How is big data used in healthcare
Healthcare is a critical area of our lives that is being digitally transformed. The amount of information that healthcare organizations can now collect, manage, and analyse is increasing exponentially with the technological improvements in medical technology and with the move to EHR (electronic health records).
Big data refers to information that is too large and complex to manage with traditional information storage systems. In the health field, huge amounts of data can be captured through patient medical records, hospital records, medical tests and personal health monitoring devices such as smartwatches.
Using big data analytics in healthcare allows medical professionals to make better decisions about patient care and resource allocation. Big data can provide insights on how and when serious illness emerges, allowing doctors to provide treatment at an earlier stage, improving outcomes and reducing costs.
What are examples or applications of big data in the healthcare industry?
Big data analytic tools are being used to help promote health and assist in medical intervention and management. Insights from big data analytics can improve patient experience, increase efficiency, reduce costs and enhance quality of care.
Healthcare administrators can use big data to support planning and resource provision. “Health maps” created from health records and Google maps have helped to identify underserved areas. Another initiative Google has been working on in collaboration with Mayo Clinic is the construction of its Healthcare Data Engine. This cloud-based tool will allow healthcare organizations to combine and standardize data from a variety of sources including, medical records, insurance claims and medical research.
In an earlier post, we described Alteryx, a software tool that allows healthcare service providers a way to prepare, synthesize and analyse patient and operation data in-house. This is just one example of how data analytics can be used to drive improvements in service delivery and improve patient experience.
Insights mined from Big Data can be used by public health administrators, hospital and clinic managers, researchers, insurance companies, individuals and so on. Some real-life applications of big data in the health field include:
- Disease research and disease prediction by identifying individual and community trends
- Faster product development
- Improved testing and tracking of health outcomes
Public Health Initiatives
- Healthcare strategic planning – mapping chronic disease, demographic and geographic data to identify problem areas and gaps.
- Identifying public health risks earlier and more accurately than traditional tracking and reporting
- Hospital administrative process automation – reducing routine workloads
- Medical resource allocation – managing staffing and operations by forecasting patient admission trends
Digitalizing Healthcare Records
- Streamlined patient data-sharing – and centralization of individual health data
- Ability to mine digital health data from a variety of sources including tests, scans, doctor reports, patient feedback and wearables
Personalized Patient Care
- Early illness detection
- Prevention of unnecessary doctor’s visits
- Personalized patient healthcare experiences
- Empowering patients through access to medical records
- Encouraging tele-medicine
- Detecting fraud
- Personalizing coverage
- Predictive analytics of health trends
What are the challenges of using big data in healthcare
The critical challenges of using big data in healthcare can be summarized as the kinds of data being collected, how it is being compiled, and who is using it. During the early days of Covid-19, it was hoped that big data analytics could help in fighting the virus. But this did not happen. The big technology companies provided public health researchers with access to their datasets. But it was clear early on, that the priorities of organizations such as Facebook or the location app developers diverged from those of public health professionals impacting the kinds of data collected and its usefulness in tracking transmission trends or correlate risk factors.
The use of big data in healthcare is still new. The amount of data being generated is vast and healthcare providers are still adapting and learning. Many healthcare organizations still lack the systems, databases, and skilled calibres to manage them. There are serious concerns about the ways in which some health data is being gathered and its potential uses. For instance, a recent study found that 9 out of 10 mobile health apps on Google Play were harvesting sensitive data about users’ health without adequate protection for individual privacy.
What is the future of big data in healthcare
The application of big data and analytics is revolutionizing healthcare. We are only just scratching the surface of the new world of applications and tools that will redefine how individuals manage and control their own health, and how health care providers structure and deliver services. Big Data and data modelling helps improve medical outcomes by eliminating bias in algorithms.
Some of the things we will begin to see more of in the coming days:
Improving patient tracking
Remote Patient Monitoring (RPM) solutions are already allowing improved patient care. There are various digital devices that allow the monitoring and capture of data from patients including continuous glucose monitors for diabetics, and digital blood pressure monitors that allow patients to send their doctors blood pressure and oxygen level readings remotely. RPM data can be used to improve home care, reduce clinic visits and hospital admissions. As these devices become more widely available, there is the opportunity to use the data compiled for research and development.
Empowering individuals to manage their own health
Big data and analytics will create more opportunities for individuals to manage their own health outcomes. For instance, wearables are already enabling individuals to track their calorie intake and monitor their heart rates. In the future, the ability of individual digital devices to collect data will improve – creating the opportunity for individuals to monitor their own health more closely. In the future, we’ll also be able to access our entire medical history more easily.
More accurate diagnoses and better treatment
Big data analytics can help in earlier disease identification. Earlier detection and diagnosis are critically important in providing better treatment options. Predictive analytics, data mining and analysis play an increasingly important role in symptom identification and tracking of treatment efficacy.
Data analytics will also contribute to medical and pharmacological research. Big data will enable deep drilling into enormous data sets – for example, genome analysis and pharmacological responses.
Big data will be very useful in identifying data “inconsistencies” caused by human input errors or faulty equipment. It will also allow healthcare organizations to detect and prevent fraud.
Improved resource planning and management in healthcare facilities
Big data will allow clinics and hospitals to identify trends in visits and admissions, which will improve staff scheduling and supply management on a daily, seasonal, or annual basis. This will help to manage costs, reduce waiting times and enhance quality of care.
You don’t have to wait for the future to start benefiting from big data analytics. Pangaea X can link you up with the top freelancers in the field to help you start extracting insights from your healthcare data.