Is Automated Data Extraction the Lifesaver Healthcare Desperately Needs?
Are you paying more for less in healthcare? The United States is grappling with a severe healthcare crisis, spending soaring to an eye-watering $4.8 trillion in 2023. That is more than the economies of all but two countries. However, the country’s healthcare system ranks an abysmal 69th worldwide despite being a leader in medical innovation. The reasons for the growing cost are present in both the clinical and administrative aspects of healthcare. Technologies for automated data extraction can help streamline the latter.
The lifecycle of healthcare services involves significant administrative procedures in which data extraction takes up the most resources. The volume of medical data keeps growing every year, and managing it is vital for good patient care and compliance. In this blog, we explore the transformative potential of automated data extraction in better managing the flood of information.
Automated Data Extraction in Healthcare
Automated data extraction refers to the use of one of many technologies to collect information from various sources automatically. These sources in healthcare include electronic health records (EHR), laboratory information systems, medical billing systems, etc. The process involves using electronic data capture systems powered by sophisticated artificial intelligence (AI) technologies to identify, extract, and process data with little or no human intervention.
Manual data extraction from healthcare documents leads to a high percentage of errors, which have serious repercussions. For example, nearly 30% of medical charts are misplaced due to inefficient tagging and document archiving. Additionally, over 80% of serious medical errors happen during care transitions. Studies show that automating just over 35% of the healthcare document processes can save up to $11 billion in claims alone.
“Automating just over 35% of the healthcare document processes can save up to $11 billion in claims alone.”
Using automation technologies with electronic data capture in healthcare speeds up data processing and accessibility. It allows clinicians to retrieve patient information faster and make treatment decisions sooner. Furthermore, automation in data extraction also improves the accuracy of medical data analysis, directly resulting in better patient care and allowing clinicians to respond to emergencies faster.
Improving Data Accuracy in Health Information Management
The healthcare industry in the United States is experiencing a severe shortage of workers at every level. The COVID-19 pandemic worsened this crisis. The American Hospital Association estimates that the industry will face a shortage of 124,000 physicians and over 200,000 nurses by 2033. It also concluded that at the current rates, over 6.5 million healthcare professionals will permanently leave their positions by 2026, and only 1.9 million will replace them.
“More than 6.5 million healthcare professionals will permanently leave their positions by 2026.”
Doctors and nurses at several care facilities spend more time on paperwork than patient care. Studies have suggested that many primary care physicians spend nearly 20 minutes on paperwork every 5 minutes with a patient. As the volume of patients grows, the burden of paperwork is only bound to increase. This will directly impact the accuracy of health data entered and negatively affect health information management at hospitals and clinics. That is where automated data extraction can make a difference.
Data accuracy is paramount in healthcare. Inaccurate data can lead to incorrect diagnoses, inappropriate treatment plans, and, ultimately, harm to patients. For example, consider a situation where patient information from different sources needs to be consolidated into a single record. These sources could include EMRs from multiple clinics, laboratory systems, or even IoT-powered wearable devices.
Automated systems can extract relevant data, such as medication lists and allergy information, and integrate it accurately, ensuring that healthcare providers have up-to-date and correct information at all times.
Automating the process of electronic data capture and extraction makes up for the shortage of healthcare professionals. It reduces the burden of paperwork on physicians and nurses and lets them focus on patient care.
Regulatory Compliance Through Automated Data Extraction
The healthcare industry is one of the most heavily regulated in the United States and the rest of the world. Regulations like HIPAA (Health Insurance Portability and Accountability Act) in the US and the GDPR (General Data Protection Regulation) mandate strict data privacy requirements. Automated data extraction is vital for ensuring that medical organizations meet these requirements effectively.
In the healthcare industry, adhering to regulatory standards is crucial not just for legal adherence but also for ensuring patient safety and privacy. As healthcare providers handle sensitive patient data, they are bound by rigorous regulations.
Let’s talk a bit more about how automated extraction of data helps organizations comply with regulations:
Data Privacy and Security
Solutions for automated data extraction and electronic data capture are designed with robust security features to protect sensitive patient information. These systems use encryption, secure data storage, and access controls to ensure that data is only accessible by authorized users. Automating data extraction at healthcare facilities lowers the risk of human errors, such as accidental disclosures or data breaches.
HIPAA violations can result in fines ranging from $100 to $50,000 per violation, depending on the level of negligence. In other words, violations can sometimes lead to the closing down of medical facilities due to financial losses.
“Violations of the Health Insurance Portability and Accountability Act (HIPAA) can result in fines ranging from $100 to $50,000 per violation.”
Reporting and Audit Trails
An important aspect of ensuring compliance with regulations is the ability to produce audit trails and reports. Software for automated data extraction logs every action taken on the data, including the people who accessed it, what changes were made, and from where. This kind of tracking is invaluable during audits and investigations, providing transparency and accountability.
The best part about audit trails is that they deter potential bad actors from doing illegal activities. They also help organizations quickly identify and rectify compliance issues, minimizing the risk of fines and reputational damage.
Adapting to Changes
Healthcare regulations evolve with emerging technologies and innovations, forcing organizations to adapt to stay compliant. Tools for electronic data capture and automated data extraction are designed to be flexible. They allow for quick updates in response to changes in regulatory requirements. Healthcare organizations can have compliant workflows built into the automated data extraction system for improved compliance.
For example, consider a new regulation that mandates additional patient consent forms for certain procedures. The automated system for electronic data capture and extraction can be programmed to present those forms and upload data from them.
Streamlined Health Information Management
One of the most important compliance requirements is the ability to consolidate data in specific formats for reporting purposes. Software for automated data extraction helps with this by integrating and organizing data from various sources. This capability is particularly important for compliance, as healthcare providers often need to consolidate data in specific formats for reporting purposes.
Automated systems can gather, format, and store data according to regulatory standards, simplifying the process of preparing compliance reports and reducing the likelihood of errors.
To sum it up, automated data extraction not only enhances operational efficiency in healthcare settings but also significantly contributes to regulatory compliance. By automating complicated and error-prone tasks in data extraction, these systems help healthcare providers protect patient data, comply with evolving regulations, and maintain high standards of accountability and transparency.
Cost-Efficiency With Automated Data Extraction
Hospitals and clinics that rely on manual data extraction and processing require large administrative teams. This directly translates into higher operational costs. However, automating data extraction reduces the need for manual labor, thus decreasing payroll expenses. Furthermore, it also minimizes errors that can lead to costly corrective actions and liability.
Automating data extraction improves the overall efficiency of healthcare data management and lets physicians focus more on patient care.
A hidden problem with physicians doing manual documentation is burnout. A large number of physicians must often do the data extraction and paperwork themselves in addition to their clinical duties. This results in burnout. A study found that physician burnout had risen to over 63% in the United States.
“At the end of 2021, nearly 63% of physicians reported symptoms of burnout.”
Burnout has serious consequences not only for the physicians themselves but also for the patients. Overworked doctors are more likely to make mistakes and endanger patient health. Automating data processes eases the burden on the clinical staff and helps them focus better on patient care.
Integration of Healthcare Data Systems
Integrating healthcare data systems is crucial for good clinical outcomes. Data systems that can seamlessly share medical information provide a comprehensive 360-degree view of patients. Automated data extraction facilitates this integration by enabling seamless data flow between different systems, such as EHRs, diagnostic tools, and management software.
When physicians have a complete holistic view of patient information, they can coordinate better on complicated medical cases. However, a lack of integration leads to data silos in healthcare, which in turn leads to fragmentation of available patient information. Needless to say, this leads to a higher administrative burden and also increases the chances of medical errors.
But, with a solution for automated data extraction, medical information can be consolidated seamlessly into a centralized repository. For example, data extracted from diagnostic devices can be automatically uploaded into a patient’s EHR, accessible by all treating physicians. Integration ensures that every healthcare provider has the same information, facilitating coordinated care and preventing issues such as duplicate testing or conflicting treatments.
Tools and Technologies Used for Healthcare Data Extraction
Here are some of the tools and technologies that enable efficient data extraction in healthcare:
Optical Character Recognition (OCR)
Optical Character Recognition is widely used in healthcare and other industries to convert documents, such as scanned paper records and image-based PDFs, into editable and searchable data. It helps to accelerate medical data entry by automating the process.
Artificial Intelligence (AI)
The use of AI in healthcare data extraction will help physicians garner patient information and draw useful insights. Artificial intelligence provides the double advantage of fast, error-free data extraction and insights, which will help in making better treatment decisions.
Natural Language Processing (NLP)
Data extraction software powered by the latest NLP technologies can interpret and analyze human language from patient records, helping to extract meaningful information from unstructured data, such as doctor’s notes and clinical reports.
Conclusion
Automated data extraction can address many challenges the US healthcare industry faces. It has enormous potential to improve data accuracy, ensure regulatory compliance, reduce costs, and integrate disparate data systems. As the industry continues to embrace emerging technologies, its adoption is likely to become more widespread, driving improvements in patient care and operational efficiency.
In light of all the problems facing the country’s healthcare system, embracing automated data extraction is not just an option but a major necessity. It can usher in a future where data-driven decisions pave the way for better health outcomes.
Data Entry Outsourced has been a pioneer in data extraction services for the last 15 years. We have served clients across the USA, Canada, Europe, and Australia and solved some of the most pertaining challenges. We take the time to understand your requirements and customize our services to match them.
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