It doesn’t take a physician to tell you that an adhesive strip can’t fix a broken arm, nor can a bandage repair a broken system of disparate databases of important medical records, patient histories and billing information. Working in data siloes can lead to critical operational and clinical decisions that are less informed and less effective.
In an environment where healthcare providers face rising costs and strained resources, where can the O’s – CFOs, CIOs and CMOs – find savings, efficiencies and better quality care especially in countries that are facing rapidly aging populations with increasing life expectancy like South Korea and Taiwan . This, along with richer diets and a more sedentary lifestyles, has led to an increase in chronic diseases among Asians in developed countries.
A recent study by the Advisory Board Company forecasts that over the next decade, the average health provider will see a five percent annual increase in their expenses. And to remain viable, the report recommends that providers eliminate up to 20 percent of their cost structure through measures such as adopting more flexible staffing models and standardizing care.
As a preventive measure, the Advisory Board Company suggests looking to innovations that could “pay off over the long term.” One such innovation is the use of data analytics. Findings from a newly-released, Microsoft-sponsored study by IDC Research suggest that organizations in the health industry worldwide could gain US$109 billion in value from leveraging available data over the course of the next four years.
Beyond rising costs, shortage of beds and manpower is an issue faced by developed Asian cities such as in Singapore and Hong Kong, healthcare providers are forced to make more efficient use of limited resources to meet the needs of the population.
Locked within the networks of many healthcare facilities is a sea of operational, financial and clinical data, which, when harnessed correctly, could lead to significant cost savings and operational improvements that make the impossible job of chief executives a bit more feasible.
In one example, personnel from Djerriwarrh Health Services in Australia enjoy instant access to information about health practitioner activity to help them analyze the service’s resourcing requirements with a cube-based solution that leverages data across diaries, appointments and non-patient events.
By using some of the latest breakthroughs in data analytics tools and machine learning, healthcare executives can combine disparate data sets into one stream, revealing patterns in patient population and staffing levels that not only help to optimize labor costs and improve the quality of care based on patient needs, but also provide a base-level of understanding from which predictions can be made about where to invest in new services, equipment or capabilities.
Beyond the use of analytics, we’ve now arrived at the point where it’s possible to not only anticipate outcomes, but also prescribe treatments based on those projections. With the use of data visualization and other self-service BI tools, health professionals can more quickly make an informed decision on the treatment plan most likely to be cost-effective.
Using mobile devices, members of the care team can now access the same business intelligence (BI) tools from anywhere on the hospital floor, gaining actionable insight from clinical records, emergency room notes, and social media feeds while monitoring a patient’s condition. Care teams can gain a better understanding of patients suffering from multiple conditions and, based on early indicators, predict which patients are likely to deteriorate and require re-admission.
With the knowledge gleaned from historical data, as well as the awareness of what’s happening in real-time, care teams can respond at a moment’s notice with preventive measures that keep patients on the road to recovery, rather than responding to complications and rerouting them off of costly and potentially harmful detours.
In Ajou University Medical Center, Korea, the deployment Clinical Data Warehouse has resulted in a system for easy usage of statistics and analysis, which has helped in the acceleration of various clinical research projects undertaken by its medical staff, as well as more effective and fast support of treatment coursers for patients.
The Center has also developed a system for integrating and analyzing clinical information from various other medical institutions, which has opened new doors for research exchanges and collaborations with other institutions.
In the current era of fiscal frugality and chronic disease, BI and data analytics could be the biggest breakthrough for healthcare executives, providing sharpened insights and prescribed actions that coordinate chronic care, drive out waste, and proactively prevent the need for costly care.
This story was first published on Enterprise Innovation on January 22, 2015.