What Key Factors Should Risk Officers Consider When Using Generative AI
15_Mooney_RevenueCycle_Final
1. Revenue Cycle
Stephen M. Mooney
Senior Vice President, Patient Financial Services
2. The Story of Measuring, Monitoring, & Collecting
• Flashback to 2005 through 2007
• 2008 & beyond
• What we‟re doing to improve:
– Pre-patient care experience
– Collections & Follow-Up
• The future of PFS
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3. Flashback to 2005
Centralization
to Improve
Scale
Integrity &
Data Integrity Transparency
Business
Intelligence
2
5. A Year Ago…
• Optimize processes
• Consumer-focused
4
6. A Year Ago…
• Optimize processes
• Consumer-focused
• Shift in focus
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7. Our Vision is Maturing…
Become a full-service, revenue cycle service delivery organization
that leads the industry in seven distinct ways.
1. Maximize yield of the revenue cycle in alignment with our
customers‟ missions
2. Utilize business intelligence to drive our decisions
3. Drive innovation into the healthcare industry revenue cycle
4. Be an employer of choice for the best talent in the healthcare
industry
5. Provide superior service to our customers, on par with the best
service delivery organizations in the world
6. Make the patient experience with the revenue cycle as
transparent, integrated and easy to navigate as possible
7. Make our services a positive differentiator with physicians
for the customers we serve
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8. We Can Drive Volume and Satisfaction…
High Being kept
Scheduling
informed
appointments
Ease of
Timeliness of
billing
Supportive
Importance to
appointments
environment
physicians in
determining
Convenience
where to send
for the
patients Ease of
patient registration
Room
Value for amenities
money
Common
areas
Aligned on importance
Room options
Not aligned on importance
Low
Low High
Importance to patients for
determining future visits
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Source: 2007 McKinsey Patient Experience Survey; 2007 McKinsey Physician Survey Regarding Patient Experience
10. Continued Improvements in Patient Access
More focus on Patient Access drives our
ability to…
• Make it easy to do business with Tenet
• Improve the patient experience
• Reduce bad debt and increase cash
QA &
Rapid Online
CPAS Pricing
Registration Bill Pay
Tools
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11. Center for Patient Access Services (CPAS)
Implementations finishing in our new Pre-Service Center
1 Hospital schedules patient 2 CPAS processes the account
Center for Patient
Access Services
Certification &
Checks (ABN)
Verification &
authorization
Pre-Register
Pre-Service
Counseling
Insurance
Necessity
Eligibility
Financial
Medical
Pre-
Pre-
Payors Payors Payors
Patients
Payors Payors Payors
™
3 Patient arrives and goes through an
expedited check-in at the hospital
QA &
Rapid Online
CPAS Pricing
Registration Bill Pay
Tools
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12. CPAS Progress as of Q1 2008
Percent of Accounts Percent of Accounts 24-Month Change in
Pre-Registered Verified POS Collections
60% 90% 25%
80%
50%
20%
70%
40% 60%
15%
50%
CPAS
30%
CPAS
40%
CPAS
Non-CPAS
10%
Non-CPAS
20% 30%
Non-CPAS
20% 5%
10%
10%
0% 0% 0%
Source: Corporate Patient Access Scorecard, through March 2008. Comparison of “Y” CPAS vs. “N” non-CPAS hospitals. POS
improvement based on Q1-08 vs. Q1-06 change in actual dollars collected at Point-of-Service; Pre-Registration and Verification
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metrics based on actual number of accounts in Q1-08
13. Quality Assurance (QA) & Pricing Tools
Q1-2008 Quality Improvements
• New QA tool alerts 100%
Registration if inaccurate 90%
data is entered 80%
70%
• Reduced QA staff by >50% 60%
50%
40%
• Standard tools calculate 30%
patient-liability balances 20%
10%
0%
Insured Name
Insured Name
Documentation
Documentation
• Written estimates given to
Complete
Complete
Match
Match
Auth
Auth
patients
Medicaid HMO Managed Care Medicaid Medicare
• Automatic processing of
applications for funding
QA &
Rapid Online
CPAS Pricing
Registration Bill Pay
Tools
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14. Rapid Registration: Kiosk & e-Signature
• 3 sites piloted
beginning
December 2007
• 87% reduction in
paper used during
registration
West Boca: Desktop Park Plaza: Wall Mount
• 30% initial
improvement in
cycle time
• 3 minute average
check-in time
Lake Pointe: Free Standing All: Tablets
QA &
Rapid Online
CPAS Pricing
Registration Bill Pay
Tools
13
16. Rapid Registration: Kiosk & e-Signature
Patients can sign forms
electronically, which are
automatically fed into our
imaging system
Later in 2008 patients
will be able to make
co-payments directly
at the kiosk
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17. Online Bill Pay
QA &
Rapid Online
CPAS Pricing
Registration Bill Pay
Tools
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19. PFS Segmentation is Gaining Momentum…
We are collecting about $9 million more per quarter than our average collections in the pre-
redesign period. About $15 million per quarter has been accelerated out of bad debt into
collections in active A/R. While net patient billed dollars have declined 34% due to Compact
and divestitures.
Early Out/CFC Total Cash Collections, 2004 – 2008 Q1
$100 $500
Early Out
$90 $450
Growth
CFC
Q1 2008
Net Patient Bills
$80 $400
vs.
$70 $350
Q1 2004
Collected $
$60 $300
Billed $
EO
$50 $250
+49%
$40 $200
$30 $150
Total
$20 $100
+11%
$10 $50
$0 $0 CFC
Q1 2004
Q2 2004
Q3 2004
Q4 2004
Q1 2005
Q2 2005
Q3 2005
Q4 2005
Q1 2006
Q2 2006
Q3 2006
Q4 2006
Q1 2007
Q2 2007
Q3 2007
Q4 2007
Q1 2008
(-44%)
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20. MicroSegmentation™
• PFS employs an in-house PhD statistician
• Unlimited number of custom models can be
implemented
• Models can be continuously “tuned” with most
recent actual data
– Easy to identify macroeconomic trends and adjust work
processes to compensate
– Quick response to shifts in payor behavior
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21. MicroSegmentation™ MicroSegmentation™
(44 variables)
New insurance:
- payor variables
- Clinical/service
details
- Denial/dispute
details
New self pay:
Original - Census block data
Segmentation - Credit report detail
- Prior visits &
(8 variables) payments
Original self pay:
Original self pay:
- Credit Score
- Credit Score
- Visit Variables
- Visit Variables
- Demographics
- Demographics
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22. MicroSegmentation™
• 99% of payments come from 71% of patients
New model
much better at
identifying the
Comparison of Tenet Segmentation Models non-paying
Early Out Self Pay accounts
100%
90%
Near-perfect
prediction for
80%
Accounts With Payment
30% of paying
population
70%
60%
50%
40%
Microsegmentation™
30%
Original Segmentation
20%
Random
10%
Theoretical Max
0%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Total Population
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23. MicroSegmentation™
• Our pilot model was secondary bad debt self pay accounts
• Significant improvement in predictive strength
Comparison of Tenet Segmentation Models
Secondary Bad Debt Placements
100%
At the 10th percentile
MicroSegmentation™ captures
90%
45.6% of good accounts vs.
25.7% under original model
80%
Accounts With Payment
77% Improvement!
70%
60%
50%
40%
30%
Microsegmentation™
20%
Original Segmentation
10%
Random
0%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Total Population
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24. Next Iteration – Managed Care
• MicroSegmentation™ is predicting the number of
days it will take a commercial or managed care
payor to respond to an initial bill
• Opportunity is to refocus people resources to
spend time following up on claims at the optimal
point to accelerate cash and reduce aging
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25. Distribution of Predicted Follow Up Dates
• Modeling shows that about 45% of accounts should be
worked by day 28 and 60% by day 34
Predicted Follow Up Date
30000
25000
20000
Claim Volume
15000
10000
5000
0
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44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
Days from Bill Date
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26. Insurance Follow Up Model Variables
• The MicroSegmentation™ Major Insurance Payor
(Blue Cross, United, etc.)
Payor‟s Zip Code
process identified 15 data (regional payor claims processing differences)
Category of Services Rendered
Hospital
elements as statistically Financial Class
(contracted vs. non contracted payors; managed government vs. managed care)
significant based on regression Expected Reimbursement from Payor
Type of Insurance Product
(HMO, PPO, etc.)
analysis of recent actual Tenet Length of Stay in Hospital
Managed Care IPA Group
data (IPA may pay managed care bills rather than the payor)
Hospital Department
DRG Primary Illness Category
• Insurance tree has 4,200+ Inpatient or Outpatient
Pass Through Flag
(contract requires copies of invoices for medical equipment)
branches and leaves which are Emergent or Non-Emergent Services
Days from Discharge for Initial Bill to Payor
different possible outcomes
Example MicroSegmentation™ Tree with 1,000 Leaves
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27. Validating the Model
• 22,000 accounts have been modeled and have had enough time to
measure accuracy of predictions
• ~70% of accounts paid on or before the expected date
Actual Payment Date vs. Predicted Date
75%
% of Claims Paid
50%
25%
0%
or Before
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Paid On
+ + + + + + + + +
+ + + + + +
Paid On or Before
Predicted Date
Variance (in Days) between Actual Payment Date and Predicted Date
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28. What does MicroSegmentation™ Mean?
• Optimized use of resources based on scientific
models
• Ability to focus on resolving billing issues quickly
• Patients experience shorter delays in
copay/deductible billing when there is an issue
to be resolved with the payor
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29. Continuing the Focus on Physicians
and Patients
Initiatives Driving
High Being kept
Scheduling
Satisfaction
informed
appointments
• CPAS
Ease of
Timeliness of
• Quality Assurance
billing
Supportive
Importance to
appointments
environment
physicians in
• Pricing Estimates &
determining
Convenience
where to send Point of Service
for the
patients Ease of Collections
patient registration • Rapid Registration
Room
Value for • Online Bill Pay
amenities
money
Common
• Segmentation &
areas
MicroSegmentation™
Room options
Low
Aligned on importance
Low High
Not aligned on importance
Importance to patients for
determining future visits
28
Source: 2007 McKinsey Patient Experience Survey; 2007 McKinsey Physician Survey Regarding Patient Experience
30. Continued Momentum & Efficiencies…
Across our hospitals, A/R days Managed Care and Medicare aging are
all down, releasing significant incremental cash.
Managed Care Medicare A/R
Days1
A/R A/R Greater than Greater than 60
180 days2 days2
Q1 Q1
Q1
2003 2004 2005 2006 2007 2003 2004 2005 2006 2007
2003 2004 2005 2006 2007
2008 2008
2008
74 56 58 55 54 54 $63M $40M $28M $13M $15M $34M
N/A $481M $357M $324M $247M $217M
Overall Reduced Reduced
reduction MC A/R by MCR A/R
of 20 days $264M or by $29M
or 27% 55% or 46%
1 Same store hospital only core acute facilities with prior year cost settlement for all years plus new facilities
2 Same store hospital only core acute facilities plus Rio and Pinecrest Rehab excluding Plaza Specialty, Coastal Carolina,
Centennial, Bartlett and Norris Cancer Center for all years; 2003 Managed care data not available – no detail at that level in 2003
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31. Revenue Cycle Initiatives to Decrease
A/R Days, Increase Cash Collections,
& Improve Patient Satisfaction
• Increase Point of Service (POS) Collection
• MicroSegmentation™
• Reduction in Discharged Not Final Coded (DNFC)
• Payor collaboration
• Legal action when appropriate
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33. External Business – Market Maturity: Current
Evolution of Three Outsourcing Markets
RCO’s market evolution can be best understood by analyzing the evolution of two other
outsourcing industries: ITO and HRO
I. Proof of Concept II. Growth III. Maturation
ITO
Adoption
HRO
Rate
RCO
Time
Few end-to-end offers Offers increasingly SLAs are standard
Offers standardized and industry practices
comprehensive
Consider „value‟ of offer in
Differences in acceptance, View as an accepted,
sophistication and addition to potential cost strategic component of
Customers
expectations savings their operations
Heavily fragmented Rapid consolidation of Few, large players
Providers landscape with no providers dominate market
dominant providers 32
34. External Business – Market Opportunity
2004 U.S. Hospital Market
7,000
6,556
6,000 1,146
Number of Hospitals
Less Non-Acute Care
746
5,000 Hospitals
195
4,469
Less Military and
Less Stand-
VA Hospitals
Alone Critical
4,000
Access Hospitals
2004 Net Patient
3,000
Revenue (NPR)
of addressable
hospital market
2,000
baseline ~$536B
Remaining
Addressable Hospital
Total AHA Baseline
Baseline
1,000
0
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35. External Business – Addressable Market:
Revenue Cycle Spend Estimate
Based on a conservative 4% cost-to-collect estimate, we can approximate
the revenue cycle spend for our addressable market as ~$20Bn
Estimate of Revenue Cycle Spend by Function
Patient
Cost-to- Access
2004 2004 Revenue Cycle
Operate Billing and
NPR ($B) Spend Estimate ($B)
Estimate Follow-up
27%
Patient
1% to 2% ~$5 to ~$11
46%
Access
HIM and
1% to 2% ~$5 to ~$11
Coding
AR
2% to 3% ~$10 to ~$16
Management
Total ~$536 4% to 7% ~$20 to ~$38
27%
HIM & Coding
Sources: The Monitor Group - 2006-2007 Target Market Survey, Tenet Internal Data, Modern Healthcare, Center for Medicare and Medicaid Services, AHA
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36. Closing – Roadmap
• Continuing our focus on patient and physician
satisfaction
• Driving performance improvement
• Carrying operations momentum forward through
innovation and thought leadership
• Provides an opportunity to leverage our services
in a third party market
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