Case Studies

Care Management Program Case Study-Payer

Clalit Health (an integrated delivery system in Israel) used the ACG System to identify high-risk patients for enrollment in a comprehensive complex care management program for its multimorbid population. This led to a reduction in length of time spent in the hospital, reductions in readmission rates and lower costs.

Provider Profiling and Engagement Case Study – Payer

Johns Hopkins HealthCare (JHHC), the managed care arm of Johns Hopkins, created Provider Profile reports leveraging outputs from the Johns Hopkins ACG System to build a comprehensive Provider Engagement program.

Case Mix Adjustment Case Study – Payer

This Case Study shows how Leicester City CCG, one of the most ethnically diverse areas of the UK, analyzed emergency admission rates for all practices, to learn that practices with lower emergency admission rates had significantly higher coding completeness and GP patient survey scores. Learn more.

Data Visualization and Patient Identification – Military

The Defense Health Agency (DHA) supports the delivery of integrated, affordable, and high-quality health services to Military Health System (MHS) beneficiaries and is responsible for […]

Population Health Management through Care Coordination and Interventions

Population health management at JHHC represents a comprehensive approach to health care considering the distribution of health outcomes within a population, and the health determinants […]

Resource Allocation Case Study-Government

Sweden became one of the first international adopters of the Johns Hopkins ACG System in the mid 1990s and has expanded its use to cover […]

Population Health and Resource Allocation Case Study Payer

Slough CCG used data output from the Johns Hopkins ACG System to gain a better understanding of their patient population, understand the factors that drive […]

Resource Allocation Case Study-Government

The Ministry of Health in Chile used the ACG® System as a risk-adjustment mechanism to improve health care resource allocation and better describe the disease […]

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