Shared risk programmes are ‘flavour of the month’ in many countries. From the United States’ accountable care organisations (ACOs) to Spain’s integrated hospital arrangements and the introduction of alternative contracting models in the NHS, passing population utilisation risk via capitated payment models to providers is much in vogue.
This is driven by an attempt to change the traditional healthcare
model that operates on a fee-for-service reimbursement model
and incentivises activity, to one that delivers integrated care
that is centred on the patient. Such transformation is fraught
with complexities that, unless implemented with care and due
attention, can de-stabilise individual delivery units and the health
economy at large. A successful risk contract is not one that
passes the maximum risk from payers to providers, irrespective
of whether they can manage that risk, but about entering into
a mutually beneficial risk-sharing arrangement that promotes a
sustainable health economy from a financial perspective, while
providing better clinical care and outcomes for patients. In this
article we share some of the considerations for both payers and
providers in designing a successful risk contract and some of
the pitfalls. These are mainly from the provider perspective, but
it is worth reinforcing that success from a payer perspective
also hinges on allowing providers to create sustainable and
replicable business models.
Many hospitals and payers are negotiating new payment models
In the NHS in particular, the push for finding new payment
models stems from a recognition that the Payment by Results
(PbR) system has resulted in conflicting incentives for hospitals.
There is little point in trying to move patient care away from
hospitals with a financial reimbursement system that rewards
admission. Clinical Commissioning Groups (CCGs) have neither
the tools nor the resources to manage utilisation intensively in the
traditional way; some are therefore looking to pass utilisation risk
to their provider network (and in some cases also pass the wider
health population risk).
Understandably, most hospitals are being extremely cautious in
transitioning to new payment models. But shared risk agreements
can be a good starting point for hospitals and other providers
to transition away from PbR payment structures to populationbased
payment arrangements without taking on unnecessary
exposure to ‘insurance’ risks. At the same time, CCGs are keen
to establish shared-savings programmes and other value-based
payment models to drive incentives for health providers to
meet cost savings targets, while meeting obligations to provide
high-quality care. Many CCGs have stated goals in terms of the
number of integrated care initiatives they are targeting to have in
place over the next few years.
It is critical to understand the characteristics of the risk each party assumes
In simple terms, risk can be split into two parts: a) trend risk
and b) volatility risk. Trend risk can be further subdivided into
- The population size risk – i.e., the risk that the covered population is larger or smaller than assumed.
- The population demographic risk – i.e., the risk that the covered population is less healthy than assumed (because it is older or has higher long-term condition prevalence than average, or a different socio-economic profile).
- Utilisation or activity risk – the risk of using healthcare services more than expected, regardless of the demographics.
- Average or unit cost risk – the risk of the average cost of the activity being higher than expected.
In a true capitation contract, the first two components are
removed from trend risk, as they are compensated for via the
calculation of the capitation rate. Therefore, trend risk should
centre on managing utilisation and unit costs.
Volatility risk is true insurance risk and decreases as the
population size increases, but is also highly dependent on the
types of services being delivered. Common, low-cost services
such as physiotherapy have very low volatility risk and therefore
will not experience much random variation from year to year, even
with small populations. Rare cancers will have extremely high
volatility risk and will be subject to material changes in utilisation
from year to year, unless the population over which they are
spread is very large.
Fair deals often require substantial and thoughtful collaboration
When negotiating the terms of a new shared risk agreement with a
CCG, it is important for providers to understand what ‘fair’ can mean
and to understand the types of risks they are being asked to assume.
For many, it involves care management incentive agreements
rather than insurance risk transfer agreements. While it is entirely
appropriate for a provider to be asked to manage utilisation risk in
addition to the unit cost risk it has assumed under PbR, it may not be appropriate for a provider to be asked to manage population
size and demographic risk, over which it has no means of control,
or even measurement. The guiding principle is that risks should be
allocated to the party most able to control those risks. If a provider
is being asked to assume volatility risk, this should be clear and
transparent, to enable appropriate mechanisms (such as risk
pooling or commercial reinsurance) to be employed.
CCG and provider incentives should be aligned, with appropriate
and realistic targets, based on an understanding of the level
of clinical re-design necessary to achieve those targets. Some
CCGs have been quite prescriptive in the contracting model
and targets, with limited opportunity for the provider to negotiate
desired refinements to the contract framework or to the detailed
terms and assumptions used to populate the model. Other
CCGs have facilitated workshops to design an outcomes-based
contract alongside their providers almost from scratch. The level of
collaboration varies significantly.
While deal concepts are often straightforward, details are almost always complex
In theory, the concept of shared risk is relatively straightforward:
- Define the attributed population
- Develop a baseline per person per month (PPPM) cost
- Mutually agree on an appropriate trend and project the baseline cost to the performance year
- When the performance year is complete, measure the actual PPPM cost
- Risk-adjust the result for population health differences (either through a simple demographic adjustment or more complex predictive model approach)
- Calculate the net savings/loss
- Apply any agreed upon adjustments for quality parameters
- Share the savings/loss
However, in practice, shared risk agreements can be incredibly
complex to put together. Even the first component, the attributed
population, is not straightforward for a CCG. CCGs are reliant
on counts of those registered at GP practices, which may be
inaccurate for many reasons, and projections based off historical
The second component is also not simple for a CCG. Data
systems have not been designed to report historical activity on an
attributed population basis and therefore even getting accurate
historical spending for the services specified in the contract can
be a Herculean task—particularly when any services outside of
a hospital setting are involved. Developing a baseline PPPM
cost means precisely and accurately identifying the utilisation
and unit cost of every service used historically over the prior
one or two years for the proposed clinical specification and the exact attributed population. For example, if you are designing a
musculoskeletal outcomes-based contract for the adult population,
covering the entire MSK pathway, it is not sufficient to know
that the CCG spent £3m on a block community physiotherapy
contract last year. You must know exactly what cost is related to
services proposed under the contract for those over 18 years
only. In many systems around the world, these metrics are a
standard part of business intelligence reporting, but this is not
typically the case in the NHS.
The financial terms alone in risk-sharing programmes comprise
many different and often interrelated components, all of which need
careful consideration. Additionally, a prime contractor/provider1
may face additional implementation considerations such as
identifying where the savings opportunities lie, how to accrue and
report savings/losses in financial statements, administration of the
programme, ongoing reporting requirements through the contract
period, and how to divide up a surplus or deficit among the different
providers and other groups within the integrated care pathways.
Many CCGs have tried to circumvent the complexity by effectively
ignoring the population and demographic risk component and
trying to negotiate a block multi-year contract to cover all defined
services for the CCG population, with additional quality-related
payments and some component of risk share/gain share. Unless
the parameters of the deal are extremely clear up front, including
the remedy should assumptions about population size and
demography deviate materially from the initial starting assumptions,
this could be a significant financial risk to the provider.
This paper highlights some of the key issues both parties should
consider when negotiating a shared risk programme. The
issues presented here are covered at a high level and are by no
means exhaustive. The structures and terms of agreements vary
significantly, there is no one-size-fits-all or off-the-shelf solution. An
optimal model is one that reflects the underlying circumstances of
the local health economy.
Some lessons from overseas
While many countries are experimenting with risk-sharing
arrangements, the United States tends to have the most
advanced contractual agreements in place and be far ahead
in implementing these, which provides some useful lessons.
Perhaps the most dominant consideration of any proposed
agreement is the full economic impact on the health system.
What might appear to be a good deal on paper (the ‘stated’
share of any surplus or deficit) might actually be something very
different in practice (the ‘true’ share). Some of the components
commonly included in US shared risk models are:
- Target rebasing methods
- Minimum risk corridors
- Quality adjustments
Depending on how these components are dealt with in the
contracting model, it is feasible that a provider may receive as little
as 20% (possibly less) of the aggregate savings over a five-year
period under many ‘50/50’ agreements proposed by some payers.
Watch out for target rebasing that shifts savings to payers too quickly
Using the most recent available data to establish the following
year’s cost target can shift 100% of savings to the payer in
subsequent years. This can result in less opportunity for the health
system to recover the initial investment used to generate savings.
Minimum risk corridors can push modest savings to payers
Intended to avoid payments that are due to random variation,
this is a percentage range around the target within which there
is no settlement of savings or losses. However, it can lead
to a provider losing out on sharing in savings from small but
consistent reductions to utilisation. Wide corridors may also
lead to the payer keeping 100% of any savings. If providers
are entering these agreements because they are confident
of generating savings, then there is a higher likelihood that
risk corridors will reduce savings shared by the provider than
minimize deficits shared by the provider, which leads to potential
high downside for the provider, but little possible upside.
Quality adjustments can be inappropriately biased towards the payer
Most shared risk models will incorporate a link between quality
and the provider’s share of any savings/deficit. Many are
structured such that the provider does not receive the full savings
unless there are significant improvements in quality beyond
current levels. In many standard models, quality adjustments are
used to reduce the provider’s share of surplus while having no
impact on the provider’s share of any deficits. This is particularly
onerous for the provider if the quality targets are not realistic.
Figures 1 and 2 provide a simple illustration to demonstrate the
above concepts. In this illustrative scenario, the key terms of the
- The PPPM cost used to set the target for each year is based on
the PPPM cost from two years prior (e.g., the Year 3 target is
based on the Year 1 PPPM costs)
- The target is rebased each year such that the baseline PPPM cost used to set the target is the actual PPPM cost that the prime provider achieved from two years prior
- Savings and deficits are shared 50/50 (the ‘stated’ share)
- The ACO (integrated care provider) receives its full 50% share if quality measures are achieved, less if some are not fully met
- There is a minimum risk corridor of 1.5% (i.e., no savings or deficits are shared if within 1.5% of the target PPPM)
- The market trend used to set the cost target is 5% annually
The scenario further assumes the ACO achieves an annual trend of 4% over the five-year contract period, and partially meets the quality measures, resulting in it receiving 80% of its 50% share of savings.
Figure 1 illustrates the share of the savings under the terms of
the agreement. On average over the five-year contract period, the
ACO receives 36% of the total savings achieved (i.e., on average
a $3.73 PPPM share of the $10.37 PPPM total average saving
measured against the rebased cost target). The ACO’s share of
available savings over the five-year period is less than the stated
share of 50% because the minimum risk corridor impacts Year 1
and the quality adjustment impacts Years 2 through 5.
Figure 2 presents the calculation of savings using a different cost
target than Figure 1. Note that for this use, cost target refers
to the estimated projected costs absent any ACO intervention.
Under this view, the projected costs for the entire five-year period
are calculated by applying the market trends to the actual PPPM
cost from two years prior to Year 1 of the agreement. This results
in a larger measurement of total savings, $17.74 PPPM, than the
total savings as defined in the agreement, $10.37. As a result,
even though the ACO receives the same $3.73 PPPM in shared
savings, this amount now represents just 21% of this alternative
definition of total savings. This illustrates the adverse impact on the
ACO of rebasing the agreement’s cost targets, if the ACO is able
to demonstrate sustainable reductions in cost trends.
Tactics to mitigate the impact of random variation are important
Typically, utilisation of medical services will fluctuate from year to
year for temporary reasons. These include short-term economic
changes, flu season intensity, environmental changes, natural
disasters, short-term change in birth rates, changes in medical
practice, and patient behaviour. Therefore, mitigating the impact of
random variation is an important consideration when developing
a shared risk model. However, health systems should recognize
that it will still exist, especially within programmes with smaller
attributed populations. For this reason, some programmes require
a minimum attributed population. The minimum size will vary from
one programme to another, depending on factors such as current
utilisation levels and the use of other contract terms designed to
minimize the destabilising impact of random variation.
Agreements in other countries often include specific stop-loss
to remove variation caused by high-cost claimants. Questions
to consider are: At what level should the stop-loss be set? Are
medical costs truncated at the stop-loss level or is the patient
removed completely? How much cost—and what type of cost—is
likely to be removed? Will it remove cost the provider believes
it can manage better? Answers to these questions will differ
from one health system to another and from one deal to another.
Actuarial analysis can provide valuable insight to health systems in terms of the magnitude of the likely random variation. For many
NHS contracts, national commissioning of specialist services will
remove some of this risk, but potentially not all.
Some US agreements also carve out other high-cost cases such
as transplants and major burns. A few health systems have even
considered carving out the risk of increases in the birth rate of the
attributed population by excluding newborns and delivery costs
from their agreements.
Random variation for small populations can also be mitigated by
basing the target off more than one year of past history. From the
prime provider’s perspective this removes the risk of the single
year used to set the target being one with utilisation levels that are
lower than typical. The base point for projection can be critical in
achieving the necessary cost savings.
To limit the maximum downside, some providers have also
considered purchasing stop-loss reinsurance to cover overall
programme risk or incorporating maximum loss provisions in their
agreements with payers.
Selection of the trend assumption is critical
The selection of the trend assumption to project the target PPPM
from the base period cost is clearly a fundamental and important
consideration. A key question is whether it makes sense to set
the target using a static trend. If so, what should that static
trend be based on? A second key question is whether the trend
should be market-based. A market-based trend that reflects
the local historical trend for the attributed members is often the
best indication for setting a target. The trend should include fee
schedule or tariff increases for the health system, and, as far as
possible, other local health systems too. Ideally, where applicable,
the trend should include adjustments for technology and case
mix, because these risks are often beyond the control of the prime
contractor. The payer will be looking for the system to achieve a
net utilisation trend lower than the cost curve for the market, but
should not be trying to shift risk for new technologies and drugs to
the prime provider wholesale.
The appropriate target trend will vary from one market to another
and from one agreement to another. This is an area where actuarial
scenario testing of potential outcomes is particularly valuable.
Development of the population count methodology needs careful consideration
Counting the attributed population for a capitation contract is not
straightforward in the NHS. CCGs do not have an accurate count
of the total population for which they are responsible, let alone
an accurate count of sub-populations. Existing prime contractor
arrangements rely on Exeter registration count data or census
projections, where the units may or may not be coterminous with
CCG geographical boundaries.
If contracts involve specific sub-populations which are diseasespecific,
things become even more complex. The number of
over-65s is relatively simple to estimate, but who can define what
the ‘frail and elderly’ or the ‘seniors with diabetes’ population count
is? To find a population with chronic diseases relies on mining
primary care and prescription drug data, which is not typically
available to CCGs at an individual patient level. Some methods
of finding disease-specific cohorts can introduce statistical
anomalies, such as regression to the mean, which can dramatically
affect the savings calculation.
Many other components influence perceived fairness and financial outcome
A health system should carefully consider many other components
of a shared risk model. The most common additional elements are
discussed below, with key questions the prime provider needs to
- Upside/downside risk and upside/downside shares: Does it
make sense, and is the prime provider willing, to take downside
risk from Year 1? Are the upside and downside shares equal?
Other components of the contracting model will often influence
the answers to these questions.
- Quality initiatives: Does this act as a threshold that needs to
be met before any savings can be shared? Are the benchmark
measures realistic, relevant to the attributed population,
measurable, and credible? How dependent are the results
to a few individual measurements? Do both the upside and
downside risks get adjusted? Are the adjustments tiered (defined
adjustments for meeting stepped thresholds) or continuous?
- Maximum loss: What is the likely maximum loss each year and
in total over the duration of the agreement? Does the agreement
have any caps on losses, or a provision to renegotiate the terms
if experience is less favourable or subject to more variation than
- Risk scores: What risk model is used to adjust both base period
and performance year costs? When are risk scores calculated
(i.e., what run-out period is used for services which have been
rendered, but which are not yet in payer reporting)? How is
normalisation—the adjustment for “coding creep”—applied? What
adjustments are made for any recalibration of the model between
the base period and the measurement period?
- Choice of contract period: How does this impact the attributed
population throughout the measurement year?
- Run-out period: When is the final settlement calculated? How
much run-out is included for services which have been provided,
but not yet accounted for in the financials? Is it a hard cut-off,
or is an allowance made for estimated incurred but not paid
services as of the date of settlement? Who prepares the final
financial reconciliation and who reviews it? Consistency with the
approach used to develop the target is important.
- Unforeseen events: Does the agreement include provisions
to adjust the target (or any other model components) following
unforeseen events, such as major changes in the population mix
or size during the contract year?
- Infrastructure costs: Who pays for the cost of the health
system organisational realignment that will likely be needed to
implement a new model of care management? Many agreements
include a contribution from the payer, sometimes called a
‘care coordination fee.’ In this scenario, the agreement should
specify how that fee is included (if at all) in the shared savings
Appropriate interpretation of timely and accurate interim reports is a necessity
Reports received by the prime provider during the contract period
typically seek to answer three fundamental questions:
1. Who are we managing? To be able to successfully manage
the population, the prime provider needs to know on a
timely basis who is in (or likely to be in) the attribution. Many
providers have little business intelligence useful for population
2. How are we performing? The prime provider needs to
understand how it is performing against the terms of the
contract. How much should the system accrue/provision for the
potential likely surplus/deficit in its financial statements?
3. Where are the opportunities? The system will need to
understand where the greatest opportunities for savings lie, in
terms of type of service (e.g., inpatient, outpatient, professional,
drugs, etc.), specialty, and leakage.
A balance will often need to be made between timeliness of
information and the credibility—or usefulness—of that data. For
example, information using one-month run-out periods will provide
more ‘instantaneous’ metrics, but will typically involve greater
uncertainty, which is due to a greater component of incurred but
not reported or paid services estimates. Longer run-out periods
have greater certainty but may be provided too late to be useful for
decision making, e.g., a Q1 report will likely not be available until
partway into Q3.
Care is also needed when interpreting reports. For example, an
increase in primary or community care and/or pharmaceutical
spending might initially be thought of as cause for concern.
However, it may result in fewer inpatient admissions and surgical
procedures. Understanding any comparative benchmarks is also
important. At a minimum the benchmarks should be appropriately
risk-adjusted, reflect differences in contract payment levels, and
possibly also be adjusted for a number of other components of the
shared risk agreement (e.g., attribution method, any service carve
outs, stop-loss, etc.).
A carefully considered model for slicing up the pie can engage doctors and incentivize success
One aspect often initially overlooked during the development of
a shared risk programme is how the prime provider will divide up
a surplus or provision for a deficit among the different provider
and other groups that make up the integrated care system. Many
attributes define a successful distribution model, but the most
important is to engage and incentivise everyone to row in the same
direction. Perceived fairness is key to providers’ engagement and
the greater likelihood of achieving savings.
Surplus may be allocated to various individuals or groups in a
number of different ways, and some may also be withheld to fund
items such as infrastructure costs or future deficits (as shown in
Figure 3). The slices marked with an asterisk may be ‘sometimes
slices,’ i.e., they may not always receive a share of any surplus.
How big should each slice be? A traditional ‘actuarial’ approach
allocates larger shares to providers that see the largest fall in
PPPM costs, as it will generally be reflective of lost fee-for-service
revenues from improved cost management, i.e., larger shares will
be allocated to hospitals and surgical specialists. However, an
‘impact’ approach allocates larger shares to providers that have
the greatest potential to improve care efficiency. This approach
matches incentive with opportunity and typically allocates larger
shares to primary care doctors and medical specialists. The
optimal solution will vary from one health system to another, and
include a number of other considerations that may be unique to
each health system.
Thoughtful evaluation and appropriate financial
modelling will yield well-informed decisions
Although it is clearly advantageous to develop agreements that
are simple to implement and administer, shared risk programmes
are complex, with many intertwined components, and significant
practical implementation issues to consider. No two deals will be
the same, so it is likely that one deal struck with one CCG will
be very different from one struck with another CCG. Thoughtful
evaluation and careful consideration is recommended, enabling
prime providers and the CCG to make well-informed decisions.
These programmes are still evolving and will continue to do so
over the next few years as more shared risk programmes are
implemented and results begin to flow through. Prime providers
and CCGs should be fully prepared for the prevalence of
unintended consequences, certainly during the first year or two
of the contract period. Experience from other countries indicates
that a good collaborative relationship between payer and prime
provider is certainly very helpful, if not essential.