St. Paul, Minnesota – March 16, 2011 – Quality control of claims is becoming increasingly important as greater pressure is felt by the health care industry for increased accuracy in claims, faster turn around times, and lower costs. Improved quality control of claims, through the implementation of the following seven quality control steps, will help you to reduce claim rework, reduce turn around time and reduce costs. These quality control steps are in use, and have been proven to minimize errors, by Smart Data Solutions, a Minnesota-based provider of data processing solutions for the health care industry.
The seven quality control steps are:
1. Mailroom: Document Receipt Tracking
It is important to begin tracking documents from the minute they reach the mailroom so there is no information missing from any point in the process. In this initial step, the date the claim is received, the scan date, the prep person, the scanning operator, and the form type are recorded. The above information should also be web viewable. Smart Data Solutions claims processing system is unique due to its extensive use of the above described mailroom tracking and it has found that the tracking significantly improves the quality of the data.
2. Scanning Reconciliation
This step entails comparing the number of documents scanned with the document count from step one. This process should be a fully automated process. In the event there is a discrepancy, the scanning process is automatically stopped to ensure reconciliation.
3. Image Fidelity Review
After the documents are physically scanned it is important to review each digital image to ensure it is fully scanned, legible and of the correct batch type.
4. Critical Field Double Key
OCR enhanced double key ensures critical fields’ quality while maintaining price competitiveness. In order to guarantee the most accurate data, the referee keyer must agree with one of the first two entries or the claim goes to a fourth senior keyer. Smart Data Solutions quality control process is also unique in its use of these stringent matching criteria.
5. Quality Control
It is also important to employ higher-level business logic for both data transformation and quality assurance. For example, if the entered name is not in the US census bureau database it automatically triggers a second review. Double key of quality control events further increases quality.
6. Apply Billing Line Edits
This quality control queue is used to improve the data quality of charge and billing lines. Specifically if the total charge does not equal the sum of billing line charges, the claim is routed to a module where the keyer may modify, add or remove billing lines.
7. Provider and Member Matching
Verifying provider and member information to validate the eligibility of the providers and members is important to catch any ineligible claims or inconsistencies. In order to be most cost efficient it is important for this process to be fully automated. By increasing the accuracy of the claim through provider and member matching you will experience lower direct labor costs and an improved payment process.
In a field as dynamic as health care technology, Smart Data stands out for its stability and growth. For more than ten years, Smart Data Solutions Inc. has been leveraging technology to meet the needs of health care claims managers. Today, more than 130 TPAs, PPOs, HMOs, hospitals and insurance companies depend on SDS technology to save money and streamline their business. From paper processing to claims management and EDI, Smart Data Solutions offers the solutions critically needed by today’s health care industry. Smart Data Solution’s proven quality management systems results in exceptionally high data quality and an industry leading ISO compliant system. For more information please visit our web site at http://www.localhost:10003, contact Pat Bollom at 651-690-3140 or email firstname.lastname@example.org.