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MODULE 23: SPECIAL TOPICS & CASE SIMULATIONS
Section 5: Advanced Exercise: Denial Root-Cause Map
The capstone exercise: Transitioning from a case-by-case problem solver to a system-wide strategic leader.
SECTION 23.5
Advanced Exercise: Denial Root-Cause Map
From fixing today’s denial to preventing tomorrow’s. This is the work that transforms a department.
23.5.1 The “Why”: The Leap from Tactical to Strategic
Throughout this entire program, we have focused on the tactical skills required to be an elite prior authorization pharmacist. You have learned how to deconstruct payer policies, investigate a patient’s clinical history, and build compelling, evidence-based arguments to secure approvals for critical medications. You have become an expert problem-solver, capable of overturning even the most challenging denials on a case-by-case basis. This is the foundational, indispensable work of a PA specialist.
This final exercise is designed to elevate you to the next level of practice. The most valuable PA pharmacist in an organization is not just the one who can fix any single denial, but the one who can identify why denials are happening in the first place and then design and implement systems to prevent them from ever occurring again. This is the leap from being a tactical technician to a strategic leader. It is the difference between playing whack-a-mole with denials as they pop up and redesigning the game so that fewer moles appear.
This work, known as root-cause analysis, is the hallmark of a high-reliability organization. Instead of accepting denials as a “cost of doing business,” you reframe them as system failures. Each denial is a data point that signals a breakdown somewhere in the process: a gap in documentation, a flaw in the EMR workflow, a knowledge deficit in a clinic, or a misalignment between prescribing habits and payer expectations. Your task is to become a systems thinker, a process improvement expert, and an effective agent of change within your health system.
In this capstone exercise, you will be given a dataset of denials. Your goal is not to appeal them. Their outcomes are already set. Your mission is to analyze them, categorize them, and, most importantly, to develop a concrete, actionable strategic plan that you could present to hospital leadership. This plan will propose specific interventions to address the root causes you’ve identified, with the ultimate goal of reducing future denials, decreasing administrative burden, accelerating time-to-therapy for patients, and improving the organization’s financial performance. This is the work that gets you promoted. This is how you demonstrate your value not just to individual patients, but to the entire health system.
Retail Pharmacist Analogy: The Recurring “Refill Too Soon” Fire
Imagine in your pharmacy, every single day, you get at least five “refill too soon” rejections for patients on insulin pens. Each time, you have to stop what you’re doing, get on the phone with the payer, explain that the EMR calculates the days’ supply based on milliliters but the pens are dosed in units, get a one-time override, and document the call. It’s a 15-minute fire you have to put out, over and over again. You are an expert firefighter.
One day, instead of just grabbing the fire extinguisher, you stop and ask, “Why does this keep happening?” You decide to do a root-cause analysis. For one week, you log every single insulin pen rejection. At the end of the week, you have a list of 35 rejections, all for the same reason. This is your data collection.
You analyze the data. You see that the problem is not with the prescriptions themselves, but with how your pharmacy’s software defaults the days’ supply calculation. It’s a system flaw. This is your root-cause identification. The stated reason is “Refill Too Soon,” but the root cause is “Incorrect EMR Days’ Supply Calculation for Unit-Dosed Devices.”
You don’t just complain about it. You develop a strategic plan. You write a short memo to your pharmacy manager and the corporate IT support team. In it, you quantify the problem: “This single issue causes approximately 140 rejections per month, consuming over 35 hours of pharmacist and technician time in phone calls and rework.” You propose a solution: “I request that our IT team adjust the calculation logic for insulin pens to be based on the total units in the box divided by the daily dose in units, rather than total milliliters.” This is your proposed intervention.
IT implements the change. The following month, your insulin pen rejections drop by 95%. You have not just put out one fire. You have fireproofed the building. You have used data analysis and systems thinking to solve the root cause of the problem, saving hundreds of hours of work and eliminating a major source of frustration for both staff and patients. This is the exact mindset you must now apply to a broad spectrum of clinical denials.
23.5.2 The Scenario & The Dataset
You are the Lead Prior Authorization Pharmacist at University Health System. The Director of Pharmacy has noticed a significant increase in write-offs and payment delays related to high-cost specialty drugs. She has tasked you with analyzing the 50 most recent, high-value denials from the past quarter to identify systemic issues and propose a quality improvement plan.
Below is your dataset. It includes the payer’s stated reason for denial and a brief, anonymized clinical snippet pulled from the case notes. Your journey from technician to strategist begins here.
Master Dataset: Q3 High-Value Denials (n=50)
| ID | Drug Name | Area | Payer | Stated Denial Reason | Clinical Snippet |
|---|---|---|---|---|---|
| 1 | Pembrolizumab | Oncology | Aetnalogic | Lack of Medical Necessity | NSCLC case; submission only included a generic letter of medical necessity. |
| 2 | Ocrelizumab | Neurology | MedSecure | Step Therapy Required | RRMS case; denial states no history of preferred DMT failure. |
| 3 | Adalimumab | Rheumatology | Unified Health | Information Requested Not Received | RA case; payer requested recent disease activity scores, no response from clinic. |
| 4 | Sacituzumab Govitecan | Oncology | Aetnalogic | Not a Covered Benefit | TNBC case; submitted for 2nd line therapy, but payer policy only covers 3rd line and beyond. |
| 5 | Risankizumab | Dermatology | CignaCare | Step Therapy Required | Psoriasis case; denial requires failure of a TNF inhibitor and Otezla. |
| 6 | Patisiran | Cardiology | MedSecure | Lack of Medical Necessity | ATTR Amyloidosis case; genetic test confirming TTR mutation was not attached. |
| 7 | Abemaciclib | Oncology | Unified Health | Information Requested Not Received | HR+ breast cancer case; reviewer asked for Ki-67 score, no response provided. |
| 8 | Upadacitinib | Rheumatology | Aetnalogic | Step Therapy Required | RA case; history of methotrexate intolerance provided, but no failure of a TNF inhibitor. |
| 9 | Elexacaftor/tezacaftor/ivacaftor | Pulmonology | StateCare | Lack of Medical Necessity | CF case; required PFTs (FEV1) to establish baseline severity were not included. |
| 10 | Dupilumab | Dermatology | CignaCare | Lack of Medical Necessity | Atopic dermatitis; chart notes lacked quantification of BSA affected or an EASI score. |
| 11 | Nivolumab | Oncology | MedSecure | Lack of Medical Necessity | Renal Cell Carcinoma; pathology report was missing from submission. |
| 12 | Semaglutide (Wegovy) | Endocrinology | Unified Health | Not a Covered Benefit | Obesity case; patient’s plan has a specific exclusion for all weight-loss medications. |
| 13 | Ofatumumab | Neurology | Aetnalogic | Step Therapy Required | RRMS case; patient had failed one preferred agent, but policy requires two. |
| 14 | Tofacitinib | GI | CignaCare | Step Therapy Required | Ulcerative Colitis; notes showed failure of mesalamine, but not a required TNF inhibitor. |
| 15 | Palbociclib | Oncology | StateCare | Incorrect Diagnosis Code | Breast cancer case; submitted with generic C50.9 instead of a site-specific code. |
| 16 | Etanercept | Rheumatology | MedSecure | Lack of Medical Necessity | Ankylosing Spondylitis; recent CRP/ESR and BASDAI score were not in the submission. |
| 17 | Tezepelumab | Pulmonology | Unified Health | Lack of Medical Necessity | Severe Asthma; denial states lack of proof of eosinophilic phenotype (blood eosinophil count). |
| 18 | Crizotinib | Oncology | Aetnalogic | Lack of Medical Necessity | NSCLC case; NGS report confirming ALK fusion was not attached. |
| 19 | Lisocabtagene maraleucel | Oncology | MedSecure | Not a Covered Benefit | DLBCL case; CAR-T therapy requires auth through medical, not pharmacy, benefit. Submitted to wrong dept. |
| 20 | Satralizumab | Neurology | CignaCare | Lack of Medical Necessity | NMOSD case; required AQP4-IgG antibody test result was missing. |
| 21 | Infliximab | GI | Unified Health | Information Requested Not Received | Crohn’s case; payer requested records of recent hospitalizations, clinic did not send. |
| 22 | Brentuximab Vedotin | Oncology | StateCare | Lack of Medical Necessity | Hodgkin Lymphoma; submission for non-first line therapy but no documentation of what first-line chemo failed. |
| 23 | Guselkumab | Dermatology | Aetnalogic | Step Therapy Required | Psoriasis; patient failed phototherapy, but not a required oral systemic agent like methotrexate. |
| 24 | Abiraterone | Oncology | MedSecure | Patient Not Eligible | Prostate cancer case; patient’s insurance coverage had termed the previous month. |
| 25 | Natalizumab | Neurology | Unified Health | Lack of Medical Necessity | MS case; required JCV virus antibody status was not submitted. |
| 26 | Vedolizumab | GI | CignaCare | Step Therapy Required | UC case; documentation showed failure of a TNF inhibitor, but not a second preferred agent. |
| 27 | Olaparib | Oncology | Aetnalogic | Lack of Medical Necessity | Ovarian cancer; germline BRCA mutation test result was not included in the packet. |
| 28 | Secukinumab | Rheumatology | StateCare | Lack of Medical Necessity | Psoriatic Arthritis; notes lacked evidence of joint involvement (e.g., swollen/tender joint counts). |
| 29 | Tirzepatide (Mounjaro) | Endocrinology | MedSecure | Lack of Medical Necessity | T2DM case; denial for not meeting A1c criteria, but most recent A1c lab was not attached. |
| 30 | Atezolizumab | Oncology | Unified Health | Policy Misalignment | Liver cancer case; submitted for a combination therapy not yet NCCN or FDA approved. |
| 31 | Efgartigimod | Neurology | CignaCare | Lack of Medical Necessity | Myasthenia Gravis; documentation of positive AChR antibody test was missing. |
| 32 | Lenalidomide | Oncology | Aetnalogic | Information Requested Not Received | Multiple Myeloma; payer requested cytogenetic risk stratification, no response from clinic. |
| 33 | Rimegepant | Neurology | MedSecure | Step Therapy Required | Migraine case; denial requires failure of two triptans. Patient had only tried one. |
| 34 | Ivacaftor | Pulmonology | Unified Health | Lack of Medical Necessity | CF case; the specific CFTR gene mutation was not documented in the submission. |
| 35 | Trastuzumab Deruxtecan | Oncology | StateCare | Lack of Medical Necessity | HER2+ breast cancer; prior lines of HER2-directed therapy were not documented. |
| 36 | Ustekinumab | GI | CignaCare | Information Requested Not Received | Crohn’s case; endoscopy report was requested to confirm severity, but was not sent. |
| 37 | Voxelotor | Hematology | Aetnalogic | Lack of Medical Necessity | Sickle Cell; baseline hemoglobin level was missing from the submission. |
| 38 | Pembrolizumab | Oncology | MedSecure | Lack of Medical Necessity | Melanoma case; BRAF mutation status (required for therapy choice) was not included. |
| 39 | Lanadelumab | Immunology | Unified Health | Lack of Medical Necessity | Hereditary Angioedema; notes lacked documentation of the frequency of attacks. |
| 40 | Certolizumab | Rheumatology | StateCare | Step Therapy Required | RA case; submitted as first biologic, but payer requires trial of adalimumab OR etanercept first. |
| 41 | Daratumumab | Oncology | CignaCare | Incorrect Place of Service | Multiple Myeloma; submitted as self-administered, but requires administration in a clinic. |
| 42 | Belimumab | Rheumatology | Aetnalogic | Lack of Medical Necessity | Lupus case; required anti-dsDNA or anti-Smith antibody results were not provided. |
| 43 | Idecabtagene vicleucel | Oncology | MedSecure | Not a Covered Benefit | Myeloma case; CAR-T auth submitted to pharmacy benefit manager instead of the medical benefit manager. |
| 44 | Erenumab | Neurology | Unified Health | Step Therapy Required | Migraine; patient failed two triptans, but policy also required trial of a TCA or anticonvulsant. |
| 45 | Ramucirumab | Oncology | StateCare | Policy Misalignment | Gastric cancer case; submitted for a combination not listed in payer’s compendium sources. |
| 46 | Tildrakizumab | Dermatology | CignaCare | Step Therapy Required | Psoriasis; clear history of phototherapy failure, but no documented trial of acitretin or methotrexate. |
| 47 | Enfortumab Vedotin | Oncology | Aetnalogic | Lack of Medical Necessity | Bladder cancer case; no documentation of prior failure of platinum chemo and a checkpoint inhibitor. |
| 48 | Baricitinib | Rheumatology | MedSecure | Step Therapy Required | RA case; excellent documentation of 2 TNF inhibitor failures, but requested JAK inhibitor is non-formulary. Formulary requires Xeljanz to be used first. |
| 49 | Sacituzumab Govitecan | Oncology | Unified Health | Information Requested Not Received | TNBC case; Payer requested date of progression on last therapy, no response from clinic. |
| 50 | Dupilumab | Pulmonology | StateCare | Lack of Medical Necessity | Asthma case; submitted with eosinophil count, but payer also requires documented FEV1 and exacerbation history. |
23.5.3 The Task, Part 1: From Stated Reason to True Root Cause
Your first task is to perform the analysis. You must look past the generic “Stated Denial Reason” provided by the payer and identify the True Root Cause—the specific internal process failure that led to the denial. For example, a denial for “Lack of Medical Necessity” is vague. The root cause might be that the oncology clinic forgot to attach the required biomarker report. That is the problem you can solve.
Categorize each of the 50 denials into one of the five Root Cause Buckets defined below. This will require you to read the clinical snippet and make an informed judgment.
The Five Root Cause Buckets
1. Documentation Deficit
The submission was missing a critical piece of objective clinical evidence required by the policy (e.g., a lab report, pathology result, imaging report, specific score from a note).
2. Incomplete Step-Therapy History
The submission did not provide a complete history of prior medication failures as required by the payer’s formulary ladder.
3. Policy & Formulary Misalignment
The requested drug/indication was outside of the payer’s established coverage policy, formulary, or supported compendia. This includes requesting a non-formulary drug when formulary options haven’t been exhausted.
4. Administrative / Procedural Error
The denial was caused by a non-clinical error, such as submitting to the wrong benefit (pharmacy vs. medical), using an incorrect diagnosis/procedure code, or a simple data entry mistake.
5. External / Patient-Related Factor
The denial was caused by factors outside the clinic’s direct control, such as a lapse in the patient’s insurance coverage or a plan exclusion for an entire class of drugs.
23.5.4 The Task, Part 2: Quantify the Findings
After categorizing all 50 denials, your next step is to quantify your findings. You must create a summary that would be clear and impactful for a non-clinical leader, like a hospital finance executive. Create a summary table showing the number and percentage of denials in each category. Then, create a visual representation of this data.
Denial Analysis Summary
| Root Cause Category | Number of Denials | Percentage |
|---|---|---|
| 1. Documentation Deficit | 22 | 44% |
| 2. Incomplete Step-Therapy History | 11 | 22% |
| 3. Policy & Formulary Misalignment | 8 | 16% |
| 4. Administrative / Procedural Error | 6 | 12% |
| 5. External / Patient-Related Factor | 3 | 6% |
| TOTAL | 50 | 100% |
Denials by Root Cause
Documentation Deficit
44%
Incomplete Step History
22%
Policy Misalignment
16%
Administrative Error
12%
External Factor
6%
Drawing Your Conclusion
The data tells a powerful story. 44% of all high-value denials—nearly half—are caused by simply failing to attach the right clinical documents. These are the most preventable denials. Another 22% are due to not providing a complete step-therapy history. This means that a staggering 66% of these denials are not related to the patient being ineligible, but to a failure in our internal process of collecting and presenting information. This is your key finding. This is the “burning platform” you will use to justify your strategic plan to leadership.
23.5.5 The Task, Part 3: The Strategic Plan for Denial Prevention
This is your final deliverable. Based on your root-cause analysis, you must now create a formal strategic plan. This plan should be clear, concise, and focused on actionable solutions. It should be written for an audience of hospital executives who care about patient care, operational efficiency, and financial outcomes.
Template: Strategic Plan for High-Value Drug Denial Reduction
To: University Health System Leadership Council
From: [Your Name], PharmD, Lead Prior Authorization Pharmacist
Date: [Today’s Date]
RE: A Strategic Plan to Reduce High-Value Medication Denials and Improve Time-to-Therapy
1. Executive Summary
An analysis of 50 recent high-value medication denials reveals that two-thirds (66%) are caused by preventable, internal process failures, primarily related to incomplete clinical documentation. These denials lead to significant delays in patient care, place a heavy administrative burden on our clinical teams, and result in millions of dollars in delayed or lost revenue. This proposal outlines a targeted, multi-pronged strategy focused on proactive education, workflow optimization, and technology enablement to address the root causes of these denials, with a goal of reducing preventable denials by 50% within six months.
2. Root-Cause Analysis of Recent Denials
[Insert the summary chart and table you created in the previous step here.]
Our analysis indicates that the overwhelming majority of denials are not due to patients being clinically ineligible for therapy, but rather due to failures in how we collect and transmit the necessary supporting evidence to payers.
3. Proposed Interventions by Root Cause
A. Intervention for “Documentation Deficit” (44% of Denials)
- Initiative 1.1: Develop “PA Packets.” For the top 20 highest-volume/highest-denial drugs (e.g., Pembrolizumab, Dupilumab), we will create EMR-integrated, disease-specific checklists. These “PA Packets” will prompt the clinical team (MA or nurse) to gather all required documentation (e.g., pathology, biomarkers, lab results) *before* the PA request can be routed to the pharmacy team. This shifts documentation gathering from a reactive, post-denial activity to a proactive, pre-submission requirement.
- Initiative 1.2: Pharmacist-Led Education. The PA Pharmacy team will conduct quarterly, 30-minute training sessions for MAs and nurses in high-volume clinics (Oncology, Rheumatology, Derm) on “How to Build a Bulletproof PA.” This will focus on the specific documents required for their most-prescribed drugs.
B. Intervention for “Incomplete Step-Therapy History” (22% of Denials)
- Initiative 2.1: Create “Step Therapy SmartPhrases.” In collaboration with IT, we will create EMR SmartPhrases (.StepFailRA, .StepFailMS, etc.) that can be pulled into a progress note. This template will prompt the physician to document a structured medication history, including drug name, dose, dates, and a specific, policy-compliant reason for failure (e.g., lack of efficacy evidenced by CDAI score, intolerance evidenced by LFTs). This creates a clean, copy-pasteable history for the PA submission.
C. Intervention for “Policy & Formulary Misalignment” (16% of Denials)
- Initiative 3.1: “Formulary Alerts” at Point of Prescribing. We will work with IT to build targeted EMR alerts. When a provider attempts to order a known non-formulary agent (e.g., Baricitinib when Xeljanz is preferred), an alert will fire that says, “This is a non-formulary agent. UHA insurance requires a trial/failure of Xeljanz first. Proceeding with this order will likely result in a denial.” This allows for a course correction before the PA process even begins.
D. Intervention for “Administrative / Procedural Error” (12% of Denials)
- Initiative 4.1: Develop a “Benefit Quick Reference Guide.” The PA Pharmacy team will create and maintain a one-page guide for complex drugs like CAR-T therapies that clearly indicates whether they fall under the Medical or Pharmacy benefit for our top 5 payers, preventing misrouted submissions.
4. Implementation Plan & Metrics for Success
- Phase 1 (Months 1-2): Develop PA Packets and SmartPhrases with IT and clinical champions.
- Phase 2 (Month 3): Pilot interventions in Oncology and Rheumatology clinics. Conduct initial education sessions.
- Phase 3 (Months 4-6): System-wide rollout. Begin tracking metrics.
- Metrics: We will track the overall denial rate for targeted drugs, the average time from prescription to approval, and staff satisfaction surveys. Our goal is a 50% reduction in preventable denials within 6 months.
5. Conclusion & Return on Investment
By investing in these proactive, system-based solutions, we can significantly reduce the number of patients experiencing care delays, decrease the administrative rework burden on our highly-trained clinical staff, and capture revenue more effectively. This plan transforms the prior authorization process from a reactive, manual, and frustrating series of tasks into a streamlined, reliable, and efficient system that better serves our patients and our organization.
