Ozcan: Chapter 9 Productivity ISE 491 Dr. Joan Burtner.

Ozcan: Chapter 9 Productivity

ISE 491

Dr. Joan Burtner

ISE 491 Fall 2009 Dr. Burtner Ozcan Chapter 9 Productivity Slide 2

Outline

Productivity Improvement Trends in Healthcare Productivity: Consequences of Medicare

Prospective Payment System (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


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.

Improving Healthcare Productivity


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 the Prospective Payment System (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).


Trends in Productivity: Productivity Wall

• 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.


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.

Input

OutputtyProductivi


• 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.


DaysPatient

HoursTotalHPPD


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.

55

25

DaysPatient

HoursTotalHPPDA 4

4

16

DaysPatient

HoursTotalHPPDB

Since the HPPD productivity ratio is expressed as input over output, lower is better.

Unit B productivity is better than Unit A.



• 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.


Multi-factor Productivity

Looking only at labor productivity may not yield an accurate picture.

Newer productivity measures tend to include not onlylabor inputs, but the other operating costs for the product or service as well.

OverheadMaterialLabor

iceItemServiceoductivityrMultifacto

Pr*Pr


Example 9.2 Statement

A specialty laboratory performs lab tests for the area hospitals. During its first two years of operation the following measurements were gathered:

Measurement Year 1 Year 2Price per test ($) 50 50Annual tests 10,000 10,700Total labor costs($) 150,000 158,000 Material costs ($) 8,000 8,400Overhead ($) 12,000 12,200

Determine and compare the multifactor productivity for historical benchmarking.


Example 9.2 Solution

0.3200,12400,8000,158

50*700,10Pr 2

YearoductivityrMultifacto

9.2000,12000,8000,150

50*000,10Pr 1

YearoductivityrMultifacto

Since the multi-factor productivity ratio is expressed as output over input, higher is better.

Year 2 productivity is better than Year 1.


Commonly Used Productivity Ratios

DaysPatients

WorkedHoursDayPatientperHours

VisitsPatient

WorkedHoursVisitPatientperHours

inpatient

outpatient


Annual statistical data for two nursing units in Memorial Hospital are as follows:Measurements Unit A Unit BAnnual Patient Days 14,000 10,000Annual Hours Worked 210,000 180,000

Calculate and compare hours per patient day for two units of this hospital.

15000,14

000,210AUnitDayPatientperHours 18

000,10

000,180BUnitDayPatientperHours

Solution:

Example 9.3

Since the HPPD productivity ratio is expressed as input over output, lower is better. Unit A productivity is better than Unit B.


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 Suburban DowntownAnnual Visits 135,000 97,000Annual Paid Hours 115,000 112,000

Calculate and compare the hours per patient visit for the suburban and the downtown locations of this practice. Solution:

85.000,135

000,115SuburbVisitPatientperHours

hours or 69 minutes.15.1000,97

000,112DowntownVisitPatientperHours

hours or 51 minutes.

Conclusion: Suburb is better than Downtown


Adjustments for Inputs.

Skill-Mix Adjustment weighs the hours of personnel of different skill levels by their economic valuation.

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.

Let’s assume RNs, LPNs and Nurses Aides are earning $35.00, $28.00, and $17.50 an hour, respectively.

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.


Calculations: Adjustments for Inputs

ii XwHoursAdjusted *

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

DaysPatients

HoursAdjusteddaypatientperHoursAdjusted



Similarly, in outpatient settings, if one hour of a nurse practitioner's (NP) time is economically equivalent to 0.6 hours 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)

VisitsPatient

HoursAdjustedVisitperHoursAdjusted


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.

Adjustments for Inputs: Example 9.5


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) = 1.0 (180,000*.45) + 0.80 (180,000*.30) + 0.50 (180,000*.25).

Adjusted Hours (Unit B) = 1.0 (81,000) + 0.80 (54,000) + 0.50 (45,000).

Adjusted Hours (Unit B) = 146,700.

In this way, using the economic equivalencies of the skill-mix, the number of hours is standardized as 146,700 instead of 180,000.

0.15000,14

000,210AUnitDayPatientperHoursAdjusted hours.

7.14000,10

700,146BUnitDayPatientperHoursAdjusted

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

hours.

Standardized Cost of Labor.

Adjustments for Inputs Example 9.5 Solution



Standardized Cost of Labor. Total labor cost comprises the payments to various professionals at varying skills. To 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

ii XcCostLabor *

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

DaysPatient

CareofCostLaborDayPatientCostLabor

VisitsPatient

CareofCostLaborVisitperCostLabor


Adjustments for Inputs Ex. 9.6

Example 9.6:

Performsbetter Associates in Example 9.4 pays $110, $85, and $45 per hour, respectively, to its SPs, GPs and NPs in both locations.

Currently, the suburban location staff comprises 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.


Based on Annual Visits and Annual Paid Hours listed in Example 9.4Based on Annual Visits and Annual Paid Hours listed in Example 9.4

Adjustments for Inputs: 9.6 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 CostSuburban = $110 (115,000*0.50) + $85 (115,000*0.30) + $45 (115,000*0.20).

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

Labor CostSuburban = $10,292,500.

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

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

Labor CostDowntown = $9,464,000.

24.76$000,135

500,292,10SuburbanVisitperCostLabor

57.97$000,97

000,464,9DowntownVisitperCostLabor

Lower volume at Downtown location, Higher labor cost per visitLower volume at Downtown location, Higher labor cost per visit


Adjustments for Outputs

.

Service-Mix Adjustments. Service-mix adjustment is useful 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.

nH

HW

i

ii

ii XWVolumeAdjusted *



.

Example 9.7:

Two hospitals, each with unadjusted volume of 10,000 patient days per month, provide only two services, S1 and S2, requiring respectively 3 and 7 hours of nursing time per patient day.

Hospital A has a service-mix distribution of 2000 patient days for S1 and 8000 patient days for S2. Hospital B has 8000 days for S1 and 2000 days for S2.

Calculate adjusted patient days for both hospitals.

Service-Mix Adjustments



Solution: page 217In this case, total unadjusted volume is simply the sum of the volume for each service in each hospital, or Unadjusted Volume = X1 + X2.

Hospital-A Hospital-B

Service S1 (3 hours/patient day) X1=2000 X1=8000

Service S2 (7 hours/patient day) X2=8000 X2=2000

Total Unadjusted Volume 10,000 10,000

Adjusted Volume = W1X1 + W2X2.

6.05

3

210

3

2)73(

311

nH

HW

i

. 4.15

7

210

7

2)73(

722

nH

HW

i

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.

Service-Mix Adjustments



Case-Mix Adjustments. 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 acuity categories.

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.

ijij PWIndexMixCase *



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, 4.0, 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.

Case-Mix Adjustments


Adjustments for OutputsCase-Mix Adjustments

17.03

5.0

412

5.0

4)0.60.45.15.0(

5.011

nH

HW

i

.

.

.

.5.0

3

5.1

412

5.1

4)0.60.45.15.0(

5.122

nH

HW

i

.33.1

3

0.4

412

0.4

4)0.60.45.15.0(

0.433

nH

HW

i

.

00.23

0.6

412

0.6

4)0.60.45.15.0(

0.644

nH

HW

i

Solution: Page 219

.12.1)25.0*00.2()35.0*33.1()25.0*5.0()15.0*17.0(* iAiA PWIndexmixCase

.01.1)15.0*00.2()40.0*33.1()30.0*5.0()15.0*17.0(* iBiB PWIndexmixCase


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.


Case-Mix Adjustments


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:

jij

n

ii NPH **CareDirect of Hours

1j



Percentage of Hours in Direct Care. This is an additional measure can be derived from the “Hours of Direct Care” calculation, as the ratio of direct care hours to total care hours.

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.

WorkedHours

CareDirect in HoursCareDirect in Hours ofPercent

Hours Adjusted

CareDirect in HoursCareDirect in Hours Adjusted of Percentage



Example 9.9:

Using information from Examples 9.3 and 9.8calculate:

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 ofadjusted hours in direct care.



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 210,000 and 180,000, respectively.



Solution:

.

).**(CareDirect of Hours4

1A AiA

ii NPH

)000,14*25.*0.6()000,14*35.*0.4()000,14*25.*5.1()000,14*15.*5.0(CareDirect of Hours A

900,46CareDirect of Hours A .

).**(CareDirect of Hours4

1B BiB

ii NPH

)000,10*15.*0.6()000,10*40.*0.4()000,10*30.*5.1()000,10*15.*5.0(CareDirect of Hours B

250,30CareDirect of Hours B



%3.22223.0000,210

900,46

WorkedHours

CareDirect in HoursCareDirect in Hours ofPercentage orA

.

%8.16168.0000,180

250,30

WorkedHours

CareDirect in HoursCareDirect in Hours of Percentage orB

%.3.22223.0000,210

46900

Hours Adjusted

CareDirect in HoursCareDirect in Hours Adjusted ofPercentage orA

%.6.20206.0700,146

30250

Hours Adjusted

CareDirect in HoursCareDirect in Hours Adjusted ofPercentage orB

Solution:


Hospital A

Hospital B

Quantity of Inputs(Staffing Level)

Quality of Output

I2 I1

QA

QB

Figure 9.1 Productivity and Quality Tradeoff

A

BA’

I

QA’’

QA”

IA”

Source: Shukla, R.K. Theories and Strategies of Healthcare: Technology-Strategy-Performance, Chapter 4, Unpublished Manuscript, 1991. Printed with permission.


Inputs-- staffing level Output-- quality of output (uniform

definition of quality?) Hospital A provides better level of quality

for a given staffing level According to Ozcan, this quality-adjusted

productivity measurement is possible only if a uniform quality definition and a known quality-quantity relationship exist.

Interpretation of Figure 9.1


Efficiency-- using the minimum number of inputs for a given number of outputs

Effectiveness-- refers to outputs. Are the proper inputs being used to produce the appropriate outcomes?

Productivity-- a broader concept than efficiency; refers to effective use of a given set of resources

New Methods 1


Dimensions of Efficiency Technical Efficiency-- relationship between

various inputs and related outputs; use minimum combination of resources for a given level of quantity or level of care.

Allocative (Economic) Eficiency-- adds cost to the measure of technical efficiency.

Data Envelope Analysis Uses linear programming to search for optimal

combinations of inputs and outputs

New Methods 2

Ozcan: Chapter 9 Productivity ISE 491 Dr. Joan Burtner.

Documents

Transcript of Ozcan: Chapter 9 Productivity ISE 491 Dr. Joan Burtner.