Dmytro is the founder of Solvid and Pridicto. Featured in Hackernoon, TechRadar and Entreprepreneur.
In the healthcare landscape, providers and lawmakers alike are faced with the challenge of making the best possible decisions for patients and the industry as a whole. From choosing the best treatments to using resources in a responsible manner, medical leaders are making decisions on a daily basis that can significantly impact health outcomes and costs.
With so many decisions to make and plenty of information to consider, it’s no surprise that big data and analytical tools are continually playing a more significant role in decision making within the field of healthcare.
As we can see from the chart above, the role of big data within healthcare is only set to increase over the course of the coming years, with significant advancements set to be made in the field of clinical analytics.
Researchers, providers and policymakers alike are turning to big data analytics models to help improve the delivery of care, the allocation of resources, and preventative health measures.
As the industry continues to seek out ways to innovate and refine the quality of tools at its disposal, data-driven decisions could soon become an industry standard. This, in turn, is likely to lead to more proactive and successful healthcare operations.
With this in mind, let’s explore some of the key ways in which big data, and its incorporation into AI, can help to drive transformative improvements in the field of healthcare - and especially for private healthcare practices in the coming years:
Big data offers a robust system of information that enables service providers to offer a high-quality of customer service that can take place in real-time. Whether you’re acting as a hospital or an insurer, having a better level of data-centric tools enables customer-facing representatives to focus their service.
This, in turn, allows services to become more informed, analytically driven and - most importantly - accurate. If a healthcare provider has access to a database that contains all the correct medical information, they can simply look up the answers to the patient’s queries. If they don’t have the answers to hand, they should be equipped with the right resources to swiftly pass on the information to more qualified representatives.
This development will be particularly effective for private health insurance providers, who will be looking to optimise their level of customer experience to stand out from competitors while continuing to deliver an accurate service in an industry that has no room for error.
(Graph showing global healthcare big data analytics services market. Image: Statista)
When appropriately utilised, big data allows healthcare companies to access the information needed to streamline customer service processes and personalise their healthcare to create the best practices for working with both consumers and patients. Customers will be able to receive a more thorough and personalised experience which will see them better catered and cared for.
Big data, and the analytical platforms that encapsulate it, may sound like an expensive piece of technology to accommodate for practices, but it will play a significant role in lowering the costs of healthcare in the long-run.
For instance, we can look at the performance of the six-hospital system in the US, Memorial Care. Through the tracking and collection of physician performance analytics, the organisation successfully lowered the average cost per patient by $280 - a figure that leads to annual savings of $13.8 million.
High percentages of healthcare costs come from thousands of accidental patient deaths per year - resulting in billions of dollars of expenses. This issue stems from clinicians who have been overwhelmed by the staggering amount of patient data that needs analyses for the correct applications of drug therapies.
By utilising big data and cloud analytics to better manage medications, clinicians can effectively and methodically analyse adverse side effects for patients, interactions and counter-indications. This can, in turn, help to cut down on patient admissions, hospitalisations and cases of patient death.
The adoption of big data in healthcare can significantly boost patient privacy and alleviate security concerns. The key reason behind this is because their information is stored in data centres with varying levels of security.
Data arriving from a wider range of places can bring a higher level of risk. However, a cloud-based big data solution can add a heavy layer of security for HIPAA compliance that’s unique to the healthcare industry. It also makes for a cost-effective solution that can benefit the bottom line and quality service for many private healthcare endeavours.
Many companies look to build a hybrid approach when it comes to data storage and flexibility. However, it’s worth noting that all systems are required to share data and cooperate with other segments of a company.
Without sufficient control, fraudulent behaviour could infiltrate the system and bring significant losses for the company. When it comes to the protection of big data, perimeter-based security is a comprehensive solution that ensures that information remains accessible without the risk of it being incorrectly manipulated.
Healthcare today needs technology to make information easier to access, more private, and more straightforward to innovate on. Big data is an essential facet for overcoming the many existing challenges in global healthcare, such as the management of tight budgets and the heavy workloads of medical professionals.
Big data can not only help to free up staff but also to improve the quality of services they provide. When big data allows doctors to have all the information they need in a single place, it’s possible to achieve great levels of personalisation while bringing tailor suited treatments in a significantly faster manner.
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