Claims Reconnaissance

Phase 1: Mission Setup & Strategy

Welcome, Analyst. Your mission is to extract high-level financial intel for the C-Suite. We're bypassing granular data dumps for clean, powerful summaries. Our tool of choice is SlicerDicer—it's fast, agile, and visual. Let's get to work.

⚡ Your Weapon: SlicerDicer

This is your data exploration engine. It transforms millions of records into actionable charts and totals instantly. Master it, and you'll answer executive questions before they're even finished asking.

Phase 2: Professional Billing (PB) Data Hunt

Your primary target data model, Resolute PB Claims Cube, is offline. We'll pivot to the Resolute PB Transaction Cube. This is your strongest alternative and will yield the same intel.

Step 1: Select New Data Model

Launch SlicerDicer and load the transaction data core. This is our new point of entry.

Data Model: Resolute PB Transaction Cube

Step 2: Isolate Charges (Critical Step)

This is the most important filter. We must isolate only charge transactions to avoid summing payments or adjustments.

Slice: Transaction Type → Select: Charge

Step 3: Target Acquisition by Payer

Use the "Payer" slice to filter for our specific insurance partner.

Step 4: Isolate by Claim Status

Use the Current Claim Status slice to find claims that are on hold. Select all pre-AR statuses like Held - DNB, Held - Error, and Pre-Billed.

Step 5: Quantify the Value

Switch the "Measure" to Transaction Amount. Because we isolated charges in Step 2, this total is your accurate Metric 1. Secure it.

Step 6: Analyze the "Why"

Change "Slice By" to Claim Edit WQ or DNB Reason. This visual breakdown provides the context leadership needs. Mission objective complete.

⚠️ Contingency Plans

If the PB Transaction Cube is also unavailable, here are your fallback options:

Specialized Cubes: Search SlicerDicer for cubes with names like Claim Edit WQ or DNB Cube. These are purpose-built and even easier to use.
Reporting Workbench (RWB): Your final option. Use a template like "Unbilled Claims," filter by Payer and Workqueue, then export to Excel to get your SUM and a PivotTable breakdown.

Phase 3: Hospital Billing (HB) Data Hunt

New target, new data set. We're now hunting for high-value hospital claims in the "Candidate for Bill" workqueue. Stay sharp.

Step 1: Deploy New Session

Open a fresh SlicerDicer session. Load the HB data core to avoid cross-contamination.

Data Model: Resolute HB Claims Cube

Step 2: Re-acquire Target

Filter by "Payer" again, selecting the same insurance partner.

Step 3: Pinpoint the Workqueue

This is key. Use the "HB Workqueue" slice and select ONLY Candidate for Bill. This is our specific target.

Step 4: Quantify the Value

Switch the "Measure" to Total Charges. This is your Metric 2. Confirm and record.

Step 5: Uncover Bottlenecks

Change "Slice By" to HB DNB Error. This reveals why these accounts aren't billed. Second objective complete.

Phase 4: The Intel Report

Data secured. It's time to package our findings into a high-impact visual report. Below is a live-data mock-up of how to present your extracted intel. Clear, concise, and ready for the executive summary.