MEMORANDUM
DATE:
TO:
FROM:
RE:
August 17, 2017
Mr. Louis Pasture, Director of Strategic Planning
Group 1 Consulting Group
Cost Control Analysis
Pursuant to your instructions we have prepared a report detailing the company’s current
financial situation and an evaluation of the two options for controlling costs.
Green Guard Care – Cost Control Analysis
Executive Summary:
The purpose of this report is to prepare a report of Green Guard Care’s current financial
situation and include an evaluation of the two options for controlling costs on the Arc Electric
account.
Green Guard Care is a managed care company that provides financial health care services for
employees of Arc Electric, Inc. Louis Pasture, the company’s Director of Strategic Planning and
Forecasting, recently directed his staff to perform a financial analysis or current utilization and
costs incurred under the Arc Electric account. The data gathered from the aforementioned
analysis indicated a sharp increase in the number of physician office visits over the past month.
Concerned about the company’s profitability and retaining a valued client (Arc ELectric), Mr.
Pasture contracted our consulting group to analyze Green Guard’s financial situation and to
evaluate whether his staff’s suggestions to either (a) increase the copayment, or (b) implement
a reduction in charges for physician office visits are appropriate and beneficial.
Our analysis consisted of using the given allocation of revenue to compare the profitability of
hospital and surgical services to physician services. We calculated visits per employee and the
cost per visit for each week and used statistical calculations (e.g., mean, standard deviation,
and coefficient of variation) for a six month period to better understand the trend in total
outpatient physician costs per Arc Electric employee. We ran two regressions to evaluate the
relationship between visits per week and week, cost per visit and week, and compared the
results to determine how the resulting information would be useful in helping Mr. Pasture
make a decision. To evaluate the feasibility of increasing the copayment level, we calculated
elasticity of demand at each copayment level to determine how sensitive the insured would be
to changes in price. We also used six months of data to simulate profitability of the physician
services department if copayments were increased to $20 and $25 respectively. We calculated
the percentage reduction in physician payments that would be required to achieve the same
level of profits as in the profitability simulation previously noted. Finally, we considered
suggesting rationing health care services as a method of controlling costs.
Introduction:
Background: Green Guard Care is a managed care company that provides financial health care
services for employees of Arc Electric, Inc. Louis Pasture, the company’s Director of Strategic
Planning and Forecasting, recently directed his staff to perform a financial analysis or current
utilization and costs incurred under the Arc Electric account. The data gathered from the
aforementioned analysis indicated a sharp increase in the number of physician office visits over
the past month. Concerned about the company’s profitability and retaining a valued client (Arc
ELectric), Mr. Pasture contracted our consulting group to analyze Green Guard’s financial
situation and to evaluate whether his staff’s suggestions to either (a) increase the copayment,
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Green Guard Care – Cost Control Analysis
or (b) implement a reduction in charges for physician office visits are appropriate and
beneficial.
Statement of purpose: the purpose of this report is to prepare a report of Green Guard’s
current financial situation and include an evaluation of the two options for controlling costs on
the Arc Electric account.
Our analysis was informed by the following information:
1. Compare the profitability of hospital and surgical services to physician services.
2. Used statistical data to understand the trend in total outpatient physician costs per Arc
Electric employee.
3. Regression analysis (two sets).
4. Calculated elasticity of demand for physician visits at each copayment level.
5. Simulate profitability of the physician services department by increasing copayments
levels to $20 and $25.
6. Calculated the percentage reduction in physician payments that would be required to
achieve the same level of profits as in the profitability simulation previously noted.
7. Analyzed rationing health care services as a method of controlling costs and submitted a
recommendation.
Question 1 – Profitability Comparison
Further analysis of physician visits may be needed due to the large increase in physician office
visits from the old (July 2006) to the new (August 2006). This difference of $337,900 to
$391,450 is a 15.84% jump increase from old to new. The change from physician office visits
cost from July 2006 to August 2006 increased by %3.1 or $53,550 .
Hospital and surgical services are $137.50 and make up 55% of the monthly premium
allocation, physician office visits are $75.00 which make up 30% of the monthly premium
allocation, and services and administration fees of $37.50 which makes up 15% of the monthly
premium allocation. The total monthly premium collected per an employee is $250.00.
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Green Guard Care – Cost Control Analysis
Question 1 – Profitability Comparison (Continued):
Green Guard Care has a target budgeted revenue of $1,250,000.00 from providing healthcare
to 5,000 members and in the following months this is what they actually received; the number
of member’s premiums collected for the month of July were 4,129 making the total revenue for
the month of July to be $1,032,250.00 and for the month of August 4,137 making the total
revenue for August of $1,034,250.00.
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Green Guard Care – Cost Control Analysis
Using the data provided, we observe in Figure 1 that Green Guard Care has been spending a
significant percentage of their budget on physician visits. We have the total cost of physician
visits for the month of July at $337,900 and the budget for physician office visits is 30% which
Question 1 – Profitability Comparison (continued):
should be $309,675.00 but they’re 2.73% above the anticipated budget. For the month of
August, we have $391,450 for physician office visits which exceeds the expected budget by
7.84%, our projection for the physician visits budget was $375,000.00 which we exceeded the
threshold. (Appendix 1)
Question 2 – Statistical Calculations
Refer to appendix 4 for the scatter plots that show the relationship between the number of
employees, number of visits per week, and the total physician costs. The calculations for visits
per employee and the cost per visit for each week can been found in appendix 3 (calculation
average). These calculations are without the copayments.
The tables below show the calculations of the two variables, visits/employees and cost/visits,
that include the means, standard deviation, and coefficient of variation. Going through each
statistic to see how they help explain total outpatient physician costs per Arc Electric employee.
The mean shows the average of the total number over the 25 weeks. The standard deviation is
the measure of the dispersion of the data set as a whole. As you can see variable 1 has a much
smaller standard deviation compared to variable 2 suggesting that cost fluctuates much more
than visits per employee. The coefficient of variation is the standard deviation divided by the
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Green Guard Care – Cost Control Analysis
mean which is good to compare different variables with different units. The variable with the
smaller coefficient of variation is less dispersed than the other variable. So even though variable
1 has the smaller standard deviation, it has a much more variability compared to the mean. So
the trend in cost has increased as the amount of visits has increased.
Variable #1 (#Visits/#Employees)
Variable #2 (Cost/#Visits)
Count
25
Count
25
Mean
0.1133
Mean
176.9
Standard Deviation
0.0086
Standard Deviation
10.5
Coefficient of Variation
7.60%
Coefficient of Variation
5.94%
Question 3 – Regression Analysis
Graph A
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Green Guard Care – Cost Control Analysis
Graph A shows the relationship between the numbers of visits per week in 25- week period.
Using the values from Green-Guard date file, we found the following linear regression equation:
Y= 403.439 + 4.68X, where Y is the number of visits per week “dependent variable” and X is
the week number “Independent variable.” This equation tells us that as the value of X, which
is the number of week, increase by a value of 1, the number of visits per week “Y” increases by
a value of 4.68 visits per week.
The correlation coefficient “R” of this relationship is 0.912. This value indicates that there is a
strong positive linear relationship between the visits per week and week. As we go further in
weeks, the number of visits per week increases. Moreover, the computed p-value for this
relationship is estimated to be 2e-10. This small p-value indicates that the significance of an
existing linear relationship between the two variables is strong.
Question 3 – Regression Analysis (continued)
Graph B
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Green Guard Care – Cost Control Analysis
Graph B shows the relationship between the costs per visits in a 25-week period. Using the
values from the Green Guard date file, we found the following linear regression equation:
Y = 174.86 + 0.157X, where Y is the cost per visit (the “dependent variable”) and X is the week
number (the “independent variable”). This equation tells us that as the value of X, which is the
week number, increases by a value of 1, the cost per visits “Y” increases by a value of 0.157
U.S. dollars. However, by looking at the graph, this formula is not necessarily right and to
validate the formula, we computed the correlation coefficient and p-value of the data.
The correlation coefficient “R” of this relationship is 0.110. This value indicates that there is
almost no linear relationship between the cost per visit and week. By looking at the graph, It is
clear that the change in the cost per visit is not associated with the week number. Moreover,
the computed p-value for this relationship is estimated to be 0.60103. This large p-value
corresponds to the conclusion we assumed using the correlation coefficient value, that the
significance of an existing linear relationship between the two variables is weak.
Based on Graph A the number of visits from week 0-25 increased on average by 4.68 visits per
week. Mr. Pasture may view this graph and notice that the $15 copayment has a very small
effect on the increasing physician visits. This $15 copayment is low and does not deter physician
visits from decreasing. In order to offset the increasing visits Mr. Pasture may choose to
increase the $15 copayment to keep up with the current copayments utilized by other
companies as several employees could be price sensitive. This increase in copayments will
decrease the amount of physician visits per week and regulate the increasing cost.
c)
Based on Graph B Mr. Pasture may notice there is a weak linear relationship with the p-value
estimated at 0.601. Graph B shows high jumps and declines in visits throughout the 25 weeks.
This information may be interpreted by showing that regardless of the price of copayment,
patients who absolutely had to visit the physician were going to go regardless of a copayment
increase of 10 dollars.
Our recommendation to Mr. Pasture is to increase the copayment to keep up to date with
similar copayments and this will regulate the increasing physician visits by lowering the demand
of physician visits that were not necessary.
Question 4 – Copayment Scenarios and Profitability Simulation
To evaluate the feasibility of increasing the copayment level, we calculated elasticity of demand
at each copayment level to determine how sensitive the insured would be to changes in price.
The data in Figure 3 displays the calculated price elasticity of demand for physician visits at
each copayment level using the arc method. (Appendix 2)
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Green Guard Care – Cost Control Analysis
The data in figure 3 shows that as copayment levels increase, price sensitivity to the
incremental changes increases. Unless there is a life-threatening emergency, patients are more
likely to reduce the number of visits to their physician if they have a higher copayment. The
graph in figure 4 shows the relationship between price (copayment) and quantity demanded
(physician visits per capita).
This information will assist Mr. Pasture in deciding whether or not raising copayment prices is
an appropriate cost control mechanism policy to implement at Green Guard Care.
Figure 3
Question 4 – Copayment Scenarios and Profitability Simulation (continued)
Figure 4
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Green Guard Care – Cost Control Analysis
Question 5 – Reduction in Physician Payments - Calculations
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Green Guard Care – Cost Control Analysis
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Green Guard Care – Cost Control Analysis
Conclusion:
In conclusion we would advise Mr. Pasture to raise the copayments for physician visits from $15
to $25. The reasoning behind raising copayments and not lowering physician payments is that
lowering physician payments may affect the quality of care from physicians. Another issue that
arises is that due to the rising physician visits there may be a lack of availability of physicians. In
order to offset the rising physician visits and ensure the highest quality of care we recommend
that Mr. Pasture raises copayments to $25. The reason for raising the copayment is that this
would keep up with the up to date copayment levels of other health insurers. This raise in
copayment would also offset the rising physician visits, and would not affect necessary
physician visits as seen on graph 3b and the weak correlation. This rise in copayment price
would lower and offset the rising physician visits and ensure the quality of care remains as high
as possible.
Appendix 1
July 2006
Cost/Total Cost
Percentage of Total Cost
Hospital Services Inpatient
$203,425/$915,015
%22.23
Hospital Services Outpatient
$182,440/$915,015
%19.94
Surgical Service
$101,250/$915,015
%11.06
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Green Guard Care – Cost Control Analysis
Physician Office Visits
$337,900/$915,015
%36.93
Administrative Expenses
$90,000/$915,015
%9.84
August 2006
Cost/Total Cost
Percentage of Total Cost
Hospital Services Inpatient
$212,250/$977,800
%21.70
Hospital Services Outpatient
$180,700/$977,800
%18.49
Surgical Services
$103,400/$977,800
%10.58
Physician Office Visits
$391,450/$977,800
%40.03
Administrative Expenses
$90,000/$977,800
%9.20
Appendix 2
Formula (Arc Elasticity of Demand)
Individual Calculations For Arc Elasticity of Demand
$10 copayment level
(6.3 - 6.0)/(10 - 15)*(10 + 15)/(6.3 + 6.0)
$15 copayment level
(6.0 - 5.7)/(15 - 20)*(15 + 20)/(6.0 + 5.7)
$20 copayment level
(5.7 - 5.4)/(20 - 25)*(20 + 25)/(5.7 + 5.4)
$25 copayment level
(5.4 - 5.1)/(25 - 30)*(25 + 30)/(5.4 + 5.1)
$30 copayment level
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Green Guard Care – Cost Control Analysis
(5.1 - 4.8)/(30 - 35)*(30 + 35)/(5.1 + 4.8)
$35 copayment level
(4.8 - 4.5)/(35 - 40)*(35 + 40)/(4.8 + 4.5)
Appendix 3
July 2006
Hospital Services - Inpatient - $203,425/$915,015= %22.23
Hospital Services - Outpatient - $182,440/$915,015= %19.94
Surgical Service - $101,250/ $915,015= %11.06
Physician Office Visits - $337,900/ $915,015= %36.93
Administrative Expenses- $90,000/$915,015= %9.84
August 2006
Hospital Services - Inpatient - $212,250/$977,800=%21.70
Hospital Services - Outpatient - $180,700/$977,800=%18.49
Surgical Service - $103,400/$977,800=%10.58
Physician Office Visits - $391,450/$977,800= %40.03
Administrative Expenses - $90000/$977,800= %9.20
Calculations (Averages)
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Green Guard Care – Cost Control Analysis
Appendix 4
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Green Guard Care – Cost Control Analysis
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Visit per week: Analysis
Strong correlation between visits per week and visits
• The R-square is 0.8313
• This proves an extremely strong relationship, it is very close to 1
• P- Value is 2.31829E-10, which is very low (under 0.05)
. This tells us that we reject the null that visits and weeks are unrelated
• Regression line equation is y=4.68x+403.39
• There is a positive coefficients
• Tell us that as the weeks go by the number of visits per week increases
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Cost
per visit: Analysis
• Weak correlation between cost per visit and week
• The R-square is 0.0121
• This proves a weak relationship
• P- Value is 0.601, which is greater than 0.05
• Tells us that we do no reject the null that visits and cost are unrelated
• Regression line equation is y=0.16x+174.86
• Regression line is positive, but there is a weak correlation
• Tell us that cost per week and week are not related
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Regression: Comparing
• As the weeks go on our employees are visiting the physicians more
• We should to give employees an incentive to visit the physicians less
• Should visit less no matter what the cost is
• The cost per week is unrelated to the number of weeks
So maybe the cost of visiting the physician isn't the problem
. Since total cost will also be increasing as the weeks
• Regardless of cost since visits per week is increasing
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