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Johns Hopkins Ambulatory Care Groups (ACGs). A case-mix system for UR, QA and capitation adjustment
J P Weiner1, B H Starfield, R N Lieberman
1Johns Hopkins University, Baltimore, MD 21205.
Insights
Ambulatory Care Groups (ACGs) categorize patients by illness burden, improving prediction of healthcare resource use. This system aids in analyzing, financing, and managing ambulatory care effectively.
Area of Science:
- Health Services Research
- Medical Informatics
- Public Health
Background:
- Existing methods for describing patient populations and predicting healthcare resource needs are limited.
- There is a need for a standardized system to assess illness burden in ambulatory care settings.
Purpose of the Study:
- To introduce and describe the Ambulatory Care Groups (ACGs) system.
- To evaluate the predictive power of ACGs for ambulatory care resource utilization.
- To explore the applications of ACGs in healthcare management and financing.
Main Methods:
- Development of a case-mix system categorizing individuals into 51 Ambulatory Care Groups (ACGs).
- Utilized ICD-9-CM diagnosis codes and demographic data for ACG assignment via a computerized grouper.
- Tested the system across four Health Maintenance Organizations (HMOs) and a state Medicaid program.
Main Results:
- Ambulatory Care Groups (ACGs) provide a robust measure of population illness burden.
- ACGs are up to ten times more predictive of ambulatory care resource use than age and sex alone.
- The system demonstrated feasibility and potential utility in diverse healthcare settings.
Conclusions:
- Ambulatory Care Groups (ACGs) offer a valuable tool for understanding and managing ambulatory care.
- Potential applications include utilization review, quality assurance, and capitation payment adjustments.
- The ACG system facilitates more accurate analysis and financing of ambulatory healthcare services.
Abstract:
This paper describes a new ambulatory case-mix system developed at The Johns Hopkins University and known as Ambulatory Care Groups (ACGs). ACGs categorize a person into one of 51 categories based on the diseases and conditions for which they received treatment over a period of time, such as a year. ACGs can be used to describe the "illness-burden" of a population and are up to ten times more predictive of ambulatory care resource use than age and sex alone. ACGs can be determined using a computerized "grouper" software package based on ICD-9-CM diagnosis codes and demographic information presently found in virtually all claims or encounter data systems. They were developed and tested at four HMOs and a state's Medicaid program. This paper discusses the potential application of ACGs to analysis, financing, and management of ambulatory care, specifically as it relates to utilization review (UR), quality assurance (QA) and the adjustment of capitation payment within managed care settings.