Maximizing Data Integrity

In an era of pricing transparency and increasing calls for even greater government pricing regulation, government pricing risk is heightened for drug manufacturers.

American Patients First, the Trump administration’s blueprint attempting to lower drug prices, includes more than 50 regulatory and legislative changes, with potentially significant impacts to the pharmaceutical industry including the areas of:

• Reforming the 340B Discount Program
• Shifting some drugs from Medicare Part B to Medicare Part D
• “Experimenting” with value-based agreements
• Changing regulations regarding copay programs

Other evolving government pricing risks for manufacturers include:

Drug transparency laws--like those passed by California, Vermont, Maryland and Oregon--which will require manufacturers to report increases in drug prices and provide consumers and states with more transparency. Reporting requirements vary by state.

Manufacturer copay cards and coupons are intended to provide patients with cost saving assistance for prescriptions, usually for products with high out-of-pocket costs. Historically manufacturer copay assistance has counted towards a patient’s deductible or annual out-of-pocket maximums, with plans covering the cost of prescriptions once these thresholds are met. Plan accumulator programs however disallow the application of manufacturer copay assistance towards a patient’s deductibles or annual out-of-pocket maximus, thus shifting more of the cost of high-cost prescriptions towards the patients and manufacturers as patients rely on copay assistance for longer periods.

These changes also increase government pricing reporting risks as manufacturers attempt to manage the influx of data and ensure that excluded benefits are not retained by pharmacies or other entities administering the benefit.

How can data integrity help?

Without sound data integrity, manufacturers become vulnerable to inaccurate determinations of best prices, miscalculated Average Manufacturer Prices and Non-Federal Average Manufacturer Price calculations, which can lead to revenue leakage and inaccurate gross-to-net values.

Challenges to data integrity include the following:

1. Data is often managed by parties that are not GP-knowledgeable which means they may not understand the impact of transactional sales data decisions.
2. Lack of visibility into the granular details of the data when it’s managed by a third-party vendor.
3. Lack of transparency into changes when working with a third-party vendor to amend inaccuracies.
4. Uncertainty as to whether third-party vendors have correctly interpreted and implemented updates.

How can pharmaceutical manufacturers overcome data integrity challenges?

Routine data monitoring, fostering relationships with data owners and IT departments, and developing proper policies and procedures are key.

Data integrity policies and procedures should:

1. Establish a list of data integrity checks that ensure compliance with regulations and prevents revenue leakage;
2. Address and specify the documentation process, appropriate points of contact and processes for reviewing data;
3. Address how to document and amend data errors in a transparent manner;
4. Create templates for data check results and an assumptions document.

Some easy, but effective data integrity checks include:

1. Data field anomalies, e.g. blanks, numeric characters in an alpha-numeric field, etc.
2. New / unknown codes, like COT, transaction type, or state codes.
3. Pricing validations, e.g. WAC, contract, chargeback amount, etc.
4. Sum totals on dollar and unit fields.
5. New / unknown customer IDs, contract IDs, etc.

Data integrity is integral to ensuring compliance in an ever-changing industry. Organizations should ensure they have proper policies and procedures in place sooner rather than later or risk steep fines and penalties that result in more than just revenue leakage.