Chapter 3. Decision Making in Healthcare Facilities

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Chapter 3. Decision Making in Healthcare
Facilities
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Outline

• Decision Process
• What Causes Poor Decisions?
• The Decision Level Decision Milieu
• Decision Making under Uncertainty
• Payoff Table
• Methods
• Decision Making under Risk
• EVM, EOL, EVPI
• Decision Tree Approach
• Rollback Procedure
• What if Payoff Values are Cost?
• Decision Analysis with Non-Monetary Values
  Multiple-Attributes
• Dominance
• Minimum Attribute Satisfaction
• Most Important Attribute

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The Decision Process

• Identification of the problem and its nature
• Specification of objectives and decision criteria
• Development of alternatives
• Analysis and comparison of alternatives
• Selection of the best alternative
• Implementation of the choice
• Controlling and monitoring the results

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What Causes Poor Decisions?

• Mistakes in the Decision Process
• Bounded Rationality is the limits imposed on
  decision making by costs, human abilities and
  errors, time, technology, and the tractability of
  data.
• Suboptimization is characterized by Decisions
  are often departmentalized as separate
  organizational units compete for scarce
  resources. Individual departments often seek
  solutions that benefit their own department, but
  not necessarily the healthcare organization as a
  whole.

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Decision Theory
represents a general approach to decision making
which is suitable for a wide range of operations
management decisions, including capacity,
service design, location planning, equipment
selection, etc.
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The Decision Level Decision Milieu

• Certainty-- Known values for parameters of
  interest
• Uncertainty-- Impossible to assess the likelihood
  of various possible future events
• Risk-- Certain parameters have probabilistic
  outcomes

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Certainty

• Certainty rarely exists, especially in health
  care decisions. But if it does, simply choose
  the best available option (highest profit/least
  cost).

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Decision Making under Uncertainty

• Maximin-- best of the worst (pessimist)
• Maximax-- best of the best (optimist)
• Hurwitz-- allows you to adjust the
  probabilities/weighing between maximin and
  maximax or pessimist vs. optimist
• Laplace-- best average payoff
• Minimax Regret-- best of the worst regrets

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Decision Tools
Table 3.1 Payoff Table
Alternative\State of Nature S1 S2 . Sn
A1 O11 O12 . O1n
A2 O21 O22 . O2n
. ..
Am Om1 Om2 . Omn
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Example 3.1 A major imaging center is not able
to meet the increased demand from patients for
MRIs. The administration is willing to explore
the possibilities by evaluating such alternatives
as adding one or two additional units or out
sourcing to other image centers and earning a
commission of 30.00 per MRI. A feasibility
analysis showed that three major demand chunks
could occur in the future, summarized as 500,
750 and 1000 additional MRI requests. The
financial analysis of the potential business
summarizes profits/losses under additional MRI
demand chunks in a payoff table shown in Table
below.
Alternatives 500 Cases 750 Cases 1000 Cases
Buy One MRI Unit -15 200 300
Buy Two MRI Units -150 100 725
Outsource 15 22.5 40
in 000s
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Maximin Solution
Alternatives 500 Cases 750 Cases 1000 Cases Worst
Buy One MRI Unit -15 200 300 -15
Buy Two MRI Units -150 100 725 -150
Outsource 15 22.5 40 15
in 000s
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Maximax Solution
Alternatives 500 Cases 750 Cases 1000 Cases Best
Buy One MRI Unit -15 200 300 300
Buy Two MRI Units -150 100 725 725
Outsource 15 22.5 40 40
in 000s
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Hurwitz Solution
For optimism with a 0.5. Then the HV value
for the three alternatives would be HV (Buy
one MRI unit) .5(300,000)(.5)(-15,000)
142,500. HV (Buy two MRI units)
.5(725,000)(.5)(-150,000) 287,500. HV
(Outsource) .5(40,000)(.5)(15,000)
27,500.
a HV Decision Alternative
1.0 725,000 Buy Two MRI Units
.5 287,500 Buy Two MRI Units
.4 200,000 Buy Two MRI Units
.3 112.500 Buy Two MRI Units
.24 60,600 Buy One MRI Unit
.2 48,000 Buy One MRI Unit
.1 17,500 Outsource
0 15,000 Outsource
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Opportunity Losses (Regrets)
Alternatives 500 Cases 750 Cases 1000 Cases Worst
Buy One MRI Unit 30 0 425 425
Buy Two MRI Units 165 100 0 165
Outsource 0 177.5 685 685
in 000s
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Laplace Strategy
Probability 1/3 1/3 1/3 Expected Value
Alternatives 500 Cases 750 Cases 1000 Cases Expected Value
Buy One MRI Units -15 200 300 161.67
Buy Two MRI Units -150 100 725 225
Outsource 15 22.5 40 25.89
in 000s
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Expected Value Model
Once the healthcare manager has assessed the
probability distribution, computation of the
expected values for each alternative is
straightforward, as follows
EMV(Ai) Sj pj Oij
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Payoff Table for EMV
Probability .2 .6 .2 Expected Value
Alternatives 500 Cases 750 Cases 1000 Cases Expected Value
Buy One MRI Unit -15 200 300 177
Buy Two MRI Units -150 100 725 175
Outsource 15 22.5 40 24.5
in 000s
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Expected Opportunity Loss
The probabilities can also be incorporated into
the regrets (or opportunity losses) calculated
earlier. In this way the healthcare manager can
assess the expected losses and try to minimize
them with proper decision. Calculations of
expected opportunity loss follow the formula
EOL(Ai) Sj pj Rij
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Expected Opportunity Loss
Probability .2 .6 .2 Expected Opportunity Loss
Alternative 500 Cases 750 Cases 1000 Cases Expected Opportunity Loss
Buy One MRI Unit 30 0 425 91
Buy Two MRI Units 165 100 0 93
Outsource 0 177.5 685 243.5
in 000s
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Expected Value of Perfect Information (EVPI)
EVPI EVUC-EMV
EVUC Sj pj (Best Oij given Sj)
Probability .2 .6 .2
Alternatives 500 Cases 750 Cases 1000 Cases
Buy One MRI Unit -15 200 300
Buy Two MRI Units -150 100 725
Outsource 15 22.5 40
in 000s
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Expected Value of Perfect Information (EVPI)
EVPI EVUC-EMV
EVUC Sj pj (Best Oij given Sj)
EVUC (.215000) (.6200000) (.2725000)
268000.
EMV 177,000
EVPI 268,000 177,000 91,000
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What if Payoffs are Costs?
Alternatives 500 Cases 750 Cases 1000 Cases
Buy One MRI Unit 2,050 2,075 2,100
Buy Two MRI Units 4,050 4,075 4,100
Outsource 5 10 15
in 000s
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Regret Table Using Costs
Alternatives 500 Cases 750 Cases 1000 Cases
Buy One MRI Unit 2,050-52,045 2,075-102,065 2,100-152,085
Buy Two MRI Units 4,050-54,045 4,075-104,065 4,100-154,085
Outsource 5-50 10-100 15-150
in 000s
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Decision Tools-- The Decision Tree
Outcomes
Events
Outcome 1 Outcome 4 Outcome 7
Outcome 2 Outcome 5 Outcome 8
Outcome 3 Outcome 6 Outcome 9
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Figure 3.1 Decision Tree
-15
500 Cases, p.2
750 Cases, p.6
200
1000 Cases, p.2
300
Buy One MRI Unit
-150
500 Cases, p.2
Buy Two MRI Units
750 Cases, p.6
100
1000 Cases, p.2
725
Outsource
15
500 Cases, p.2
750 Cases, p.6
22.5
in 000
1000 Cases, p.2
40
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Analysis of the Decision Tree Rollback Procedure
-15
500 Cases, p.2
177
750 Cases, p.6
200
1000 Cases, p.2
300
Buy One MRI Unit
-150
500 Cases, p.2
Buy Two MRI Units
750 Cases, p.6
175
100
177

1000 Cases, p.2
725

Outsource
15
500 Cases, p.2
750 Cases, p.6
24.5
22.5
in 000
1000 Cases, p.2
40
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Multi-attribute Decisions

• Dominance Procedure compares a pair of
  alternatives attribute by attribute.
• Minimum Attribute Satisfaction Procedure
  satisfactory levels are set for each alternative
• Most Important Attribute Procedure attributes
  are ranked in order of importance
• Combination combines two or more of the above
  procedures.

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Decision Analysis with Non-Monetary Values and
Multiple Attributes
Attributes \ Alternative Cardinal McKesson Owens Minor Importance Ranking Minimum Acceptable Level
Availability 7 7 7 1 gt 7
Reliability of IT Technology 7 5 7 2 gt 6
Quality of Products 8 9 8 3 gt 7
Cost in 000 per year 23,749 24,195 23,688 5 lt25,000
On Time Delivery 97 95 97 4 gt95
Attributes are scored on a 1-10 scale (with the
exception of those associated with costs and
on-time-delivery percentage), score of 10 being
most favorable.
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The End