OBJECTIVES: The aims of this study were to determine the prevalence of prescribing potentially inappropriate medications (PIMs) based on the 2002 Beers criteria among ambulatory patients aged > or =65 years, to compare PIM prevalence rates based on the 1997 Beers criteria and Zhan criteria with the rate obtained using the 2002 Beers criteria, and to examine patient, provider, and visit characteristics associated with receiving a PIM. METHODS: Retrospective analysis was conducted of the year-2001 public-use data files of the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey. The 2002 Beers criteria 1997 Beers criteria, and Zhan criteria were used to determine presence of PIMs. Multivariate logistic regression was performed to identify patient, visit, and provider characteristics associated with receiving a PIM. RESULTS: A total of 7243 ambulatory visits by individuals aged > or =65 years with > or =1 prescription were projected to an estimated 157 million such ambulatory visits. An estimated 21 million visits (13.4%) involved PIMs based on the 2002 Beers criteria, compared with 13.9 million visits (8.8%) based on the 1997 Beers criteria and 6.6 million visits (4.2%) based on the Zhan criteria. An additional 7.2 million visits (4.6%) by eligible patients involved medications defined by the Zhan criteria as having some indications but often being misused. After adjusting for other factors, visits made in metropolitan areas (odds ratio [OR], 2.42 195% Cl, 1.14-5.12) or by referred patients (OR, 2.28 195% CI, 1.43-3.61) were more likely to involve a PIM. Compared with visits involving 1 medication, those involving 2 (OR, 2.39 [95% CI, 1.30-4.41]), 3 (OR, 7.01 [95% Cl, 3.42-14.35]), or > or =4 medications (OR, 7.35 [95% Cl, 4.44-12.17]) were more likely to be associated with a PIM. CONCLUSIONS: Prevalence of PIMs among ambulatory patients aged > or =65 years is high. The most frequently prescribed PIMs and positive risk factors warrant greater attention from a policy perspective.
OBJECTIVES: The aims of this study were to determine the prevalence of prescribing potentially inappropriate medications (PIMs) based on the 2002 Beers criteria among ambulatory patients aged > or =65 years, to compare PIM prevalence rates based on the 1997 Beers criteria and Zhan criteria with the rate obtained using the 2002 Beers criteria, and to examine patient, provider, and visit characteristics associated with receiving a PIM. METHODS: Retrospective analysis was conducted of the year-2001 public-use data files of the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey. The 2002 Beers criteria 1997 Beers criteria, and Zhan criteria were used to determine presence of PIMs. Multivariate logistic regression was performed to identify patient, visit, and provider characteristics associated with receiving a PIM. RESULTS: A total of 7243 ambulatory visits by individuals aged > or =65 years with > or =1 prescription were projected to an estimated 157 million such ambulatory visits. An estimated 21 million visits (13.4%) involved PIMs based on the 2002 Beers criteria, compared with 13.9 million visits (8.8%) based on the 1997 Beers criteria and 6.6 million visits (4.2%) based on the Zhan criteria. An additional 7.2 million visits (4.6%) by eligible patients involved medications defined by the Zhan criteria as having some indications but often being misused. After adjusting for other factors, visits made in metropolitan areas (odds ratio [OR], 2.42 195% Cl, 1.14-5.12) or by referred patients (OR, 2.28 195% CI, 1.43-3.61) were more likely to involve a PIM. Compared with visits involving 1 medication, those involving 2 (OR, 2.39 [95% CI, 1.30-4.41]), 3 (OR, 7.01 [95% Cl, 3.42-14.35]), or > or =4 medications (OR, 7.35 [95% Cl, 4.44-12.17]) were more likely to be associated with a PIM. CONCLUSIONS: Prevalence of PIMs among ambulatory patients aged > or =65 years is high. The most frequently prescribed PIMs and positive risk factors warrant greater attention from a policy perspective.
Authors: Matthew C Lohman; Brandi P Cotton; Alexandra B Zagaria; Yuhua Bao; Rebecca L Greenberg; Karen L Fortuna; Martha L Bruce Journal: J Gen Intern Med Date: 2017-08-28 Impact factor: 5.128
Authors: Sabin S Egger; Andrea Bachmann; Nathalie Hubmann; Raymond G Schlienger; Stephan Krähenbühl Journal: Drugs Aging Date: 2006 Impact factor: 3.923
Authors: Ronald J Maggiore; William Dale; Cary P Gross; Tao Feng; William P Tew; Supriya G Mohile; Cynthia Owusu; Heidi D Klepin; Stuart M Lichtman; Ajeet Gajra; Rupal Ramani; Vani Katheria; Laura Zavala; Arti Hurria Journal: J Am Geriatr Soc Date: 2014-07-15 Impact factor: 5.562