How PBM Data Can Reveal Workers’ Compensation Claim Trends

When a workers’ compensation claim starts to go off track — costs rising, recovery slowing, and prescriptions increasing — the warning signs are usually there early. The challenge is knowing where to look. One of the most useful sources of insight is PBM data.

What is a PBM and Why Does It Matter?

A Pharmacy Benefit Manager (PBM) is a company that handles prescription drug benefits for insurers, third-party administrators (TPAs), and self-insured employers. Think of it as the behind-the-scenes system that manages pharmacy networks, negotiates drug prices, and processes prescriptions for workers’ comp claims.

Every prescription creates a record: the drug name, dosage, prescribing doctor, pharmacy, fill date, and related claim codes. On their own, these records help manage individual claims. But when looked at across many claims, they reveal patterns that can improve claims management.

For claims professionals, case managers, and TPAs, understanding these patterns helps shift from reacting to issues to preventing them.

Spotting Prescription Patterns Before They Become Problems

PBM data shows whether prescription use matches what is normally expected for a given injury.

For example, a simple soft tissue injury usually follows a predictable pattern: anti-inflammatory medication and muscle relaxants early on, then decreasing as recovery improves. When that happens, the claim is progressing normally.

When it doesn’t — such as a soft tissue claim with 12 prescriptions over 18 months across multiple drug types — it may be a sign something is off.

PBM data can help flag:

• Claims with unusually high prescription counts for the injury type
• Medications used for longer than expected
• Multiple types of drugs used at the same time
• Gaps in refills followed by sudden increases, which may suggest stockpiling

According to NCCI analysis, prescription drugs make up about 7% of total workers’ comp medical costs. While overall drug costs per claim have gone down, some categories, especially topical medications, have increased about 96%. PBM data helps show where these cost changes are happening.

Catching Chronic Pain Before It Becomes Long-Term

Not every long-term claim starts out that way. PBM data can give early warning signs.

If a claim that began as a simple injury starts including medications like antidepressants, sleep aids, or long-acting opioids, it may suggest the pain has become chronic.

Seeing this early allows case managers and claims professionals to step in sooner, coordinate care, and explore treatment options before costs and recovery time increase.

Understanding the Full Patient Picture Through PBM Data

Prescription data doesn’t just show what is being prescribed for the injury; it can also show the worker’s overall health.

A claims reviewer may see medications for conditions like high blood pressure, diabetes, depression, or sleep issues.

These existing health conditions (called comorbidities) can affect recovery. For example, someone managing multiple health conditions may recover more slowly from a knee injury than someone without them.

Research published in JAMA Network found that in nearly 10,000 workers’ comp cases, about 30% continued filling opioid prescriptions more than 90 days after injury.

It also found that workers with prior chronic joint pain were almost twice as likely to still be using opioids after 90 days. Looking at the full medication profile helps identify where extra clinical support may be needed.

Identifying Provider Outliers and Fraud Signals

PBM data also shows prescribing behavior, not just what injured workers receive.

Some providers stand out by consistently prescribing higher opioid doses, choosing brand-name drugs over cheaper generics, or using compounded medications more often than expected.

Not all differences are a problem; many have valid reasons. But patterns that repeat across many claims may need closer review. PBM clinical pharmacists can also help review these cases and speak with providers when needed.

PBM data can also help spot possible fraud, such as:

• The same prescription filled at multiple pharmacies in a short time
• Unusual prescription quantities
• Prescriptions filled in locations that don’t match the provider or worker’s location

The Coalition Against Insurance Fraud estimates workers’ compensation fraud costs about $34 billion per year. PBM data helps surface suspicious patterns earlier so they can be reviewed.

PBM Data Is Only Useful If It Leads to Action

The real value of PBM data isn’t just spotting issues; it’s acting early.

When data shows a claim moving toward long-term disability in the first few weeks instead of months later, there is still time to intervene. Case managers can contact the treating doctor, adjust the care plan, or introduce recovery programs before the claim becomes long-term.

PBM data gives a real-time view of what is happening across claims in a way that medical records and adjuster notes often can’t. For claims professionals, it supports a more proactive approach instead of a reactive one.

Want to better understand what PBM data is revealing across your claims portfolio? Our team can help you turn prescription insights into informed decisions. Let’s connect.

Check out our sources:

Coalition Against Insurance Fraud and Colorado State University Global. The Impact of Insurance Fraud on the U.S. Economy. Coalition Against Insurance Fraud, 2022, insurancefraud.org/wp-content/uploads/The-Impact-of-Insurance-Fraud-on-the-U.S.-Economy-Report-2022-8.26.2022.pdf.

National Council on Compensation Insurance. “Inflation and Workers Compensation Medical Costs — Prescription Drugs.” NCCI, 28 Mar. 2023, ncci.com/Articles/Pages/Insights-Inflation-WorkersComp-Medical-Costs-Prescription-Drugs.aspx.

National Council on Compensation Insurance. “NCCI Publishes Medical Cost Trends Report.” Healthesystems, 25 June 2024, healthesystems.com/workerscomprehensive/ncci-publishes-medical-cost-trends-report/.

O’Hara, Nathan N., et al. “Factors Associated With Persistent Opioid Use Among Injured Workers’ Compensation Claimants.” JAMA Network Open, vol. 1, no. 6, 2018, doi:10.1001/jamanetworkopen.2018.4050. PubMed Central, pmc.ncbi.nlm.nih.gov/articles/PMC6324441/.