Community pharmacist collaboration with a primary care clinic to improve diabetes care

2020 ◽  
Vol 60 (3) ◽  
pp. S84-S90
Author(s):  
Joy M. Snyder ◽  
Nabila Ahmed-Sarwar ◽  
Christopher Gardiner ◽  
Elizabeth Sutton Burke
2007 ◽  
Vol 16 (4) ◽  
pp. 244-247 ◽  
Author(s):  
C. R Taylor ◽  
J. T Hepworth ◽  
P. I Buerhaus ◽  
R. Dittus ◽  
T. Speroff

2000 ◽  
Vol 6 (5) ◽  
pp. 361-366 ◽  
Author(s):  
Matthew C. Leinung, MD, FACE ◽  
Andrew G. Gianoukakis, MD ◽  
Daniel W. Lee, MD ◽  
Stacey L. Jeronis, MD ◽  
James Desemone, MD, FACE

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 93A-93A
Author(s):  
Lwbba Chait ◽  
Angeliki Makri ◽  
Rawan Nahas ◽  
Gwen Raphan

2021 ◽  
Vol 12 ◽  
pp. 215013272110350
Author(s):  
Pasitpon Vatcharavongvan ◽  
Viwat Puttawanchai

Background Most older adults with comorbidities in primary care clinics use multiple medications and are at risk of potentially inappropriate medications (PIMs) prescription. Objective This study examined the prevalence of polypharmacy and PIMs using Thai criteria for PIMs. Methods This study was a retrospective cross-sectional study. Data were collected from electronic medical records in a primary care clinic in 2018. Samples were patients aged ≥65 years old with at least 1 prescription. Variables included age, gender, comorbidities, and medications. The list of risk drugs for Thai elderly version 2 was the criteria for PIMs. The prevalence of polypharmacy and PIMs were calculated, and multiple logistic regression was conducted to examine associations between variables and PIMs. Results Of 2806 patients, 27.5% and 43.7% used ≥5 medications and PIMs, respectively. Of 10 290 prescriptions, 47% had at least 1 PIM. The top 3 PIMs were anticholinergics, proton-pump inhibitors, and nonsteroidal anti-inflammatory drugs (NSAIDs). Polypharmacy and dyspepsia were associated with PIM prescriptions (adjusted odds ratio 2.48 [95% confident interval or 95% CI 2.07-2.96] and 3.88 [95% CI 2.65-5.68], respectively). Conclusion Prescriptions with PIMs were high in the primary care clinic. Describing unnecessary medications is crucial to prevent negative health outcomes from PIMs. Computer-based clinical decision support, pharmacy-led interventions, and patient-specific drug recommendations are promising interventions to reduce PIMs in a primary care setting.


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