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Data Management Challenges for Healthcare: How to Manage Patient Data
Written by: Micah Horner, Product Marketing Manager, TimeXtender - November 5, 2021
The healthcare industry is massive and critically important. In the United States, healthcare costs make up more than 17% of GDP.
The data healthcare organizations generate, collect, and manage is also massive, having an ever-growing impact on the industry. RBC Capital Markets estimates that approximately 30% of the world’s data volume is being generated by the healthcare industry. By 2025, the compound annual growth rate of data for healthcare will reach 36%. That’s 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media & entertainment.
With such a large amount of data being generated by healthcare providers, it's no surprise that data management challenges are becoming increasingly difficult to manage.
In this post, we will discuss 5 of the most common data management challenges for healthcare organizations and how they can overcome each.
Data Management Challenge #1: How do you maintain security and compliance with HIPAA?
HIPAA stands for the Health Insurance Portability and Accountability Act, which was enacted in 1996. HIPAA set data protection standards for healthcare data, ensuring that data is accessible to those who are authorized to see it while also keeping data secure from hackers or other unauthorized individuals.
In 2020 alone, healthcare data breaches totaled 599, up 55.1% from 2019, according to a new report from cloud security company Bitglass. These breaches affected more than 26 million people. These data breaches can be financially devastating for healthcare providers and can cause significant damage to a person’s reputation.
As mentioned earlier, data generation for healthcare organizations is massive. Managing all of this data can be difficult—and with HIPAA compliance being so important, the stakes are high if something goes wrong.
How to Overcome This Challenge:
A data management platform that includes data security, data lineage, and data quality monitoring features can help healthcare organizations maintain data privacy, protection, and security.
With TimeXtender, healthcare organizations can proactively manage data access, monitor data activity across the entire data environment, and stop sensitive data from falling into the wrong hands.
TimeXtender provides automated data project documentation, data lineage, and data quality alerts so you know exactly who has access to your data every second of every day.
With TimeXtender, you can create users, determine access rights, and enable object- and row-level permissions to ensure data security and quality. By only giving users access to what they need to do their jobs well, you can be sure that your healthcare records remain secure.
Data Management Challenge #2: How do you maintain data quality?
Data quality is vital in data management. After all, what good is data if it's not accurate data?
The data collected and used by healthcare organizations helps data scientists create data models that can predict future patient outcomes. This data is then used to help healthcare providers create better treatment protocols and it even helps pharmaceutical companies develop new treatments for patients.
With data quality being so important, healthcare data management teams need to be sure they are collecting data that is accurate, which can be difficult with data being spread across so many different data sources.
How to Overcome This Challenge:
To better manage data quality, healthcare organizations must have complete data lineage. Data lineage is the data management challenge that involves data owners being able to trace data lineage back to its source data, then identify data accuracy and quality issues.
TimeXtender's data lineage and data impact analysis features provide data owners with a full audit trail of data changes, allowing them to quickly detect data anomalies and respond accordingly.
In addition, data quality alerts let data managers know if data is inaccurate or incomplete so they can take action to correct it before making reports, storing for backup purposes, etc.
Our metadata-driven approach provides a fast, scalable structure for organizing data projects with "read-only" access; TimeXtender never has access to your actual data which eliminates many security concerns.
All features are available within the product itself to support easy integration, without requiring extensive customization or a patchwork of third-party tools.
Data Management Challenge #3: How do you ensure data availability?
In modern healthcare organizations, it is becoming increasingly important to be able to make data-driven decisions quickly. However, to make data-driven decisions, you need high-quality data that's easy to access and understand.
If data is hard to access and understand, data scientists won't be able to use data effectively, and healthcare providers won't be able to provide patients with the best care possible.
How to Overcome This Challenge:
The need for easy, fast access to data is why data warehouses are so important. A data warehouse is a data management strategy that collects data from other data sources, cleans it up, and stores it in one central location to be used for analytics and reporting purposes.
There are several benefits to using data warehouses:
- Data warehouses are able to handle data from multiple sources, making it easier to consolidate data across different data silos.
- Data warehouses allow for more robust data analysis due to data structured in a specific way.
- They offer data governance and data management, which ensures data quality while also improving data security.
- Data warehouses remove data redundancies, making the data more streamlined for analysis purposes. This leads to faster analytical processing speeds.
However, data warehouses can be complex and time-consuming to set up and manage without the right data management software. Fortunately, TimeXtender's drag-and-drop interface allows you to build a data warehouse 10x faster than standard methods.
Once your data is integrated, cleansed, and prepared for analysis by TimeXtender, you can deliver a subset of data to individual users, teams, and departments using semantic models. This allows for fast creation and flexible modification of dashboards and reports.
Having all of your data stored in a single format and location also lays the foundation for any type of advanced analytics, such as AI and Machine Learning.
Data Management Challenge #4: How do you find enough qualified staff who know how to use these complex systems?
The data management skills shortage is one of the most pressing data management challenges in healthcare today. Data management has evolved into a complex profession that requires many years of hands-on experience to master its tools and processes. Healthcare data is growing by the day, and there are not enough data professionals to cope with the increase.
Few data professionals have the data management skills necessary to take data architecture strategies from concept to completion, whether it's creating data warehouses or data lakes.
The data also needs to be cleansed, prepared for analysis, and transformed into a format that is compatible with the data warehouse platform — a process that can take several months.
For healthcare organizations that don't have a large IT team or a data scientist on staff to prepare data, the data management process can be extremely challenging.
How to Overcome This Challenge:
As healthcare organizations are expected to embrace data analytics, many are seeking new tools that give data scientists the data they need quickly and easily, removing the need for a large team of data engineers who are experts in data cleansing and preparation.
Your data management system should be smart enough to do much of the data preparation for you so that data scientists and data engineers can focus on higher-impact activities like analysis, rather than data preparation.
Fortunately, TimeXtender's drag-and-drop Data Estate Builder makes data integration, cleansing, and preparation extremely fast and easy. TimeXtender provides automated data preparation and data quality capabilities that make it easy for any healthcare professional to join the data science revolution, regardless of technical expertise.
Built on automated, low-code/no-code technology, TimeXtender connects to 250+ data sources, performs data transformations automatically, and instantly integrates data into your data warehouse.
Once data is integrated, healthcare professionals can use semantic data modeling to quickly create data reports and dashboards while ensuring data quality, data governance, and data security.
This allows healthcare professionals to quickly access the data they need without having to rely on a large team of data scientists or data engineers, accelerating data journeys and making data-driven healthcare a reality.
Data Management Challenge #5: How do I decide which healthcare data management tool to use?
The data management market is full of tools that promise to meet the data challenges of the healthcare industry. However, few of these data tools give healthcare data professionals the capabilities they need to succeed.
Even worse, the vast majority of data management "platforms" on the market are actually just a patchwork of slow, complex, manual tools that data professionals have to cobble together.
Many data management platforms claim to be simple, automated, low-code/no-code solutions for data integration and preparation. However, when you look a little further under the hood, you'll find that the "low-code/no-code" elements are extremely limited, and data professionals are still stuck manually coding most data integration processes.
The healthcare data management industry is in desperate need of a solution that makes data integration and data preparation quick and easy. The tools that data professionals need to succeed are out there, but healthcare data teams must do their homework before choosing a data management tool.
Data management tools should provide healthcare organizations with options for both cloud-based and on-premises deployments, giving them the flexibility they need to build data architectures that fit their unique data requirements.
They should also provide a data modeling tool, data integration capabilities, data cleansing and preparation, data governance and security capabilities, and the scalability to grow as a healthcare organization grows.
How to Overcome This Challenge:
Fortunately, there are data tools out there that provide automated data integration and data preparation, reducing the learning curve for healthcare data management professionals, speeding up data journeys, all while giving data scientists access to more data in less time.
TimeXtender's Data Estate Builder is designed to meet all of your healthcare data challenges. TimeXtender is a low-code data management solution that's simple, easy to use, and affordable for data managers of any size.
Not only can you choose between cloud-based or on-premises deployments, but TimeXtender provides your healthcare organization with automated data integration, data cleansing, and data preparation capabilities, and allows you to deploy data warehouses, data lakes, and data marts, all in a single data platform.
Once data is integrated, healthcare data professionals can use semantic modeling to quickly create data reports and dashboards, all while ensuring data quality and security.
With TimeXtender, you no longer have to wait days or weeks for data to be ready for analysis, allowing you to drive higher value from your healthcare data.
Additionally, TimeXtender's data governance and data lineage features allow you to monitor your data at every step, ensuring compliance with HIPAA regulations and other patient privacy regulations.
With a single data management platform powering all of your data needs, you can reduce data silos, increase data accessibility, and dramatically speed up your healthcare data journey.
Learn More About TimeXtender
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Visit the TimeXtender product page to learn how we are helping clients build reliable, modern Data Estates 10x faster than standard methods.