Literature DB >> 33838274

More than two-dozen prescription drug-based risk scores are available for risk adjustment: A systematic review.

Hemalkumar B Mehta1, Lin Wang2, Ioannis Malagaris3, Yanjun Duan2, Lori Rosman4, G Caleb Alexander5.   

Abstract

OBJECTIVE: While several prescription drug-based risk indices have been developed, their design, performance, and application has not previously been synthesized. STUDY DESIGN AND
SETTING: 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 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: More than two-dozen prescription drug-based risk indices have been developed and they differ significantly in design, performance and application.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Administrative healthcare data; Comorbidity scores; Pharmacy data; Prescription drugs; Risk index; Systematic review

Year:  2021        PMID: 33838274     DOI: 10.1016/j.jclinepi.2021.03.029

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  2 in total

1.  Evaluating Drug Risk Using GAN and SMOTE Based on CFDA's Spontaneous Reporting Data.

Authors:  Jianxiang Wei; Guanzhong Feng; Zhiqiang Lu; Pu Han; Yunxia Zhu; Weidong Huang
Journal:  J Healthc Eng       Date:  2021-08-27       Impact factor: 2.682

2.  Clinical Utility of Medication-Based Risk Scores to Reduce Polypharmacy and Potentially Avoidable Healthcare Utilization.

Authors:  Armando Silva-Almodóvar; Milap C Nahata
Journal:  Pharmaceuticals (Basel)       Date:  2022-05-28
  2 in total

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