Use of a diagnosis-based risk adjustment model to estimate costs of indigent care in a community at Medicaid reimbursement rates

Objectives: This study used a diagnosis-based risk adjustment model to estimate the annual costs of uninsured patients in Austin, Texas, and describe the prevalence and costs of their chronic conditions. The data were supplied by the Indigent Care Collaboration, a partnership of local safety-net hospitals and clinics.

Methods: This study used the Diagnostic Cost Groups prospective Medicaid All-Encounters model, which uses diagnoses, age and gender to assign relative risk scores to patients. The relative risk scores were multiplied by the per capita Texas Medicaid expenditure to obtain estimated annual costs. Chronic diseases were described in terms of prevalence and total estimated annual cost.

Results: A total of 471,194 encounters were recorded for 163,729 patients meeting the study inclusion criteria between the 1st March 2004 and the 28th February 2005. The mean estimated patient yearly cost was US $1,307, and the total estimated yearly population cost was $228,909,529. The most common chronic conditions included hypertension, diabetes, depression, substance abuse, pregnancy, asthma, chronic obstructive pulmonary disease and congestive heart failure.

Conclusions: This study demonstrates how the unknown costs associated with caring for indigent uninsured patients in a community can be estimated at Medicaid reimbursement rates using the Diagnostic Cost Group model on aggregated patient encounter data.