Insider Intelligence indicates the global healthcare market to reach $665 billion, while the national healthcare expenditure presented $4.1 trillion in 2021. It drives two distinct opinions. First, there will be an increasing use of healthcare software services because the industry is driven by digitalization and innovation. Second, digitization brings a growing volume of data that needs to be stored, processed, and managed, boosting demand for healthcare data storage.
It is safe to say that the success of digitalization within the healthcare industry, in general, and mHealth, in particular, depends on the proper selection of data storage and management options, along with learning from previous best practices. Further, let’s explore these options and suggest the benefits and challenges of healthcare data storage solutions.
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Table of Contents
What Constitutes Healthcare Data?
Simply put, data is every type of information that one can translate into a particular form making processing more efficient. In such a case, healthcare data is every bit of information generated by patients, healthcare providers, physicians, and administrators. The key is translating this information into accurate data and actionable insights. Considering the size of the current healthcare IT market, a vast amount of data is waiting for data analysis.
In contrast to other industries, health data directly relates to health conditions and is represented by Protected Health Information (PHI). Common data sources in healthcare cover:
- Electronic Health Record (EHR). This dataset includes all information on the patient’s health status and medical history. Developing a good platform means practitioners have access to a patient’s full history.
- Claims Data. These are billing and payment codes, including insurance claims, submitted to companies. Administrative data like this is vital for resource allocation.
- Health Surveys. Public health is assessed using this source. It shows health statistics on a grand scale and helps help healthcare leaders design a better health policy.
- Clinical Data. Obtained from clinical studies and laboratory tests during drug development. This helps in the discovery of new treatment options and medications.
- Medical Imaging. PACS systems store medical data like CTs and MRIs. Advanced medical imaging is crucial for modern clinical decision-making.
- Patient register. A relevant data source covers secondary information on clinical outcomes within a patient’s medical history.
Healthcare Data Storage and Management Benefits
The growth of markets linked to data storage stems from the outstanding potential of healthcare technologies. Let’s explore some notable advantages.
Better Data Growth
With the potential of big data, better practices offer a seamless way to handle electronic data. Also, with the healthcare industry undergoing digital transformation, you must expect irreversible data growth. Data storage and management help prepare for such development.
Greater Access Control
To handle data correctly, healthcare organizations need information at their fingertips. Proper storage ensures clinical data is available when most needed for treatment plans. It all leads to the emergence of more excellent value.
Enforcing Compliance
Any software working with PHIs must follow the Health Insurance Portability and Accountability Act (HIPAA). For instance, if you want to develop a telemedicine platform, you must cover all aspects of the HIPAA checklist. Proper solutions ensure privacy and security by preventing unauthorized access and providing proper data authorization.
Bringing Innovation
Healthcare data storage methods drive innovation. They ensure a healthcare provider has all the up-to-date data analytics and processing capabilities. It boosts R&D within healthcare segments and helps adopt innovation seamlessly.
Well-Organized Healthcare
A properly functioning healthcare organization is one with a particular degree of coordination involved. Thus, knowing how to manage data sources in healthcare grants better access and sharing of health records and PHIs regardless of the vendor’s location. Such transfer improves internal coordination.
Enhanced Analytics
Digitalization brings tools like predictive analytics used for disease prediction in healthcare. Analytics involves various methods, from descriptive analytics to prescriptive analytics, to gain insight into care patterns. Data analytics for precision medicine is the next evolutionary step.
To illustrate, AI and ML within innovative healthcare applications can analyze millions of patient records and correlate the insights to health trends for better diagnosing. In addition, healthcare big data analytics can be the next evolutionary step in healthcare data storage solutions.
Improved Patient Service
Healthcare providers can develop tools for handling appointments and scheduling with properly adopted data storage and management solutions. It takes patient experience to a whole new level. Properly adopted solutions take patient outcomes to a whole new level by supporting personalized healthcare and evidence-based treatment decisions. However, for innovative tools like mHealth technologies to bring value, it is essential to address some pressing challenges.
Data Storage Challenges in Healthcare
With the healthcare sector storage market projected to grow to $6.12 billion by 2027, there is a need to address key current concerns. Aspects like security, quality of infrastructure, maintenance, and scalability are the ones to consider.
Security and Data Privacy
The healthcare industry is a top target for breaches. The adoption of high-quality cybersecurity and information security is paramount.
This report indicates that about 45 million medical images and other PHIs were recently exposed in countries like France, the United Kingdom, and the United States.Using top-grade encryption and the Insurance Portability and Accountability Act standards should always come along with data security measures to protect data. No one should share sensitive information or sensitive data over publicly accessible or insecure websites.
Infrastructure
Digitization brings high demands for data storage and management. Healthcare systems generate unstructured data (like clinical notes) and comprehensive healthcare data that require massive electronic medical records infrastructure. Thus, the growing volumes of data can only be managed with a large and sophisticated infrastructure intact. Often, such infrastructure types depend on costly on-premise hardware unless some more cost-effective options are found.
Maintenance
Having an on-premise healthcare data storage solution up and running is a costly endeavor. More specifically, it entails investment and operational costs. In short, on-premise solutions often result in expenditures for regular maintenance, data quality and accuracy checks, and disaster recovery packages. Besides, companies often pay experts to troubleshoot any risks and issues with the infrastructure that might happen. Thus, to effectively store and manage data sources in healthcare, you need to take care of data security and infrastructure size. Also, you must have a budget dedicated to covering maintenance costs.
Healthcare Data Storage Options
Here are some critical options for storing and managing healthcare information.
Cloud Storage
Migrating to the cloud is a trend many healthcare organizations use. It provides faster backup and easier data privacy management.
In general, cloud-based data storage is all about saving costs because you do not need any on-premise hardware, and it also provides the following aspects:
- Faster data backup
- Top-grade security
- Expansion options
- Automated back-end
- Easier compliance
The cloud-based tool is an excellent substitute for on-premise solutions. However, the success of your chosen option also depends on whether you use a public or hybrid cloud.
Public Cloud
Many companies consider the public cloud as a primary cloud computing solution. Tools like Microsoft Azure and Google Cloud Platform offer a public harbor for any data. This sub-option entails a low-cost, pay-per-use payment model, data access expansion, and accessible scalability elements. In turn, the public cloud entails more significant data sharing and privacy concerns and has downtime risks.
Hybrid Cloud
A hybrid cloud option is the one balancing between the public cloud and on-premise data storage. It means you have part of your infrastructure stored on-premise, the other part stored in the cloud, and everything managed by a third-party provider. The hybrid cloud allows you to streamline clinical workflows while keeping sensitive information local.
The upside of such a healthcare data storage solution is the on-premise type of security, disaster recovery package, and cloud-based scalability. As to the downsides, the option is complicated in terms of implementation and is not portable.
On-Premise Storage
On-premise data storage and management options essentially mean all hospital data is stored within the organization. Usually, it entails having a dedicated data center. To illustrate, you will need to store data if you consider developing a telemedicine application or a telehealth solution. These solutions often work with patient data. Thus, on-premise healthcare data storage offers the best privacy and security possible.
Moreover, with an on-premise option, you get total control over data. In contrast, this method entails high capital and operating costs and has significant scaling challenges. Luckily, you can always couple an on-premise server with a cloud by having a hybrid or private cloud. On-premise data storage option costs the most, while it offers the best security in return if the human factor is eliminated.
Secondary Healthcare Data Storage Solutions
While on-premise, cloud, or something in between are the primary data storage and management options, some less-known choices are also available. These are the following:
- Storage area networks (SAN). SAN is a network of storage devices with multilateral access to various servers. It often uses fiber channels to transfer medical data quickly — an excellent data management option for PACS.
- Network-attached storage (NAS). NAS is a single storage device granting data access to a particular network. It connects healthcare professionals to data like patient files via a local network.
- External storage. Data can always be stored on hard drives, SSDs, and even tapes. This option is handy, yet it lacks security and durability.
- Outsourced storage. Many healthcare providers outsource their IT infrastructure needs. This report indicates that almost 93% of healthcare organizations use this option. While it takes the issue of data storage and management off your hands thoroughly, this solution costs a lot.
Choosing the right option is about balancing cost, security, and scalability. For instance, the on-premise option is secure yet costly. The public cloud option is cheap yet least secure.
Healthcare Data Management Best Practices
As we covered the key options for healthcare data storage solutions, it is time to proceed to the best practices. Effectively, it all boils down to aspects like governance, quality, automation, and interoperability.
Data Governance and Visualization
Proper data storage and management originate from developing a correct data governance strategy. Governance includes the people and processes linked to health information. Using data visualization helps staff track performance indicators. To ensure data governance:
- Categorize your system to protect data between patients
- Track unauthorized access to electronic health record files
- Update data storage regularly
Data Quality
Inadvertently, healthcare records will have errors. The data quality depends on how well you manage them. In such a case, a healthcare data storage solution is delivered through data standardization, removal of data clones, flagging mistakes, and matching information from different sources. Keep your data clean and organized.
Automation and Natural Language Processing (NLP)
Healthcare data sources can massively benefit from automation. Healthcare providers save billions by automating administrative data tasks. Using natural language processing allows healthcare systems to extract meaning from unstructured data, helping doctors make treatment decisions without manual entry. You can automate everything from billing to customer services.
Interoperability
Healthcare data process solutions need effective means for exchanging, using, and interpreting medical information. Interoperability ensures data sharing is seamless. This allows a data-driven approach to support population health and improve care delivery. By using real-world data, clinics can achieve quality improvement and better patient safety.
Final Thoughts
The quality of healthcare data storage depends on the balance between cost and security. It can be either on-premise or cloud-based. Also, you can balance between the two and have the best from both approaches. But it would help if you always kept cost, security, and infrastructure in mind, regardless of the method. An effective healthcare data storage solution must be built on a proper foundation.
After choosing the option, it is time to think about governance, data quality, automation, and interoperability. Whether you use big data analytics or simple claims data storage, the goal is to improve the side of healthcare that touches patients. Ensure you have the right decision support and treatment strategies to harness the best healthcare research and clinical data.
Are you finding the complexity of modern medical imaging and electronic data a barrier to innovation? Contact our experts to build a scalable, secure infrastructure that unlocks the potential of big data for your health system!
What is the role of Big Data Analytics in the healthcare sector?
Big data analytics in the healthcare sector allows organizations to process vast amounts of information to identify care patterns and improve patient safety. By analyzing a comprehensive healthcare dataset, healthcare professionals can gain insight into which treatment strategies are most effective for specific demographics. This data-driven approach supports clinical decision-making and allows for the discovery of new treatment plans that were previously hidden in unstructured data.
How do healthcare systems ensure the privacy and security of patient records?
Healthcare systems ensure privacy and security by adhering to the Health Insurance Portability and Accountability Act guidelines. This involves implementing robust information security measures, such as 256-bit encryption and multi-factor authentication, to protect data from unauthorized access. Furthermore, healthcare organizations use secure websites and internal protocols to ensure that only authorized practitioners have access to sensitive information, thereby maintaining data privacy and patient records integrity.
What is the difference between descriptive and prescriptive analytics in medicine?
Descriptive analytics focuses on summarizing real-world data and health statistics from the past to understand what happened. In contrast, prescriptive analytics uses data analysis and predictive analytics to suggest specific treatment decisions or actions for the future. While the former provides a systematic review of past performance indicators, the latter acts as a decision support tool to help healthcare providers choose the best care delivery paths.
Why is interoperability important for modern healthcare providers?
Interoperability is crucial for healthcare providers because it enables the seamless data sharing of medical data across different healthcare systems. When patient records can move securely data between patients and different healthcare organizations, it reduces the need for redundant laboratory tests and ensures that treatment plans are based on the most accurate data. This coordination is vital for quality improvement and helps support population health initiatives on a national healthcare level.
How does natural language processing assist in healthcare research?
Natural language processing (NLP) assists in healthcare research by allowing machines to read and interpret unstructured data, such as handwritten notes in an electronic health record. This technology enables healthcare professionals to extract valuable clinical data from vast amounts of text-based medical imaging reports and clinical studies. By automating this data analysis, researchers can quickly gain insight into disease prediction and develop more effective personalized healthcare strategies based on evidence-based findings.
What are the main sources of data collected for health policy development?
The primary data collected for health policy development includes health surveys, claims data, and health statistics from national healthcare databases. These data sources provide a broad overview of the health status of a population, allowing officials to make informed resource allocation decisions. By analyzing administrative data alongside real-world data, policymakers can create treatment plans and healthcare services that address the most pressing needs of the healthcare industry.
How does data analytics for precision medicine improve quality of life?
Data analytics for precision medicine improves quality of life by allowing for the creation of treatment plans tailored to an individual’s genetic makeup and health status. By using big data analytics to analyze a patient’s unique medical data, doctors can make more accurate treatment decisions and avoid the “trial and error” approach. This methodology ensures that care delivery is optimized for each patient, leading to better patient outcomes and enhanced patient safety.
What are the challenges of managing claims data and insurance claims?
Managing claims data and insurance claims is challenging because it involves processing vast amounts of sensitive data that must remain secure under health insurance portability and accountability laws. Healthcare organizations must ensure data quality and accuracy to avoid billing errors while navigating complex clinical workflows. Furthermore, as claims data is a primary source of administrative data, any unauthorized access could lead to severe security concerns and financial loss for both the patient and the healthcare market.
