Healthcare Analytics
By Germain Tanoh, PhD The Afro News Vancouver
During the past decade, spending in healthcare has reached a high level in most OECD countries (Organisation for Economic Co-operation and Development). In October 2010, the Canadian Institute for Health Information reported that Canada healthcare spending counts for more than 10% of the Gross Domestic product (GDP) and about $172 billion a year. It consumes over 40% of some provincial and territorial government budgets. As the population continues to grow, particularly the aging population, healthcare services are in more demand.
Healthcare executives are expected to be proactive, and provide plans and strategies to face rapid changes in population health status. Despite the increase in healthcare spending, more and more healthcare organizations struggle to match their capacity with the demand for healthcare services. The following situations are symptomatic of demand not being fully met: Overcrowded Emergency Rooms (ER), excessive length of stay in hospital, and long wait time for diagnostic imaging. In his 2010 annual report, Ontario Auditor General Jim McCarter revealed that more than 50,000 patients were kept in hospitals longer than was necessary last year due to a lack of long-term care beds and home care services – a problem that will only get bigger, he said, as the population ages. In addition to patient dissatisfaction over timely access to healthcare services, the actual situation may decrease quality of life of Canadians.
Predicting the basic complement of beds, physicians, triage nurses and all the other personnel essential to the optimal functioning of an ER, is a classic application of queuing theory. This term refers to the mathematics behind the phenomenon of waiting for services. The sooner health care leaders recognize that, the more patients’ lives will be saved; not to mention millions of dollars!
A 2008 report by the Aberdeen Group (Business Intelligence in Healthcare: Have Providers Found a Cure?) mentioned that an increasing internal and external financial pressures have pushed healthcare organizations to explore advanced analytics technology. For long healthcare executives have been making decision based solely on experience and gut-feeling. To be successful in the future, healthcare providers will need to use clinical data to improve operational efficiency and outcomes. The introduction of electronic health records (EHR) and other health information technologies are paving the way for more data-driven decision-making. Increasingly, healthcare financial executives are recognizing the benefits of advanced analytics for the financial health of their organization.
Now, it is time to move beyond the static (descriptive) reporting system into a more predictive one that will enable healthcare leaders to predict and plan for the future in an effective way. Healthcare analytics anticipates how proposed changes will play out, predict and prevent bottlenecks. To better manage their expenditures healthcare leaders must have a better insight of the population they serve. For instance, mining of the population based data can be use to define healthcare needs, find vulnerable population, detect hidden patterns in health status, and prevent and monitor disease better. Healthcare analytics will improve quality of care and help healthcare leaders find the best response or action, given the limited capacity, and restricted budget at their disposal.
About the Author: Germain Tanoh is the founder and President of Quantimal Consulting. He is a dedicated consultant with expertise in business analytics, project management, and strategic planning for business growth. He can be reached at gtanoh@quantimal.com or go to Germain’s web site at www.quantimal.ca to learn more.
