The Montefiore Health System in New York is a pioneering accountable care organisation which has been able to improve the quality of patient care while reducing expenditure through enhanced care coordination. In this report The King’s Fund focuses on Montefiore’s improvement journey and the key components of the model that could provide lessons for the NHS.
Listen to Stephen Rosenthal, Chief Operating Officer at Montefiore Health System and Herb Fillmore, Senior Director, Market Development, Populations and Payment Solutions at 3M, discuss how to run a successful accountable care organisation.
3M Health Information Systems is delighted to present a webinar with Sheryl Terlouw, a key innovator in the US healthcare transformation journey. Hear first-hand how Wellmark® Blue Cross® and Blue Shield® of Iowa worked with their providers to launch a groundbreaking accountable care model in 2012 to reduce and sustain the percentage increase in annual healthcare costs.“It’s not about withholding care to reduce costs, it’s about better health outcomes, which, in turn, help control costs.” Sheryl Terlouw.
Spain has a similar health system to the NHS but its regions have a high level of responsibility for running their own services. Find out more about some interesting parallels between Catalan and British health policy and lessons for the NHS to take from the Catalan health model.
The 3M Clinical Risk Groups (CRGs) are a population classification system that uses inpatient and ambulatory diagnosis and procedure codes, pharmaceutical data and functional health status to assign each individual to a single, severity-adjusted group.
3M CRGs are patient-centric, focusing on the total burden of illness rather than one disease or service, and use a categorical approach to patient classification that provides clinicians with actionable data. 3M’s approach contrasts sharply with statistical models that yield regression-based risk scores that have little clinical meaning.
3M CRGs were developed for use in all populations, including pediatrics. Particular attention was paid to the most complex and expensive patients across the full spectrum of age and insurance status. Among other uses, 3M CRGs are commonly used in measuring the illness burden of medically complex children.
3M CRGs are available in both prospective and retrospective models, useful for understanding both past utilization and predicting future utilization. 3M provides multiple levels of 3M CRG aggregation to fit the required level of detail. And, unlike regression-based models, the 3M CRG categorical approach allows the clinical model to remain stable while relative weights vary depending on the population, covered benefits and payer policies.
3M CRGs are closely integrated with the Potentially Preventable Admission (PPA), Potentially Preventable Emergency Department Visit (PPV) and Potentially Preventable Service (PPS) methodologies. PPAs, PPVs, and PPSs are increasingly popular ways to measure and manage potentially preventable events to improve population health.
All about 3M CRGs
3M CRGs can provide a comparative and detailed population-based understanding of disease severity, which can help you design care coordination strategies and best practices to control costs, maintain quality and improve outcomes.
Here are a few examples of how the 3M CRG methodology can bring value to customers.
3M CRG grouping logic is the same for every user, although different organizations may use different versions (the most recent version is recommended). Each user makes own decisions about appropriate use, including population profiling, risk adjustment and capitation rate formulas and amounts. At this time, 3M does not offer software that emulates 3M CRG assignment and pricing used by specific payers.
3M CRGs are integrated with the other 3M patient classification methodologies.
The 3M CRG Software is also at work in several 3M products, including:
Licensees of the 3M CRG methodology can access the following documents on the 3M customer support website.
The development of the 3M Clinical Risk Groups was greatly influenced by the success of Medicare payment for inpatient hospital care using the Diagnosis Related Groups (DRGs), first implemented in 1983. While the DRG unit of analysis is an inpatient hospital stay, the 3M CRG unit of analysis is an individual within an identified population. Like DRGs, the 3M CRG methodology comprises a comprehensive set of mutually exclusive and clinically coherent groups. A fundamental distinction between the two methodologies is that DRGs classify a single encounter at a point in time while 3M CRGs classify the individual and all of his or her healthcare services within an extended period of time.
A second distinction is that DRGs are assigned after the services are provided, that is, retrospectively. On the other hand, 3M CRGs can be used either prospectively or retrospectively. Prospectively, the 3M CRG assignment is used to predict healthcare utilization costs for a period that has yet to occur. Retrospectively, the 3M CRGs are used to risk adjust for healthcare utilization and costs for the period that has just finished. 3M CRGs provide healthcare planners, managers and clinicians a meaningful basis for evaluating both the processes of care, the outcomes and the associated financial impacts.
As a categorical clinical model, 3M CRGs differ from most other population risk-adjustment methodologies, which are statistical methods developed with regression analysis. Regression models produce a numeric score for each individual, but this score has minimal communication and management value. Regression models can do a good job explaining the past, but they do a poor job giving clinicians and managers actionable information needed to improve the future.
3M first released 3M CRGs in 2000. The methodology was published in the prestigious journal Medical Care in 2004. In 2006, the U.S. government awarded 3M a patent for 3M CRGs. In 2008, New York state adopted 3M CRGs for use in calculating capitation payment rates to Medicaid managed care organizations (MCOs). 3M CRG v2.0 was released in 2016, and CRG v2.1 in 2018. In v2.1, there are 392 base CRG groups and approximately 1,470 total risk groups including severity levels (the count differs slightly depending on the prospective or retrospective models). For example, 3M CRG 70602 is used for a person with congestive heart failure, diabetes and chronic obstructive pulmonary disease. The first digit indicates that this person is in Health Status Group 7, Dominant Chronic Disease in Three or More Organ Systems. There are nine Health Status Groups, ranging from group 1 (healthy/nonuser) to group 9 for catastrophic conditions such as renal dialysis and major organ transplants. The next three digits (060) indicate that this patient has the combination of heart failure, diabetes and COPD, and may have other conditions as well. The final digit (2) indicates that of all the people in base 3M CRG 7060, this individual is severity 2. For most chronic base 3M CRGs, there are four or six severity levels.
For each 3M CRG, a relative weight indicates the typical healthcare costs for this 3M CRG relative to the average individual in the population (given the benefits covered, utilization levels and payer policies). For example, 3M calculated a 3M CRG 70602 relative weight of 8.1364, indicating that individuals in this 3M CRG are about eight times more expensive than average. We should note that 3M CRG licensees are responsible for choosing or calculating 3M CRG relative weights are appropriate for their population and purpose. (3M consultants are available to assist licensees with 3M CRG analysis.)
With as many as 1,470 individual 3M CRGs compared with as few as nine Health Status Groups, 3M CRGs are a very flexible tool. To enable analysts and other licensees to fit the 3M CRG methodology to their specific needs, 3M provides three levels of aggregated 3M CRGs (ACRGs). Each level provides fewer categories while maintaining key clinical detail and severity information.
The 3M CRG clinical logic is maintained by a team of 3M clinicians, data analysts, nosologists, programmers and economists. The logic is proprietary to 3M but is available for licensees to view in an online definitions manual. The methodology is updated annually to reflect changes in the standard diagnosis and procedure code sets as well as 3M enhancements to the 3M CRG clinical logic.
Learn more about 3M CRGs
Please note that documents not published by 3M do not necessarily reflect 3M recommendations and have not been approved by 3M. These documents are listed here for the information of readers interested in the various ways that 3M patient classification methodologies have been applied. Also note that listing these references does not imply endorsement of 3M methodologies by individual authors, other organizations or government agencies.
The 3M CRG methodology is a categorical clinical model that uses standard claims data (i.e., inpatient, ambulatory and pharmaceutical) to assign each patient to a single, mutually exclusive risk category.
First released in 2000 as clinically-based classifications for measuring a patient’s burden of illness, 3M Clinical Risk Groups (CRGs) have steadily evolved into a widely-used risk-adjustment tool applied to many of today’s most complex, real-world challenges in health care.
While today’s marketplace offers numerous risk-adjustment solutions, an independent evaluation concluded that the 3M™ Clinical Risk Groups (CRGs) performed more favorably than other major risk-adjustment methodologies in three areas: Clinical relevance, resource prediction and convenient resource weighing.
3M CRGs create a bridge between the clinical and financial aspects of health care. However much the financial side of health care may change, 3M CRGs remain a stable and consistent clinical model.
3M CRGs have the potential to provide risk adjustment for capitated payment systems and management systems that support care pathways and case management.
The objective of the study was to stratify children using available software, Clinical Risk Groups (CRGs), in a tertiary children’s hospital, Seattle Children’s Hospital (SCH), and a state's Medicaid claims data, Washington State (WSM), into three condition groups: complex chronic disease, noncomplex chronic disease and nonchronic disease..
The addition of functional health status within existing risk-adjustment models has the potential to improve equitable resource allocation in the financing of care costs for more complex enrollees, if handled appropriately.
Risk adjustment of managed care organization (MCO) payments is essential to avoid creating financial incentives for MCOs adopting enrollee selection strategies. However, all risk-adjustment methods have an inherent structural flaw that rewards preventable deterioration in enrollee health status and improved coding of disease burden.
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