What does ACG stand for in healthcare?

September 22, 2025 •

4 min read

According to Johns Hopkins, the ACG System is the leading population health analytics software worldwide, impacting over 250 million lives. In healthcare, ACG stands for Adjusted Clinical Group, a sophisticated system used to measure the overall illness burden of a patient population.

Quick Summary

ACG stands for Adjusted Clinical Group, a system developed at Johns Hopkins University to classify individuals based on age, gender, and disease patterns to predict future healthcare resource use.

Key Points

Definition: ACG stands for Adjusted Clinical Group, a Johns Hopkins system for classifying patient populations based on morbidity.
Methodology: It groups thousands of diagnostic codes into 32 Aggregated Diagnosis Groups (ADGs) and combines these with age and gender to assign a patient to a single ACG.
Predictive Power: ACGs are used to predict a population's future healthcare resource use more accurately than traditional methods by focusing on overall illness burden.
Primary Applications: Key uses include risk adjustment for payment models, targeting patients for care management, fair resource allocation, and evaluating provider performance.
Holistic Approach: Unlike many systems that focus on single conditions, the ACG provides a person-centric, multi-morbidity perspective.
Widespread Use: The system is widely used globally by health plans, governments, and health systems to manage and improve care for large populations.

Understanding the Adjusted Clinical Groups (ACG) System

The Adjusted Clinical Groups (ACG) System is a risk-adjustment methodology developed by researchers at Johns Hopkins University. It operates on the core principle that a person's total health needs, defined by their collection of morbidities, are a better predictor of future healthcare resource utilization than specific diseases alone. Unlike traditional systems that focus on single episodes or conditions, the ACG system provides a holistic view of the patient's health over time. By analyzing a person's complete history of diagnoses, age, and gender, it classifies them into a single, mutually exclusive ACG category. This provides a powerful, person-focused method for understanding population health.

The Mechanics of the ACG System

To understand how the ACG system works, it is helpful to explore its foundational building blocks. The process begins with administrative data, such as medical and pharmacy claims or electronic health records (EHRs), which contain detailed diagnostic and procedural codes.

Aggregated Diagnosis Groups (ADGs): The first step involves classifying the thousands of possible diagnostic codes (e.g., ICD-10) into one of 32 broader Aggregated Diagnosis Groups (ADGs). Each ADG represents clinically cohesive conditions with similar severity and resource implications. For example, all diagnosis codes related to asthma or a specific type of chronic heart failure would be grouped into a single ADG.
Collapsing ADGs into ACGs: Once all a patient's diagnostic codes have been mapped to ADGs, the system analyzes the pattern and number of these ADGs. This multimorbidity profile, along with the patient's age and gender, is used to place them into a single, comprehensive Adjusted Clinical Group (ACG). These final ACG categories represent a patient's overall burden of illness. The system also uses Resource Utilization Bands (RUBs), a higher-level classification, to group patients by their anticipated healthcare needs.
Predictive Modeling: The ACG assignment provides a robust measure of an individual's predicted consumption of medical care resources. This information can be used to forecast health service utilization for different population groups, identify at-risk individuals, and inform strategic planning.

Core Applications in Healthcare

The applications of the ACG system are far-reaching and provide substantial benefits for healthcare payers, providers, and public health agencies alike.

Risk Adjustment and Capitation: Health plans and governmental agencies use ACGs to set equitable capitation rates and adjust insurance premiums. By accounting for the differing illness burdens of patient populations, the ACG system ensures that providers who serve sicker patients receive appropriate funding.
Care Management: The system is an invaluable tool for proactively identifying high-risk patients who would benefit from targeted case management or disease management programs. It can flag individuals with complex needs before they become high utilizers of hospital services.
Resource Allocation: Healthcare systems use ACG data to appropriately distribute resources, anticipate staffing needs, and budget more effectively. By understanding the health profile of different subpopulations, organizations can allocate resources to where they are most needed.
Performance Analysis: The ACG system enables fair comparison of provider performance by adjusting for variations in patient health. This helps administrators evaluate the efficiency and quality of care while accounting for differences in case-mix.
Research and Public Health: Researchers worldwide use ACG data to analyze population health trends, measure comorbidity levels, and understand healthcare utilization patterns. It is a powerful tool for studying health disparities and evaluating the effectiveness of health interventions.

The ACG System vs. Traditional Risk Adjustment

To highlight the unique value of the ACG methodology, it is useful to compare it with more traditional risk adjustment methods. Many older models focused on single disease states or demographics. The table below illustrates the key differences.


Feature	Traditional Risk Adjustment	Johns Hopkins ACG System
Primary Focus	Specific diseases or demographic characteristics.	Multi-morbidity and overall illness burden over time.
Data Input	Often limited to a narrow set of claims or episodes.	Comprehensive, utilizing all diagnostic and pharmacy data over a period.
Patient View	Event-focused, capturing individual episodes of care.	Person-focused, classifying the whole patient based on their cumulative health status.
Predictive Power	May underpredict costs for patients with multiple, less-severe conditions.	Better at predicting future resource use for a diverse range of patient populations.
Equity Evaluation	Can lead to misleading conclusions if not adjusted for patient health status differences.	More robust for assessing equity and health disparities because it accounts for case-mix.

Limitations and Considerations

While the ACG system is a powerful tool, it's not without limitations. It is designed for analyzing groups of patients, not for making clinical decisions for a single individual. Input data quality is crucial; if administrative claims are incomplete or inaccurate, the ACG assignment may be affected. Special considerations are also required for certain patient groups, such as newborns or pregnant women, whose resource use patterns differ significantly from other populations. Despite these considerations, ongoing research and development at Johns Hopkins ensures the system continues to evolve, integrating new data sources like socioeconomic factors to provide even more robust insights.

Conclusion

In summary, the next time you encounter the acronym ACG in a healthcare context, you will know it refers to the Adjusted Clinical Group system. It is a cornerstone of modern population health analytics, providing a comprehensive and clinically coherent way to understand the health status and resource needs of patient populations. The ACG system helps healthcare organizations move from reactive care to proactive, data-driven management, ultimately leading to more equitable resource allocation and improved patient outcomes worldwide. You can learn more about its impact and applications through trusted resources like the Johns Hopkins ACG System website.(https://www.hopkinsacg.org/)

Frequently Asked Questions

The ACG system uses patient administrative data, such as medical and pharmacy claims and electronic health records, to process diagnostic and pharmaceutical codes. It also incorporates patient age and gender to provide a comprehensive health profile.

The system helps allocate resources equitably by providing a risk-adjusted view of a population's health needs. It allows health systems and governments to distribute funding and services based on the actual illness burden of a population, ensuring that sicker groups receive appropriate attention.

No, while widely used for financial purposes like risk adjustment and budgeting, the ACG system also has crucial clinical applications. It helps identify high-risk patients for targeted care management, allows for performance analysis of providers, and informs public health strategies.

The ACG system can identify patients with complex needs or those at high risk for future hospitalization before they become high utilizers. This allows care managers to intervene proactively with preventative or educational services, improving health outcomes and potentially lowering costs.

An ADG (Aggregated Diagnosis Group) is a foundational component of the ACG system, grouping similar diagnostic codes together. A patient may have multiple ADGs. An ACG (Adjusted Clinical Group) is the final, mutually exclusive category assigned to a patient, representing their overall burden of illness.

The Adjusted Clinical Groups (ACG) system was developed by researchers at the Johns Hopkins University, specifically Barbara Starfield and Jonathan Weiner, in the early 1990s.

Yes, the ACG system has been validated and implemented globally. It is used in over 20 countries, including Canada, England, Spain, and Australia, to help manage and finance healthcare for millions of people.