When paper documents are scanned, the images themselves are only part of the finished digital record. Important information, such as names, dates, account numbers, and other identifying details, often needs to be captured so those documents can be organized, searched, and retrieved later.
This information is stored as metadata, and getting it right is an important part of the document scanning process.
In many cases, optical character recognition (OCR) technology can automatically extract text from scanned documents. However, OCR isn’t always the best choice, particularly when records contain handwriting, faded text, inconsistent formatting, or information that requires a high degree of accuracy.
In these situations, manual data entry may be necessary. But because people can make mistakes, an additional verification process helps reduce the likelihood of errors making their way into the finished digital records.
That’s where double-blind data entry comes in. Also known as two-pass verification, this process uses two independent rounds of data entry to identify discrepancies and improve the accuracy of captured information.
What Is Double-Blind Data Entry?
Double-blind data entry is a verification process in which two operators independently enter the same information without seeing each other’s work.
Once both entries are complete, the information is compared to identify any differences. When discrepancies are found, a quality control professional reviews the original source material to determine which entry is correct.
This additional review helps catch mistakes such as transposed numbers, misspelled names, missing characters, and other errors that might otherwise go unnoticed.
The advantage of this approach is that neither operator is influenced by the other’s work. Each person enters the information independently, allowing differences between the two entries to be identified and investigated before the data is finalized.
How Does Double-Blind Data Entry Work?
The double-blind data entry process is relatively straightforward. Instead of relying on a single person to enter information correctly, the same data is captured twice and the results are compared.
The process typically involves five steps:
Step 1: First Round of Data Entry
The first operator reviews the source documents and manually enters the required information into the system. This might include names, dates, account numbers, identification numbers, or other details needed to organize and retrieve the digitized records.
Step 2: Independent Second Round
A second operator enters the same information separately, without access to the first operator’s entries.
Keeping the two rounds independent is an important part of the process. It prevents the second operator from simply repeating or overlooking mistakes made during the first round.
Step 3: Comparison of Both Entries
Once both rounds are complete, the two sets of data are compared to identify differences.
If both operators entered the same information, the entries match and can proceed through the remaining quality control process. If they entered different information, the discrepancy is flagged for review.
Step 4: Investigation and Correction of Discrepancies
A quality control professional reviews any discrepancies and compares the entries against the original document.
For example, if one operator enters an account number as 108592 and the other enters 108529, the difference is flagged. The reviewer checks the original document to determine which number is correct and resolves the discrepancy.
This helps prevent incorrect information from being carried into the finished digital records.
Step 5: Final Validation
After discrepancies have been resolved, the verified information is prepared for use in the finished digital records.
Depending on the project’s requirements, additional quality control checks may be performed to confirm that the data follows the expected format and meets the agreed-upon specifications.
The result is a more dependable set of information that can be used for document indexing, retrieval, and other records management purposes.
How Does Two-Pass Verification Improve Data Accuracy?
The biggest advantage of double-blind data entry is that it provides an independent way to identify mistakes that might otherwise go unnoticed.
When one person enters information manually, small errors can make their way into the finished record. A transposed number, misspelled name, or missing character may seem insignificant, but even a minor mistake can affect how information is organized or retrieved later.
Two-pass verification helps address this problem by having two operators enter the same information independently. Their results are then compared, and any differences are flagged for further review.
Because neither operator relies on the other’s work, the process reduces the likelihood of an individual mistake going undetected.
Of course, double-blind data entry doesn’t guarantee that every error will be identified. Both operators could misinterpret the same handwritten character, for example. However, independently capturing and comparing information provides an additional layer of quality control that isn’t present with single-pass data entry.
This approach is particularly useful when maintaining data integrity is a priority and organizations need greater confidence in the accuracy of their digitized information.
Why Accurate Data Matters Beyond the Scanned Image
Producing a clear, readable digital image is only one part of a successful document scanning project. The information used to identify, organize, and retrieve that document also needs to be accurate.
Consider a collection of employee files indexed by name and employee identification number. Even if the scanned documents are perfectly readable, an incorrect identification number could make a record difficult to locate through a database search.
The same issue can arise with medical records, financial documents, legal files, and other records that rely on accurate identifying information.
Double-blind data entry helps reduce these errors before they affect the usability of the finished records. By improving the accuracy of the information associated with each document, organizations can have greater confidence that their digital records will be accessible when needed.
When Is Double-Blind Data Entry Necessary?
Not every document scanning project requires the same level of data verification.
For records with clear, consistent formatting, automated data extraction using OCR may provide the accuracy needed for the project. Other collections may contain information that is more difficult to capture reliably or where even small errors could create problems later.
Double-blind data entry is particularly useful in situations involving:
- Handwritten records: Names, dates, numbers, and other handwritten information can be difficult for automated recognition software to interpret consistently.
- Faded or damaged documents: Poor print quality and deteriorating source materials can make accurate data extraction more challenging.
- Medical records: Patient identifiers and other information used to organize records may require additional verification.
- Legal documents: Case numbers, names, dates, and other identifying details often need to be captured accurately for future retrieval and reference.
- Financial records: Account numbers, transaction details, and other numerical information can be particularly sensitive to data entry mistakes.
- Historical records: Older documents may contain handwritten information, inconsistent formatting, or print quality issues that complicate automated extraction.
The right approach depends on the condition of the original documents, the information being captured, and how the finished records will be used.
For some projects, automated extraction and standard quality control measures may be sufficient. For others, two-pass verification provides an additional level of assurance that can justify the extra time and effort involved.
Why SecureScan Uses Double-Blind Data Entry
Accuracy is an important part of any document scanning project. A digital record needs to be readable, but the information used to identify and retrieve it must also be reliable.
At SecureScan, double-blind data entry is one of the quality control methods we use to reduce errors during document conversion. By independently verifying information and resolving discrepancies, we help ensure that important details are captured correctly and that finished digital records are organized and ready to use.
Our approach to data extraction considers the condition of the original documents, the type of information being collected, and the accuracy requirements of each project. With more than 23 years of experience, we help organizations choose the appropriate scanning and verification methods for their records.
Whether it’s a collection of employee files, financial documents, medical records, or legal records, our goal is to deliver digital files that are accurate, organized, and easy to retrieve.
Considering a document scanning project? Contact SecureScan to discuss your records and data accuracy requirements, or request a free quote to get started.
