Chapter 9.

Productivity

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 1

         

Outline

Trends in Healthcare Productivity: Consequences of PPS Productivity Definitions and Measurements

– Productivity Benchmarking – Multifactor Productivity

Commonly Used Productivity Ratios

– Hours per Patient Day or Visit

Adjustment for Inputs

– Skill-Mix Adjustment to Worked Hours – Cost of Labor

Adjustments for Output Measures

– Service/Case-Mix Adjustments

Productivity Measures Using Direct Care Hours Productivity – Quality Relationship Productivity Dilemmas Multiple Dimensions of Productivity: New Methods

– Data Envelopment Analysis (DEA)

Productivity Improvement

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 2

Trends in Productivity: Consequences of PPS

• •

The recent decades’ changes in reimbursement strategies aimed to end waste and promote innovative and cost-efficient delivery systems. productivity gains from PPS have not materialized to the extent predicted.

•

Hospitals now employ more people to treat fewer patients, and the increase is not accounted for by the greater severity of patient illness in the late 1980s and in1990s.

•

Although employers, insurers and public are spending less on inpatient care, the rising use of outpatient procedures has simply increased costs in that area which counters the savings (Altman, Goldberger, and Crane, 1990).

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 3

Trends in Productivity: Consequences of PPS

• • •

The constraints that force healthcare institutions into the role of cost centers, coupled with shifting patterns of inpatient acuity, tight healthcare labor markets, and society's expectations of high quality of care are leading healthcare organizations to a "productivity wall." When the wall is reached, it is quality of care that inevitably is sacrificed for the sake of productivity and profit (Kirk, 1990).

It must be recognized that there are limits to ratcheting up productivity. It is not always possible to do more with less.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 4

Productivity Definitions and Measurements

• Productivity is one measure of the effective

use of resources within an organization, industry, or nation.

• The classical productivity definition

measures outputs relative to the inputs needed to produce them. That is, productivity is defined as the number of output units per unit of input

Pr

oductivity



Output Input

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 5

Productivity Definitions and Measurements

• Sometimes, an inverse calculation is used

that measures inputs per unit of output. Care must be taken to interpret this inverse calculation appropriately; the greater the number of units of input per unit of output, the lower the productivity.

• For example, traditionally productivity in

hospital nursing units has been measured by hours per patient day (HPPD). That requires an inversion of the typical calculations: meaning total hours are divided by total patient days.

HPPD



Total Hours Patient Days

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 6

Example 9.1

Nurses in Unit A worked collectively a total of 25 hours to treat a patient who stayed 5 days, and nurses in Unit B worked a total of 16 hours to treat a patient who stayed 4 days. Calculate which of the two similar hospital nursing units is more productive.

Solution:

First, define the inputs and the outputs for the analysis. Is the proper measure of inputs the number of nurses or of hours worked? In this case the definition of the input would be total nursing hours. When the total number of nursing hours worked per nurse is used as the input measure, then the productivity measures for the two units are:

HPPD

A



Total Hours Patient Days



25 5



5

HPPD

B



Total Hours Patient Days

 16 4  4 Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 7

Productivity Definitions and Measurements

• Productivity Benchmarking

. Productivity must be considered as a relative measure; the calculated ratio should be either compared to a similar unit, or compared to the productivity ratio of the same unit in previous years. Such comparisons characterize benchmarking. Many organizations use benchmarking to help set the direction for change.

• Historical Benchmarking

is monitoring an operational units’ own productivity or performance over the last few years. Another way of benchmarking is to identify the best practices (best productivity ratios of similar units) across health organizations and incorporate them in one’s own.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 8

Productivity Definitions and Measurements

Multifactor Productivity

.

Example 9.1

demonstrated a measure of labor productivity. Because it looks at only one input, nursing hours, it is example of a partial productivity measure. Looking only at labor productivity may not yield an accurate picture. Newer productivity measures tend to include not only labor inputs, but the other operating costs for the product or service as well.

Multifacto r

Pr

oductivity



Service Labor



Item Material

*  Pr

ice Overhead

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 9

.

Example 9.2

A specialty laboratory performs lab tests for the area hospitals. During its first two years of operation the following measurements were gathered: Measurement Price per test ($) Year 1 50 Annual tests 10,000 Total labor costs($) 150,000 Material costs ($) Overhead ($) 8,000 12,000 Year 2 50 10,700 158,000 8,400 12,200 Determine and compare the multifactor productivity for historical benchmarking.

Solution:

Multifacto r

Pr

oductivity Year

 1  10 150 , 000  , 000 8 , * 50 000  12 , 000  2 .

9

Multifacto r

Pr

oductivity Year

 2  10 158 , 000  , 700 8 , * 50 400  12 , 200 Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan  3 .

0 10

Commonly Used Productivity Ratios

•

Hours Per Patient Day (or Visit)

Hours per Patient Day



Hours Worked Patients Days

inpatient

Hours per Patient Visit



Hours Worked Patient Visits

outpatient Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 11

Commonly Used Productivity Ratios

Example 9.3: A

nnual statistical data for two nursing units in Memorial Hospital are as follows: Measurements Annual Patient Days Annual Hours Worked Unit A 14,000 210,000 Unit B 10,000 180,000 Calculate and compare hours per patient day for two units of this hospital.

Solution:

Hours per Patient Day Unit A

 210 , 000 14 , 000  15

hours

Hours per Patient Day Unit B

 180 , 000 10 , 000  18 Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan

hours

12

Commonly Used Productivity Ratios

Example 9.4:

Performsbetter Associates – a two-site group practice, requires productivity monitoring. The following initial data are provided for both sites of the practice: Measurements Annual Visits Annual Paid Hours Suburban 135,000 115,000 Downtown 97,000 112,000 Calculate and compare the hours per patient visit for the suburban and the downtown locations of this practice.

Solution:

Hours per Patient Visit Suburb

 115 , 000 135 , 000  .

85

hours or 51 minutes.

Hours per Patient Visit Downtown

 112 , 000 97 , 000  1 .

15

hours or 69 minutes.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 13

Adjustments for Inputs .

weigh the hours of personnel of different One approach is to calculate weights based on the average wage or salary of each skill class. To do that, a given skill class wage/salary would be divided into the top class skill salary. If RNs, LPNs and Aides are earning $35.00, $28.00, and $17.50 an hour, respectively; Then , one hour of a nurse aide’s time is economically equivalent to 0.5 hours of a RN's time; and one hour of a LPN's time is equal to 0.8 hours of a RN's time.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 14

Adjustments for Inputs

Adjusted Hours

 

w

i

*

X

i

Adjusted Hours = 1.0*(RN hours) + 0.8*(LPN hours) + 0.5*(Aide hours)

Adjusted Hours per patient day



Adjusted Hours Patients Days

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 15

Adjustments for Inputs

Adjusted Hours

 

w

i

*

X

i

Adjusted Hours = 1.0*(RN hours) + 0.8*(LPN hours) + 0.5*(Aide hours)

Adjusted Hours per patient day



Adjusted Hours Patients Days

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 16

Adjustments for Inputs Similarly, in outpatient settings, if one hour of a nurse .

of a specialist's (SP) time, and if one hour of a general practitioner’s (GP) time is equal to 0.85 hours of a specialist’s time, adjusted hours would be calculated as: Adjusted Hours = 1.0 (SP hours) + 0.85 (GP hours) + 0.6 (NP hours)

Adjusted Hours per Visit



Adjusted Hours Patient Visits

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 17

Adjustments for Inputs Example 9.5: Using data from Example 9.3

, and economic equivalencies of 0.5 Aide = RN, 0.8 LPN = RN, calculate the adjusted hours per patient day for Unit A and Unit B. Unit A at Memorial Hospital employs 100% RNs. The current skill mix distribution of Unit B is 45% RNs, 30% LPNs, and 25% nursing aides (NAs). Compare unadjusted and adjusted productivity scores.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 18

Adjustments for Inputs Solution:

The first step is to calculate adjusted hours for each unit. For Unit A, since it employs 100% RNs, there is no need for adjustment. For Unit B: Adjusted Hours (Unit B) Adjusted Hours (Unit B) Adjusted Hours (Unit B) = 1.0 (180,000*.45) + 0.80 (180,000*.30) + 0.50 (180,000*.25).

= 1.0 (81,000) + 0.80 (54,000) + 0.50 (45,000).

= 146,700.

standardized as 146,700 instead of 180,000.

Adjusted Hours per Patient Day Unit A

 210 , 000  15 .

0 14 , 000 hours.

Adjusted Hours per Patient Day Unit B

 146 , 700 10 , 000  14 .

7 hours.

Using adjusted hours, Unit A, which appeared productive according to the first measure (see example 9.3), no longer appears as productive.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 19

Adjustments for Inputs Standardized Cost of Labor .

. Total labor cost comprises the account for differences in salary structure across hospitals or group practices, cost calculations can be standardized using a standard salary per hour for each of the skill levels

Labor Cost

 

c

i

*

X

i

Labor Cost = RN wages (RN hours) + LPN wages (LPN hours) + NA wages (Aide hours).

Labor Cost Patient Day



Labor Cost of Care Patient Days Labor Cost

Chapter 9: Quantitatve Methods in Health Care Management

per Visit



Labor Cost of Care Patient Visits

Yasar A. Ozcan 20

Adjustments for Inputs Example 9.6: Performsbetter Associates in $45 per hour, respectively, to its SPs, GPs and NPs in both locations. Example 9.4

pays $110, $85, and Currently, the suburban location staff comprises of 50% SPs, 30% GPs, and 20% NPs. The downtown location, on the other hand, comprises 30% SPs, 50% GPs, and 20% NPs. Calculate and compare the labor cost of care, and labor cost per visit for both locations.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 21

Adjustments for Inputs Solution:

First, calculate “Labor Cost of Care” for each location. Labor Cost = SP wages (SP hours) + GP wages (GP hours) + NP wages (NP hours), Labor Cost Suburban Labor Cost Suburban Labor Cost Suburban Labor Cost Downtown = $10,292,500 .

= $110 (112,000*.30) + $85 (112,000*0.50) + $45 (112,000*0.20).

Labor Cost Downtown Labor Cost Downtown = $110 (115,000*0.50) + $85 (115,000*0.30) + $45 (115,000*0.20).

= $110 (57,500) + $85 (34,500) + $45 (23,000).

= $110 (33,600) + $85 (56,000) + $45 (22,400).

= $9,464,000 .

Labor Cost per Visit Suburban

 10 , 292 , 500 135 , 000  $ 76 .

24

Labor Cost per Visit Downtown

 9 , 464 , 000  $ 97 .

57 97 , 000 Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 22

Adjustments for Outputs .

tool for comparison of, for instance, two community hospitals that provide different services or have significantly different distributions of patients among their services. The service mix adjusted volume is weighted by a normalized service intensity factor.

. Service-mix adjustment is useful

W i

 

H H i i n

Adjusted Volume

 

W

i

*

X

i

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 23

Adjustments for Outputs Service-Mix Adjustments Two hospitals, each with unadjusted volume of 10,000 patient days per month, provide only two services, S patient day. 1 and S 2 , requiring respectively 3 and 7 hours of nursing time per Hospital A has a service-mix distribution of 2000 patient days for S 1 and 8000 patient days for S 2 .

Hospital B has 8000 days for S 1 and 2000 days for S 2 . Calculate adjusted patient days for both hospitals.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 24

Adjustments for Outputs Service-Mix Adjustments Solution:

In this case, total unadjusted volume is simply the sum of the volume for each service in each hospital, or Unadjusted Volume = X 1 + X 2 .

Hospital-A Hospital-B .

W

1  

H H

1

i

Service S 1 (3 hours/patient day) Service S 2 (7 hours/patient day) Total Unadjusted Volume

n

 ( 3  3 7 ) 2  10 3 2  3 5  0 .

6 X 1 =2000 X 2 =8000 10,000 X 1 =8000 X 2 =2000 10,000

W

2  

H H

2

i n

 ( 3  7 7 ) 2  10 7 2  7 5  1 .

4 Adjusted Volume = W 1 X 1 + W 2 X 2.

Adjusted volume for Hospital-A = 0.6*2,000+1.4*8,000 = 12,400.

Adjusted volume for Hospital-B = 0.6*8,000+1.4*2,000 = 7,600.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 25

Adjustments for Outputs Case-Mix Adjustments acuity categories.

. The methodology for case-mix adjustment is similar to that for service-mix adjustment. Although most hospitals rely on advanced acuity systems, each system is based on the weight factors for the different Patients in each category require similar amounts of nursing care over a given 24 hour time period; however, across categories the care requirements differ significantly. For acuity, the focus is on patients’ direct care requirements. The ratio of the hours of direct care provided to the total hours worked is another measure of productivity.

Case



Mix Index

j

Chapter 9: Quantitatve Methods in Health Care Management  Yasar A. Ozcan 

W

i

*

P

ij

26

Adjustments for Outputs Case-Mix Adjustments Example 9.8: Unit A and Unit B (from Example 9.3

), a medical care unit in Memorial Hospital, classify patients into four acuity categories (Type I through Type IV), with direct care requirements per patient day being respectively, 0.5, 1.5, 4.5, and 6.0 hours. Annual distributions of patients in these four acuity categories in Unit A were 0.15, 0.25, 0.35, and 0.25. Annual distributions of patients in Unit B were 0.15, 0.30, 0.40, and 0.15. Calculate the case mix for these two units, and determine which unit has been serving more severe patients.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 27

.

.

.

.

Adjustments for Outputs Case-Mix Adjustments Solution:

W

1  

H

1

H i n

 ( 0 .

5  1 .

5  0 .

5 4 .

0  6 .

0 ) 4  0 12 .

5 4  0 .

5 3  0 .

17

W

2  

H H

2

i n

 ( 0 .

5  1 .

5 1 .

5  4 .

0  6 .

0 ) 4  1 12 .

5 4  1 .

5 3  0 .

5

W

3  

H H

3

i n

 ( 0 .

5  1 .

5  4 .

0 4 .

0  6 .

0 ) 4  4 12 .

0 4  4 .

0  1 .

33 3

W

4  

H H

4

i n

 ( 0 .

5  1 .

5  6 .

0 4 .

0  6 .

0 ) 4  6 12 .

0 4  6 .

0 3  2 .

00 .

.

Case



mix Index A

 

W i

*

P iA

 ( 0 .

17 * 0 .

15 )  ( 0 .

5 * 0 .

25 )  ( 1 .

33 * 0 .

35 )  ( 2 .

00 * 0 .

25 )  1 .

12 .

Case



mix Index B

 

W i

*

P iB

 ( 0 .

17 * 0 .

15 )  ( 0 .

5 * 0 .

30 )  ( 1 .

33 * 0 .

40 )  ( 2 .

00 * 0 .

15 )  1 .

01 .

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 28

Adjustments for Outputs Case-Mix Adjustments

Once the case-mix is determined, the output side of the productivity ratios can be adjusted by simply multiplying volume (patient days, discharges, visits) by case-mix index as: Adjusted Patient Days = Patient Days * Case-mix index.

Adjusted Discharges = Discharges * Case-mix index.

Adjusted Visits = Visits * Case-mix index.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 29

Productivity Measures Using Direct Care Hours Hours of Direct Care . “Hours of direct care” is an important component of productivity ratios. It serves as a building block for other ratios. To illustrate its development, let us assume that patients are categorized into acuity groupings requiring H1, H2, H3, …., Hm hours of direct nursing care per patient day. Further, assume that there are N1, N2, N3, .…, Nm annual patient days in units 1 through m. The total amount of direct nursing care in nursing unit j would be calculated as:

Hours of Direct Care j 

i n

  1

H i

*

P ij

*

N j

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 30

Productivity Measures Using Direct Care Hours Percentage of Hours in Direct Care.

hours to total care hours.

This is an additional measure can be derived from the “Hours of Direct Care” calculation, as the ratio of direct care

Percent of Hours in Direct Care  Hours in Direct Care Hours Worked

Percentage of Adjusted Hours in Direct Care . We also can determine the percentage of adjusted nursing hours as adjusted for skill-mix in direct patient care.

Percentage of Adjusted Hours in Direct Care  Hours in Direct Care Adjusted Hours Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 31

Productivity Measures Using Direct Care Hours Example 9.9: Using information from Examples 9.3 and 9.8

calculate: a) hours of direct care b) percentage of hours in direct care, and c) percentage of adjusted hours in direct care for Units A and B of Memorial Hospital. Compare these results in terms of percentage of adjusted hours in direct care.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 32

Productivity Measures Using Direct Care Hours Solution: Memorial Hospital uses an acuity classification system with 4 categories of direct hours of care per patient day: 0.5, 1.5, 4.0, and 6.0 hours. The annual distributions of patients in these four acuity categories in Unit A were 0.15, 0.25, 0.35, and 0.25. The annual distributions of patients in Unit B were 0.15, 0.30, 0.40, and 0.15. Annual patient days for Unit A were 14,000, and for unit B 10,000. Annual hours worked were 115,000 and 112,000, respectively.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 33

Productivity Measures Using Direct Care Hours Solution:

Hours of Direct Care A 

i

4   1 (

H i

*

P iA

*

N A

).

Hours of Direct Care A  ( 0 .

5 * .

15 * 14 , 000 )  ( 1 .

5 * .

25 * 14 , 000 )  ( 4 .

0 * .

35 * 14 , 000 )  ( 6 .

0 * .

25 * 14 , 000 )

Hours of Direct Care

A 

46 , 900

.

.

Hours of Direct Care B 

i

4   1 (

H i

*

P iB

*

N B

).

Hours of Direct Care B  ( 0 .

5 * .

15 * 10 , 000 )  ( 1 .

5 * .

30 * 10 , 000 )  ( 4 .

0 * .

40 * 10 , 000 )  ( 6 .

0 * .

15 * 10 , 000 )

Hours of Direct Care

B 

30 , 250

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 34

Productivity Measures Using Direct Care Hours Solution:

Percentage of Hours in Direct Care

A

 Hours in Direct Care  Hours Worked 46 , 900 210 , 000  0 .

223

or

22 .

3 % Percentage of Hours in Direct Care

B

 Hours in Direct Care Hours Worked  30 , 250 180 , 000  0 .

168

or

16 .

8 % . Percentage of Adjusted Hours in Direct Care

A

 Hours in Direct Care  Adjusted Hours 46900 210 , 000  0 .

223

or

22 .

3 %.

Percentage of Adjusted Hours in Direct Care

B

 Hours in Direct Care Adjusted Hours  30250 146 , 700  0 .

206

or

20 .

6 %.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 35

Figure 9.1 Productivity and Quality Tradeoff

Quality of Output Q A Q B Q A” A ’ A ’’ A Q B I Hospital A Hospital B I 2

I A”

I 1

Source: Shukla, R.K.

Theories and Strategies of Healthcare: Technology-Strategy-Performance

, Chapter 4, Unpublished Manuscript, 1991. Printed with permission.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan

Quantity of Inputs (Staffing Level)

36

Productivity Wall?

  Quality is difficult to measure, and its definition is ambiguous The relationships between quantity of care provided and quality are often uncertain Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 37

Many people confuse. . .

The concepts of productivity, efficiency, and effectiveness. Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 38

It’s quite simple really!



Efficiency--

using the minimum number of inputs for a given number of outputs 

Effectiveness--

outcomes?

refers to outputs; are the proper inputs being used to produce the appropriate 

Productivity--

a broader concept than efficiency; refers to effective use of a given set of resources Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 39

But efficiency has varying dimensions..



Technical Efficiency--

quantity or level of care.

relationship between various inputs and related outputs; use minimum combination of resources for a given level of 

Allocative (Economic) efficiency -

adds cost to the measure of technical efficiency.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 40

Iso-cost

Graphically,

MDs 4 3 2 1 A Isoquant C 0 1 2 3 4 5 B Nurse Practitioners (NPs)

Assume NPs and MDs can be substituted. The hospital can either use 3 MDs and 2 NPs (pt. A), or 1 MD and 5 NPs (pt. B). Both result in the same level of quality and can produce the same quantity of output.

Are points A and B both technically efficient?

Is point C technically efficient, why or why not?

Remember what an

isoquant

is? Are all points on an isoquant technically efficient? economically efficient?

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 41

Let’s expand our discussion. . .

 Data envelopment analysis is a recently developed technique that can be used to measure the multiple dimensions of productivity.

 It allows multiple inputs and outputs to be used in a linear programming model that develops a score of technical efficiency.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 42



Data Envelopment Analysis (DEA)

DEA can be used to measure productivity of hospitals, physicians, group practices, or any other unit of analysis, referred to as the decision making unit (DMU)  The technical efficiency score of optimally producing DMUs equals 1 (and lies on the isoquant). All other DMUs are measured against these technically efficient DMUs, and have a score of between 0 and 1.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 43

DEA-- A Simple Example

Inputs Visits P 2 Medications 1 1 Physicians P 2 1 4 P 3 1 3 P 4 2 3 Inefficiency

Physicians P 1 , P 2 , and P 3 are technically efficient, ceteris paribus, and would receive an efficiency score of 1. Physician 4, however is inefficient and must reduce either visits and or use of medications to become as efficient as his/her peers. The amount of the

Supplies

reduction necessary is called inefficiency.

4 3 2 1 0 Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan P 2 1 2 P 1 P 4 P 3 3 LOS 44

DEA-- An Application

Ozcan and Luke (1993), A National Study of the Efficiency of Hospitals in Urban Markets    The study examines the contribution of various hospital characteristics to hospital technical efficiency Outputs included: – Treated cases – Outpatient visits – Teaching FTEs Inputs included: – Capital – Plant complexity – Labor – Supplies Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 45

DEA Applications, cont.

  Slack values allow the manager to determine just how much the input/output mix must be changed for inefficient DMUs to reach efficiency DEA is also useful for benchmarking or development of report cards, making it particularly useful in a managed care environment Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 46

Improving Healthcare Productivity

1. Develop productivity measures for all operations in their organization, 2. Look at the system as a whole (do not sub optimize) in deciding on which operations/procedures to focus productivity improvements.

3. Develop methods for achieving productivity improvements, and especially benchmarking by studying peer healthcare providers that have increased productivity; and reengineer care delivery and business processes.

4. Establish reasonable and attainable standards and improvement goals.

5. Consider incentives to reward workers for contributions and to demonstrate management’s support of productivity improvements.

6. Measure and publicize improvements.

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 47

The End

Chapter 9: Quantitatve Methods in Health Care Management Yasar A. Ozcan 48