BACKGROUND: There is increasing interest in the study and improvement of health system resource allocation. The Adjusted Clinical Groups (ACG) System measures the morbidity burden of patient populations based on disease patterns, age and gender. This system can be used in primary health care settings. AIM: To report the use of the ACG system as a risk based patient classification system and its potential as a resource allocation mechanism in primary health care. MATERIAL AND METHODS: Patient diagnoses from a sample of primary care establishments were processed using the Johns Hopkins ACG System. Linear regressions were used to measure the ACG System's ability to explain resource use and ambulatory visit rates. RESULTS: The ACG System had a statistically significant capacity to explain primary health care costs with an adjusted R² of 0.26. These results are significantly better, compared with risk assessment models based on patients' age and sex, whose adjusted R² is 0.05. CONCLUSIONS: The use of risk adjustment mechanisms will contribute to improve health care resource allocation as well to know the disease profile of the population.
BACKGROUND: There is increasing interest in the study and improvement of health system resource allocation. The Adjusted Clinical Groups (ACG) System measures the morbidity burden of patient populations based on disease patterns, age and gender. This system can be used in primary health care settings. AIM: To report the use of the ACG system as a risk based patient classification system and its potential as a resource allocation mechanism in primary health care. MATERIAL AND METHODS:Patient diagnoses from a sample of primary care establishments were processed using the Johns Hopkins ACG System. Linear regressions were used to measure the ACG System's ability to explain resource use and ambulatory visit rates. RESULTS: The ACG System had a statistically significant capacity to explain primary health care costs with an adjusted R² of 0.26. These results are significantly better, compared with risk assessment models based on patients' age and sex, whose adjusted R² is 0.05. CONCLUSIONS: The use of risk adjustment mechanisms will contribute to improve health care resource allocation as well to know the disease profile of the population.
Authors: Paula Zamorano; Paulina Muñoz; Manuel Espinoza; Alvaro Tellez; Teresita Varela; Francisco Suarez; Maria Jose Fernandez Journal: PLoS One Date: 2022-01-14 Impact factor: 3.240