Cost of Delayed Diagnosis Modelling and Planning Tool

Cost of Delayed Diagnosis Modelling and Planning Tool

Commissioned by NASS, Health Economics Consulting (HEC) undertook the research to create a new health economics model to assess the cost of delayed diagnosis, up to the point of diagnosis of axial SpA (including Ankylosing Spondylitis or AS) by combining healthcare, out of pocket costs and productivity costs/losses.

HEC considered the best way to model the potential cost and established that a Markov Chain model process was the most effective in representing the NASS Act on Axial SpA campaign aiming to drive down the time to diagnosis.

Read here an overview of the model and how you can request access or ask more.


To develop the model, a mixed method approach was taken. It included semi-structured interviews with key stakeholders (12 clinicians, 4 people living with axial SpA) to understand the experiences and impacts of delayed diagnosis and the costs incurred. Researchers also gathered survey data and data sets of anonymised patient information. Key clinical stakeholders also assisted in the validation of the model.

The model projects diagnosis progression (“Not Diagnosed” to “Diagnosed” and “Dead”) forward in time-steps with feedback loops to allow movement in states back and forth. Transition states within each time-step were constructed according to the various stage of the diagnosis process and they were used primarily to demonstrate an assessment of the costs in the time taken to a confirmed diagnosis.


The main inputs into the model included:

  • the probability of patients engaging with healthcare services in different period from the onset of the symptoms.
  • the probability of getting diagnosed, by gender and age group.
  • the sensitivity and specificity of various diagnostic strategies.
  • the health resources utilised.
  • the cost of managing the symptoms and comorbidities.
  • the cost related to productivity losses.
  • any other parameters and costs reflecting real resources required to diagnose, confirm, treat, cope with, manage and accommodate axial SpA symptoms.

The model relied upon assumptions due to the non-availability of data, which is a limitation. There is a need for detailed records of societal costs that impact on people with axial SpA to be collated. Such data would reduce the assumptions needed and, therefore, improve the predictiveness of the model.

Symptoms starting slowly

Pain in the lower back

Improves with movement

Night time waking

Early onset (under 40)