The use of big data analytics in healthcare

01 April 2013 Dr Jonathan Broomberg, Discovery Health

Healthcare funders today need to be able to address the many complex factors that have an impact on the quality and cost of care for their members.

Any approach must optimise access to care and contain costs, without having a negative impact on the quality of care that members receive. A challenge for healthcare funders is to find innovative ways to ensure that both are optimised. If quality of care is sacrificed in the short-term to contain costs, this can compromise quality of care later on.

The use of managed care services, programmes and strategies forms an important part of a healthcare funder’s overall model to manage benefits and care in a sustainable fashion. Managed care strategies range from managed care and disease management programmes to health analytics, forensics capability to detect fraud, and alternative reimbursement models.

Improving quality of care while eliminating system inefficiencies

Data analytics is absolutely critical to any modern approach to managed care, and Discovery Health has been investing in its capacity to analyse large amounts of health claims data for over a decade. Key to our approach is the ability to compare and analyse huge volumes of claims data on a sophisticated risk-adjusted basis. This approach involves a combination of clinical, statistical and actuarial skills and has led to the development of a range of tools and software assets.
These tools are used to analyse key trends in our claims data, as well as to design appropriate interventions to manage claims risk while improving quality of care at the same time. Such approaches are applied in the hospital environment, in pathology and radiology and in medicines risk management. They are also used when it comes to identifying and preventing fraud.
We estimate that these approaches have saved the medical schemes under our management approximately R3bn in 2012, including R250m in fraud savings.

Big data analytics is increasingly playing a role in a healthcare funder’s ability to improve the quality of care for members and eliminate any inefficiencies in the system.
The McKinsey Global Institute estimates that big data analysis could save the American healthcare system US$300 bn per year, and it could save the European public healthcare sector €250 bn per year. It is therefore a critical skill and asset for healthcare funders as it enables the funder to better manage risk over the long term.

Case study: big data analytics assist in establishing alternative reimbursement models aimed at optimising cost and quality

An example of the benefit of big data analytics is evident from a collaboration undertaken among Discovery Health, the South African Paediatric Association and the Paediatric Management Group.
Using the claims and clinical data of affected members over a number of years, we were able to build a profile of 352 paediatricians. Comparing the performance data of this group, we determined 81 outliers, which had resulted in an admission inefficiency cost of R50.4m.

Their approach was to engage with paediatricians in a project to improve the quality of clinical care and to increase the cost-effectiveness of treatment.

The project in question has been found to be successful in four key areas:
• There has been a significant improvement in the relationship between Discovery Health and the paediatric societies;
• Important changes in the behaviour of outlier practices have been recorded;
• In 2011, there was a 9.4% reduction in the actual admission rate versus the expected rate of admission; and
• There have been improvements in data collection and the quality of clinical coding by paediatricians.

Since the start of the project in 2006, the cumulative savings of the project, up until December 2011, was R255m. There was a cumulative increase of R43m in remuneration for paediatricians over this period. Over the past six years, 84% of paediatricians have taken part in the project, which is a significant number.

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