Third Party Collection Program Initiatives:

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• Third Party Collection Program Initiatives
• Leveraging Technology and Best Business Practices
• Tripler Army Medical Center
• Madigan Army Medical Center

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Agenda

• Purpose
• Tripler Army Medical Center
• Madigan Army Medical Center
• Overview
• Initiatives (3)
• Questions

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Purpose

• This information brief is designed to share Third
  Party Collection Program (TPCP) initiatives with
  the field from the perspective of two Army
  medical centers
• Tripler Army Medical Center (TAMC), Honolulu, HI
• Madigan Army Medical Center (MAMC), Ft. Lewis, WA

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Tripler Army Medical CenterHonolulu, HI
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Revenue Cycle Management
What does it mean to you?
Registration
Documentation
Claims/Denials Management
Insurance Verification
Contract Management
Coding/Compliance
Utilization Management
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Revenue Cycle Management
Different things to different people...
a mindset to improve health processes affecting
the bottom line
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What to Do about the Trends?
Third Party Collection Trends
Interdependent Revenue Initiatives

• TPC is lt20 of Tripler Reimbursements

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Initiatives Improve Processes
FY06 initiatives
Established a contract for remote discovery of
insurance on on all APV, inpatient Surgery and
high cost procedures Obtain insurance handbooks
for all local insurance carriers
Hire GS Nurse CHCS Adhoc Reports-ER patient list,
Surgical/Ambulatory Procedure Visits UM
Nurse/Clinical Team to document medical necessity
Established a contract for denial management
software Consultant added to evaluate 5 years
worth of claims Posted denials in TPOCs for last
six years Trained GS staff to manage claims since
2006
Unique approach
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Initiatives Return on Investment
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Third Party Collection Program
Moving in the Right Direction?
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Madigan Army Medical CenterFt. Lewis, WA
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Madigan Army Medical Center TPC Overview

• MAMC is located in Tacoma, WA
• gt1 million outpatient encounters per year
• 12,000 dispositions per year
• 100,000 beneficiaries
• 14 TPC Staff Members
• Collection
• Average 5.2 million
• FY07 6.3

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MAMC OHI Discovery

• 2569 Program is Unproductive
• Competing interests
• Least paid/least trained personnel
• Barriers to success
• Data quality
• eOHI Discovery
• Outsourced to Signature Performance
• Remove patient and clerk from process
• Followed by phone verification

TPC Myths
it will raise my insurance
clerk training
cant be bothered
bad policy data
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MAMC OHI Discovery - Results

• Initiated 1 Sep 07
• Pre-Contract (4 mos)
• 150 New OHI
• Post-Contract (4 mos)
• 2142 positive hits
• 50 per day
• Return on Investment (ROI)
• Cost 10,710 or 5 per hit
• Benefits
• Billed 100,074
• Collected 25,979
• Plus future encounters!

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MAMC OHI Discovery- Implementation

• Issues
• Slow at first
• Duplicates
• Minimal time left on policy
• Victim of your own success
• Keys to implementation
• Identify your top payors
• Establish business rules and expectations up
  front
• Phone verification
• Communicate with your contractor

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MAMC Lab/Rad Procedure Tools

• Problem Long-standing issue of inability for
  lab and Rad systems to link their procedures with
  the primary care visit required for billing.
• Often long gaps between initial visit and follow
  on labs and rads
• Multiple systems
• Solution
• Old Biller files through multiple medical
  records systems (paper and electronic) for 30
  minutes per claim
• New Leverage Technology 2 tools
• TPB1 Ad Hoc
• Lab/Rad Matching Process

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MAMC TPB1 Ad Hoc for Lab/Rad

• Takes TPOCS raw data and using the IEN, locates
  the initial encounter Dx codes
• Key to use is AHLTA order entry (IEN)
• Reduces process from 30 minutes to 3 seconds
• Steps
• Locate the IEN number in TPOCS
• Enter IEN in CHCS TPB1 Ad Hoc
• Enter diagnosis codes

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MAMC Lab/Rad Matching Process

• Matching process for Labs/Rads for
• Encounters in TPOCS without IENs
• Labs/Rads that do not make it to TPOCS
• Complex series of data pulls, queries and
  filtering, results in clean data to be billed
• Initial run identified 143,000 in billables

Labs
Rads
Matching Process
Billable Spreadsheet
ADMs
Insurance data
SQL Dbase environment
SIT OHI Filter
raw data
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Questions