Literature DB >> 25052047

Development and evaluation of an algorithm to identify users of Prolia(®) during the early postmarketing period using health insurance claims data.

Veena Hoffman1, Fei Xue, Betsey Gardstein, Kathleen Skerry, Cathy W Critchlow, Cheryl Enger.   

Abstract

PURPOSE: The goal of this study is to develop and validate an algorithm to identify Prolia(®) users within a health insurance claims database.
METHODS: Patients with a denosumab-specific or nonspecific administration claim during the early period of Prolia availability in the USA (June 1, 2010 to March 31, 2012) were classified as definite, probable, possible, and nonusers of Prolia using an algorithm consisting of nine different components based on claims patterns consistent with Prolia use. Medical record review confirmed a sample of definite, probable, and possible users and the positive predictive value (PPV) was estimated.
RESULTS: The PPV of the claims-based algorithm components varied (17.8-95.8%). Requiring claims for a bone or cartilage disorder or osteoporotic fracture after excluding claims for cancer prior to a denosumab-specific administration code gave the highest PPV (95.8%), followed by requiring a Prolia National Drug Code on the same claim as a denosumab-specific or nonspecific administration code (88.2%). Among the 87 confirmed Prolia users, osteoporosis diagnoses were seen more frequently in the medical record than in claims (83% vs 62%).
CONCLUSIONS: Prolia users are most accurately identified with administration code claims in conjunction with claims for Prolia National Drug Code and bone disorder treatment and diagnosis codes. Osteoporosis diagnoses may be under-recorded in claims data. The algorithm may require reassessment as uptake for more recently approved indications increases.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Prolia®; health insurance claims data; pharmacoepidemiology; positive predictive value; validation

Mesh:

Substances:

Year:  2014        PMID: 25052047     DOI: 10.1002/pds.3680

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  3 in total

1.  Approaches to Supporting the Analysis of Historical Medication Datasets with RxNorm.

Authors:  Lee B Peters; Olivier Bodenreider
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

2.  Assessment of off-label use of denosumab 60 mg injection during the early postmarketing period using health insurance claims data.

Authors:  V Hoffman; F Xue; B Gardstein; K Skerry; C W Critchlow; C Enger
Journal:  Osteoporos Int       Date:  2015-11-11       Impact factor: 4.507

3.  Real-world effectiveness of osteoporosis therapies for fracture reduction in post-menopausal women.

Authors:  Akeem A Yusuf; Steven R Cummings; Nelson B Watts; Maurille Tepie Feudjo; J Michael Sprafka; Jincheng Zhou; Haifeng Guo; Akhila Balasubramanian; Cyrus Cooper
Journal:  Arch Osteoporos       Date:  2018-03-21       Impact factor: 2.617

  3 in total

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