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MODULE 13: THE BUSINESS OF VALUE: CONTRACTS & REIMBURSEMENT
Section 13.3: Clinical and Economic Data Requirements
The Data Spine of VBC: From Claims and Labs to PROs and SDOH
SECTION 13.3
Clinical and Economic Data Requirements
Building the “Single Source of Truth” to Prove Your Value.
13.3.1 The “Why”: Data is the Currency of Value-Based Care
In your traditional Fee-for-Service practice, data serves one primary purpose: billing. The data you generate—an NDC, a quantity, a CPT code for an MTM—is effectively a receipt. It is a transactional record used to justify a payment for an activity. Its job is to answer the question, “What did you do?”
In a Value-Based Care contract, this entire premise is inverted. Data is no longer the receipt for the transaction; data is the product itself. It is the currency you use to purchase your reimbursement. Its job is to answer a fundamentally different question: “What did you achieve?”
Without timely, accurate, complete, and trustworthy data, your VBC contract is just an empty promise. You cannot track your patient cohort, you cannot measure your performance, you cannot prove your outcomes, and you absolutely cannot get paid. The most brilliant clinical pharmacist intervention is worthless in an OBA if it cannot be measured and reported. In this model, if it wasn’t documented, it didn’t happen. If it wasn’t measured, it didn’t improve.
In Module 12, we discussed the “how” of data infrastructure—the pipes, platforms, and security. Now, in this section, we focus on the “what.” We will define the specific, essential data elements you must acquire to satisfy the terms of a VBC contract. You will learn to stop thinking like a dispenser and start thinking like a clinical trial investigator, meticulously gathering the evidence needed to prove your case to the payer.
Pharmacist Analogy: The Dispensing Log vs. The Clinical Trial Case Report Form (CRF)
Imagine your pharmacy is asked to participate in a phase IV clinical trial for a new diabetes drug. You can’t just dispense the drug and send in your receipts. The sponsor sends you a 50-page binder called a Case Report Form (CRF). This is your data bible.
Your FFS Dispensing Log (Your “Receipt”):
It proves activity. It contains:
- Patient Name: John D.
- Drug: Metformin 1000mg, #60
- Date: 10/24/2025
- Copay: $10
Your VBC “Case Report Form” (Your “Evidence”):
It proves an outcome. To get paid your $1,000 success fee, your OBA contract requires this CRF to be filled perfectly:
- Patient: John D. (Attributed Member ID: 345B-12)
- Cohort Inclusion: Baseline A1c 9.8% on 07/15/2025 (LOINC: 4548-4).
- Intervention: CMM performed 07/20/2025. (CPT: 99605).
- Intervention Note: “Recommended adding SGLT2i. Coordinated with PCP. Patient agreed.”
- Adherence: PDC for SGLT2i at 6 months = 92%. (Pharmacy Claim Feed).
- SDOH Screen: Patient reports transportation barriers. (Z-Code: Z59.8).
- Outcome Metric: Follow-up A1c 7.9% on 01/18/2026. (LOINC: 4548-4).
- Result: Success. (A1c < 8.0% target met).
- Payment: $1,000 success fee earned.
This section is your guide to building that Case Report Form. Every VBC contract you sign is, in effect, a real-world clinical trial. You are the Principal Investigator, and your data is the only thing that will get your “study” published and paid.
13.3.2 The Four Pillars of VBC Data: A Conceptual Framework
No single data source is sufficient for a VBC contract. You cannot prove an A1c reduction (a clinical outcome) using only pharmacy claims, and you cannot prove an adherence score (a process metric) using only EMR data. Success requires you to build a longitudinal patient record by combining data from four distinct pillars. Your mastery as a VBC pharmacist will be defined by your ability to acquire, integrate, and analyze all four.
Pillar 1: Claims Data
(The “What, When, & Where”)
Data generated after a care event for billing. It tells you what happened, when it happened, and where it happened.
Examples: Pharmacy Claims (NDC, Fill Date), Medical Claims (ICD-10, CPT, Place of Service).
Pillar 2: Clinical Data
(The “How Sick & How Well”)
Data generated during a care event. It is the “ground truth” of a patient’s physiological state.
Examples: Lab Values (A1c, INR, SCr), Vitals (BP, Weight), EMR Problem Lists (LVEF).
Pillar 3: Patient-Generated Data
(The “Why”)
Data that only the patient can provide. It explains the “why” behind their behavior and clinical results.
Examples: Patient-Reported Outcomes (PROs like PHQ-9), Adherence Barriers, SDOH data (food, transport).
Pillar 4: Cost Data
(The “How Much”)
Proprietary financial data from the payer that shows the actual cost of care. This is essential for all shared savings and economic OBAs.
Examples: Allowed Amount, PMPM (Per Member Per Month), Total Medical Spend.
13.3.3 Masterclass Deep Dive: Pillar 1 – Claims Data (The “Receipts”)
Claims data is your foundational layer. It is the most standardized, accessible, and complete dataset for an entire population. It is excellent at telling you what happened, but terrible at telling you why. As a pharmacist, you must become an expert at reading and interpreting these data feeds, as they are the source for all adherence metrics and many economic outcomes.
Masterclass Table: Decoding Pharmacy Claims for VBC
| Data Element | Example | VBC Contractual Use & (Tutorial) |
|---|---|---|
| 2025-10-24 |
Primary Use: Calculating Adherence (Proportion of Days Covered – PDC) This is the most common P4P and OBA “process” metric. The contract will state: “Success = PDC $\ge$ 80% for all members on an oral diabetes medication.” Tutorial: How to Calculate PDC
$$PDC = \frac{\text{Number of Days Covered in Period}}{\text{Days in Period (e.g., 365)}}$$
$$PDC = \frac{330 \text{ Days Covered}}{365 \text{ Days}} = 90.4\% \text{ (Success)}$$
|
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| 00071-0156-23 | ||
| 30 | ||
| 30 | ||
| $15.00 |
Primary Use: Tracking Financial Metrics & SDOH Barriers Economic Metrics: Used in pharma-led OBAs to track total drug spend. “Did NewDrug-A (Plan Cost $5000) reduce total medical spend by more than OldDrug-B (Plan Cost $500)?” SDOH Signal: A high “Patient Cost Share” is a key data point for your CMM. A $150 copay is not just a number; it’s an adherence barrier. You use this data to flag patients for financial assistance programs. |
|
| $250.80 |
Masterclass Table: Decoding Medical Claims for VBC
| Data Element | Example | VBC Contractual Use & (Tutorial) |
|---|---|---|
| I50.9 (Heart Failure, Unspecified) |
Primary Use: Identifying Patient Cohort This is how you define your population. The OBA contract will state: “This agreement applies to all attributed members with $\ge$ 2 medical claims bearing an ICD-10 diagnosis of I50.xx (Heart Failure) in the last 12 months.” |
|
| 99223 (Initial Hospital Care, Day 1) |
Primary Use: Identifying Interventions & Baseline Events This tells you what was done. You can use it to find your baseline (e.g., “Find all patients with CPT 99223 to identify the start of a hospitalization”) or to track competing interventions. |
|
| ’21’ (Inpatient Hospital)
’23’ (Emergency Room) ’11’ (Provider Office) |
Primary Use: Measuring Economic Outcomes (The “Holy Grail”) Tutorial: How to Prove an “Avoided Hospitalization”
$$Reduction = \frac{(\text{Baseline} – \text{Performance})}{\text{Baseline}}$$
$$Reduction = \frac{(100 – 80)}{100} = 20\% \text{ (Success)}$$
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The VBC Killer: “Claims Lag”
You must understand this limitation, or you will fail. Claims data is slow.
A patient is discharged from the hospital on October 1st. The hospital’s billing department might not submit the claim to the payer until November 15th. The payer might not process and finalize that claim until December 10th. It might not appear in your data feed until January 1st.
This 30-90 day “claims lag” means that claims data is always retrospective. It’s a history report, not a real-time feed.
Clinical Impact: You cannot use claims data for proactive interventions. You will find out about a patient’s hospitalization 60 days after they were discharged, which is far too late to perform a post-discharge med rec and prevent a 30-day readmission.
The Solution: You MUST use claims data for your final economic reconciliation, but you need a different, real-time data source (like an ADT feed, covered next) to manage your patients day-to-day.
13.3.4 Masterclass Deep Dive: Pillar 2 – Clinical Data (The “Ground Truth”)
This is the data that excites clinicians. It’s the “ground truth” of a patient’s health: their labs, their vitals, their diagnoses. In FFS, you hoped you could get this data by calling a doctor’s office. In a VBC contract, you must get this data. It is the only way to measure a clinical outcome.
The Problem: This data does not live with the payer. It lives in thousands of separate, siloed EMRs (Epic, Cerner, Allscripts, eClinicalWorks) that famously do not talk to each other or to your pharmacy system.
The Solution: Your OBA contract must solve this interoperability problem. As we discussed in 13.2, you must contractually define your “source of truth” for clinical data. This is a non-negotiable prerequisite.
Solving the Clinical Data Problem: The “How-To” Guide
When negotiating the OBA, you have four primary options for getting clinical data. You must get one of them in writing.
- Payer as Aggregator (Easiest for You): The payer (e.g., Aetna) uses its leverage to get data feeds from all major labs (Quest, LabCorp) and health systems. They aggregate this data and provide it to you in one clean, simple feed. This is the ideal.
- Direct EMR Access (Common in Health Systems): If your pharmacy is part of an ACO or health system, you get read-only access to the system’s EMR (e.g., Epic). You can look up your patients’ lab values directly. This is highly effective but labor-intensive (the swivel chair method).
- HIE Connection (The Future): You connect your pharmacy platform to a regional or state Health Information Exchange (HIE). This allows you to “query” the HIE for your patient’s labs from any connected provider in the area. This is powerful but has technical costs and setup.
- ADT Feeds (The “Real-Time” Signal): This is the most actionable data. An ADT (Admit, Discharge, Transfer) feed is a real-time “ping” from a hospital’s EMR that tells you the moment your patient is admitted or discharged. This is the data you need to trigger your proactive med rec and prevent a readmission.
Masterclass Table: Leveraging Clinical Data for OBA Metrics
| Data Type | Key Elements | VBC Contractual Use & (Tutorial) |
|---|---|---|
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Primary Use: Measuring Clinical Outcomes (A1c, INR, Cholesterol) Tutorial: Proving an A1c Reduction OBA
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Primary Use: Measuring Clinical Outcomes (BP) This is harder, as BP is not a single lab value but a snapshot in time.
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13.3.5 Masterclass Deep Dive: Pillar 3 – Patient-Generated & Operational Data (The “Context”)
This is the data that explains the “why” behind the numbers from Pillars 1 & 2. A claim shows a patient didn’t refill their statin. A lab shows their LDL is 250. Why? This pillar tells you: “Patient reports $150 copay and cannot afford it” or “Patient believes statins will harm their liver.”
This data does not exist anywhere. You, the pharmacist, must create it. It is generated by your CMM platform, your adherence conversations, and your clinical documentation. This data is your #1 tool for managing risk.
Masterclass Table: Creating Data to Manage Risk
| Data Type | How to Generate It | VBC Contractual Use |
|---|---|---|
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Administering validated, standardized surveys to patients at baseline and follow-up.
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This can BE the OBA metric.
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Integrating SDOH screening (e.g., the “PRAPARE” tool) into your CMM workflow.
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This is your #1 Risk Mitigation Tool.
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This is your own clinical documentation, structured in a reportable way.
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This is your proof of attribution.
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13.3.6 Masterclass Deep Dive: Pillar 4 – Cost Data (The “CFO’s View”)
This is the most proprietary and sensitive data. You will never generate this data yourself; it is provided by the payer and is the entire basis for Shared Savings models and economic OBAs. You must learn to speak this language to justify your existence to the C-Suite.
Masterclass Table: The Language of Cost
| Data Type / Metric | How It’s Calculated | VBC Contractual Use |
|---|---|---|
| The sum of ALL medical and pharmacy claims “allowed amounts” for a patient in a given period. | This is the master number. All shared savings contracts are based on lowering the TCOC for a population. | |
| $$ \frac{\text{Total Cost of Care}}{\text{Number of Members in Cohort} \times \text{Number of Months in Period}} $$ |
This is the unit of cost in VBC. It normalizes cost across time and population size.
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| $$ \frac{\text{Total Medical & Pharmacy Claims Cost}}{\text{Total Premiums Collected by Payer}} $$ |
This is the payer’s master performance metric. The ACA mandates that plans spend 80-85% of premiums on care (an MLR of 80-85%).
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13.3.7 Putting It All Together: A Sample OBA Data Dossier
Let’s build the complete “Case Report Form” for a complex, high-value OBA. This shows how all four pillars must work in perfect harmony.
Case Study: The Post-Discharge Heart Failure OBA
The Contract: A Provider-Led OBA with a local health system.
The Goal: “Reduce 30-day all-cause readmissions by 25% for the attributed HF population.”
The Payment: “$2,000 success fee paid to the pharmacy for each readmission avoided below the 25% target.”
| Required Task | Data Pillar | Specific Data Elements Needed | Source of Data |
|---|---|---|---|
| Clinical (Real-time) | ADT Feed: “Discharge” ping with an ICD-10 of ‘I50.xx’. | Hospital EMR (via HIE or direct access) | |
| Clinical + Patient-Generated | EMR Data: Discharge med list, LVEF, baseline SCr. PRO Data: Patient-reported daily weights, diet, adherence barriers. |
Hospital EMR + Your CMM Platform | |
| Claims (Retrospective) | Medical Claims Feed: Query for any `POS = ’21’` (Inpatient) with an admission date within 30 days of the baseline discharge date. | Payer’s Claims Feed | |
| Operational (Your Data) | Intervention Logs: “Post-discharge med rec completed in 48h,” “Lisinopril dose optimized,” “Patient educated on 2g sodium diet.” | Digital CMM Platform||
| Patient-Generated + Claims | SDOH Data: “Patient has no transportation for follow-up” (Z59.8). Payer Data: “Patient disenrolled on Day 15,” “Patient entered hospice.” |
Digital CMM Platform + Payer’s Eligibility File | |
| Claims + Cost Data | Baseline: 100 readmissions last year. Performance: 70 readmissions this year. Result: 30% reduction (Target met). 5 readmissions avoided below target. 5 x $2,000 = $10,000 payment. |
Payer’s Final Reconciled Claims Data |
13.3.8 Conclusion: Data is Your Advocate and Your Business
In Fee-for-Service, data is a burden—a set of fields you must fill out to get your $1.50 dispensing fee. It is an administrative afterthought.
In Value-Based Care, data is your advocate. It is the silent, objective witness that stands up to the payer and says, “This pharmacist’s intervention saved you $15,000. This pharmacist’s coaching got the A1c from 10% to 8%. Pay them what they are worth.”
A pharmacist who cannot get this data, integrate this data, and analyze this data is invisible in the world of VBC. It doesn’t matter how great your clinical skills are. If you can’t prove it, you can’t get paid for it. This is why the concepts in Module 12 (infrastructure) and this section (data requirements) are the absolute foundation of your advanced practice.
Now that we understand the “what”—the specific data we need to hunt for—the next section (13.4) will focus on the “how.” How do we operationally implement a program to track these patients? And most importantly, how do we conduct the final, high-stakes financial reconciliation to ensure we get paid every dollar we have earned?
