(P-603) Prescription Drug-based Risk Scores: A Systematic Review

Background: While several prescription drug-based risk indices have been developed, their design, performance, and application has not previously been synthesized.

Objectives: We conducted a systematic review of prescription drug-based risk indices and described their design, performance and application.

Methods: We searched Ovid MEDLINE, CINAHL and Embase from inception through March 3, 2020 and included studies that developed or updated a prescription drug-based risk index. Two reviewers independently performed screening and extracted information on data source, study population, cohort sizes, outcomes, study methodology and performance. Predictive performance was evaluated using C statistics for binary outcomes and R2 for continuous outcomes. The PROSPERO ID for this review is CRD42020165498.

Results: Of 19,112 articles that were retrieved, 124 were full-text screened and 25 were included, each of which represented a de novo or updated drug-based index. The Chronic Disease Score represents the first and most widely assessed index; developed in 1992, it has been updated 6 times, most recently in 2018. Nearly half of the risk indices were developed in the U.S. The indices were customized to varied age groups and clinical populations and most commonly evaluated outcomes including mortality (36%), hospitalization (24%) and healthcare costs (24%). C statistics ranged from 0.62 to 0.92 for mortality and 0.59 to 0.72 for hospitalization, while adjusted R2 for healthcare costs ranged from 0.06 to 0.62. Seven of the 25 risk indices included used global drug classification algorithms.

Conclusions: Despite the potential value of prescription-based risk indices, their use is relatively uncommon. We identified 25 prescription drug-based risk indices that have been developed during the last three decades using different populations and validated using outcomes including mortality, hospitalization, health resource utilization and costs. Our analysis of index design, performance, and application may assist researchers in selecting an index most suitable for their study population, data and outcomes.