SANTA FE HEALTHCARE: Capitation and Risk Sharing
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Model with Questions, Student Version
This case requires students to examine the issues involved with payment allocation and risk sharing
within a Physician Hospital Organization (PHO). The model calculates the dollar distributions to each
provider category and the budgeted and actual total reimbursement for the PHO's primary care
physicians, specialist physicians, and hospital. In addition, the model provides the calculations for two
illustrative risk pools.
The model consists of a complete base case analysis--no changes need to be made to the existing
MODEL-GENERATED DATA section. However, values in the INPUT DATA section of the student
spreadsheet have been replaced by zeros. Students must select appropriate input values and enter
them into the cells with values colored red. After this is done, any error cells will be corrected and
the base case solution will appear. The KEY OUTPUT section includes the most important output
from the MODEL-GENERATED DATA section.
INPUT DATA: KEY OUTPUT:
PMPM payment from the Plan $0 Total Budgeted Reimbursement
Primary care physicians:
Number of members 0 Premium allocation $0
Professional services risk pool 0
Allocation of premium dollar (%): Inpatient services risk pool 0
PHO administration / overhead 0.0% Total $0
Paid to within-system physicians: Specialist care physicians:
Primary care 0.0% Premium allocation $0
Specialists 0.0% Professional services risk pool 0
Ancillary services 0.0% Inpatient services risk pool 0
Administration / profit 0.0% Total $0
Paid to within-system hospital 0.0% Within-system hospital:
Paid for prescription drugs 0.0% Premium allocation $0
Paid to out-of-system providers 0.0% Inpatient services risk pool 0
Professional services risk pool 0.0% Total $0
Inpatient services risk pool 0.0%
Total premium dollar 0.0% Total Actual Reimbursement
Primary care physicians:
Distribution of professional services risk pool: Actual payment $0
Primary care physicians 0% Professional services risk pool 0
Specialist care physicians 0% Inpatient services risk pool 0
Total 0% Total $0
Specialist care physicians:
Distribution of inpatient services risk pool: Actual payment $0
Primary care physicians 0% Professional services risk pool 0
Specialist care physicians 0% Inpatient services risk pool 0
Hospital 0% Total $0
Total 0% Within-system hospital:
Actual payment $0
Sensitivity analysis: Inpatient services risk pool 0
Suppose actual payment differs from premium Total $0
allocation by the percentages below:
Specialists 0%
Hospital 0%
MODEL-GENERATED DATA:
Sensitivity analysis:
Allocation of Premium: Results if Actual Payment Differs from Premium Allocation
PHO administration / overhead $0 PHO administration / overhead $0
Paid to within-system physicians: Paid to within-system physicians:
Primary care 0 Primary care 0
Specialists 0 Specialists 0
Ancillary services 0 Ancillary services 0
Administration / profit 0 Administration / profit 0
Paid to within-system hospital 0 Paid to within-system hospital 0
Paid for prescription drugs 0 Paid for prescription drugs 0
Paid to out-of-system providers 0 Paid to out-of-system providers 0
Professional services risk pool 0 Professional services risk pool 0
Inpatient services risk pool 0 Inpatient services risk pool 0
Total premium dollar $0 Total revenue $0
Professional Services Risk Pool:
Budgeted payments for specialists $0
Actual payments for specialists $0
Variance from budget $0
Risk pool starting amount $0
Remainder in pool $0
Risk pool allocation
Primary care physicians $0
Specialists $0
Inpatient Services Risk Pool:
Budgeted payments for inpatient services $0
Actual payments for inpatient services $0
Variance from budget $0
Risk pool starting amount $0
Remainder in pool $0
Risk pool allocation
Primary care physicians $0
Specialists $0
Hospital $0
END
Sample Solution
experienced labour shortages. Nattrass (1996:46; 2001) notes that in response to this challenge the South African government used coercive measures to ensure cheap labour to meet the demands of industry, mines, and commercial farms. Development driven by gold revenues and foreign capital ensured a consistent flow of labour away from traditional agriculture in favour of rapid urbanization (Nattrass 1996:46; Stander 1996). But this growth ground to a halt in the mid-1970s when the gold boom burst and effectively lost its luster. By the late 1970s unemployment had taken hold such that by 1994, one third of the African labour force was simply unable to find work. From the mid-1920s South Africa’s industrialisation strategy mirrored that of Latin America with a strong inward focus. Initially, this strategy supported labour-intensive industries but slowly began losing steam by the 1960s. Unlike the East Asian economies, who at that time adopted a more outward-orientated export approach, South Africa closed in with heavier protectionist measures and a capital-intensive industry approach. These developments, together with negative real interest rates and large-scale strategic investments such as Sasol, made for a lethal concoction of rising capital intensity. The net result is that economy became increasingly more capital intensive at the expense of labour intensity. The issue of employment creation is a hotly contested one in South African politics. Twenty years after democracy, it is still the election-dominating card, and the priority of national, provincial and municipal card. In fact, amongst the biggest and most visible political parties, the promise to create jobs is at the top of their election manifestos. ‘We have created 3.7million work opportunities over the past 5years’ ‘ Zuma, State of the Nation 2014 ‘The manifest we release today is a manifesto for jobs’ ‘ Helen Zille, Leader of opposition Democratic Alliance. Without getting into the political semantics it is important to heed Bhora’s (2003) cautions that we must understand the absolute expansion of employment within context. More simply, the number of jobs that have been created must be understood against the number of new entrants that have come into the labour market over the same period. For example, between 1995 and 2002: 1.6million jobs were created. However, 5 million new entrants entered the labour market over the same period. The inability of the labour force to absorb new entrants in addition to the graduate unemploy