How understanding financial data can help transform healthcare
Interview with Steve Haines, Managing Director, Civica Singapore.
When analysed well, up-to-date costing data can provide a window into the everyday activities and decisions made at hospitals. This creates opportunities for healthcare providers to improve patient outcomes, optimise capacity and save money, which can then be redirected to more necessary services.
Artificial intelligence can help hospitals reduce unnecessary costs, understand activities, make better use of resources and our valued workforce time, explains Steve Haines, Managing Director, Civica Singapore.
Reduce unnecessary spending
Healthcare costs have ballooned during the pandemic, making it more important than ever for hospitals to use their budgets wisely. On top of that, the backlog of elective care delayed by the pandemic is going to provide additional strain on our healthcare services for some time to come, shares Haines.
Hospitals can use up-to-date costing data to reduce unnecessary spending. Everything a doctor does in healthcare has a financial consequence, he explains. If healthcare providers can understand how much each activity costs, it can help maximise the value of every dollar of their budget spent.
Patient Level Costing software can provide insights on how money is spent on everyday decisions, such as tests ordered, drugs prescribed right down to how many minutes a clinician spends in an operating theatre. Though this may seem insignificant, operating theatres are expensive - in Australia, the average cost of running one is AUD$42 a minute, or AUD$2500 an hour, reported Science Direct.
Using AI software on this data, we are able to detect systemic variation in clinical activity, identifying unwarranted consumption of our valuable resources, explains Haines. For example, it might detect a doctor who consistently spends twice as long on a standard operation compared to their peers for a procedure with a directly comparable level of complexity, which can then lead to improvement in productivity.
Once identified, service managers are able to work with clinicians to understand opportunities to improve their efficiency, offering a better experience and outcome for the patients, who may spend less time having a procedure, freeing up theatre capacity to enable the treatment of more patients.
Another example found has been where some clinicians consistently order more tests as part of a diagnosis than are perhaps necessary, compared again to peer group best practice. The money saved by optimising consistent clinical best practice can then be redirected to commissioning more necessary services, or hiring more nurses for example, suggests Haines.
“The key word is value. We're optimising the value of every dollar we spend in healthcare,” he notes. When they initially piloted the AI software with six hospitals in England’s NHS, they identified GBP £44 million worth of potential savings opportunities, equating on average to 3 per cent of each hospital’s total annual income, equivalent to around SGD$80 million, he shares.
Understanding spending as it happens
When cost data is collected more regularly, hospitals can identify more quickly areas where systemic variation in activity may be occurring, how and where it may be best to target any service improvement or transformation activities to ensure optimum value for its spending. The ultimate for governments is maximising population health.
Right now, due to the historic manual approach to costing in Singapore, cost analysis is only done once every three to four years meaning the sector is not able analysing the most up to date data. Haines shares. This year’s National Costing Exercise (NCE) for example, will be based on data collected in 2018.
This obviously does not take into account how the pandemic has changed the healthcare landscape. The pandemic for example has introduced even more rigorous cleaning exercises that can make some procedures take more time and invariably cost more.
In contrast, the UK Department of Health has done annual cost analyses for many years. They have also, during the pandemic, started analysing quarterly data at a National level to get information that better reflects the changing landscape of healthcare, he notes.
Implementing a new National Costing system will enable Singapore to complete costing exercises much more accurately, efficiently, and frequently in the future.
As Civica supports the roll out of its costing systemisation software across Singapore, cost analysis will start to reflect a more accurate picture of spending, he shares. In turn, this can help the government provide funding better targeted to current needs, he explains.
Making better use of talent
Once more consistent, accurate and timely patient level costing data is collected, we are then able to apply our latest our AI software that can enable analysis of these very large data sets a lot quicker than traditional data analysis.
When accountants have to spend less time manually crunching data, the health sector can make better use of their talent by redeploying them to provide advice and guidance to front line staff on what the data is telling us.
“With our initial UK NHS pilot project, we completed the equivalent of 13 years of traditional analysis using industry standard BI tools, in just 7 minutes,” shares Haines.
Accountants can use that freed up time to perform more meaningful, value adding tasks.
Much like how doctors can examine your body for unusual signs, AI can examine how healthcare organisations can get better value out of their spending. With this technology, hospitals can ensure that every dollar is spent wisely and that budgets remain in peak health.
Civica is a global leader in software for public services, and the developer of CostMaster and CostMaster Aurum, the solutions referenced in the article.