Literature DB >> 28149500

Pragmatic trials may help to identify effective strategies to reduce nursing home antipsychotic medication use.

Rosa R Baier1, Vincent Mor1.   

Abstract

Despite widespread agreement that nursing homes' use of antipsychotic medications for residents without specific psychiatric diagnoses is a marker of poor quality of care, prevalence remains high. Additionally, variation suggests continued opportunity to improve care even in countries, like the United States, that have long-standing policies designed to decrease antipsychotic medication use. In a recent Israel Journal of Health Policy Research article, Frankenthal et al. presented results linking increased antipsychotic medication use prevalence in Tel Aviv nursing homes with facility characteristics, including some that "undermine quality of care," and called for increased national focus on this area. While we agree with the authors that government focus can help to decrease antipsychotic medication use, experience in the United States shows that such efforts may not be sufficient: we present data showing significant variation among United States nursing homes' antipsychotic medication use prevalence after more than ten years of national warnings and programs. This suggests that United States nursing home clinicians and caregivers continue to need effective non-pharmacologic interventions to substitute for antipsychotic medications. We suggest expanded use of cluster-randomized trials to test strategies to withdraw residents from antipsychotic medications and to implement alternate, non-pharmacological approaches for addressing the behavioral and psychological symptoms of dementia.

Entities:  

Keywords:  Antipsychotic medications; Chemical restraints; Dementia; Nursing homes; Quality

Mesh:

Substances:

Year:  2017        PMID: 28149500      PMCID: PMC5270358          DOI: 10.1186/s13584-016-0130-3

Source DB:  PubMed          Journal:  Isr J Health Policy Res        ISSN: 2045-4015


Main text

The off-label use of antipsychotic medications to address the behavioral and psychological symptoms of dementia is controversial, because antipsychotic medications may increase older adults’ risk of heart failure, sudden death, and pneumonia [1, 2]. As a result, nursing homes’ use of antipsychotics as chemical restraints for the purpose of behavioral control is widely considered inappropriate, absent a psychiatric diagnosis, and is increasingly considered to be a marker of poor quality of care. Despite general agreement that non-pharmacological approaches are preferable, studies in Europe [3], Canada [4], the United States [5, 6], and elsewhere show that antipsychotic medication use remains highly prevalent in this setting with evidence of substantial variation between facilities [5, 7] and between countries [3, 8]. Understanding this variation can inform programs and policies intended to reduce antipsychotic medication use. The SHELTER study compared treatment of nursing home residents in seven European countries and Israel, and found that 32% of residents with a dementia diagnosis had an antipsychotic prescription; prevalence ranged from 18% in Israel to 60% in the Czech Republic [3]. However, this study only included a relatively small number of volunteer facilities in each country, with considerable intra-country variation. In a recent Israel Journal of Health Policy Research (IJHPR) article, Frankenthal et al. [7] presented results linking increased APM prevalence among Tel Aviv nursing homes with facility characteristics, including some that “undermine quality of care.” These included the presence of medical directors without specialized geriatrics training, shortages of social workers and occupational therapists, and the use of unsafe or non-fitting self-aid equipment [7]. The authors argue that their findings shed light on a problematic care process, making it transparent in a country where antipsychotic medication use is not regulated or publicly reported, and call for increased national focus on this area. In the United States, there has been a national spotlight on reducing nursing home antipsychotic medication use since our country’s Food and Drug Administration issued a “boxed warning” against the use of these medications for off-label indications among older adults, in 2005 [1]. More recently, the Centers for Medicare & Medicaid Services began publicly reporting nursing home antipsychotic medication rates on its Nursing Home Compare website (in 2011) [9] and implemented a national campaign to lower use (in 2012) [10]. Although national prevalence has decreased over the past 10 years, our analysis of longitudinal data available through Brown University’s LTCFocus.org database [11] illustrates significant, ongoing variation in facility-level antipsychotic medication prevalence (Fig. 1) and suggests continued need for intervention in the United States. While there are many nursing facilities with no residents (or virtually none) taking antipsychotics, even in 2014 there were hundreds of facilities with 40% or more of their residents prescribed these medications.
Fig. 1

Percent of United States nursing home residents on antipsychotic medications without a psychiatric diagnosis, 2000–2010

Percent of United States nursing home residents on antipsychotic medications without a psychiatric diagnosis, 2000–2010 To reduce nursing home antipsychotic medication use, clinicians must implement strategies to identify and discontinue inappropriate off-label use among residents with existing prescriptions [12] and practices to avoid new prescriptions when the behavioral and psychological symptoms of dementia become manifest [13]. Both approaches require alternative techniques so that clinicians and caregivers have strategies to implement in lieu of antipsychotic medications if dementia behaviors re-emerge or persist. Although there are numerous studies evaluating various non-pharmacological strategies to reduce antipsychotic medications use or address dementia behaviors, much of the evidence for the effectiveness of these interventions is insufficient [14]. Furthermore, complex, labor-intensive interventions that might substitute for antipsychotics can be difficult to implement with existing staff and resources. Indeed, many interventions that reveal a positive effect in small- scale studies implemented by research staff have difficulty showing similar effects in real-world replications. Additionally, some researchers argue that rigorously testing such interventions may be difficult, in part because it is not possible to blind nursing home clinicians to interventions. Cluster-randomized trial methods are one methodological approach to overcome research limitations for testing strategies to reduce antipsychotic medication use or improve the behavioral and psychological symptoms of dementia using non-pharmacological approaches. By randomizing NHs to implement antipsychotic medication practice guidelines, for example, or to serve as control sites, we can rigorously test such interventions using pragmatic methods. At Brown University, we use cluster-randomized trials to conduct studies on topics such as influenza vaccination [15, 16]; others have used these methods for antipsychotic medication reduction interventions [17-19]. The Brown studies pair cluster-randomized trial methods with the use of existing clinical and administrative data, such as United States Minimum Data Set resident assessment data; this allows us to conduct rigorous nursing home research efficiently. We suggest that others use similar approaches and data sources, e.g., the Minimum Data Set or InterRAI assessment tools [20], to test antipsychotic medication interventions using approaches that mimic real-world conditions. One such trial is currently underway in Ontario, offering a model for others around the developed world [21].

Conclusions

Despite widespread agreement that nursing homes’ use of antipsychotic medications as chemical restraints is associated with poor clinical outcomes and as such constitutes a marker of poor quality of care, prevalence remains high and variation suggests continued opportunity to improve care even in countries, like the United States, that have long-standing policies designed to decrease APM use. While we agree with Frankenthal et al. [7] that regulation and public reporting can help to decrease prevalence, the United States experience suggests that nursing home clinicians and caregivers also need effective alternative interventions to employ as substitutes for antipsychotics. We suggest expanded use of cluster-randomized trials to test strategies to remove residents from antipsychotics and to implement alternate, non-pharmacological approaches for addressing the behavioral and psychological symptoms of dementia.
  15 in total

1.  Dissemination of Evidence-Based Antipsychotic Prescribing Guidelines to Nursing Homes: A Cluster Randomized Trial.

Authors:  Jennifer Tjia; Terry Field; Kathleen Mazor; Celeste A Lemay; Abir O Kanaan; Jennifer L Donovan; Becky A Briesacher; Daniel Peterson; Michelle Pandolfi; Ann Spenard; Jerry H Gurwitz
Journal:  J Am Geriatr Soc       Date:  2015-07-14       Impact factor: 5.562

2.  Use of antipsychotic drugs among residents with dementia in European long-term care facilities: results from the SHELTER study.

Authors:  Andrea D Foebel; Rosa Liperoti; Graziano Onder; Harriet Finne-Soveri; Jean Claude Henrard; Albert Lukas; Michael D Denkinger; Giovanni Gambassi; Roberto Bernabei
Journal:  J Am Med Dir Assoc       Date:  2014-09-24       Impact factor: 4.669

3.  Use of physical restraints and antipsychotic medications in nursing homes: a cross-national study.

Authors:  Zhanlian Feng; John P Hirdes; Trevor F Smith; Harriet Finne-Soveri; Iris Chi; Jean-Noel Du Pasquier; Ruedi Gilgen; Naoki Ikegami; Vincent Mor
Journal:  Int J Geriatr Psychiatry       Date:  2009-10       Impact factor: 3.485

4.  Effects of a Stepwise Multidisciplinary Intervention for Challenging Behavior in Advanced Dementia: A Cluster Randomized Controlled Trial.

Authors:  Marjoleine J C Pieper; Anneke L Francke; Jenny T van der Steen; Erik J A Scherder; Jos W R Twisk; Christine R Kovach; Wilco P Achterberg
Journal:  J Am Geriatr Soc       Date:  2016-01-25       Impact factor: 5.562

5.  Unexplained variation across US nursing homes in antipsychotic prescribing rates.

Authors:  Yong Chen; Becky A Briesacher; Terry S Field; Jennifer Tjia; Denys T Lau; Jerry H Gurwitz
Journal:  Arch Intern Med       Date:  2010-01-11

6.  Psychotropic use and associated neuropsychiatric symptoms among patients with dementia in the USA.

Authors:  Donovan T Maust; Kenneth M Langa; Frederic C Blow; Helen C Kales
Journal:  Int J Geriatr Psychiatry       Date:  2016-02-18       Impact factor: 3.485

Review 7.  Approaches to Gradual Dose Reduction of Chronic Off-Label Antipsychotics Used for Behavioral and Psychological Symptoms of Dementia.

Authors:  Jennifer Tjia; Marcus M Reidenberg; Jacob N Hunnicutt; Kelli Paice; Jennifer L Donovan; Abir Kanaan; Becky A Briesacher; Kate L Lapane
Journal:  Consult Pharm       Date:  2015-10

8.  A retrospective, longitudinal study of factors associated with new antipsychotic medication use among recently admitted long-term care residents.

Authors:  Andrea Foebel; Anna Ballokova; Nathalie I H Wellens; Daniela Fialova; Koen Milisen; Rosa Liperoti; John P Hirdes
Journal:  BMC Geriatr       Date:  2015-10-19       Impact factor: 3.921

Review 9.  Dealing with behavioral and psychological symptoms of dementia: a general overview.

Authors:  Majda Azermai
Journal:  Psychol Res Behav Manag       Date:  2015-07-03

10.  Impact of Antipsychotic Review and Nonpharmacological Intervention on Antipsychotic Use, Neuropsychiatric Symptoms, and Mortality in People With Dementia Living in Nursing Homes: A Factorial Cluster-Randomized Controlled Trial by the Well-Being and Health for People With Dementia (WHELD) Program.

Authors:  Clive Ballard; Martin Orrell; Sun YongZhong; Esme Moniz-Cook; Jane Stafford; Rhiannon Whittaker; Bob Woods; Anne Corbett; Lucy Garrod; Zunera Khan; Barbara Woodward-Carlton; Jennifer Wenborn; Jane Fossey
Journal:  Am J Psychiatry       Date:  2015-11-20       Impact factor: 18.112

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