Veteran Health
Network
CDR Bard, LCDR Campbell, MAJ Ford
5 June 2012
Outline
•
Backstory / Problem
•
Abstract Network
•
Network Operation
•
Measure of Effectiveness
•
Network Analysis
•
Summary and Conclusion
2
U.S. Dept. of Veteran Affairs (VA)
VA Mission: Fulfill Lincoln’s
promise
Serve and honor America’s
Veterans
Lincoln’s Promise:
“to care for him who shall
have borne the battle, and
for his widow, and his
orphan”
3
VA 2011-2015 Strategic Plan
Strategic Goals
Access to Care
Optimal Value
Mindful of President
Lincoln’s promise
4
Veteran Health Administration (VHA)
Largest integrated health
care system in United States
152 medical centers
1400 community-based
outpatient clinics
21 Veteran Integrated
Service Networks (VISNs)
Meets needs of 8.3 million
Veterans each year
5
VA Sierra Pacific Network
•
VISN-21 serves 1.2 million Veterans in northern
and central California, northern Nevada, Hawaii,
the Philippines, and Guam
•
Consists of 40 sites across six Systems
•
Each Health Care System is sub-network of
larger VISN-21 network
6
Abstract of VISN-21
Examine three independent
Health Care Systems
VA Palo Alto
VA Sierra Nevada
VA Northern California
Representative of urban,
rural and hybrid areas
7
Community Terms
•
Urban (Palo Alto):
Consists of major
population centers
•
Rural (Sierra Nevada):
Sparsely populated with a
few small urban areas
•
Hybrid (Northern CA):
Consists of major
population centers
surrounded by rural areas
8
Nodes and Edges
•
•
Nodes:
•
SUPPLY - Veteran populations by county
•
DEMAND - Treatment facilities
Edges:
•
Connect each county with network facility
•
Cost is distance in miles
9
Simplified Graph
Veterans
Treatment
Treatment
Demand
COUNTIES
CLINICS
10
Abstract of VISN-21
Siskiyou
County
1
9
2
8
VA Northern
7
California
(Hybrid)
Yreka
3
4
5
6
11
VA Northern California (Hybrid)
COUNTIES
S
U
P
P
L
Y
CLINICS
D
E
M
A
N
D
Network Analysis
•
Purpose: Provide outpatient care to Veterans
•
Data Tracked:
•
Cumulative Distance Traveled
•
Per Capita Distance Traveled (outputs)
•
Patients Assigned to Clinics
13
Measures of Effectiveness
•
•
Model allocates Veterans to treatment facilities
•
Minimum-Cost Flow Modeling
•
Minimize Veteran travel distance to treatment
Objective Function:
min S cij yij
cij: cost (distance) per unit flow
yij: number of veterans (flow) on arc
14
Assumptions
•
All eligible Vets receive care from VA System
•
One City per County for distance calculations
•
•
No population distribution for veterans in county
•
Community near geographic or population center
Health Care Systems (HCS) operate independently
•
Ability for interchange among HCSs for specialty care
•
Not modeled for simplicity and tractability
15
Modeling
•
Begin with an unconstrained model
•
Add network design constraints and evaluate responses
•
Patient limits
•
Patient limits with buffers
•
Facility closure or patient capacity reductions
•
Open a new clinic
•
Year 2030 veteran populations
16
Unconstrained Results
•
All patients go to nearest
clinic
Distance to Care
35
30
Per Capita Distance:
•
•
Urban: 13.69 miles
Hybrid: 17.37
25
Distance (miles)
•
20
15
10
5
•
Rural: 30.02
0
Urban
17
Hybrid
Network
Rural
Patient Limits
•
Capacities chosen to ensure no unmet demand
•
•
•
Urban / Suburban Outpatient Clinics
•
Capacity: 30,000 (urban / hybrid)
•
Capacity: 25,000 (rural)
Rural Outpatient Clinics
•
•
Modeled as upper bound on Clinic – Treatment Arcs
Capacity: 10,000
Hospitals
•
Capacity: 75,000 (hybrid)
•
Capacity: 50,000 (urban / rural)
18
Patient Limits Results
•
Per Capita Distance:
Distance to Care
45
•
Urban: 16.26 miles
40
35
•
Hybrid: 22.36
Rural: 40.93
30
Distance
•
25
Urban
Hybrid
20
Rural
•
20 - 35% increase
15
10
5
0
Unconstrained
Patient Limits
Model
19
Patient Limits with Buffers
•
1% buffer below capacity for all facilities
•
Allow for patient transfers
•
New sign-ups
•
Recently moved
•
Flexibility
20
Patient Limits with Buffers Results
•
Distance to Care
Per Capita Distance:
•
45
40
Urban: 16.32 miles
35
•
Hybrid: 23.0
Rural: 41.25
30
Distance
•
25
Urban
Hybrid
20
Rural
15
•
Baseline
•
Closest to Reality
10
5
0
21
Unconstrained
Patient Limits
Model
With Buffers
Budget Cuts
•
•
All HCSs must close a clinic or reduce staffing to save costs
•
Force a clinic closure in each region
•
Reduce patient limits across the board to simulate staffing cuts
Model chooses optimal clinic to close and redistributes
patients
22
Closures
Hybrid: Yreka, CA
Rural: Winnemucca, NV
Urban: Capitola, CA
23
Budget Cuts Results
•
Per Capita Distance (optimal):
Distance to Care
50
•
•
Urban: 16.99 miles
45
40
Hybrid: 23.60
35
•
Rural: 41.25
Optimal Decision
•
Urban: Staff Cuts (+0.67)
30
Distance
•
25
Urban
Hybrid
Rural
20
15
10
•
•
Hybrid: Closure (+0.60)
Rural: Closure (+1.50)
5
0
Unconstrained
24
Patient Limits
With Buffers
Model
Closure
Staff Reductions
Budget Cut Takeaways
•
•
Can safely close one clinic in each network without disruption
•
Two or more closures trigger unmet demand (untreated patients)
•
Network is efficient but vulnerable
•
Redundancy is expensive and not an efficient use of limited resources
Maximum reductions in patient capacities (staff cuts) without disruption
•
Urban: 10 percent – unmet demand
•
Rural: 5 percent – unacceptable patient assignments
•
Hybrid: 2.5 percent – unmet demand
25
Open New Clinic
•
Political Pressures
•
Can’t close a clinic and displace vets
•
Must open a new clinic in each network
•
Modeled after VA’s Rural Outreach Program
•
•
Opening new small clinics in rural, underserved areas
•
Yreka (CA) and Winnemucca (NV) are examples
Optimal choice from among three communities in each region
26
Urban
Three possible locations
Rancho Calaveras, CA
Tracy, CA
Hollister, CA
27
Hybrid
Three possible locations
Weaverville, CA
Orland, CA
Colusa, CA
28
Rural
Three possible locations
Austin, NV
Fernley, NV
Mammoth Lakes, CA
29
Open Clinic Results
•
Per Capita Distance:
Distance to Care
50
•
Urban: 16.06 miles
45
40
•
•
Hybrid: 21.92
Rural: 49.72
Reduction from Baseline
35
30
Distance
•
25
Urban
Hybrid
20
Rural
15
•
•
Urban: 0.26 (1.5%)
Hybrid: 1.08 (4.7%)
10
5
0
•
Rural: 1.53 (3.7%)
Unconstrained Patient Limits
With Buffers
Model
30
Closure
Staff
Reductions
Open Clinic
Open Clinic Takeaways
•
•
Not worthwhile in urban network
•
Slight decrease in objective function
•
No patient load decreases on full capacity clinics
Effective in hybrid and rural networks
•
Larger decreases in objective function
•
Decreased patient loads at full clinics
31
2030
•
What does the future hold?
•
•
Veteran population projections by county from the VA for 2030
•
40% reduction from current level
•
Fewer WWII, Korea, and Vietnam era vets
•
Drafts vs. Volunteer Force
Assumed all current clinics remain
•
•
Not likely to be true
Will VA system be folded into National Health Care System?
32
2030 Results
•
Distance to Care
Per Capita Distance:
•
50
45
Urban: 14.88 miles
40
•
Hybrid: 17.69
35
•
•
Rural: 32.2
Similar to Unconstrained
model results
Distance
30
25
Urban
20
Hybrid
Rural
15
10
•
•
Clinic capacities become
inconsequential
5
0
Future closures?
Model
33
Conclusion
•
Network satisfies strategic objective
•
Network resilient to limited disruption
•
Offers insight to VA network of networks
•
Project results in alignment with VA
practices
•
Flexibility for future Veteran population
34
Future Work
•
Add competing objective function(s)
•
Minimize Veteran traveling distance
•
Minimize cost per patient
•
Minimize overhead costs
•
Increase granularity
•
Determine Optimum Staffing Levels
•
Model to help VA meet strategic goals
considering 35-40% decrease in Veteran
population by 2030
35
QUESTIONS?
36
BACKUP
37
Patient Limits and Buffers Results
Urban Patient Loads
45
80000
40
70000
35
60000
Patients Assigned
Distance (miles)
Distance to Care
30
25
Unconstrained
20
Patient Limits
15
With Buffers
50000
40000
Unconstrained
30000
Patient Limits
20000
10
10000
5
0
With Buffers
0
Urban
Hybrid
Network
Rural
Facilites
Rural Patient Loads
Hybrid Patient Loads
60000
120000
50000
80000
60000
Unconstrained
Patient Limits
40000
Patients Assigned
Patients Assigned
100000
40000
30000
Unconstrained
Patient Limits
20000
With Buffers
With Buffers
10000
20000
0
0
Facilities
38
Facilities
Budget Cuts Results
Distance to Care
Urban Patient Loads
80000
45
70000
40
60000
Patients Assigned
50
Distance (miles)
35
30
Unconstrained
25
Patient Limits
With Buffers
20
15
50000
Unconstrained
40000
Patient Limits
30000
With Buffers
Closure
20000
Closure
Staff Reductions
10000
Staff Reductions
10
0
5
0
Urban
Hybrid
Network
Rural
Facilites
Rural Patient Loads
120000
60000
100000
50000
80000
40000
Unconstrained
60000
Patient Limits
With Buffers
40000
Patients Assigned
Patients Assigned
Hybrid Patient Loads
30000
Unconstrained
Patient Limits
With Buffers
20000
Closure
Closure
Staff Reductions
20000
Staff Reductions
10000
0
0
Facilities
39
Facilities
Open Clinic Results
Urban Patient Loads
45
80000
40
70000
35
60000
30
25
Unconstrained
20
Patient Limits
With Buffers
15
Patients Assigned
Distance (miles)
Distance to Care
50000
40000
Unconstrained
30000
Patient Limits
With Buffers
20000
Open Clinic
Open Clinic
10000
10
0
5
0
Urban
Hybrid
Network
Rural
Facilites
Rural Patient Loads
Hybrid Patient Loads
60000
120000
50000
80000
60000
Unconstrained
Patient Limits
40000
With Buffers
Patients Assigned
Patients Assigned
100000
40000
30000
Unconstrained
Patient Limits
20000
With Buffers
Open Clinic
Open Clinic
10000
20000
0
0
Facilities
40
Facilities
2030 Results
Urban Patient Loads
45
80000
40
70000
35
60000
Patients Assigned
Distance (miles)
Distance to Care
30
25
Unconstrained
20
Patient Limits
With Buffers
15
50000
40000
Unconstrained
30000
Patient Limits
With Buffers
20000
2030
2030
10000
10
0
5
0
Urban
Hybrid
Network
Rural
Facilites
Rural Patient Loads
120000
60000
100000
50000
80000
40000
60000
Unconstrained
Patient Limits
40000
With Buffers
Patients Assigned
Patients Assigned
Hybrid Patient Loads
30000
Unconstrained
Patient Limits
20000
With Buffers
2030
2030
10000
20000
0
0
Facilities
41
Facilities