Purpose: We define personalized concurrent risk (PCR) as the subject-specific probability of an index outcome within a defined interval of time, while currently at risk for a separate outcome, where the outcomes are not mutually exclusive and can be jointly modeled with a shared random-intercept. We further define typical concurrent risk (TCR) as the risk obtained by setting the random intercept to null. Methods: Drawing data from the Medical Expenditure Panel Survey (cohorts 2008 – 2013), we jointly model limitations in social activity and mobility over two years among older community-dwelling persons with both hypertension and chronic obstructive pulmonary disease. The joint model employs inverse probability of treatment weighting based on each participant’s baseline propensity of polypharmacy (≥ 5 classes of medication). Results: Even among participants with the same covariates, older persons with multiple chronic conditions exhibit wide-ranging heterogeneity of the treatment effect from polypharmacy, a risk factor for negative health outcomes among older persons. The magnitude of the PCRs are dominated by the value of the subject-specific random effect. Conclusions: Estimates of PCR and TCR can be calculated from national or institutional datasets and may facilitate the practice of personalized care for older patients with multiple chronic conditions.