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What America Can Learn from the U.K.’s Experience with Risk Adjustment and Population Health

We’ve discussed on the Apixio blog how critical risk adjustment is to the functioning of a healthy insurance market in the U.S., but how is risk adjustment applied in the healthcare systems of other countries?

What makes this a fascinating question is that many other countries provide health insurance for a greater percentage of their population than the U.S. —which has  a hybrid public-private insurance system with pools based on factors such as age (Medicare), income level (Medicaid), or employment1.

The US system leaves some 10% of adult Americans under 65 uninsured, down from a high of 18.2% in 2010 largely due to the Affordable Care Act2. Conversely, across Western Europe for example, there are many interpretations and implementations of the universal health care model, where the government insures the entire population. One of the most commonly known to folks in the U.S. is the National Health Service or NHS 3in the United Kingdom, the oldest single-payer, universal healthcare system in the world; and the largest system of its depth, requiring no user fees for most healthcare services. Supplemental private healthcare does exist in the U.K., but is used by just about 10% the population and is paid for largely by private, often employer based health insurance.

Given that universal healthcare dominates the system, how does the U.K. government use risk adjustment to distribute funding appropriately across the population?

The U.K. health system considers risk differently.

The U.K. risk adjusts based on something called the “weighted capitation” model. Weighted capitation is implemented by geographic regions4, allowing for these heterogeneous pools to be allocated funding according to population size, with adjustments for health5 as measured by factors such as demographics, previous usage of healthcare services, local cost differences, and age-based mortality rate for those under 75.

Weighted capitation risk adjustment models take a prospective approach.

First, the weighted capitation model is prospective as opposed to retrospective. Essentially what the U.K. government is doing is front-loading their risk assessment taking into account demographic and health service utilization factors mentioned above. While in MA, risk scores and payment is adjusted after-the-fact based on data on actual healthcare services provided, the U.K. risk adjusts before covering organizations ever receive their money transfers. (You can read a great Guardian piece about how healthcare dollars flow through the NHS here.)

Second, risk adjustment data in the U.K. is collected and managed by NHS, while for MA, private payers submit diagnosis and treatment data to the government. That’s a lot of responsibility on the shoulders of payers and providers, and they flesh out their diagnosis data with that of traditional coding companies or technology firms such as Apixio. This introduction of payers in the MA system naturally adds a layer of complexity and administrative challenge. In the U.K. the collection of the data about the health of the population is entirely handled by the government,  from point of access, straight through to data analysis — because the physicians are an intrinsic part of the NHS system (this method has yielded the U.K. a uniquely strong national health data sets). The NHS Digital, the I.T. arm of the NHS,  compiles statistics and information on healthcare, which helps inform the weighted capitation models.

Third, while both the U.K. and MA risk models consider population size, local costs, age, and baseline levels of health, U.K. uses utilization levels to measure health levels. In MA, the HCC model is used to measure health levels via recorded treatment of  chronic conditions, a kind of risk assessment  that would trend towards a perception of higher risk. If this system were extrapolated to build metrics for overall population health, it would over represent those with HCCs, presenting a misleading snapshot of population health.

What issues do people have with the U.K.’s weighted capitation model?

The NHS has faced criticism over its use of prior utilization of health services to measure health status. After all, low use of health care doesn’t necessarily mean that a population is healthier, it could mean that a population has limited access to health care facilities or limited mobility. It could mean that they are homebound because of illness and, in fact, need healthcare more.

NHS has tried introducing a health inequality factor called “disability-free life expectancy”6 or DFLE to account for this. According to the UK Office of National Statistics (ONS)  DFLE, also often called ‘healthy life years expectancy’ estimates “lifetime free from a limiting persistent illness or disability”. This is based greatly upon a self-rated assessment of how health limits an individual’s ability to carry out day-to-day activities. However, these formulas remain controversial and there is regular disagreement about funding levels.

Lessons for the U.S. from healthcare data in the U.K.

With all this set to the backdrop of an NHS operating in increasingly austere times, it’s becoming increasingly evident, and I’m sure you guessed where we’re going with this one: Healthcare in the U.K. has a data problem.

In the U.K., it’s been about anecdote for far too long that healthcare funding is allocated by broad demographic umbrellas such as age and gender rather than truly comprehensive patient data.

“Over the past twenty years, the NHS has amassed increasing amounts of data. There is an almost universal consensus that, when used ethically and responsibly, with respect for the confidentiality of all patients (especially of vulnerable populations such as immigrants), better use of data could bring about more high quality, accessible and effective services”, says academic and policy expert Beth Simone Noveck.

It’s clear that both systems have their own unique challenges in improving health outcomes. The U.K. could do well to learn from the U.S. application of data mining to calculate risk scoring, and the U.S. could learn from the U.K.’s creation of a connected and straightforward data pipeline from the clinic to the capitol.

Technology’s role is clear.

Despite the differences in the US and U.K. systems, and the very different challenges they pose — it’s clear technology remains at the heart of the solution.  

From the U.K. example, we learn that even if the U.S. were to adopt universal healthcare — regardless of whether payments are handled through private insurance or publicly funded schemes, proper population health management will be inextricably linked to massive data sets. Data sets that have to be collected, digested, and translated into meaningful information which can be applied to advise on payments to the bodies tasked with administering healthcare regionally.

While the private insurance system in the US has many challenges, the private sector push for accurate and complete compensation has driven important advances in healthcare technology and patient data processing. It has created opportunities for improved patient care and healthcare delivery and more efficient and complete payment for more comprehensive care.

It’s going to be an exciting time for healthcare futurists, technologists and data scientists here, or across the pond.

Additional Resources


1. Smith, P. C., & Witter, S. N. Risk Pooling in Health Care Financing: The Implications for Health System Performance. Pg 5

2. The U.S. health care system has no universal coverage, only recently enacting legislation mandating healthcare coverage for almost everyone, and has a hybrid of public and private insurance— rather than a singular national health service, a single-payer national health insurance system, or a multi-payer universal health insurance fund.

3. Technically, the NHS is the publicly funded national health care system for England and is actually one of the four National Health Services of the U.K.. The other three are NHS Wales, NHS Scotland and Health and Social Care in Ireland (often also called the NHS). For simplicity in this blog’s purpose, we’ll refer to the collective national health program of the entire U.K. as the NHS. .

4. These regions have healthcare funding administered by clinically-led NHS statutory bodies called Clinical Commissioning Groups (CCGs)..

5. For further information on CCG funding, read: Equality Analysis: For 2016-17 to 2020-21 revenue allocations to Clinical Commissioning Groups and commissioning areas..

6. Weighting of this component within the overall additional need adjustment has varied in recent years from 10% to 15%. ..

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