Case Study: How One Integrated Care System in England Used the ACG System to Address Health Inequities, Measure Need at a Patient Level and Develop a Better Funding Model

February 2nd, 2023
Population Health Management & Improvement  |  
Social Determinants of Health
Case Study: How One Integrated Care System in England Used the ACG System to Address Health Inequities, Measure Need at a Patient Level and Develop a Better Funding Model

As part of the National Health Service (NHS), primary care in England has long relied on a formula to determine funding for services. The Carr-Hill formula1 was developed in 2004 and has remained unchanged since then.

Back in 2004, it was known that the formula had certain limitations. It did not account for differing patient needs within individual clinics, such as lower income patients and those with language barriers.

Today, we are highlighting how one Integrated Care System (ICS) – Leicester, Leicestershire and Rutland (LLR) – used the ACG System to successfully address health inequities, measure need at a patient level and develop a more effective funding model. Why use the ACG System? It includes all of the metrics needed to properly assess patient need and determine more accurate funding.

Developing the Model

LLR used the ACG System to analyze existing data from electronic medical records and assist with activities such as population profiling, high-risk case identification and casemix-adjusted outcomes assessment. Each of these activities was key to the creation of the new funding model.

Unlike traditional payment models which rely solely on age, gender or a health-based weighting factor (such as the Center for Medicaid Services HCCs), LLR’s new model incorporated adjustments for deprivation, patient turnover and language needs. This resulted in more equitable payments to primary care practices, based on the underlying health and social needs of their population.

LLR also discovered that smaller practices and those in lower income areas had more coding errors and more trouble obtaining long-term history from high-turnover patients. LLR’s leadership understood that any funding formula based on diagnoses could result in less funding for high-deprivation areas – worsening the problem they were trying to solve.

In response, LLR identified a set of codes and diagnoses that were highly likely to be coded correctly across practice types and, therefore, give a clearer view of population health. LLR modeled this variation and inserted formula adjustments to compensate for it. This ensured that practices with poor coding were not further penalized by receiving less money intended to improve health equity.

A New and Better Formula

Throughout the project, LLR leadership gave equal weight to the analytics, physician viewpoint and patient needs. The result was a new funding formula that was more in line with patient need, transparent and trusted throughout the region. The new formula is a model for improving casemix adjustment in clinics across the globe, as we strive to improve health equity and allocate resources fairly to high-need and unhealthy population subgroups.

Sarah Kachur, PharmD, MBA, BCACP, and Executive Director of Population Health Analytics at the ACG System said:

“What strikes me most about Leicestershire’s success was their leadership, transparency and relentless focus on equity for patients and practices. The leadership accepted existing practice variations and kept the focus on fair resource allocation improving health equity. This approach garnered physician trust and is what elevates this work from a routine statistical exercise to an embraced tool to drive change.”

To learn how the LLR team used the ACG System to create their new and more equitable funding model, download the case study or contact us at acginfo@jh.edu.


[1] The Carr-Hill formula is applied to calculate the Global Sum payments for essential and some additional services. Global Sum payments are based on an estimate of a practice’s patient workload and certain unavoidable costs (e.g., the additional costs of serving a rural or remote area or the effect of geography on staff markets and pay), not on the actual recorded delivery of services.





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