Section 5: Data Integrity and Case Intake Accuracy

7.5.1 The “Why”: The Compounding Cost of a Single Error

In the world of computing, there is a foundational principle known as “Garbage In, Garbage Out” (GIGO). It means that the quality of the output is determined by the quality of the input. A supercomputer running the most advanced algorithm in the world will produce a nonsensical, flawed result if it is fed inaccurate initial data. The same principle applies with absolute certainty to the prior authorization process. You can be the most brilliant clinical mind with the most persuasive arguments, but your entire case will collapse if the patient’s date of birth is off by a single day in your system.

The case intake process—the initial gathering and entry of demographic, insurance, and clinical data—is the most critical preventative step in the entire PA workflow. It is not “clerical work” or a low-skill task to be rushed through. It is a high-stakes clinical and administrative function that builds the foundation upon which the entire case rests. A single error introduced at this stage does not create a single problem; it creates a cascading chain reaction of failures, where the cost in time and resources compounds with every subsequent step.

7.5.2 The “Perfect Intake” Checklist: A Standard Operating Procedure

To eliminate errors and ensure consistency, every PA team must operate from a standardized intake checklist. This is the Standard Operating Procedure (SOP) that guarantees no critical piece of information is ever missed. The checklist is divided into the three core data domains: Demographics, Insurance, and Clinical. A new case should not be considered “Ready to Work” until every item on this checklist has been verified.

Part A: Patient Demographic Data Integrity

This is the most fundamental layer of data. An error here makes it impossible for the payer’s system to identify the correct person.

t d>Pitfall: An old address or phone number prevents communication about approvals, denials, costs, or shipment of specialty drugs, leading to therapy delays.

Data Field	Best Practice for Verification	Common Pitfalls & Why It Matters
Patient Legal First Name	Must match the name on the insurance card exactly. Verbally confirm spelling with the patient or cross-reference with the EHR registration data.	Pitfall: Using nicknames (e.g., “Bob” for Robert, “Liz” for Elizabeth). Payer systems use algorithmic matching. “Bob Smith” may not match “Robert Smith,” leading to a “Patient Not Found” denial.
Patient Legal Last Name	Verify against the insurance card. Pay close attention to hyphenated names or recent name changes (e.g., due to marriage).	Pitfall: A recently married patient gives her new name, but her insurance is still under her maiden name. The check will fail. Rule: The name used must match the name on the insurance policy.
Patient Date of Birth (DOB)	The “Unforgivable Error.” This must be checked and double-checked. Verbally confirm with the patient and visually check against a reliable source (EHR, ID card).	Pitfall: Transposing the month and day (e.g., 04/08/XXXX vs. 08/04/XXXX). This is the second most common cause of “Patient Not Found” denials and is entirely preventable.
Patient Gender	Verify from the EHR.	Pitfall: While less common for matching, some clinical criteria for medications are gender-specific. Incorrect entry can cause problems with automated criteria checkers.
Patient Address & Phone Number	Verify from the EHR and confirm with the patient if possible. Ensure it is the current, correct contact information.

Part B: Payer & Insurance Data Integrity

This domain requires capturing the specific routing and identification data needed to navigate the complex payer landscape. A single missing code can make it impossible to perform a benefit investigation.

Data Field	Best Practice for Verification	Common Pitfalls & Why It Matters
Payer/Plan Name	Transcribe the name of the insurer exactly as it appears on the card (e.g., “Blue Cross Blue Shield of Illinois,” not just “BCBS”).	Pitfall: Different state Blue Cross plans are often separate entities. Identifying the correct state plan is crucial for finding the right policies and portals.
Member ID Number	The primary identifier. Transcribe every single character, including any letter prefixes or suffixes. Perform a “read-back” check to verify accuracy.	Pitfall: Omitting a prefix like “ZGP” or confusing the letter ‘O’ with the number ‘0’. This is the #1 cause of “Patient Not Found” errors.
Group Number (GRP)	Locate and transcribe the GRP number.	Pitfall: Ignoring the group number. This number identifies the specific employer’s plan, and different employer groups with the same payer can have vastly different formularies and benefits.
RXBIN & RXPCN	Locate these critical six-digit (BIN) and alphanumeric (PCN) codes, which are often on the back of the card under “Pharmacy Information.”	Pitfall: Failing to capture these codes. Without the BIN, you cannot definitively identify the PBM and cannot perform a pharmacy benefit investigation. This is a non-negotiable data point.
Payer Phone Numbers	Note the phone numbers for both “Member Services” and “Provider Services.”	Pitfall: Only noting the member services number. The provider services line often has different phone tree options and more experienced agents for handling complex PA questions.

Part C: Clinical & Prescription Data Integrity

The final domain ensures that the authorization is being requested for the correct drug, for the correct reason, as prescribed by the authorized provider.

Data Field	Best Practice for Verification	Common Pitfalls & Why It Matters
Prescriber Name & NPI	Verify the correct ordering provider and their unique National Provider Identifier (NPI).	Pitfall: Listing the attending physician when the prescription was actually written by a resident or fellow. The PA must be submitted under the NPI of the actual prescriber on record.
Drug Name, Strength, Formulation	Enter the full, unambiguous drug information. Avoid all abbreviations. For example, “tacrolimus extended-release 1 mg capsule,” not “tacrolimus ER 1mg.”	Pitfall: A PA approved for an immediate-release formulation will be rejected if the pharmacy tries to fill the extended-release version. The formulation is a critical data point.
Directions for Use (Sig)	Transcribe the sig exactly as written. “1 tablet by mouth twice daily” provides a clear daily quantity.	Pitfall: A vague sig like “take as directed” is useless for a Quantity Limit (QL) review. The payer needs to see a calculable daily dose to authorize a specific monthly quantity. A vague sig requires a clarification call, causing a delay.
Primary ICD-10 Diagnosis Code	This is a mandatory field. The PA request must include the primary diagnosis code that justifies the medication’s use. This must be obtained from the prescriber.	Pitfall: Using a symptom code (e.g., “joint pain”) instead of a definitive diagnosis code (e.g., “M05.79 – Rheumatoid arthritis with rheumatoid factor of multiple sites”). Payer criteria are mapped to specific diagnosis codes. The wrong code guarantees a denial.

7.5.3 The Intake Workflow: From Referral to Actionable Case

Having a perfect checklist is one thing; integrating it into a smooth, efficient workflow is another. This is the process that turns a raw, incoming request into a fully-vetted, “ready-to-work” case in your queue. Following this workflow prevents incomplete cases from ever reaching the pharmacist, saving valuable time.

1. Step 1: The Trigger (Request Arrives)

   A new PA request is generated and arrives in the intake queue. This can be an electronic task from the EHR, an incoming e-fax, a secure email, or a phone call. All requests, regardless of source, enter the intake process at this single point.

2. Step 2: Case Shell Creation & The “Perfect Intake” Protocol

   The intake specialist (often a highly trained technician) creates a new case file in the PA management software (e.g., CoverMyMeds). They then methodically work through the three-part “Perfect Intake” checklist, populating every single data field using the source documents (referral form, EHR data, scanned insurance card).

3. Step 3: The “Red Flag” Quality Review

   Before saving the new case, the specialist performs a mandatory quality check, specifically looking for common intake errors or omissions. This is a final verification step.

   The Intake Quality Checklist

   • Is there a scanned copy of the front AND back of the pharmacy insurance card? If NO → Flag as INCOMPLETE.
   • Is the Patient Name and DOB a 100% match between the EHR and the insurance card? If NO → Flag for VERIFICATION.
   • Are the RXBIN and RXPCN fields filled? If NO → Flag as INCOMPLETE.
   • Is there a specific, billable ICD-10 code listed? If NO → Flag as INCOMPLETE.

4. Step 4: Resolve Incomplete Cases

   Any case flagged as INCOMPLETE or for VERIFICATION does not proceed to the pharmacist’s queue. The intake specialist is responsible for resolving the issue. This typically involves sending a templated, specific request back to the originating clinic (e.g., “Missing ICD-10 code for this PA request. Please provide.”) or contacting the patient registration department to resolve a demographic discrepancy.

5. Step 5: Triage and Queue Placement

   Once a case passes the quality review and all fields are complete, it is considered “Ready to Work.” The intake specialist or lead pharmacist then applies the Urgency/Complexity Matrix to assign a priority level and places the case in the appropriate pharmacist’s work queue for benefit investigation and submission.