scholarly journals Adherence to self-administered biologic disease-modifying antirheumatic drugs across health-system specialty pharmacies

Author(s):  
Autumn D Zuckerman ◽  
Josh DeClercq ◽  
Leena Choi ◽  
Nicole Cowgill ◽  
Kate McCarthy ◽  
...  

Abstract Disclaimer In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Adherence to self-administered biologic disease-modifying antirheumatic drugs (bDMARDs) is necessary for therapeutic benefit. Health-system specialty pharmacies (HSSPs) have reported high adherence rates across several disease states; however, adherence outcomes in rheumatoid arthritis (RA) populations have not yet been established. Methods We performed a multisite retrospective cohort study including patients with RA and 3 or more documented dispenses of bDMARDs from January through December 2018. Pharmacy claims were used to calculate proportion of days covered (PDC). Electronic health records of patients with a PDC of <0.8 were reviewed to identify reasons for gaps in pharmacy claims (true nonadherence or appropriate treatment holds). Outcomes included median PDC across sites, reasons for treatment gaps in patients with a PDC of <0.8, and the impact of adjusting PDC when accounting for appropriate therapy gaps. Results There were 29,994 prescriptions for 3,530 patients across 20 sites. The patient cohort was mostly female (75%), with a median age of 55 years (interquartile range [IQR], 42-63 years). The original(ie, prereview) median PDC was 0.94 (IQR, 0.83-0.99). Upon review, 327 patients had no appropriate treatment gaps identified, 6 patients were excluded due to multiple unquantifiable appropriate gaps, and 420 patients had an adjustment in the PDC denominator due to appropriate treatment gaps (43 instances of days’ supply adjusted based on discordant days’ supply information between prescriptions and physician administration instructions, 11 instances of missing fills added, and 421 instances of clinically appropriate treatment gaps). The final median PDC after accounting for appropriate gaps in therapy was 0.95 (IQR, 0.87-0.99). Conclusion This large, multisite retrospective cohort study was the first to demonstrate adherence rates across several HSSPs and provided novel insights into rates and reasons for appropriate gaps in therapy.

2015 ◽  
Vol 30 (12) ◽  
pp. 1733-1740 ◽  
Author(s):  
Anna Lee D. Amarnath ◽  
Peter Franks ◽  
John A. Robbins ◽  
Guibo Xing ◽  
Joshua J. Fenton

Medicina ◽  
2021 ◽  
Vol 57 (10) ◽  
pp. 1068
Author(s):  
Juliana Neide Amato ◽  
Paula Midori Castelo ◽  
Ferla Maria Simas Bastos Cirino ◽  
Guilherme Meyer ◽  
Luciano José Pereira ◽  
...  

Background and Objectives: The aim of this retrospective cohort study was to search individual, sociodemographic and environmental predictors of COVID-19 outcomes. Materials and Methods: A convenience sample of 1036 COVID-19 confirmed patients (3–99 years, mean 59 years; 482 females) who sought treatment at the emergency units of the public health system of Diadema (Brazil; March–October 2020) was included. Primary data were collected from medical records: sex, age, occupation/education, onset of symptoms, presence of chronic diseases/treatment and outcome (death and non-death). Secondary socioeconomic and environmental data were provided by the Department of Health. Results: The mean time spent between COVID-19 symptom onset and admission to the health system was 7.4 days. Principal component analysis summarized secondary sociodemographic data, and a Poisson regression model showed that the time between symptom onset and health system admission was higher for younger people and those from the least advantaged regions (availability of electricity, a sewage network, a water supply and garbage collection). A multiple logistic regression model showed an association of age (OR = 1.08; 1.05–1.1), diabetes (OR = 1.9; 1.1–3.4) and obesity (OR = 2.9; 1.1–7.6) with death outcome, while hypertension and sex showed no significant association. Conclusion: The identification of vulnerable groups may help the development of health strategies for the prevention and treatment of COVID-19.


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