Table 2 Features of complex systems identified in key informant interviews

Uncertainty

Arises from the inability to predict outcomes in a CAS, or from clinical situations (e.g., around a patient’s prognosis) due to a range of factors, including the number of inputs and lack of knowledge

Uncertainty around who owns the data and how the data will be reused in the future

So many questions. Can patients access their data? Who can have access or store it? What are you going to do with the data? Are you going to sell it? Can insurance companies use the data to discriminate against the person? [KI2]

Dealing with unexpected findings that do not fit the work plan

There is one size fits all [with no room for variation]. So, for example, what happens when a trio comes in [testing of child and both parents] and the dad is not the dad? [KI2]

Will the different stakeholders adapt and adopt genomic new technologies and processes?

There’s uncertainty around how we get the different states [in Australia] to adapt and adopt these new technologies and processes and industry—this will be critical. [KI7]

Uncertainty about demand for genome sequencing

There’s a huge amount of uncertainty; we are building it as we go and trying to get it right.[KI2]

How will we fund clinical genomics once the research funding is withdrawn?

We do wonder where funding might come from for patients [in the future] [KI4]

Non-linear processes

Occur in complex systems as the dynamic nature of agent interactions, interconnections and emergence means processes cannot be linked causally to outcomes in a linear way

Patients were sometimes unwilling to have genomic tests as they thought it may affect their insurance

Uptake [of genomic testing] on a large scale is affected by non-health and biomedical issues such as insurance. It’s been affecting recruitment and research participation [KI7]

Unintended consequences

Interactions can occur on multiple timescales. As interdependencies increase, so does the likelihood that a given action will generate unintended consequences

Additional meetings and paperwork were necessary to allocate limited funding for tests

The amount of paperwork is mind boggling. I’m spending so many hours on it instead of looking after patients or interpreting data [KI9]

One of the hardest thing about my job is trying to figure out how to help people access testing. It’s time-consuming. You need to consider what they’re eligible for, how do I make it happen, what paperwork needs to be filled out. It’s a significant part of my job now. [KI4]

The [genomic] data’s so complex that the lab people can’t analyse it. It started with the clinicians doing all the analysis for about 18 months while the lab were hardly involved in it at all. That was when it was a research project through [State-based genomic project]; it wasn’t an accredited clinical test. When it became clinically accredited it sat much more firmly with the lab but they still needed input for several hours a week and that was not accounted for in either budget [KI9]

Amount of clinician time spent with laboratory services in data analysis and interpretation was unexpected and contributed to time pressures to return results and budget issues

The model for how the laboratory should work is changing. They’re negotiating that with them and there isn’t a good established model for how that should work in the future. 30% of {Clinician X’s] time is spent helping them analyse cases and that’s not accounted for in the clinical or laboratory budget. It’s been like that for the past 3 or 4 years and remains unresolved. It’s also unresolved in the UK. There’s an increasing need for clinical input in the laboratory as part of laboratory services. The job description/KPI for this hasn’t been created. [KI9]

Investment in time spent in teaching for the senior clinicians and scientists was unexpected

Upskilling people to be on par contributors to [multidisciplinary teams] has been a challenge. Same thing with [genetic counsellors] and lab people. You need a few years of training to function at the required level. So, lots of supervision in my role has become a new way of working that exists because of genomics. [KI9]

Clinicians can feel lack of funding undermines their patient care

An issue as a Genetic Counsellor working as an advocate for the patients, if a result comes back … [and it is] suggested as clinically useful and beneficial for other family members to have testing, there’s often no avenue for funding for follow-on testing. Australian Genomics will fund follow-on testing for family members if it aids in firming up classification of a variant as benign to pathogenic … But if it won’t clarify the classification of a variant then they won’t fund that. [KI3]

Some diagnostic tests/roles may be made redundant as a result of genomic testing

Some of my colleagues are worried about their area of expertise not being valued anymore, for example those who look at X-rays or skilled morphologists. Genomics will replace some tests or skills … That’s now challenged by genomics. Is there a need for that particular skill set at that level? [KI9]

Interdependencies

Interdependence involves the emergence of some overall combined system to the organization, where individuals retain their autonomy with respect to each other, but they are interdependent with respect to the overall combined organization

Nature of the workforce linked to funding which is linked to capacity and experience

It’s a young [Genetic Counsellor] workforce because [with the amount of funding available] they could only afford year 1 counsellors—Junior counsellors straight out of the Masters program… [This has had flow on effects] … [the junior counsellors] get thrown into a situation with very sick children … it’s very hard for them. [KI9]

Tests are contingent on inclusion and exclusion criteria

If parents are eligible for testing but one parent is deceased, then the testing will not be funded as it is “not fully informative.” [KI3]

Tests contingent on postcode and budget models rather than on need

There are inequities… [Patients in some regions] may not have access to funding for whole exome/whole genome testing and will need to fund themselves and this is challenging because tests can cost thousands. That’s a huge barrier. It’s not due to lack of clinical or sub-speciality interest. There’s a huge interest and desire to get tests for patients, but there’s not necessarily the funding. [KI4]

Consumer groups are advocating advances in genomic technologies as the benefits are realised by their members

There are a lot of support groups that are doing advocacy work and lobbying the government … to bring awareness for how much this technology is needed. Patients go online and see that testing is available overseas and start asking why it’s not available here. [KI4]

Clinicians rather than industry should be driving new technology

Clinicians should be connected to this as they are drivers for getting the testing up and running [in the Flagships] and having the conversations with labs, “what can you do to get us this type of testing?” rather than the other way around. [KI4]

Various outcomes are reliant on partnerships

When you get to the end of a clinical flagship project funded and you just sort of assume that you're going to throw this new technology or test over the wall, and it's going to be picked up here, but it's not. And what's more, there has been communication, in some contexts like [clinical flagship], where they [industry] overtly say “you involve us at the start, or we will make sure it is not adopted.” [KI7]

Self-organisation/ emergence

Involves creating order from within rather than imposed from outside the group; based on the importance of relationships and influences between agents

New ways of working have emerged between clinicians and laboratory services; working collaboratively rather than separately

A lot of time is now devoted to working with the labs and contributing to data analysis. In the past, we might have been consulted once in a blue moon by the lab about a tricky case – how to report or word something. Now it’s many hours a week sitting with them and looking at data. [KI9]

Emergent phenomena or behaviours arise from the dynamic system, and are not predictable based on the expected outcomes

New roles are emerging

Bioinformaticians have also entered the lab workforce. The role of the bioinformatician has emerged without a formal accreditation pathway. They come from a research background and they’re university trained. Many of them are developing and operating systems [to assist in genomic result curation]. [KI9]

Bottlenecks in the genomic testing process have changed

Despite tools to help with interpretation, a lot of it is still manual; people review the literature and tools. Some more complex variants can take up to 20 h of curation…. The time required to fill a high-throughput machine with [genomic] samples used to be a big bottleneck when fewer people were ordering testing. But the space is changing so quickly that that issue has been replaced with new issues, i.e., time for curation…. [join] the queue waiting for the data to be interpreted. [KI4]

Feedback loops

A phenomenon in which the output of some process within the system is “recycled” and becomes a new input for the system. Feedback can be positive or negative: negative feedback works by reversing the direction of change of some variable; positive feedback increases the rate of change of the variable in a certain direction

Test validation requires a stable market demand

Test validation needs investment. Unless you have a budget that you can plan with – in an uncertain market you’re not going to spend money on test validation. [KI9]

More lab staff are needed to interpret results but staff who are there and can do the job are less available as they are spending their time training new staff

There’s a huge bottleneck in interpretation of data. There are not enough skilled people. It takes a couple of years to train a scientist. Senior scientists are currently used up in training, supervising and double checking everything. [KI9]

More staff are needed to make genomic testing in Australia more competitive (than overseas labs) but because they are less competitive, they do not get the business needed to employ more staff

International labs can do the testing at a much lower cost, much faster turnaround time. It makes it hard for hospitals to still go with Australian labs. It’s a feedback loop as they need more business to employ more people to decrease turnaround times. [KI4]