Members newly diagnosed with AD demonstrated greater HCRU, health care costs, and comorbidity burden compared to matched non-AD controls.

HHMs of individuals diagnosed with AD demonstrated greater medical condition burden, healthcare resource use, and direct healthcare costs than non-AD HHMs. These findings demonstrate the significant clinical and financial impact of AD on HHMs of individuals with AD.

Differences were observed between OMOP and Mini-Sentinel CDMs. The analysis of both CDMs at the data model level indicated that such conceptual differences had only a slight but not significant impact on identifying known safety associations. Our results show that differences at the ecosystem level of analyses across the CDMs can lead to strikingly different risk estimations, but this can be primarily attributed to the choices of analytic approach and their implementation in the community-developed analytic tools. The opportunities of using CDMs are clear, but our study shows the need for judicious comparison of analyses across the CDMs. Our work emphasizes the need for ongoing efforts to ensure sustainable transparent platforms to maintain and develop CDMs and associated tools for effective safety surveillance.

This study provided evidence that certain patient characteristics and healthcare utilization are predictive of readmission. An algorithm with good discriminant ability was developed which could be used to target readmission reduction programs. Physician gender, specialty, and ownership status did not appear to influence the likelihood of readmission.

No abstract