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Analysis: Data analytics can deliver Healthcare 2020

Kamal Brar, vice president and general manager of Asia Pacific for data software company Hortonworks, looks at how data analytics can provide effective and affordable healthcare in Singapore.

One of the greatest challenges facing governments around the world is how to provide their citizens with effective and affordable healthcare. This is in fact a highly complex set of problems with multiple causes and a variety of actions needed in response. Happily, advances in technology are holding out the promise of addressing the challenge.

As in developed countries around the world, Singapore’s healthcare providers must deal with a rapidly ageing and fast-growing population, leading to an influx of patients and increasing pressure on general practitioners and hospital emergency departments. People are living longer and while we have largely conquered the prevalent diseases of the past, the incidence of chronic medical problems such as cardiovascular disease, diabetes, hypertension, cancer and dementia are increasing.

Recognising the burden this situation could present, Singapore’s ministry of health in 2012 launched the Healthcare 2020 Masterplan. The plan comprises measures to enhance the accessibility, affordability and quality of healthcare to meet the needs of Singaporeans across different stages of their healthcare journey – from diagnosis and treatment, to post-discharge follow-up.

The healthcare industry has always generated large amounts of data, for purposes of patient care, compliance, and record keeping. The advent of the Internet of Things has caused an explosion in data, from sensors to health tracking applications and devices that healthcare providers can tap into to optimise resources, bring greater efficiencies and develop an integrated healthcare system.

Recognising the potential of big data and analytics to transform healthcare, the health IT master plan has also been developed to serve as a strategic development of ICT initiatives for the healthcare sector.

Big data in healthcare refers to electronic health data sets that are so large and complex that it would be difficult to manage and analyse using traditional software and data management tools and methods. With big data, healthcare organisations have the ability to let multiple hospitals exchange information, leading to a 360 view of their patients, so doctors can give a more complete diagnosis.

For example, Vizient, a US-based healthcare services company, has gained significant value through the ability to take in data from a variety of different sources such as lab and patient data to recognise patterns, and provide this data to doctors to provide recommendations for how members can improve their health. Without big data, none of this would be possible and healthcare organizations would be operating without having the complete picture.

This is one of the goals the ministry aims for with the National Electronic Health Records (NEHR), in which a person’s medical records is shared among all public health institutions. The comprehensive NEHR will then be able to simplify the patient’s journey from primary to tertiary care throughout the country, in both the public and private sectors, as any doctor treating the patient would have full access to his or her medical records.

There are many other ways in which technology is being adopted, putting health data to work in the pursuit of improved healthcare.

For example, hospitals have begun to use radio-frequency identification (RFID) to track equipment and medicines as they move throughout their facilities. RFID scans of an item or device can capture their contents, location, manufacture date, order numbers, and shipping data. This information can help ensure medicines are utilised before their expiry date, or quickly locate an important piece of equipment.

In the longer term, historical data on the interactions of medicines, equipment and doctors will provide valuable information for healthcare predictive analytics as well as helping to plan purchases, train staff and improve operational efficiency.

In another advance on traditional practice, wireless sensors are being used to capture and transmit patient vitals more frequently than staff can make bedside visits. These signals can provide real-time alerts, so caregivers can respond more promptly to unexpected changes. Accumulating this data over time enables healthcare predictive analytics to proactively help predict the likelihood of an emergency, even before it could be detected with a bedside visit.

One common problem with our existing healthcare system is re-admission rates. Patients with heart disease, for example, are closely monitored in the hospital but may skip their medications or ignore dietary and self-care instructions when they go home.

In a leap of intuition, Pennsylvania-headquartered Geisinger Health System has focused its innovations to enhance patient care, integrated health system approach, and an overall focus on caring and compassion. With a platform designed to deliver quick and easy data to caregivers, Geisinger’s staff are able to search through 200 million patient note records in seconds to find relevant conditions and medications, which helps them analyse the success of treatments, identify areas of improvement, and determine ways to save time and money for both patients and providers.

Healthcare, especially on a national level, will continue to be a major challenge for authorities. Demographic and lifestyle changes in populations, as well as outbreaks of unanticipated diseases, will constantly demand innovative responses from governments and the healthcare profession.

Fortunately, advances in healthcare data analytics are keeping pace with the evolving nature of the challenge. Patients and healthcare staff alike can be confident that technology is on their side.

Posted on: 16/11/2017 UTC+08:00


News

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