With real lives on the line, analytics technology helps improve every aspect of the health and cancer care systems by streamlining data in a way that is, quite literally, not humanly possible.
Canada is in many ways a privileged nation when it comes to healthcare. Given the realities of ongoing economic challenges around the world, Canada has fared pretty well over the past four years. However, 2012 has already proven to be a year in which new austerity measures and belt-tightening have reached Canada’s public sector, and healthcare has not been spared.
In Ontario, the Drummond Report painted a troubling – if hopeful – picture of Ontario’s economic challenges, one in which healthcare was called out as a growing source of inefficiency. Healthcare spending accounts for 40.3 percent of the province’s overall expenditures, totaling $44.77 billion. At the federal level, the Conservatives announced that they are looking to save $309.9 million in health portfolio costs by 2015.
More recently, Canada’s premiers met for high-profile discussions to find ways to reduce healthcare costs. In a first-step along what promises to be a long road to reform and efficiency, bulk purchasing for certain generic drugs is just one of the options provincial leaders are exploring.
But there are ways to become more efficient with existing solutions. Intelligent analytics technologies offer the chance to continue providing Canadians with exceptional healthcare while also working within these new austerity measures. By employing technology and analytics, Canadian healthcare providers can reduce inefficiencies that burden the system while maintaining the world-class care Canadians consider a priority.
Canada’s healthcare is a system of disjointed institutions, functioning as a series of services that fail to work as cohesively as they could. Few experience the extent of this disconnect more than those who’ve had the misfortune of being diagnosed and treated with cancer. Given the variety of diagnoses and the many stages of treatment that occur across different cities and institutions, it should come as no surprise that cancer produces a massive amount of data from diagnosis to treatment.
If the system were equipped to leverage, access and analyze the data produced every year, healthcare providers and policymakers would be empowered to make better decisions and even pre-empt many cancers. In some respects medicine already uses knowledge acquired from data: regular procedures such as colonoscopies and mammograms are recommended for certain demographics precisely because we’ve recognized trends and risk factors. Analytics technology offers the ability to look at oncology – and many other aspects of medicine – more granularly, by using accumulated information to spot unseen health trends, identify disease patterns and better predict likely outcomes.
Health providers around the world are coming to terms with the data stores in their possession and how they can use this information to better manage cancer’s impact on individuals and the healthcare system as a whole.
From a macro perspective, this can mean potentially reducing the overall incidence of cancer in a population by giving researchers access to broad data sets that will help them better understand the disease and ways to prevent it. At the same time, at the micro level, using analytics technology means reducing the impact of cancer with better screening and detection, and ensuring access to effective diagnosis and high-quality care.
Effective implementation of analytics technology empowers policymakers and cancer researchers at the highest levels to anticipate the trends, environmental factors and demographic considerations when planning cancer care years in advance.
For example, just one use of this technology involves estimating the future impact on individual hospital resources if lung cancer surgery is consolidated from approximately 50 hospitals, each performing a small volume of surgeries, to approximately 15 hospitals, which will perform higher volumes that result in better outcomes for patients.
Canada’s healthcare system needs to start consolidating data from disparate sources, analyzing it and creating an environment of data-driven decision-making, which in turn leads to better care for patients, more useable data for researchers and lower costs for everyone.
Steve Papagiannis is a lead for Information Management at SAS Canada, covering the fields of Data Governance, Decision Management and Analytics Management.