The world is becoming increasingly digital and data-driven, and healthcare processes are no exception. Keeping up with healthcare storage needs in this age of Big Data is complex but fundamental to delivering service and excellent user experience.
RBC Capital Market reckoned that by 2025, the compound annual growth rate of data for healthcare would reach 36%. This growth rate of health data is notably faster than for many other sectors, including media and entertainment, manufacturing, or financial services. This is Big Data.
For those who need to understand What Is Big Data? Oracle has some good definitions and overviews.
Such a significant increase in data creates many data storage and retrieval challenges, each of which will impact the other. Let’s look at some in more detail.
Challenge 1: Effective data processing
Healthcare organisations interact with or at least hope to interact with healthcare data in many ways. Various data processing stages (as outlined below) are a real problem in the effective use of Big Data.
Effective Data Capture:
This is an ongoing battle for healthcare organisations because more often than not…
- Medical data is not uniform. Imaging data comes in all different formats — for example, X-Rays will store differently from MRIs. Not least, general hospital images will be of a different standard to specialist hospitals that leverage more complex technology to ascertain more intricate images.
- It isn’t easy to ensure data captured is clean, complete, accurate and formatted correctly for use in multiple systems. EHR (electronic health records) are rarely transmissible, interoperable or easily deployable. In other words there is no data standardisation in the healthcare industry.
Responsible and Efficient Data Cleaning
Unsurprisingly, poor data hygiene derails Big Data projects and threatens the effectiveness of digital transformation in healthcare. This is true particularly when aggregating disparate data sources with different formats, sources, compatibility because…
- Manual scrubbing is time-consuming (although IT vendors, like Qumulo, do offer automated scrubbing).
- That being said, healthcare organisations are massively underfunded with regard to IT, so automatic solutions are often considered too expensive, and there isn’t the workforce to do it manually.
Appropriate Data Querying
A process that is absolutely foundational to effective reporting and analytics. However, effective data querying…
- Needs robust metadata and strong stewardship protocols (more on this in Challenge 2).
- Disparate and uncommunicative data silos across internal healthcare operations and external data transfers prevent centralised and holistic querying.
- In other words, data management is not standardised, and this limits the effective use of data through querying.
Regular Data Updating
In order for data to be current and relevant, the stores require regular and efficient updating. This is because…
- Medical data can change minute-by-minute. For example, the data being accumulated from life support machines, or anesthetic records throughout an operation.
- It’s true that some updating can be automated; it’s also true some need to be carried out manually — this poses challenges to determine how to update quickly without end-user downtime.
Challenge 2: Cyber security
Cybersecurity is a test for every industry, healthcare arguably more than most given the extremely personal nature of the information. Organisations must be constantly vigilant against cyber threats. User authentication, endpoint leakage, and excessive user permissions are the three most common vulnerabilities in healthcare. Taking measures to strengthen these areas is essential to data security. The focus should be on three areas:
The critical storage questions in healthcare are whether you:
- Stay with on-premises storage?
- Go to the cloud?
- Support both?
While many health organisations are more comfortable with on-premises data storage, they struggle to maintain control over security, access, and availability. On-site storage can be challenging to maintain, expensive to scale, and likely to encourage the data silos we referred to earlier.
The cloud offers many benefits. For example, agile disaster recovery, lower up-front costs, and near-infinite expansion. However, organisations must be careful about choosing partners that understand healthcare-specific healthcare compliance and cloud security issues.
… and that’s exactly what we offer – Learn more with our experts today!
Security expertise and tools
Data security has to be the number one priority for healthcare organisations, especially in the wake of high-profile breaches, hackings, and ransomware demands. Healthcare organisations need to safeguard data and ensure compliance using enterprise-class data protection and security.
They need to:
- Provide secure access to patient care information, such as EMR/EHR, imaging, from any location.
- Maintain privacy and compliance controls.
- Automatically protects data from external threats
- Integrate with corporate IT security systems
- Tracking usage by internal users.
Data stewardship ensures health information is put to practical and beneficial uses and that misuse is prevented. Health data stewardship has taken on greater urgency due to:
- The increase in the availability of electronic health data.
- A growing appreciation of its value in improving health care and population health.
- Awareness of the potential risks associated with incorrect or inappropriate use.
Most healthcare records are kept for eight years in the UK, so ongoing data stewardship is a significant concern. Understanding when data was created, by whom, and why is vital to ensuring data is fit-for-purpose and reusable for researchers and data analysts.
Challenge 3: Positive patient experiences
Data on its own is worthless unless it affects outcomes and improves user experience. Organisations may feel a need to keep up with the latest, most innovative healthcare tech trends, but unless they actually improve the patient experience, there isn’t much point to the investment. Let’s look at how well data can be used practically for better patient outcomes.
First, organisations need to ensure that when presenting data, that it is accessible to its target audience and will ensure an accurate and reliable downstream impact on the end-user. This is because…
- Poor data at the outset creates bad reports
- … So, data must be reported in a way that facilitates clinical decision making
- If reports are not accurate, reliable or accessible, patient outcomes will be affected by this lack of technical interoperability.
This is vital as it allows the clinician to absorb information and use it easily. For example, providing GPs with highly technical MRI scan data with no context and in a granular way, will not ensure the professional can see what they need to see at the right moment. In fact it could negatively impact the care and understanding the patient receives.
- Good data visualisation/presentation practices offer a more precise picture that promotes patient-record understanding.
- It is essential that the user identifies what’s relevant and can accelerate the clinical process.
With more and more patients visiting a variety of organisations for different issues or specialisms distributed access, external data sharing has become evermore essential.
- Repeating the same information to many healthcare professionals is tiring for the patient, especially when data could be shared by avoiding silos.
- System and storage design and implementation differences can impair clinician decision making, patient follow up, care strategies, and outcomes.
- Health, unlike medical specialisms, cannot be stratified into neat groups. Going to the GP for migraines cannot and should not be treated in isolation, for example, if the transmission of pharmacy data to the GP has faltered, it could be missed that the patient is on the combined contraceptive pill. These two pieces of information considered in conjunction raise concern for the patient’s overall wellbeing, and that diagnosis relies heavily on the safe and secure transmission of patient data.
The healthcare data tsunami
Healthcare providers rely on high velocity, complex, and variable data – “Big” by any definition. Providers need rapid, reliable access to data across numerous systems and devices. Combined with the need for data to be retained much longer — or forever — this presents huge challenges relating to storage, archive and backup.
Managing this data tsunami is becoming increasingly difficult (or impossible) with legacy solutions. Patient care is in danger of being compromised by costly and complicated storage systems that were not designed to handle modern healthcare workflows.
Healthcare organisations require a scalable, reliable, and modern hybrid data management solution with a simple path to the cloud (or hybrid). Many of the world’s largest and respected healthcare organisations have adopted a data storage platform to consolidate their storage and data needs.
Cloud-native and hybrid architectures such as provided by our partner Qumulo achieve:
- Unified data accessibility to streamline workflows and enhanced quality of care.
- On demand, scalable storage across on-premises and cloud.
- Built-in data protection and security to safeguard patient and clinical data.