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6/3/2015
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Identifying the Risks of Health Center Lending
Dave Kleiber, Capital Link
June 3, 2015
The CDFI Fund is an equal opportunity provider.
GoToWebinar
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CDFI Fund’s Capacity Building Initiative:Financing Community Health Centers
• Goal: Build the capacity of CDFIs to successfully finance and provide services to community health centers in underserved communities.
• Focus: Health care sector trends, underwriting, program designs for lending to CHCs, and other relevant subjects.
• Approach: Advanced forum, six trainings, five affinity groups, one-to-one technical assistance, webinars, virtual resource bank.
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Presenter
Dave Kleiber, Project Consultant
(360) 312-0481
www.caplink.org
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Agenda
• CL Financial Perspectives Issue 6 methodology
• Brief review of national financial and operational trends of the health center sector
• Key factors leading to FQHC financial distress
• Results of CDFI Lenders’ Survey
• Q&A/Discussion
5
Issue 5&6 - Methodology
• Capital Link took two approaches to identify health centers that had failed or were currently at risk of failing:
1. We reviewed the complete set of annual health center UDS reports from HRSA from 2000-2012 looking for those that abruptly stopped submitting
2. We also added in health centers known to be experiencing serious financial difficulties -these efforts initially identified 85 health centers.
• We cross-referenced that list with our database of audits with the last year that the UDS was submitted considered to be Year 0.
• Then deleted: – Any health center for which at least three years of data was not available; – Centers that appeared from the audits or web-based searches to have merged with another
organization for strategic reasons other than purely financial concerns; – Those that appeared to have failed suddenly (possibly from fraud).
• We identified a ‘clean’ list of 29 centers —and then compared this group using UDS and audited data against a like-sized control group for each of those potential 4 year periods. As a result, a total of approximately 800 health centers were used in one or more control groups.
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Issue 5&6 - Methodology
• Capital Link also conducted a survey of the 16 CDFI members of the Lenders Coalition for Community Health Centers, based on the members’ actual lending history to health centers.
• The survey asked for details about the number, size, terms and performance of the portfolio of loans made to health centers since 2004. A second part of the survey asked similar questions about any specific health center loans that had been delinquent at any time for more than 60 days, put on non-accrual status and/or had been written-off.
• This section also inquired about the reasons for the poor loan performance from the perspective of the lender. The results were tabulated and analyzed to determine the incidence of problem loans, defaults and loan losses for this group of active lenders to health centers.
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To Identify Strengths –Look for Weaknesses
Of the more than 1,280 organizations that have ever been free-standing federally-funded health centers (Section 330 grantees) from 2000 – 2012, fewer than 7% apparently
failed or merged with another entity.
We can learn from the experience of troubled health centers—to help you better understand the warning signs of weak
performance and by corollary, what is necessary to succeed.
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Key Findings Issues 5&6
• Health Center Size: The centers in the test group were uniformly smaller than their control group counterparts when measured by Patients, Visits, FTEs and Revenues.
• Payer Mix: Surprisingly, the test centers did not demonstrate a significantly higher percentage of uninsured patients than the control group . Test centers did see proportionally fewer Medicaid patients than their more successful counterparts.
• Collections/Allowances: One clear conclusion from this study that points to a management-related function is the relatively poor performance of the test centers’ accounts receivable collections efforts—and the resulting higher levels of Allowances.
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Key Findings Issues 5-6Key Findings Issues 5&6
• Productivity: Under the Fee-For-Service reimbursement system that currently predominates across the country, lower productivity translates into lower revenue and all of the test centers reported significantly lower levels of physician and mid-level productivity compared to the control group.
• Low Levels of Default and Loan Loss for the Sector as a Whole: Based on a survey of 16 Community Development Financial Institutions (CDFIs) that are active lenders to health centers, health centers appear to present remarkably low portfolio risk to lenders.
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Size of the Industry
900
950
1,000
1,050
1,100
1,150
1,200
1,250
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
2006 2007 2008 2009 2010 2011 2012 2013
# o
f G
ran
tees
# o
f Se
rvic
e Si
tes
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Patients by Income (% of FPL) - National
71% 70% 70% 71% 72% 72% 72% 72%
15% 14% 15% 14% 14% 14% 14% 14%
7% 7% 7% 7% 7% 7% 7% 7%8% 9% 8% 8% 7% 7% 7% 7%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 2007 2008 2009 2010 2011 2012 2013
>200%
151%-200%
101%-150%
<100%
Patients by Income (% of FPL) -National
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40% 39% 38% 38% 38% 36% 36% 35%
35% 35% 36% 37% 39% 39% 40% 41%
8% 8% 8% 7% 8% 8% 8% 8%
15% 15% 16% 15% 14% 14% 14% 14%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2006 2007 2008 2009 2010 2011 2012 2013
PrivateInsurance
PublicInsurance
Medicare
Medicaid
none/uninsured
13
National Payer Mix - %
13
0%
2%
4%
6%
8%
10%
12%
2007 2008 2009 2010 2011 2012 2013
%Changein HealthCenterFTEs
%Changein Visits
14
National Change in FTEs vs. Total Visits
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Patient Growth Rate
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
12%
2010 2011 2012 2013National 25th Percentile National 50th Percentile National 75th Percentile
15
75%
80%
85%
90%
95%
100%
105%
2006 2007 2008 2009 2010 2011 2012 2013
16
HC Cluster Grants as a % of Sliding Fee Discounts
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Results of the Study:
Centers Under Financial Stress
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Total Operating Revenue
$7,812,253
$9,616,583 $9,651,776
$8,345,333
$11,264,303
$12,298,831
$13,670,404
$14,933,212
$4,815,019 $4,528,081 $4,836,561 $4,878,058
$5,370,057
$6,168,678 $6,734,260
$7,330,400
$2,203,955 $1,851,501 $2,200,556 $2,096,911
$2,488,745 $2,825,964
$3,387,430
$3,565,232
$0
$2,000,000
$4,000,000
$6,000,000
$8,000,000
$10,000,000
$12,000,000
$14,000,000
$16,000,000
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
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Total FTEs
102.0 106.4
115.5 110.5
140.1 139.2
150.6 157.4
74.5 57.4 62.2
56.2
72.2 73.3 76.9 80.6
33.9 25.3 30.8 28.6
35.6 36.2
40.6 42.4
0
20
40
60
80
100
120
140
160
180
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
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Operating Margin
3% 4%
1%2%
7% 7% 7% 7%
0%
-2%
-3%
-3%
2% 2%2%
2%
-6%-7%
-10% -10%
-1%-1% -1%
-2%
-12%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
Contol(25%)
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Bottom Line Margins
6%
5%
3%3%
9% 9% 9% 10%
0%1%
-1%-1%
3% 3%4% 4%
-3.9%
-6.9%
-5.4%
-8.4%
-0.1% 0.2%0.2% 0.1%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
12%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
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Employment Related Expenses as a % of Operating Revenue
75% 76%79%
78%77%
77%
77% 78%
70% 70%
74% 74%
72%71% 72%
71%
64.7%
66.2%
66.8%
69.5%
63.7% 63.9%63.0%
63.6%
60%
65%
70%
75%
80%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
6/3/2015
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Days Cash on Hand
24
37
16
30
7274
80 81
16 19
11 11
3637 38 38
6 7 6 5
14 15 14 16
0
10
20
30
40
50
60
70
80
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
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Accounts Payable
106
153 150
128
55 56 55
5455
83 81
103
32 3132 32
32 3447
59
18 18 18 18
0
20
40
60
80
100
120
140
160
180
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
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Why would you expect FQHC’sto experience financial distress?
• Loss of Market Share - Declining patient/visit count
• High uninsured rate
• Sicker patients
• High overhead
• Low provider productivity
• Difficulty in keeping providers
• High % of patients require care in a language other than English
• Overly leveraged
• High cost per patient
….let’s test these…..25
15,051
14,013
17,590 17,541
21,647 21,648
22,975 23,229
9,9448,755
9,283 9,590
11,42311,606
12,609 12,656
4,794 4,551 4,964 4,550
6,195 6,4907,196 7,436
0
5,000
10,000
15,000
20,000
25,000
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Total Patients(Declining Patient/Visit Count)
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55,941 57,980
62,412 65,261
85,753 86,941
92,201 94,367
42,778 34,297 32,402 33,988
42,734 43,739 46,532 47,712
16,701 17,295 21,671
17,603
22,062 22,796 23,870 25,055
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Total Patients(Declining Patient/Visit Count)
51.2%54.9%
50.4% 54.2%
40.0%
31.6% 35.2% 34.0%
25.4%
24.0%
19.0%17.9%
50.6% 51.3% 50.0%50.7%
35.9%
37.0% 36.4%35.6%
24.2%24.9% 24.1%
24.3%
0%
10%
20%
30%
40%
50%
60%
Year -3 -2 -1 0
Test75%
TestMedian
Test25%
Control 75%
Patient Mix (Self-pay)(High Uninsured Rate)
6/3/2015
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81%
81%80% 80%
82% 83% 82% 83%
71%
63%64% 65%
70%
70%71% 71%
53.0%
50.2% 49.5%47.5%
56.7%58.0% 58.8%
57.1%
40%
50%
60%
70%
80%
90%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Patient Income = <100% of FPL(High Uninsured Rate)
99%
98% 98%
99%
98%
98% 98%98%
97%96%
98% 97%
96% 96% 96%96%
94%
89%
94%
90%
87%
89%
90%
90%
85%
90%
95%
100%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Patient Income = <200% of FPL(High Uninsured Rate)
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Diabetes Diagnoses as a % of All Medical Patients
(Sicker Patients)
8%
11%
10%
15%
9% 9% 9%10%
6%
7%
8%
11%
7% 7% 7%8%
4.4%
6.4%
5.2%
6.7%
5.3%5.0%
5.4%5.8%
4%
6%
8%
10%
12%
14%
16%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Hypertension Diagnoses as % of All Medical Patients
(Sicker Patients)
15%
18%18%
21%
15%
16% 16%
18%
12%
14% 14%
16%
11%12%
12%13%
8.0%
11.8%
11.0%
13.6%
7.5%
7.9% 8.0%8.9%
5%
10%
15%
20%
25%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
6/3/2015
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23%23%
30%28%
21%
23% 23%24%
10%
18%
22%21%
7%
17% 16%
19%
4% 4%5%
8%
2%3% 3%
6%
0%
5%
10%
15%
20%
25%
30%
35%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
High overhead
Admin. / IT / Facility Staff as a % of All Staff
(High Overhead)
97%
81% 82%
72%
81%
74%70% 73%
39%
60%
51%
47%45%39% 41% 43%
20%
27%
17%15%
23%19% 20% 20%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Enabling Services FTE as % of All Provider FTEs
(High Overhead)
6/3/2015
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4,286 4,209 4,158
3,607
4,366 4,324 4,290
4,147
3,590 3,495
3,333
3,056
3,784 3,740 3,660 3,572
3,010 2,960
2,729 2,838
3,241 3,194 3,084
2,984
2,500
2,750
3,000
3,250
3,500
3,750
4,000
4,250
4,500
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Physician Productivity(Low Provider Productivity)
2,543 2,651 2,683
2,815
3,573 3,566 3,539
3,382
2,450 2,349
1,936
2,449
2,949 2,959
2,851 2,808
2,348
2,101
1,572
2,076
2,349 2,309 2,355 2,293
1,500
2,000
2,500
3,000
3,500
4,000
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Midlevel Productivity(Low Provider Productivity)
6/3/2015
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Medical Support Staff Per Medical Provider
(Low Provider Productivity)
2.93.0
3.1
3.33.3
3.23.2
3.2
2.82.7
2.42.5
2.8 2.82.9
2.8
2.5
2.4
2.1
2.3
2.42.4 2.5 2.5
2
2.5
3
3.5
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Percentage of Patients Best Served in a Language other than English
(High Translation Requirement)
33% 32% 32%34%
27% 28%30%
31%
11%
14% 13%
11%
5% 4%
7% 8%
0% 1%2% 2%
0% 0% 1% 1%
-5%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
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1.71.7
1.1
1.4
4.1 4.24.3 4.4
0.4 0.3 0.40.3
1.71.8 1.8 1.8
0.0 0.1-0.1 -0.1
0.8 0.7 0.8 0.9
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Leverage(Leverage)
$708
$658
$733
$623
$662 $663 $683
$716
$583
$537
$504
$545
$514 $514
$525
$549
$439 $419
$433
$396 $411 $406 $420
$439
$350
$400
$450
$500
$550
$600
$650
$700
$750
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
Contol(25%)
Cost Per Patient(High Patient Cost)
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What else should we be looking for?
• Unfavorable Revenue Mix:
– Over-reliance on grant/contract income
– 330 grant too small to cover sliding fee discounts
– Limited Other Operating Revenue
• Unfavorable Payer Mix
– Low Medicaid % / Medicare %
• Poor Collections Experience
– High contractual allowances and/or Bad Debt expense
72%71%
76%
72%
68%
68%
70%
70%
63%60%
57%
53%
53% 53%53% 55%
46%
46% 50%
45%
33%36%
37%
37%
30%
40%
50%
60%
70%
80%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Net Patient Services Revenue (NPSR) as a percentage of All Revenue(Over-reliance on grant/contract income)
6/3/2015
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Grant and Contract Revenue as Percentage of Total Revenue(Over-reliance on grant/contract income)
47%47%
46%
52%
54% 55%53% 53%
34%35%
33%
36%
39% 38% 38%37%
24%26%
22% 23%
25%26%
24% 23%
20%
30%
40%
50%
60%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
13%
2%
4%
0%
2%
3%
7% 7%
2%
0%
2%
0%0% 0%
1%
0%0% 0% 0% 0%0% 0% 0% 0%0%
2%
4%
6%
8%
10%
12%
14%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Federal Capital Grants as a % of All GCR
(Over-reliance on grant/contract income)
6/3/2015
23
State & Local Grants as a % of All GCR
(Over-reliance on grant/contract income)
34%
31%29% 28%
37%
34%
32%34%
20%
12%14%
11%
18% 18% 18%17%
5%2% 2% 3%
7%
6% 6% 4%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
10% 11%
24%
9%
14%16% 16% 16%
5% 3% 3%3%
6%6% 6% 7%
2%0%
2%
1%
2% 2%
2%2%
0%
5%
10%
15%
20%
25%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Foundation/Private Grants as a % All GCR
(Over-reliance on grant/contract income)
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24
330 Grants as a % of All GCR(330 grant too small to cover sliding fee
discounts)
76%77%
77% 82%78%
78%
72%
72%
52%
58% 59% 62%57% 57%
53%51%
39% 40%
33%
48%
37%37%
37%
33%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
Other Operating Revenue (OOR)as a % of Total Operating Revenue
(Limited Other Operating Revenue)
9%
6%
7% 7%
10%
9% 10%10%
2%3%
3%4%4% 3%
4% 4%
0.7%
0.2%
1.4%
0.6%1% 1% 1% 1%
0%
2%
4%
6%
8%
10%
12%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%) 48
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25
Patient Mix – Medicaid(Unfavorable Payer Mix)
41.3% 39.5%43.2%
47.1%
30.0% 30.6%32.4%
33.2%
21%18%
21% 21%
45% 45% 45%
45%
32.8% 33.0% 33.4%
32.0%
21%22% 23% 23%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Year -3 -2 -1 0
Test75%
TestMedian
Test25%
Control75%
ControlMedian
Contol25%
49
23%
25%
23%
24%24%
23%
23%
24%
13%
15%
13%14%13% 12% 12% 12%
8% 8% 6% 8%6%
6%6%
6%
0%
5%
10%
15%
20%
25%
30%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Payer Mix – Private Insurance (Unfavorable Payer Mix)
6/3/2015
26
Self-Pay Collections as a % of Total Collections
(Poor Collections Experience)
18%
24%25%
28%
17%
19%19% 19%
12%13%
10%
14%
11% 12%11% 11%
5%
6% 6% 7%5%
6% 6% 5%
0%
5%
10%
15%
20%
25%
30%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)Control(Median)Test(25%)
51
Self-Pay Sliding Fee Discounts as a % of Total Self Pay Charges
(Poor Collections Experience)
52
75%
73% 72%
68%
76% 77% 76% 76%
65%
63%
68%
63%65%
63% 63%63%
50%
47%
59% 53%52%
50%
50% 51%
40%
45%
50%
55%
60%
65%
70%
75%
80%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Control(25%)
6/3/2015
27
Bad Debt Write-offs as a % of Total Self Pay Charges
(Poor Collections Experience)
24%
20%
14%14%14%
13%12%
13%
9% 9%10%
7%7%
6% 6% 6%7%4%
3% 3%3%
2% 2% 2%0%
5%
10%
15%
20%
25%
30%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Control(25%)
53
Medicaid Collections as a % of Total Collections
(Poor Collections Experience)
54
79%
69%
79%
77%75%
74%
74%
75%
51%
45%47%
51%
60%
59%
60%61%
40%
29%32%
35%
42%
42%43%
42%
20%
30%
40%
50%
60%
70%
80%
90%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
6/3/2015
28
Medicaid Allowances as a % of Total Medicaid Charges
(Poor Collections Experience)
18%
29%
33%
39%
26%
25%
26%
30%
11%
16% 19%
28%
10% 10%
11% 12%
-2%
12%
6%
16%
-3%-4%
-3%
0%
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
Private Insurance (PI) Allowances as % of Total PI Charges
(Poor Collections Experience)
57%
56%57%
58%
46% 46% 47% 46%
39%
42%
36%
42%
31% 31%35%
33%
27%30% 26% 30%
18%
19%
20% 20%
10%
15%
20%
25%
30%
35%
40%
45%
50%
55%
60%
Year -3 -2 -1 0
Test(75%)
Control(75%)
Test(Median)
Control(Median)
Test(25%)
Contol(25%)
56
6/3/2015
29
Caught in the Trap:PPS Rate & Medicare Cost Report
Caught in the Trap:PPS Rate and Medicare Cost Report
• Not all centers get the same Prospective Payment System Rate - not even in the same state.
• The initial rate is established at time they are approved as an FQHC.
• Diligent cost controls can result in an inability to justify a high PPS rate – trapping the center into an inadequate reimbursement scheme that constrains growth.
• The PPS rate can only be increased through a series of base grant adjustments (usually small) and/or scope changes.
57
CDFI Lenders’ Survey Results
58
6/3/2015
30
CDFI - FQHC Lending Survey Results
439
184
0
50
100
150
200
250
300
350
400
450 Loan Activity
Number of Loans Closed Number of Loans Currently Outstanding
CDFI – FQHC Lending Survey Results
$587,832,368
$421,637,502
$-
$100,000,000
$200,000,000
$300,000,000
$400,000,000
$500,000,000
$600,000,000Total Amount of Loans
Total Amount of Loans Closed Total Current Outstanding Principle Balance
6/3/2015
31
CDFI – FQHC Lending Survey Results
89%
8%
3% Loans By Purpose
R/E
CDFI – FQHC Lending Survey Results
$-
$500,000
$1,000,000
$1,500,000
$2,000,000
$2,500,000
$3,000,000
Average Size of R/ELoan
Average SizeWorking Capital Loan
Average SizeEquipment Loan
Average Loan Size
6/3/2015
32
CDFI – FQHC Lending Survey Results
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
Percent of LoansDelinquent 60+ Days
Percent of LoansRated High Risk
Percent of LoansEver on Non-Accrual
Percent of LoansDefaulted
FQHC Loan Performance
Looking Forward….
The business model that health centers work under is complex and the current challenges they face are complicated by:
• Large and persistent federal deficits;
• A contentious and rapidly evolving health care environment;
• Changing reimbursement systems;
• Growing income disparity in the country that further economically isolates the low-income populations health centers serve;
• Increasing expectations as to the number of patients health centers will serve;
• A shortage of primary care providers to service a growing number of patients;
• Pressure to integrate mental health and substance abuse;
• The need (and high expectations) for improved health outcomes, especially among the high-utilizers of safety net services.
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6/3/2015
33
Questions?
65
Financing Community Health Centers
Webinar Series
Upcoming topics include:
• Leveraging HRSA Capital Grants through a NMTC Structure
• Monday, June 8, 2015 at 2pm ET
• Navigating Online CHC Data Resources for Market Needs Assessment
• Thursday, June 18, 2015 at 2pm ET
• Changing Revenue Landscapes for CHCs
• Tuesday, June 23, 2015 at 2pm ET
• Updated Financial and Operating Metrics and Trends
• Tuesday, July 7, 2015 at 2pm ET
Upcoming webinar registration and webinar recordings can be found at:
The CDFI Fund’s Virtual Resource Bank.
66
6/3/2015
34
CDFI Fund’s Virtual Resource Bank
67
OFN Contact Information
• Pam Porter
Executive Vice President, Strategic Consulting
Opportunity Finance Network
215-320-4303
• Alexandra Jaskula
Senior Associate, Strategic Consulting
Opportunity Finance Network
215-320-4325
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