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Saturday, March 7, 2015

How Big Data can drive patient behaviour change 03-07

How Big Data can drive patient behaviour change 

How Big Data can drive patient behaviour change
When a patient is admitted to Khoo Teck Puat Hospital (KTPH) in northern Singapore, chances are the medical team already knows a thing or two about them.
In a bid to manage growing demand for subsidised beds, the public hospital launched Singapore’s first community healthcare programme in 2011 with the Ageing in Place (AIP) pilot. AIP targeted patients with a history of three or more admissions over a six-month period.
“What we discovered was that 20 percent of people admitted to the wards contributed to 80 percent of repeats and only 10 percent of the cases were actually health related – the majority were social issues,” said Dr Wong Sweet Fun, Director of the AIP Programme.
Based on that insight, KTPH then tailored in-home healthcare plans that aimed to cut hospital admissions. Four hundred patients were placed under the programme and the average admission rate fell from 3.5 times in six months to 1.3.
Hospitals such as KTPH are using data analytics to change the way people access healthcare services in the community and cut the number of occupied ward beds.
“The preventative healthcare is a bid to move away from ‘sick care’,” said Bastari Irwan, Director of Alexandra Health System’s Population Health Programme. “The KTPH A&E has a capacity for 300 people and we had 400 plus daily. We’re trying to filter out people who should not be coming to A&E.”
Healthcare providers look to big data to address Asia’s ageing problem
Total healthcare spending in Asia was estimated at US$1.34 trillion in 2013 and is expected to grow at an annual rate of 10.5 percent to reach US$2.21 trillion in 2018. This is a result of rapidly ageing populations and the growing middle class, who seek access to already strained healthcare systems.
Like the rest of the region, Singapore’s demographic is changing, pressuring the country’s public healthcare system. Figures from Moody’s show that Singapore is one of the countries to be hit hardest as growth in the working-age population slows from 48.1 percent in 2000-15 to 3.8 percent in 2015-30.
Big data has benefited sectors from retail to banking, but healthcare has been slow to catch on. In part, this is because of regulatory constraints surrounding privacy and data protection. Reluctance among healthcare professionals to adopt a data-driven approach has also hampered progress.
However, things are changing. Healthcare providers are looking for innovative ways to boost productivity, according to a PWC report, and analytics technology is supporting this. 95 percent of healthcare CEOs said they were exploring better ways of using and managing big data in 2014.
Diagnosing unhealthy communities with big data
In Singapore, KTPH’s work on data analytics is based on the principles of the e-health system: that healthcare is better delivered when you understand who your patients are.
Following the AIP pilot, the mining of patient information in the community extended to a larger programme. In 2013, they set out to answer a simple question: how healthy is north Singapore?
“The team screened 4,000 people in north Singapore, aged 40 years and above, for conditions such as high cholesterol and diabetes,” said Dr Mike Wong, who worked with KTPH’s analytics team to develop a unique data dashboard designed for doctors and nurses.
The team employed geospatial data technology to plot the patients on an area map. This highlighted problematic hotspots, where more unhealthy members of the community lived. For the majority of cases, they were farthest from the hospital.
This allowed the team to implement proactive solutions such as community pop-up clinics and health and wellbeing talks in strategically positioned locations to reach those deemed at risk.
“A lot of public screening is outsourced and people are then told to visit a doctor: it’s impersonal,” said Dr Wong.  “If you don’t go upstream and prevent these conditions you end up spending more and more on more hospitals, more staff for example.
“Patient behaviour makes or breaks a solution. With this model we can teach people how to manage their own health.”
Dr Wong added: “Up until 2008 all our data was on spread sheets and it took a long time to get results. With Excel it was very one dimensional, we could only sort one thing at a time. Now we can look at two or three variables, such as different conditions and age combinations or where people live.”
Building robust data-driven healthcare services
The hospital’s success in using advanced patient analytics can partially be attributed to Singapore’s existing e-health infrastructure. The national e-health record system, which allows each patient to have a single record accessible by any medical centre, was launched in 2009.
Sharing information across healthcare providers can reduce costs for the patient. The basics such as drug allergy and treatment history aside, data can cut the need for repeat clinical tests and ensure ineffective drugs aren’t prescribed multiple times.
But building a central database is just the starting point for healthcare analytics to prosper.
According to Lee Chew Chiat, Executive Director, Consulting and Public Sector Industry Leader, Deloitte Southeast Asia, the potential for data mining technology to benefit the healthcare industry today extends much further. In addition to predicting profiles of frail or elderly patients who are likely to be re-admitted into hospitals, data also allow medical professionals to balance drug efficacy and cost; and determine the locality of disease - dengue fever, for example - for better control.
“Having consistent basic information of a patient or a consumer is critical in healthcare. It is the foundation and since we have the foundation, Singapore can be a good test-bed,” said Lee.

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