Patient Demographics Entry
Accurate capture of patient details is perhaps one of the most under-rated processes in the revenue cycle process chain. Not only does the data captured in the demographic entry process form the base for the medical record, but it also affects insurance claims payment. Error-free capture of patient information is essential for clean claim submission and facilitates quick claims processing by Payers.
The front-office at the place of service should accurately capture the patient information, either via paper-based registration processes or via the scheduling system. Accurate information about the patient is critical to ascertain the patient’s eligibility and benefits, obtaining prior authorization, and error-free claims filing. Additionally, population health analytics is possible only by utilizing accurate patient information.
- Patient’s legal name, age, gender, address,
phone numbers - Patient’s social security number for
identification - Healthcare Insurance Information
- Payer information (name of the Payer, mailing
address for claims, and group and policy numbers) - Details of secondary as well as primary Payers
- Medicaid or Medicare card (if the patient
receives federal or state assistance)
- Payer information (name of the Payer, mailing
- Allergies if any
- Special requirements (interpreter, assistance for physically disabled people, medications, Ambulance, stretcher access, etc.)
- Name, address, and telephone number of the person who will be responsible for payments
- Patient’s social security number for
identification
Inaccurate capture of the Patient information could result in:
- Increased claim denials and delayed payments. Incorrect details captured cause rework as the clearinghouse systems, and the payer claims adjudication platforms may reject the claims. As a result, delays in obtaining payment or losses on account of unpaid claims can occur.
- Inaccuracies in Population Health Analytics. Identification of the right population segments based on demographics data is the anchor for Population health analytics