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The Importance of Data Extraction in Healthcare

Whether it’s negotiating reimbursements with insurers or providing optimal patient care, data extraction can take your physician group or health system to the next level. Data extraction solutions provide a wealth of benefits to providers, including improving diagnosis accuracies, treatment efficiency, and streamlining clinical decision-making.

There have been data extraction automation efforts to calculate the risk score of a beneficiary. These efforts rely on leveraging information from structured electronic health record (EHR) data. When your data extraction tools can be leveraged to support risk score calculation and enhance your healthcare practice, the benefits only multiply.

What Is Data Extraction?

In healthcare, your patients may see a wide range of providers and specialists, hopping from insurer to insurer. Their data can include lab results, previous and ongoing diagnoses, clinic results, notes from specialists, and more. In these extremely common cases, it can be difficult to consolidate this data and provide your patients with care that encapsulates them holistically.

This is where data extraction comes in. Data extraction refers to the process of collecting or retrieving varying types of data from a range of sources. Oftentimes, this data is disorganized or unstructured, making it difficult to extrapolate using the raw data alone.

With data extraction, you can easily process, consolidate, and refine this data to store in a centralized location. These locations can be on-site, cloud-based, or a combination of both.

 

Uses for Data Extraction in Healthcare

Once your data is extracted, sorted, refined, and centralized, you can build a predictive algorithm to apply predictive analytics and various techniques. This can assist with risk-based arrangements, using the data to anticipate what levels of care and required codes each patient will need. With this information, health policies can develop methods to ensure the proper care for each patient.

That’s not all–data extraction and their relevant tools can also:

  • Enable the study of genetic sequences
  • Reduce the rate for dynamic data processing
  • Automates analytical records, including disease records, demographics, and more
  • Make information, such a pharmaceutical records and comprehensive data, accessible to approved users, such as physicians

Data extraction exists in every industry, and in healthcare, it can completely transform your group’s or system’s data and care practices.

 

Benefits of Data Extraction and Mining in Healthcare

The Royal Bank of Canada Capital Markets reported that the healthcare industry produces approximately 30% of all global data. Experts estimate that by 2025, that percentage will rise to 36%. This means the amount of unfiltered, unsorted data is not going to decrease anytime soon.

Investing in a tool that streamlines your data extraction and analyses affords you with several key advantages.

 

Improve Your Treatment Efficiency

When you have your patient’s complete medical history at your fingertips, you increase your ability to provide top-quality care for your patients. Data extraction allows you to access data, unfiltered and otherwise, and consolidate it into an easy-to-digest way to analyze available treatment plans.

With a wealth of data that’s properly processed and sorted, you can compare the efficacy of possible treatment routes and select the best course of action.

 

More Accurate Diagnoses

Every reputable clinician knows that for every reason a patient books an appointment, there’s usually several other underlying conditions that influence their condition. With data extraction tools, such as Ubiquity, you can automatically analyze data in both your EHR and external resources.

 

Ubiquity pulls patient records that were generated by different healthcare providers, clinics, and lab results. Inferscience’s other software, the HCC Assistant, can analyze text from uploaded PDF documents and images using optical character recognition (OCR) technology. This allows you to view the full scope of your patient’s medical history and pinpoint the more accurate diagnosis.

 

Streamline Clinical Decision Making

The number of hospitals adopting clinical decision support systems (CDSS) is increasing. This is because these systems use a knowledge base, applying rules or utilizing machine-learning to make extrapolations based on the data analyzed.

Data extraction works with these systems, allowing clinicians to easily compare a patient’s medical history and symptoms with current research or even similar cases.

 

Data Extraction With Inferscience

Inferscience offers an array of data extraction tools that can seamlessly integrate into your current workflow and applications. Ubiquity, for example, can integrate into any web-based EHR and provide analysis insights to the provider in the patient’s chart. This allows providers working with Medicare Advantage patients to maximize their reimbursement.

Additionally, Inferscience utilizes cutting-edge OCR technology and advanced natural language processing (NLP) to analyze both structured and unstructured data. This allows providers to identify diagnoses that may typically get overlooked, all while simultaneously displaying the relevant Hierarchical Condition Category (HCC) code suggestions.

 

Ready to streamline your workflows and practice? Contact Inferscience today for a complimentary demo!

 

References:

 

https://www.talend.com/resources/data-extraction-defined/

https://www.rbccm.com/en/gib/healthcare/episode/the_healthcare_data_explosion

https://bytescout.com/blog/data-extraction-healthcare.html

https://www.inferscience.com/

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