The era of big data is having a big impact in healthcare — for good and, well, not so good. On one hand, the power of deep learning could bring dramatic improvements to medical knowledge and care provision. But on the other, organizations across the industry are faced with enormous challenges in maintaining, securing, and indeed using all this data.
The changes now being felt are driven by multiple factors. Digitalization and the Internet of Things — all those networked sensors and wearables — are driving an exponential climb in the amount of data being collected. On the demand side, the trend toward patient-centric care and the rise of machine learning create strong incentives to treat data as a precious resource that can unlock breakthroughs in medical treatment.
Well-managed information, pulling together data from GPs, specialists, clinics, pharmacists and insurers, can provide everything from a holistic view of individual patient health (enabling far better care and better outcomes) to early warning of epidemics, and even big advancements in medical research. The cost of failing to realize these benefits due to poor information management would be enormous.
The challenges are many.
While providers of all kinds are learning to share their data in the pursuit of those valuable rewards, the resulting data pools are far from the clean datasets one would like to see. In fact, according to a recent survey, only 20% of providers fully trust their data. Why is it such a mess?
Part of the problem is the vast range of data sources and types concerned. Data is gathered from personal and insurance records, from electronic medical records (collected during appointments with a range of care providers), sensors, and on and on. And it may come in the form of spreadsheets, databases, images or specialized formats such as the DICOM standard for X-rays and MRI scans. On top of that, the person capturing data at source will often not be experienced in the work at the other end (retrieving and working with the data), leading to inadequate processing. All of this contributes to fragmentation and siloed data pools.
Then there’s the problem of protection.
Health records are among the most sensitive of personal information — and the most attractive target for hackers. The 2019 Global Trustwave report found that a single healthcare record can trade hands on the black market for as much as $250, compared to $5.40 for the next most valuable class of record, a payment card. In 2019, a record number of US patients were victims of healthcare data breaches, with 40 million people affected. From crippling the IT systems of hospitals and healthcare providers to medical identity fraud, such attacks put patients at risk and have significant financial costs. In response, regulators have created strict requirements for the handling of patient data; from HIPAA in the US to GDPR in Europe, health data is recognized as a special category that demands extra care.
The burden of compliance may be heavier, but the consequences of failure may be heavier still. As in other industries, a data breach or bad data quality will result in losses both direct and indirect (such as the reputational damage and potential lawsuits). But in healthcare, one must also reckon with the human consequences of delayed treatments and bad research. It’s not too much to say that lives are on the line.
There’s an elegantly simple solution.
Given the number of stakeholders involved, any attempt to address the mess must prioritize interoperability and minimize disruption. And the highest security is non-negotiable. This is where Geeq Data shines.
Our data attestation and discovery tool runs as an add-on layer that can be integrated easily into existing systems. It is a blockchain-based platform, using our unique protocol to ensure industry-beating security, and supports full permissioning — which provides an entirely new aid for compliance: the ability to approve and trace permissions given to send, query, or approve transfers of data from any patient’s account. The technology is lightweight, low-cost and user-friendly. And best of all, it’s seamless, designed to work invisibly without interruptions to providers’ workflow and patient care.
In short, Geeq provides the private network that can tie all those data silos together into a data mesh, coupled with the permissioning settings to restrict access. A key advantage of Geeq is that it enables medical data use to be traced and recorded on a private blockchain ledger, so that the integrity of the data can be verified. A simple validation process and flexible metadata combine to provide data consistency and visibility across an organization, or between trusted collaborators.
With data quality and integrity assured, providers will be empowered to deliver better and more cost effectively at every level — from patient care, to staff support, to research. The difference could be profound.
Banner Art Image by Hal Gatewood on Unsplash.
