filled up its in-centre facilities. What the process of modelling showed was that the future of the service was, to a large extent, in their control and that a better understanding of the dynamic interplay between demand and service design could provide options that were better for the patients, better for staff and better for the financial management of the Board.