Literature DB >> 20031876

Sociodemographic and clinical characteristics are not clinically useful predictors of refill adherence in patients with hypertension.

John F Steiner1, P Michael Ho, Brenda L Beaty, L Miriam Dickinson, Rebecca Hanratty, Chan Zeng, Heather M Tavel, Edward P Havranek, Arthur J Davidson, David J Magid, Raymond O Estacio.   

Abstract

BACKGROUND: Although many studies have identified patient characteristics or chronic diseases associated with medication adherence, the clinical utility of such predictors has rarely been assessed. We attempted to develop clinical prediction rules for adherence with antihypertensive medications in 2 healthcare delivery systems. METHODS AND
RESULTS: We performed retrospective cohort studies of hypertension registries in an inner-city healthcare delivery system (n=17 176) and a health maintenance organization (n=94 297) in Denver, Colo. Adherence was defined by acquisition of 80% or more of antihypertensive medications. A multivariable model in the inner-city system found that adherent patients (36.3% of the total) were more likely than nonadherent patients to be older, white, married, and acculturated in US society, to have diabetes or cerebrovascular disease, not to abuse alcohol or controlled substances, and to be prescribed fewer than 3 antihypertensive medications. Although statistically significant, all multivariate odds ratios were 1.7 or less, and the model did not accurately discriminate adherent from nonadherent patients (C statistic=0.606). In the health maintenance organization, where 72.1% of patients were adherent, significant but weak associations existed between adherence and older age, white race, the lack of alcohol abuse, and fewer antihypertensive medications. The multivariate model again failed to accurately discriminate adherent from nonadherent individuals (C statistic=0.576).
CONCLUSIONS: Although certain sociodemographic characteristics or clinical diagnoses are statistically associated with adherence to refills of antihypertensive medications, a combination of these characteristics is not sufficiently accurate to allow clinicians to predict whether their patients will be adherent with treatment.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 20031876      PMCID: PMC2768296          DOI: 10.1161/CIRCOUTCOMES.108.841635

Source DB:  PubMed          Journal:  Circ Cardiovasc Qual Outcomes        ISSN: 1941-7713


  33 in total

Review 1.  The language of medication-taking.

Authors:  J F Steiner; M A Earnest
Journal:  Ann Intern Med       Date:  2000-06-06       Impact factor: 25.391

2.  K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification.

Authors: 
Journal:  Am J Kidney Dis       Date:  2002-02       Impact factor: 8.860

3.  Testing electronic algorithms to create disease registries in a safety net system.

Authors:  Rebecca Hanratty; Raymond O Estacio; L Miriam Dickinson; Vijayalaxmi Chandramouli; John F Steiner; Edward P Havranek
Journal:  J Health Care Poor Underserved       Date:  2008-05

4.  Physician implicit attitudes and stereotypes about race and quality of medical care.

Authors:  Janice A Sabin; Frederick P Rivara; Anthony G Greenwald
Journal:  Med Care       Date:  2008-07       Impact factor: 2.983

5.  The triple aim: care, health, and cost.

Authors:  Donald M Berwick; Thomas W Nolan; John Whittington
Journal:  Health Aff (Millwood)       Date:  2008 May-Jun       Impact factor: 6.301

6.  Long-term adherence to evidence based secondary prevention therapies after acute myocardial infarction.

Authors:  Ayse Akincigil; John R Bowblis; Carrie Levin; Saira Jan; Minalkumar Patel; Stephen Crystal
Journal:  J Gen Intern Med       Date:  2007-10-06       Impact factor: 5.128

7.  Factors influencing physicians' judgments of adherence and treatment decisions for patients with HIV disease.

Authors:  L M Bogart; S L Catz; J A Kelly; E G Benotsch
Journal:  Med Decis Making       Date:  2001 Jan-Feb       Impact factor: 2.583

8.  The effect of patient race and socio-economic status on physicians' perceptions of patients.

Authors:  M van Ryn; J Burke
Journal:  Soc Sci Med       Date:  2000-03       Impact factor: 4.634

9.  Prevalence, predictors, and outcomes of primary nonadherence after acute myocardial infarction.

Authors:  Cynthia A Jackevicius; Ping Li; Jack V Tu
Journal:  Circulation       Date:  2008-02-26       Impact factor: 29.690

10.  Impact of prescription size on statin adherence and cholesterol levels.

Authors:  Holly A Batal; Mori J Krantz; Rita A Dale; Phillip S Mehler; John F Steiner
Journal:  BMC Health Serv Res       Date:  2007-10-25       Impact factor: 2.655

View more
  41 in total

1.  Combination therapy as initial treatment for newly diagnosed hypertension.

Authors:  James B Byrd; Chan Zeng; Heather M Tavel; David J Magid; Patrick J O'Connor; Karen L Margolis; Joe V Selby; P Michael Ho
Journal:  Am Heart J       Date:  2011-07-18       Impact factor: 4.749

2.  Observing versus Predicting: Initial Patterns of Filling Predict Long-Term Adherence More Accurately Than High-Dimensional Modeling Techniques.

Authors:  Jessica M Franklin; William H Shrank; Joyce Lii; Alexis K Krumme; Olga S Matlin; Troyen A Brennan; Niteesh K Choudhry
Journal:  Health Serv Res       Date:  2015-04-16       Impact factor: 3.402

3.  Interventions aimed at improving performance on medication adherence metrics.

Authors:  Brandy McGinnis; Yardlee Kauffman; Kari L Olson; Daniel M Witt; Marsha A Raebel
Journal:  Int J Clin Pharm       Date:  2014-02

4.  A pilot study identifying statin nonadherence with visit-to-visit variability of low-density lipoprotein cholesterol.

Authors:  Devin M Mann; Nicole L Glazer; Michael Winter; Michael K Paasche-Orlow; Paul Muntner; Daichi Shimbo; William G Adams; Nancy R Kressin; Yuqing Zhang; Hyon Choi; Howard Cabral
Journal:  Am J Cardiol       Date:  2013-02-20       Impact factor: 2.778

Review 5.  Factors associated with antihypertensive medication non-adherence: a systematic review.

Authors:  D M van der Laan; P J M Elders; C C L M Boons; J J Beckeringh; G Nijpels; J G Hugtenburg
Journal:  J Hum Hypertens       Date:  2017-06-29       Impact factor: 3.012

6.  Medication Nonadherence Before Hospitalization for Acute Cardiac Events.

Authors:  Sunil Kripalani; Kathryn Goggins; Sam Nwosu; Jonathan Schildcrout; Amanda S Mixon; Candace McNaughton; Amanda M McDougald Scott; Kenneth A Wallston
Journal:  J Health Commun       Date:  2015

7.  Social Risk Factors for Medication Nonadherence: Findings from the CARDIA Study.

Authors:  Gabriela R Oates; Lucia D Juarez; Barbara Hansen; Catarina I Kiefe; James M Shikany
Journal:  Am J Health Behav       Date:  2020-03-01

8.  Characteristics associated with nonadherence to medications for hypertension, diabetes, and dyslipidemia among breast cancer survivors.

Authors:  Gregory S Calip; Joann G Elmore; Denise M Boudreau
Journal:  Breast Cancer Res Treat       Date:  2016-11-08       Impact factor: 4.872

Review 9.  Telehealth Treatment for Alcohol Misuse: Reviewing Telehealth Approaches to Increase Engagement and Reduce Risk of Alcohol-Related Hypertension.

Authors:  Dan V Blalock; Patrick S Calhoun; Matthew J Crowley; Eric A Dedert
Journal:  Curr Hypertens Rep       Date:  2019-06-17       Impact factor: 5.369

10.  Patient characteristics associated with medication adherence.

Authors:  Sharon J Rolnick; Pamala A Pawloski; Brita D Hedblom; Stephen E Asche; Richard J Bruzek
Journal:  Clin Med Res       Date:  2013-04-11
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.