Strategies for Efficiency

OPES Group

March 16, 2011

Macro

Micro

Action
Objectives

• Provide an overview of an application of Efficiency 

Measurement within VHA. 

• Provide insight into the ‘operational’ aspects of 

Efficiency Measurement as part of the HERC 

Efficiency Cyber Seminar Series.

• “Overview of Health Care Efficiency Research” 

February 23, 2011 session by Dr Paul Barnett

• Review the observed variation in efficiency within 

VHA. (macro, micro level)

• Relationship of Efficiency to Quality within VHA.

• Toolkit for sites to utilize to identify Efficiency 

Opportunities.

2
•In healthcare, measurement of efficiency 

has lagged behind that of quality.

•Common belief among providers that 

increased cost efficiency leads to decreased 

quality?

•AHRQ (2008) ideal healthcare efficiency 

measure does not exist. AHRQ has provided

a framework that calls for efficiency 

measures to be:

1)Important, 2)Scientifically Sound, 

3) Feasible, and 4) Actionable 

VHA has been a leader in Quality Measurement 

Can we follow this tradition in Efficiency Measurement?
SFA/DEA View of Efficiency

• Stochastic Frontier Analysis (SFA)*

– Involves regression and analysis of error term

– Less sensitive to data noise and outliers

– Statistical Model

• Data Envelope Analysis (DEA)

– Uses linear programming, nonparametric

– Mathematical Model

4

Methods used by academic researchers not by providers

or health plans Hussey et al 2009
5

OPES Portal 

located off the 

Main VSSC 

Website
Efficiency
 The “stochastic” 

concept is to ...

To separate the ‘random’ events 

from the ‘true’ inefficiency. 

Random events are 

considered not under the 

control of the managers 

(often referred to as 

‘uncontrollable’ costs).

Stochastic Frontier Analysis 

SFA is a specialized technique of general regression analysis

 The “frontier” 

concept is ...

The process of identifying the 

‘most efficient’ level

and/or use the technique 

to set efficiency targets.

Provides an efficiency score adjusting for 

variables that impact cost, such as, patient 

case-mix, patient demographics, 

geographic location , facility 

characteristics, facility infrastructure, etc.
Frontier and Quality

Improving 

Quality

Falling 

Costs

Efficiency/Productivity

Frontier

Relative Cost

High Low

Low

High

Relative Quality

Reference: M. E. Porter (2006)

Change Scenarios:

1. Scenario 1 

• Increase Quality

• Decrease Cost

2. Scenario 2

• Increase Quality

• Stable Costs

3. Scenario 3

• Stable Quality

• Decrease Costs

4. Scenario 4 (Unintended 

Outcome)

• Decrease Quality

• Decrease Cost

Incorporates all available best practices

(protocols, technologies, drugs, etc.)
Dependent Variable: Cost

SFA Costs, $37.5, 

90%

Program Code 

Exclusions, $0.9, 2%

Cost Center 

Exclusions, $0.3, 1%

Budget Object Code 

Exclusions, $2.8, 7% Facility Adj, $0.0, 0%

Costs (in billions) 

Total VHA Costs FY09: $65.05 Billion

Less Stimulus and Hurricane Exclusions: $23.60 Billion

VHA Healthcare Expenditures: $41.45 Billion
Cost Logic

Cost Exclusions Amount Excluded % of Total Cost Pool Examples of Cost 

Pool Excluded

Program Codes $0.90 Billion 2.2% State Home; 

Employee Training

VA Cost Centers $0.26 Billion 0.6%

Non-VHA, VHACO, CWT 

State Home & Fire 

Dept. Cost Centers

Budget Object 

Codes $2.81 Billion 6.8% NRM and Equipment

1. Begin with total costs in MA, MS, MF: $41.45 Billion

2. Exclusion of non-operating costs

3. VISN level activities prorated across facilities (new 

FY09)

4. Facility specific cost adjustments (New FY09)
Changes in Cost Logic

• VISN Level Activities

– Survey tool used to prorate VISN 

activities across all facilities:

• VISN Office

• Prosthetic Activity

• Logistics

• Finance

• Other Cost Centers

• Facility Specific Adjustments

– Canandaigua: National Suicide Hotline 

Excluded

11

(865200) 

VISN Director's 

Office, 

$130.2, 32%

(827200) 

Prosthetic 

Activity, $110.3, 

27%

(844100) Logistics, 

$78.1, 19%

(845700) Revenue 

Cycle Activity, 

$32.6, 8%

(842100) Finance, 

$26.4, 7%

Expenditure Manual Adj.

(in millions)

All Other 

Cost 

Centers,

$27.6, 

7%

Total VISN Level Costs Prorated

(In millions)

$405.2
‘Leveling the Playing Field’

• Major categories tested

– Pt case mix

– Pt demographics

– Quality performance

– Geographic

– Facility characteristics

– Infrastructure characteristics

• Tested independent variables for significance in explaining cost variation

– 117 different variables tested for clinical and administrative cost significance

– 11 variables determined to be statistically significant in explaining clinical costs

– 11 variables determined to be statistically significant in explaining administrative

costs

• Examples of variables without statistical significance in explaining cost 

variation in the SFA Efficiency Model 2009:

– Lease costs

– Gas prices

– Percentage of Vietnam Era Veterans

– Average annual snowfall 
Independent Variables (Clinical)

Level the Playing Field

GPCI = Medicare Geographic Practice Cost Index

Model Fit:

R2=.98
Average DCG by Facility (FY 09)
Variation in Disease Burden
Independent Variables (Administrative)

Level the Playing Field

Model Fit:

R2=.95
VISN 21 Standardized Non-Clinician Salary and

Geographic Pricing Cost Indexing FY09

Geographic 

Variation
VISN 21 Total Footage of 

All Buildings FY09

Variation in Facility Infrastructure 
VISN Outcomes

VISN Efficiency 

Level

20 PORTLAND

Most

Efficient

1.058

07 ATLANTA 1.059

19 DENVER 1.059

21 SAN FRANCISCO 1.060

01 BOSTON 1.062

11 ANN ARBOR 1.063

02 ALBANY 1.065

12 CHICAGO 1.066

15 KANSAS CITY 1.069

17 DALLAS 1.069

18 PHOENIX 1.073

09 NASHVILLE 1.073

16 JACKSON MS 1.074

04 PITTSBURGH 1.076

05 BALTIMORE

Least

Efficient

1.077

23 MINNEAPOLIS 1.078

22 LONG BEACH 1.085

08 BAY PINES 1.086

10 CINCINNATI 1.088

03 BRONX 1.089

06 DURHAM 1.098
Medical Center Outcomes

20
Medical Center Outcomes

Overall

Efficiency Score

Distribution (FY09)

Clinical

Efficiency Score

Distribution (FY09)

Administrative

Efficiency Score

Distribution (FY09)

1.02

1.04

1.06

1.08

1.1

1.12

1.14

1.16

1.18

1.2

1.22

Total Efficiency Score

VHA SFA Results by Facility (FY09)

1

1.05

1.1

1.15

1.2

1.25

Clinical Efficiency Score

VHA SFA Results by Facility (FY09)

1.02

1.04

1.06

1.08

1.1

1.12

1.14

1.16

1.18

1.2

1.22

Administrative Efficiency Score

VHA SFA Results by Facility (FY09)
Medical Center Outcomes

1.0000

1.0500

1.1000

1.1500

1.2000

1.2500

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150

Overall Efficiency Score

Number of Facilities (138 Facilities Plotted)

Efficiency

Score

Least

Efficient

Most

Efficient

National Median

National Average
FY 2009 SFA Total Efficiency 

1.00

1.02

1.04

1.06

1.08

1.10

1.12

1.14

1.16

1.18

1.20

1.22

Total Efficiency Score

FY09 Total Efficiency by VISN (FY09)

VISN 1VISN 2VISN 3VISN 4VISN 5VISN 6VISN 7VISN 8VISN 9

VISN 10

VISN 11VISN 12VISN 15VISN 16VISN 17VISN 18VISN 19VISN 20VISN 21VISN 22VISN 23

Average Total Efficiency 

Score=1.07

1.00

1.02

1.04

1.06

1.08

1.10

1.12

1.14

1.16

1.18

1.20

1.22

Total Efficiency Score

SFA Total Efficiency Score by MCG Complexity (FY09)

1a-High Complexity 3-Low Complexity 2-Medium

Complexity 1b-High Complexity1c-High Complexity 99-Not 

Assigned

Average Total Efficiency 

Score=1.07
FY 2009 SFA Clinical Efficiency

1.00 

1.02 

1.04 

1.06 

1.08 

1.10 

1.12 

1.14 

1.16 

1.18 

1.20 

1.22 

1.24 

Clinical Efficiency Score

SFA Clinical Efficiency by VISN (FY09)

VISN 1VISN 2VISN 3VISN 4VISN 5VISN 6VISN 7VISN 8VISN 9

VISN 10

VISN 11VISN 12VISN 15VISN 16VISN 17VISN 18VISN 19VISN 20VISN 21VISN 22VISN 23

Average Clinical Efficiency 

Score=1.07

1.00 

1.02 

1.04 

1.06 

1.08 

1.10 

1.12 

1.14 

1.16 

1.18 

1.20 

1.22 

1.24 

Clinical Efficiency Score

SFA Clinical Efficiency Score by MCG Complexity Level (FY09)

1a-High Complexity 3-Low Complexity 2-Medium

Complexity 1b-High Complexity1c-High Complexity 99-Not 

Assigned

Average Clinical Efficiency 

Score=1.07
FY 2009 Administrative Efficiency

1.00 

1.02 

1.04 

1.06 

1.08 

1.10 

1.12 

1.14 

1.16 

1.18 

1.20 

1.22 

Administrative Efficiency Score

SFA Administrative Efficiency by VISN (FY09)

VISN 1VISN 2VISN 3VISN 4VISN 5VISN 6VISN 7VISN 8VISN 9

VISN 10

VISN 11VISN 12VISN 15VISN 16VISN 17VISN 18VISN 19VISN 20VISN 21VISN 22VISN 23

Average Admin Efficiency 

Score=1.08

1.00 

1.02 

1.04 

1.06 

1.08 

1.10 

1.12 

1.14 

1.16 

1.18 

1.20 

1.22 

1.24 

Administrative Efficiency Score

SFA Administrative Efficiency Score by MCG Complexity Level (FY09)

1a-High Complexity 3-Low Complexity 2-Medium

Complexity 1b-High Complexity1c-High Complexity 99-Not 

Assigned

Average Admin Efficiency 

Score=1.08
Relationship of Efficiency to Quality

1

1.1

1.2

1.3

0.83 0.85 0.87 0.89 0.91 0.93 0.95

SFA Clinical Efficiency Score

Quality (HEDIS & ORYX)

Correlation between Clinical Efficiency and Quality (HEDIS & ORYX) by 

Facility (FY09)

Correlation = -0.168

P = 0.0494
Variation in Reliance

1.00 

1.05 

1.10 

1.15 

1.20 

1.25 

1.30 

1.35 

$0 $1,000 $2,000 $3,000 $4,000 $5,000 $6,000 $7,000

SFA Total Efficiency

Medicare Cost per VA Patient

Correlation between Medicare Cost per VA Patient and 

SFA Total Efficiency Score by Facility (FY08)

R=0.0889

P=0.2996

VHA Reliance is an issue 

that we need to consider; 

however, Medicare data 

generally lag so only 

available retrospectively

VA Medicare Cost per VA Patient by Facility (FY08)
Strategy for Looking at Efficiency

• SFA*

• DEA

Macro

• Sub-models

• ABC, DRG

• Fiscal Glide Path

Micro

• Best Practices

• System Redesign

• HERC’s

Action
Administrative FTE Model

Distribution of Administrative FTE 

“Administrative FTE not Otherwise Classified (BOC 1001). Title 38 Employees working in Admin. 

Excludes secretaries and all other clerical-type employees.”

Total 

Administrative 

FTE

50,314 (100%)

82XX 

19,640 FTE (39%)

Direct Medical Care

8652

642 FTE (1%)

All Other (VISN)

85XX 

3,673 FTE (7%)

Engineering & 

Environmental 

Management

84XX

26,358 FTE 

(52%)

Administrative
Administrative FTE Model

Dependent Variable = FY 2009 Parent Station Admin FTE (BOC=1001 & Title 38 in Admin) 

• Patients (volume)

• DxCG (patient risk)

• LTC ADC (facility characteristic)

• Salary/GPCI (Geographic)

• Residents –Program Count (Teaching 

Mission)

• Multi-Division Facility 

+

• Patient Income

• Travel Time

-

• Shared Workload
How Well Does the Model Fit?

0

200

400

600

800

1,000

1,200

1,400

1,600

0 200 400 600 800 1,000 1,200 1,400

Observed Administrative FTE

Expected Administrative FTE

VHA Administrative Model Fit (FY09)

R = 0.9598

P < 0.0001
VHA Administrative FTE O/E Ratio by 

VISN (FY09)

32
VHA Administrative FTE O/E Ratio by 

Facility (FY09)

33

HI

AK

PR

O/E Ratio

1.10 - 1.71

1.05 - 1.10

0.96 - 1.05

0.86 - 0.96

0.00 - 0.86

No Data
Is there a Correlation Between Admin 

FTE O/E and SFA Total Efficiency ?

1.00

1.02

1.04

1.06

1.08

1.10

1.12

1.14

1.16

1.18

1.20

1.22

0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00

Total Efficiency

FTE O/E Ratio

VHA ADM FTE O/E Ratio vs. Total Efficiency Score by Facility (FY09)

R=0.4275

P<0.0001
Does having more Admin. Staff lead 

to Better AES Scores?

3.4

3.5

3.6

3.7

3.8

3.9

4.0

4.1

4.2

0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00

Employee Satisfaction

FTE O/E Ratio

VHA ADM FTE O/E Ratio vs. Employee Satisfaction by Facility (FY09)

R=0.1848

P<0.0300
Does having more Admin. Staff Lead 

to Higher Patient Satisfaction Scores?

40

45

50

55

60

65

70

75

80

0.25 0.45 0.65 0.85 1.05 1.25 1.45 1.65 1.85

Patient Satisfaction

FTE O/E Ratio

VHA ADM FTE O/E Ratio vs. Patient Satisfaction by Facility (FY09)

R= - 0.0982

P=0.2520 
Does more Admin Staff lead to Better 

Quality Metrics?

0.82

0.84

0.86

0.88

0.90

0.92

0.94

0.96

0.25 0.45 0.65 0.85 1.05 1.25 1.45 1.65 1.85

(ORYX+HEDIS)/2

FTE O/E Ratio

VHA ADM FTE O/E Ratio vs. (ORYX+HEDIS)/2 by Facility (FY09)

R=0.1452

P=0.0892
38
39
40
Summary

• SFA is a Macro model looking at overall health care 

system efficiency adjusting for uncontrollable site 

characteristics

• Sub-models (micro) allow drill down (tools) in 

specific areas so sites can custom design where to 

act

• SFA is an internal benchmark and, therefore, does 

not reflect private sector differences but differences 

within VHA

• Limited in how often model can be built each year 

(Annual, Bi-annual)

• Future work: longitudinal efficiency measurement,

additional micro models for drill down