Purpose - This research describes the development and independent validation of a prospective mortality risk adjustment index for ambulatory Medicaid recipients based on automated pharmacy data.
Methods - A retrospective review of Georgia and North Carolina claims Medicaid data from 1990 to 1997 was used to identify ambulatory recipients (ages 15 to 50 years). Cox proportional hazards regression was used to model seven-year survival based on drug exposure in the year prior to an index date. Risk factors, identified on statistical empirical evidence in the GA sample, were subsequently submitted to a clinical panel for validation. The clinically validated GA model was then re-estimated, ‘frozen’, and prospectively validated on the external NC Medicaid cohort.
Results - We identified cohorts of 273,970 GA and 120,000 NC Medicaid recipients. Survival was 99%, 98%, and 97% at 1, 3, and 7 years. In the GA cohort, c-statistic for the survival model was 0.85. Female gender, blind-disabled eligibility, prior exposure to opiates, cardiac, respiratory, or antiretroviral drugs, were associated with the largest increases in odds of death. Recipients with a prior exposure to antidepressants or neuroleptics had greater likelihood of survival. The GA model c-statistic was 0.87 when prospectively tested on the NC sample.
Conclusion - This model, based on drug exposure data alone, provides a valid, risk adjusted prediction of survival of an ambulatory Medicaid population. Our model can be used by Medicaid programs managers and health service researchers to control for comorbidities based on available drug exposure data for ambulatory Medicaid patients.
Learning Objectives: At the conclusion of the session, the participant will be able to assess the role of drug exposure information as a marker of risk/protective factors in predicting long-term survival of ambulatory Medicaid populations.
Keywords: Risk Factors, Medicaid
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.