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

Background

Use of antipsychotic (AP) medications is high and often inappropriate among institutionalized populations. Little is known about the correlates of new AP drug use following admission to long-term care (LTC) settings. This study investigated the frequency and correlates of new AP drug use among newly admitted LTC residents.

Methods

This longitudinal, retrospective study used data from the interRAI - Nursing Home Minimum Data Set version 2.0 (MDS 2.0) instrument. Data about demographic, clinical and social characteristics, and medication use, were collected in Ontario, Canada, from 2003–2011 by trained nurses. Residents with complete admission and 3–6 month follow-up data were included (N = 47,768). Multivariate logistic regression analyses, stratified by gender, explored correlates of new AP drug use upon admission to LTC.

Results

New AP drug users comprised 7 % of the final cohort. Severe cognitive impairment, dementia, and motor agitation were significantly associated with new AP drug use among both sexes. Additionally, behavioural problems, conflicts with staff and reduced social engagement were strong correlates of new AP drug use.

Conclusions

Social factors were as strongly associated with new AP drug use after LTC admission as clinical factors. Strategies to prevent the potential misuse of AP drugs upon LTC admission should consider the social determinants of such prescribing.

Algorithm of medication review in frail older people: Focus on minimizing the use of high-risk medications

AIM

Frail older people typically suffer several chronic diseases, receive multiple medications and are more likely to be institutionalized in residential aged care facilities. In such patients, optimizing prescribing and avoiding use of high-risk medications might prevent adverse events. The present study aimed to develop a pragmatic, easily applied algorithm for medication review to help clinicians identify and discontinue potentially inappropriate high-risk medications.

METHODS

The literature was searched for robust evidence of the association of adverse effects related to potentially inappropriate medications in older patients to identify high-risk medications. Prior research into the cessation of potentially inappropriate medications in older patients in different settings was synthesized into a four-step algorithm for incorporation into clinical assessment protocols for patients, particularly those in residential aged care facilities.

RESULTS

The algorithm comprises several steps leading to individualized prescribing recommendations: (i) identify a high-risk medication; (ii) ascertain the current indications for the medication and assess their validity; (iii) assess if the drug is providing ongoing symptomatic benefit; and (iv) consider withdrawing, altering or continuing medications. Decision support resources were developed to complement the algorithm in ensuring a systematic and patient-centered approach to medication discontinuation. These include a comprehensive list of high-risk medications and the reasons for inappropriateness, lists of alternative treatments, and suggested medication withdrawal protocols.

CONCLUSIONS

The algorithm captures a range of different clinical scenarios in relation to potentially inappropriate medications, and offers an evidence-based approach to identifying and, if appropriate, discontinuing such medications. Studies are required to evaluate algorithm effects on prescribing decisions and patient outcomes. Geriatr Gerontol Int 2016; 16: 1002-1013.

Use of benzodiazepines and association with falls in older people admitted to hospital: a prospective cohort study

BACKGROUND

Hypnosedatives are commonly prescribed for anxiety and sleep problems. Changes in pharmacokinetics and pharmacodynamics of benzodiazepines (BZDs) during ageing may increase their potential to cause adverse outcomes.

OBJECTIVE

This study aimed to investigate the use of BZDs in acute care settings and explore their association with falls.

METHODS

A prospective cohort study was undertaken of patients aged over 70 years consecutively admitted to 11 acute care hospitals in Australia. Data were collected using the interRAI Acute Care assessment tool. Falls were recorded prospectively (in hospital) and retrospectively (in the 90 days prior to admission).

RESULTS

Of 1,412 patients, 146 (10.3 %) were taking BZDs at admission and 155 (11.3 %) at discharge. Incidence rates of in-hospital fallers for users and non-users of BZDs were not statistically different [incidence rate ratio 1.03, 95 % confidence interval (CI) 0.58-1.82]. There was also no significant association between benzodiazepine use at admission and history of falls in the previous 90 days compared with non-users. However, patients on diazepam were significantly more likely to have a history of falls than all other benzodiazepine users (70.8 vs. 36.1 %; p = 0.002), particularly when compared with oxazepam users (70.8 vs. 25.0 %; p < 0.001). Adjusting for confounders, use of diazepam at admission was positively associated with a history of falls compared with all other benzodiazepine users (odds ratio 3.0; 95 % CI 1.1-8.5; p = 0.036).

CONCLUSIONS

Different BZDs may vary in their propensity to predispose to falls, with diazepam having the strongest association. The selection of particular BZDs for older patients should be carefully evaluated.