Big data could help your health, if you let it


Blog 6: Big data could help your health, if you let it

Amy Le - 黎草嵋
D0731311
Source:  https://www.cnbc.com/2014/07/03/uld-help-your-health-if-you-let-it.html

Imagine a smartphone app that predicts what medical conditions you’re likely to suffer from and tells you how to avoid them. You are maybe able to download one sooner than you think.

Such apps would tell you what to eat, how much to exercise and when to visit the doctor based on the analysis of medical research, your medical history, family medical records and medical records of strangers of the same-sex, weight, age, and ethnicity.

Telehealth is a fast developing industry. Existing apps allow users to monitor blood pressure and blood sugar, while apps like Fitbits and Nike+ measure different aspects of fitness. Together such apps can provide insight into users’ overall health.

Privacy concerns still rife

However, the growth of big data in the health industry will only take place once privacy concerns are addressed.

In February, privacy concerns led the U.K. National Health Service to postpone the implementation care.data. The database aimed to collate anonymous information from patients to help doctors and health organizations better spot emerging health trends and provide treatment suggestions.

Even though care.data would have remained anonymous, the program met significant resistance amid concerns about how personal data would be shared and handled.

“Health data is not the same as sharing marketing data, like where you live or what washing powder you use. It’s a lot more personal,” said Wentworth.

“Before we can use big data in health, we need to build trust, and to do that we need an open conversation. Companies who are brokering the big data conversation need to be crystal clear about what patient data will be used for. The use of big data in health needs to be gradual, allowing people to choose between opting in and opting out.”

Future of big data in health

Big data analytics could save the American health care system $300 billion per year and the European public sector €250 billion, according to a 2011 report by the McKinsey Global Institute.

Big data analysis is already being used to make diagnoses in some hospitals. In Canada, Toronto Hospital uses big data to detect blood infections in premature babies and uses IBM’s analytics technology to monitor changes in heart rate, breathing and blood pressure to help predict potential changes in a baby’s condition.

Comments

  1. Celine XieJune 7, 2020 at 10:16 PM

    Healthcare big data refers to the collection, analysis and utilization of consumer, patient, physical data, which are too large or too complex to be understood by traditional data processing methods. Instead, big data is usually processed by machine learning algorithms and data scientists. The rise of healthcare big data is a response to the rise of healthcare information digitization and value-based healthcare, which has encouraged the industry to use data analytics to make strategic business decisions. Faced with the challenges of medical data, such as quantity, speed, type, and accuracy, medical systems need to adopt techniques that can collect, store, and analyze this information to generate actionable insights. So why is big data important in health care? First, Increasing amount of health care data: When medical records are digitized, the amount of virtual data medical systems that must be processed increases dramatically. In addition to EHR, through wearable technology, mobile applications, digital marketing activities, social media, a large amount of data is obtained in other ways. This makes health system effectively collect, analyze, and use this information. Second, demand for personalized care: Consumers in all industries want excellent, convenient, and personalized services-retail executives call this phenomenon the "Amazon experience." Healthcare is no exception. Customers need convenient, personalized care, which is a new standard that health systems must meet. This new nursing model focuses on quality, participation and retention. The health system is turning to medical big data to provide the insight needed to drive this level of personalization.

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