Manage Unstructured Healthcare Data with Astera ReportMiner

Healthcare data is growing in velocity, volume, and variety. You need to focus on effective data management to get rich, detailed, and qualitative insights from this data. But in an industry where up to 80 percent of clinical information is unstructured, getting the right tools in place is essential to creating a smoothly functioning process that produces truly valuable intelligence.

Enter, Astera ReportMiner.

It allows you to connect to disparate data sources, standardize them, and make data available for analysis and reporting. In this blog, we will talk about how you can manage unstructured healthcare data with Astera ReportMiner to get a holistic view of your organization.

But first, let’s understand the difference between structured and unstructured data in healthcare.

Structured vs. Unstructured Healthcare Data

Structured data in healthcare is organized into specific fields as part of a schema. Every field of structured data is stored in a pre-defined format and has a defined purpose.

On the other hand, unstructured data is a collection of many varied types of data. It does not have a pre-defined data structure.

While structured data is consistent and standardized, its unstructured counterpart is unorganized and often contains irregularities. Both structured and unstructured data have valuable insights for healthcare organizations.

For instance, granular information regarding patients’ symptoms, medical history, allergies, laboratory tests, etc., will allow optimal physician scheduling to ensure the right professional is deployed to the patients.

Sources of Unstructured Healthcare Data

Patient-generated data is one of the most common types of unstructured healthcare data. Patients produce a large volume of important data such as health histories, related clinical data from external healthcare providers, and details recorded in a wellness diary.

Meanwhile, on the administrative side, you have a range of non-medical information, including bills, invoices, and receipts from patients, insurance providers, and vendors.

All this data is hard to record in a standardized way because of different formatting and structure. Even imaging test results and lab reports vary in design and layout (see below). An advanced data capture solution becomes necessary to identify and extract relevant information efficiently.

Sample Healthcare Reports

Why Unstructured Healthcare Data Matters

A gold mine of data is available to healthcare providers that could contribute to more informed decision-making. However, most of that data does not fit properly into fields on a spreadsheet and is thus hard to analyze in a consistent manner.

Therefore, modern healthcare organizations must leverage technology to process unstructured data to make it actionable and accessible.

Understanding the large volume of unstructured data is crucial for healthcare providers. The right use of data extraction technology in healthcare can drive valuable results for medical providers.

Here’s why unstructured healthcare data matters:

1. Key to Comprehensive Care

Unstructured data, residing in electronic health records and other systems, contains important contextual information that can be key to improving treatment outcomes for a patient — like a medical provider’s notes or reports containing details on an individual’s previous surgeries could help diagnose a current issue.

For instance, a physician can go over previous medical provider’s notes to make a quicker diagnosis. Similarly, data on the social determinants of health can give invaluable insight into underlying symptoms to help medical practitioners provide patients with the best quality medical care.

2. Accurate and Updated Records

Healthcare administrators are overburdened with numerous tasks, including billing, customer service, scheduling shifts, and overseeing the financial and operational efficiency of the organization.

Capturing and converting unstructured healthcare data into meaningful information allows them to carry out these functions effectively. It enables them to report accurate information consistently and ensure compliance.

The current pandemic highlighted the importance of having accurate and timely records. Hospitals had to ensure they have the capacity, staff, and medical supplies needed to respond to COVID-19.

Moreover, they must respond to a rapidly changing environment. Critical decisions are made within hours. Having accurate and updated records played a crucial role in responding to the evolving crisis.

3. Enable Automation

Effective data management plays a pivotal role in optimizing the allocation of hospital workforces and contributes to a higher quality of patient care. The influx of data from different data sources makes automation necessary for healthcare data analytics.

A robust health data-driven system supported by automation allows hospitals to become more proactive. For instance, they can perform predictive analytics to forecast clinical and financial requirements.

As a result, they can identify high-risk patient groups, manage resources efficiently, and improve patient outcomes.

Unstructured Data to Insights Journey

The unstructured data-to-insights journey of every healthcare organization is different, depending on the methods and technology. Automation, of course, plays a significant role in improving the efficiency of the process.

Modern healthcare providers leverage template-based data capture solutions to extract meaningful information for healthcare data analytics.

These technologies allow users to create a data extraction logic for unstructured healthcare data available in specific file formats and then perform transformations and verification to move that data down the pipeline towards finished reports.

Templated-based data capture enables data extraction automation, allowing healthcare organizations to handle large volumes of unstructured data with high efficiency.

Healthcare Data Analytics

The purpose of healthcare data analytics is to use data-driven findings to solve complex challenges and improve performance. It can result in informed strategic planning and improve operational efficiency.

Some important types of analytics that can benefit healthcare organizations include:

• Descriptive Analytics (what happened?): Accurate records in the healthcare data warehouse allow hospitals to study different strategic and operational decisions and their implications on performance and clinical outcomes.
• Predictive analysis (what will happen?): Converting unstructured data to a structured format facilitates predictive analytics for healthcare providers. Using a data-driven approach, they can predict their key demographics and the treatment options that are more relevant to these audiences. With this analysis, they can work on maximizing resources in key areas to better satisfy patient demands.
• Prescriptive Analytics (how can we make it happen?): The availability of historical and real-time data in a structured format helps healthcare organizations make future predictions. They can compare multiple “what-if” scenarios to discover the best possible solution for patients.

How Astera ReportMiner Can Help

Astera ReportMiner is an enterprise-ready data extraction platform that offers template-based extraction. It can help your healthcare organizations capture data trapped in administrative databases and medical records with excellent efficiency.

It offers automated data extraction and a code-free environment. An intuitive, drag-and-drop interface allows users to structure, format, and enrich their raw inputs before feeding them to a destination of choice. It simplifies the unstructured data-to-insights journey, enabling healthcare providers to design and deploy end-to-end integration solutions for various use cases.

The key features of Astera ReportMiner are:

• It features advanced functionalities like auto-creation of data patterns to automate data extraction jobs.
• It enables users to design reusable templates to extract meaningful information from healthcare or other documents with similar layouts.
• It supports a wide range of unstructured data formats, including scanned PDFs, PDF forms, TXT, PRN, RTF, XLS, XLSX, and COBOL.
• It allows users to create custom data quality rules to eliminate errors and establish 100% confidence in extracted data.
• It offers connectivity to popular databases, file formats, enterprise applications, cloud solutions, and BI and analytics tools.

These advanced capabilities and features allow healthcare organizations to perform data analysis and streamline their operations for speedier, safer, and more accurate patient care.

If you are convinced of the benefits of Astera ReportMiner and want to manage your unstructured healthcare data efficiently, then contact our experts today to schedule a demo or learn more about our product.

Real-World Efficiency with Astera ReportMiner

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