2019
DOI: 10.1371/journal.pmed.1002763
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Comparative effectiveness of generic and brand-name medication use: A database study of US health insurance claims

Abstract: BackgroundTo the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications.Methods and … Show more

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Cited by 68 publications
(75 citation statements)
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“…Another alternative is to promote generic medicines. Some studies based on the comparative effectiveness of generic versus brand-name medications have found the clinical outcomes associated with both quite comparable; this should instill more confidence in the patients and healthcare providers on the quality of generic medicines [22,23]. However, in India, patients have a negative perception of generic medicines.…”
Section: Discussionmentioning
confidence: 99%
“…Another alternative is to promote generic medicines. Some studies based on the comparative effectiveness of generic versus brand-name medications have found the clinical outcomes associated with both quite comparable; this should instill more confidence in the patients and healthcare providers on the quality of generic medicines [22,23]. However, in India, patients have a negative perception of generic medicines.…”
Section: Discussionmentioning
confidence: 99%
“…Figure 3B shows the same t-SNE visualization found in Fig. 2, with cluster assignment colored for values of Kǫ [2,4,8,15] . This allows us to visualize the same information contained in the dendrogram for selected values of K.…”
Section: K-means Clustering Of the Medical Complaint Vectors Of The Hmentioning
confidence: 79%
“…Classification schemes for HF help clinicians determine the disease phenotype, select appropriate treatments, and define study populations for randomized controlled trials (RCT) of HF interventions. Such schemes are typically defined in a top-down manner based on HF etiology [4][5][6] , functional assessments (e.g., the New York Heart Association Functional Classification), imagingbased lab values (such as ejection fraction) and biomarkers (e.g. NT-proBNP, cardiac troponin) 1,3,7 .…”
mentioning
confidence: 99%
“…Appendix Table 2 Environmental factors and stimuli modifying placebo/nocebo effects Modifiable Non-modifiable Patient's expectations [13] Previous experiences [14] Pre-treatment verbal and non-verbal suggestions [15,16] Patient's personality [17] Speed of treatment titration [18] Cultural factors [19,20] Safety profile of treatment [21] Age [22] Patient-doctor relation/communication [23] Social Media and Internet information [24] Investigator/physician status [15] Gender [25] Affective and cognitive traits [26] Level of patients' education [22] Generic formulations [27,28] Genetics [29] The appearance of drugs or medical devices, e.g. packaging, color, price, drug taste, etc.…”
Section: Fundingmentioning
confidence: 99%