Interventions for preventing delirium in older people in institutional long‐term care
Abstract
Background
Delirium is a common and distressing complication of a range of stressor events including infection, new medications and environment change that is often experienced by older people with frailty and dementia. Older people living in institutional long‐term care (LTC) are at high risk of delirium, which increases the risk of admission to hospital, development of or worsening of dementia, and mortality. Delirium is also associated with substantial healthcare costs. Although it is possible to prevent delirium in the hospital setting by providing multicomponent delirium prevention interventions it is currently unclear whether interventions to prevent delirium in LTC are effective.
Objectives
To assess the effectiveness of interventions for preventing delirium in older people in long term care.
Search methods
We searched ALOIS (www.medicine.ox.ac.uk/alois) ‐ the Cochrane Dementia and Cognitive Improvement Group’s Specialised Register ‐ on 23 April 2013. The search was as sensitive as possible to identify all studies on ALOIS relating to delirium. We ran additional separate searches in major healthcare databases, trial registers, the Cochrane Central Register of Controlled Trials (CENTRAL) and grey literature sources, to ensure that the search was as comprehensive as possible.
Selection criteria
We included randomised controlled trials (RCTs) and cluster‐randomised controlled trials (cluster‐RCTs) of single‐ and multicomponent non‐pharmacological and pharmacological interventions for preventing delirium in older people (aged 65 years and over) in permanent LTC residence.
Data collection and analysis
Two independent review authors examined the titles and abstracts of citations identified by the search for eligibility and extracted data, with any disagreements settled by consensus. Primary outcomes were prevalence, incidence and severity of delirium. Secondary outcomes included new diagnosis of dementia, activities of daily living, quality of life and adverse outcomes. We used risk ratios (RRs) as measures of treatment effect for dichotomous outcomes and hazard ratios (HR) for time to event data.
Main results
We included two trials that recruited 3636 participants. Both were complex single‐component non‐pharmacological delirium prevention interventions. Risk of bias for many items was unclear due to inadequate reporting. Notably, there was no evidence of blinding of trial participants or assessors in either trial. One small cluster‐RCT (n = 98) of a hydration‐based intervention reported no reduction in delirium incidence in the intervention group compared to control (RR 0.85, 95% confidence interval (CI) 0.18 to 4.00, analysis not adjusted for clustering, very low quality evidence). Results were imprecise and there were serious limitations evident in trial design. One large cluster‐RCT (n = 3538) of a computerised system to identify medications that may contribute to delirium risk and trigger a pharmacist‐led medication review reported a large reduction in delirium incidence (12‐month HR 0.42, CI 0.34 to 0.51, moderate quality evidence) but no clear evidence of reduction in hospital admissions (HR 0.89, CI 0.72 to 1.10, moderate quality evidence), in mortality (HR 0.88, CI 0.66 to 1.17, moderate quality evidence) or in falls risk (HR 1.03, CI 0.92 to 1.15, moderate quality evidence).
Authors' conclusions
Our review identified very limited evidence on interventions for preventing delirium in older people in LTC. Introduction of a software‐based intervention to identify medications that could contribute to delirium risk so that a pharmacist‐led medication review and monitoring plan can be initiated may reduce incidence of delirium for older people in institutional LTC. This is based on one large RCT in the United States and may not be practical in other countries which do not have comparable information technology services available in care homes. Our review identified only one ongoing pilot trial of a multicomponent delirium prevention intervention and no trials of pharmacological agents. Future trials of computerised medication management systems and multicomponent non‐pharmacological and pharmacological delirium prevention interventions for older people in LTC are needed to help inform the provision of evidence‐based care for this vulnerable group.
PICOs
Plain language summary
Interventions for preventing delirium in older people in institutional long‐term care (LTC)
Review question
We reviewed the evidence about the effectiveness of interventions for preventing delirium in older people living in long‐term care (LTC).
Background
LTC is the name used for residential homes, which provide personal care, supervision with medications and some help with day to day activities, and nursing homes, which provide 24‐hour nursing care. Delirium is a common and serious illness for older people living in LTC. People with delirium usually become more confused over a few hours or a couple of days. Some people with delirium become quiet and sleepy but others become agitated and disorientated, so it can be a very distressing condition. It can also increase the chances of being admitted to hospital and developing dementia, and LTC residents who develop delirium are at increased risk of death.
Importantly, studies of people in hospital have shown that it is possible to prevent around a third of cases of delirium by providing an environment and care plan that target the main risk factors for delirium. For example: providing better lighting and signs to avoid disorientation; avoiding unnecessary use of catheters to help prevent infection; avoiding medications which increase delirium risk.
This review has searched for and assessed research on preventing delirium in older people living in LTC.
Study characteristics
The evidence is current to 04/2013. We found two studies that included 3636 participants. Both studies were done in the United States.
The first study tested whether delirium can be prevented by calculating how much fluid an older person in a care home needs each day and ensuring that hydration was provided by giving regular drinks. 98 people participated in the study, which lasted four weeks.
The second study tested the effect of a computer programme which searched prescriptions for medications that might increase the chance of developing delirium so that a pharmacist could adjust or stop them. 3538 people participated in the study, which lasted 12 months.
Key findings
The first study found that the hydration intervention did not reduce delirium. However, this was a small study of short duration with serious design problems.
The second study found that the computerised medication search programme and pharmacist review reduced delirium but there was no clear reduction in hospital admissions, deaths or falls. One problem with the findings of this study is that it might not be possible to use this computer programme in different countries that do not have similar computer systems.
Quality of the evidence
There is very low‐quality evidence on the effectiveness of hydration interventions for reducing the incidence of delirium in older people in LTC. It is therefore not possible to draw firm conclusions.
There is moderate‐quality evidence that a computerised medication search programme and pharmacist review may reduce the incidence of delirium in older people in LTC.
There is no clear evidence that a computerised medication search programme and pharmacist review reduces hospitalisation, mortality or falls for older people in LTC.
As this review only found a very small number of research studies, we have recommended that further research should be conducted testing different ways of preventing delirium for older people living in LTC. This may help improve the quality of care for this vulnerable group.
External funding
There was no source of external funding for this review.
Conflicts of interest
NS is chief investigator for a National Institute for Health Research (NIHR) Research for Patient Benefit (RfPB) grant to investigate the effects of a delirium prevention intervention for older people in long term care.
JY is a co‐applicant for a National Institute for Health Research (NIHR) Research for Patient Benefit (RfPB) grant to investigate the effects of a delirium prevention intervention for older people in long term care.
AC, RH and AH declare that they have no known conflicts of interest.
Authors' conclusions
Summary of findings
| Single‐component medication monitoring and adjustment intervention versus control for preventing delirium in older people in institutional long term care | ||||||
| Patient or population: People at risk of delirium in institutional long term care | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No of resident months | Quality of the evidence | Comments | |
| Assumed risk | Corresponding risk | |||||
| Control | Single‐component medication monitoring and adjustment intervention versus control | |||||
| Incidence of delirium1 | Study population | HR 0.42 | 7311 | ⊕⊕⊕⊝ | ||
| 104 per 1000 | 45 per 1000 | |||||
| Medium risk population | ||||||
| 99 per 1000 | 43 per 1000 | |||||
| Unplanned hospitalisation1 | Study population | HR 0.89 | 7599 | ⊕⊕⊕⊝ | ||
| 55 per 1000 | 49 per 1000 | |||||
| Medium risk population | ||||||
| 57 per 1000 | 51 per 1000 | |||||
| Mortality1 | Study population | HR 0.88 | 9412 | ⊕⊕⊕⊝ | ||
| 25 per 1000 | 22 per 1000 | |||||
| Medium risk population | ||||||
| 25 per 1000 | 22 per 1000 | |||||
| Falls1 | Study population | RR 1.03 | 2275 | ⊕⊕⊕⊝ | ||
| 523 per 1000 | 539 per 1000 | |||||
| Medium risk population | ||||||
| 523 per 1000 | 539 per 1000 | |||||
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| 1Assumed risk based on control group risk in included study. | ||||||
| Single‐component hydration intervention versus control for preventing delirium in older people in institutional long term care | ||||||
| Patient or population: People at risk of delirium in institutional long term care | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No of Participants | Quality of the evidence | Comments | |
| Assumed risk | Corresponding risk | |||||
| Control | Single‐component hydration intervention versus control | |||||
| Incidence of delirium1 | Study population | RR 0.85 | 98 | ⊕⊝⊝⊝ | ||
| 67 per 1000 | 57 per 1000 | |||||
| Medium risk population | ||||||
| 67 per 1000 | 57 per 1000 | |||||
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| 1Assumed risk based on control group risk in included study. | ||||||
Background
Delirium is a distressing complication of a range of stressor events, including infection, new medications and dehydration, and is often experienced by older people with frailty and dementia. Although a single event can precipitate delirium, it is more common for multiple factors to interact and a multifactorial model of delirium has been established to help illustrate how delirium is precipitated in people at risk (Inouye 1996). Using this model, a seemingly small insult such as a minor infection or new medication in those at high risk can lead to delirium.
Delirium is associated with increased morbidity, functional decline, risk of developing or worsening dementia and death (Inouye 2006; Witlox 2010). It is common throughout the health and social care system and has substantial health and socioeconomic costs (Inouye 2006; Leslie 2008). The majority of delirium research has focused on hospitalised people, but long‐term care (LTC) residents are also at high risk, with the point prevalence of delirium at around 15% in these settings (Siddiqi 2009). The multifactorial model of delirium has been validated in the LTC setting (Voyer 2010) and LTC residents with moderate to severe cognitive impairment are at particularly high risk (McCusker 2011). The development of delirium in older people in LTC is associated with increases in risk of admission to hospital, rates of re‐admission and mortality (Siddiqi 2009). Notably, the duration of delirium in LTC residents is typically increased, compared to delirium in hospitalised people (Cole 2012). Although it is possible to prevent delirium in the hospital setting by providing multicomponent delirium prevention interventions (Inouye 1999; Marcantonio 2001), it is currently unclear whether interventions to prevent delirium in LTC are effective.
LTC facilities have expanded over recent decades in response to the ageing population. In the UK, 4.5% of people aged over 65 live in LTC, rising to 20% of people aged over 85 (Soule 2005). The environment and systems of care in LTC share features with hospitals that are likely to increase the risk of delirium. As age over 65 and presence of cognitive impairment or dementia are important risk factors for delirium, the high point prevalence of delirium is likely to be a reflection of clustering of these risk factors in LTC.
LTC facilities are considered to be the 'usual place of residence', which distinguishes them from other more temporary facilities, including respite care, intermediate care and post‐acute care. LTC is the broad umbrella term for facilities including residential homes, which provide personal care, supervision with medications and some help with activities of daily living, and nursing homes, which provide 24‐hour nursing care by staff with specialist skills in management of physical and mental health conditions (Ames 2005).
Description of the condition
Delirium is characterised by the rapid onset of fluctuating confusion, disturbed awareness and inattention. The diagnostic criteria for delirium have been operationalised in the Diagnostic and Statistical Manual of Mental Disorders Volumes III, III‐revised, IV and 5 (APA 1980; APA 1987; APA 1994; APA 2013) and the International Classification of Diseases Volume 10 (WHO 1992).
A key feature of delirium is change and fluctuation in a range of key symptoms and behaviours including:
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Cognitive function (e.g. worsened concentration, slow responses, confusion);
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Perception (e.g. visual or auditory hallucinations);
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Physical function (e.g. reduced mobility, reduced movement, restlessness, agitation, changes in appetite, sleep disturbance);
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Social behaviour (e.g. lack of co‐operation, withdrawal, or alterations in communication, mood or attitude or both (NICE 2010)).
Delirium is triggered when a susceptible individual is exposed to often multiple precipitating factors, including infection, medications, pain and dehydration (Inouye 1998). These multiple factors are considered to interact in a cumulative manner; the greater the number of factors, the greater the risk of delirium. The pathophysiology of delirium is incompletely understood, but a complex interaction between acetylcholine and multiple neurotransmitters including dopamine, noradrenaline, glutamate and gamma‐amino hydroxybutyric acid (GABA) is considered important (Alagiakrishnan 2004; Hshieh 2008; Clegg 2011).
Description of the intervention
This review examines the effectiveness of single‐ and multicomponent non‐pharmacological and pharmacological interventions for preventing delirium in older people in LTC.
Non‐pharmacological interventions target the important precipitating factors for delirium and usually incorporate a multicomponent approach to address the multiple potential factors, including: actively looking for and treating infection; avoiding unnecessary urinary catheterisation; undertaking a medication review to identify medications associated with increased risk of delirium; assessing for pain and initiating treatment where appropriate; addressing sensory impairment by providing visual and hearing aids (NICE 2010). Multicomponent delirium prevention interventions incorporating such strategies have been demonstrated to be effective at reducing delirium in hospitalised people (Inouye 1999; Marcantonio 2001; NICE 2010). Introduction of protocols, staff education or systems redesign are methods that have been used to introduce these interventions (Inouye 1999; Rockwood 1999). As many of the reported risk factors for delirium are similar in both hospitalised people and LTC residents (Siddiqi 2009), non‐pharmacological interventions that have been shown to be effective in hospitals by targeting these risk factors may have a role in reducing the incidence of delirium in LTC, with appropriate modification to account for differences in environmental factors and care processes (McCusker 2013).
Although it is biologically plausible that pharmacological agents could prevent delirium by acting on neurotransmitter pathways, a small number of trials of pharmacological interventions for preventing delirium in hospitalised people have demonstrated limited effectiveness (Kalisvaart 2005; Siddiqi 2007; Tabet 2009) and require further investigation (NICE 2010).
How the intervention might work
Non‐pharmacological interventions target the multiple potential precipitating factors for delirium to reduce their cumulative effect. Pharmacological interventions target the important neurotransmitter pathways that have been implicated in the complex pathophysiology of delirium.
Why it is important to do this review
This review examines evidence from randomised controlled trials (RCTs) and cluster‐randomised controlled trials (cluster‐RCTs) for the clinical and cost effectiveness of non‐pharmacological and pharmacological interventions to prevent delirium in older people in LTC. This evidence will help inform the development and future commissioning of evidence‐based services to improve the health and well‐being of this vulnerable group. It will also help improve knowledge about delirium in LTC, inform the development of LTC staff education programmes and help stimulate future research into prevention of delirium in LTC residents.
Objectives
To assess the effectiveness of interventions for preventing delirium in older people in LTC.
Methods
Criteria for considering studies for this review
Types of studies
We considered randomised controlled trials (RCTs) and cluster‐randomised controlled trials (cluster‐RCTs) for this review.
Types of participants
For this review, LTC is defined as an institution that is the permanent residence of an individual, providing accommodation together with personal or nursing care.
Inclusion criteria
Trials investigating interventions for preventing delirium in older people in LTC were eligible for inclusion. It is possible that any general health intervention for older people in LTC will have the effect of reducing delirium. However, we only considered trials that used a validated method of delirium diagnosis, such as DSM‐III, DSM‐III‐R, DSM‐IV and ICD‐10 (APA 1980; APA 1987; APA 1994; WHO 1992), or a diagnostic tool validated against these, e.g. confusion assessment method (CAM) (Inouye 1990), delirium rating scale (DRS) (Trzepacz 1988).
Trials in which the mean age of participants was 65 years or older.
Exclusion criteria
Trials of hospitalised people.
Trials taking place in a setting that was not the permanent residence of study participants (e.g. post‐acute care, intermediate care, continuing care).
Trials taking place in a palliative care setting.
Non‐randomised intervention trials, observational studies.
Types of interventions
We considered interventions designed to prevent delirium, including non‐pharmacological and pharmacological single‐ and multicomponent interventions which included a control group for comparison.
Types of outcome measures
We identified the primary, secondary and adverse outcome measures that are important both for older people in LTC and for health and social care systems.
Primary outcomes
Prevalence and incidence of delirium, using a validated diagnostic method (see Types of studies).
Severity of delirium, using a validated diagnostic method (e.g. delirium rating scale (Trzepacz 1988)).
Secondary outcomes
Length of delirium episode.
Proportion of time spent with delirium (total number of days of delirium/length of follow‐up period).
Total number of delirium episodes.
Cognitive function, using any validated continuous scale.
New diagnosis of dementia.
Worsening severity of dementia, using a validated diagnostic method e.g. clinical dementia rating (CDR) scale (Morris 1993), dementia severity rating scale (DSRS) (Clark 1996).
Quality of life.
Direct costs of intervention.
Health utility change and cost effectiveness of intervention.
Activities of daily living.
Adverse outcomes (adverse medication outcomes, falls, new pressure ulcers, unplanned hospitalisation, mortality).
We will include the following outcomes in the final 'Summary of findings' tables:
Prevalence of delirium.
Incidence of delirium.
Severity of delirium.
Length of delirium episode.
Cognitive function, using any validated continuous scale.
Cost effectiveness of intervention.
Adverse outcomes.
Search methods for identification of studies
Electronic searches
We searched ALOIS (www.medicine.ox.ac.uk/alois) ‐ the Cochrane Dementia and Cognitive Improvement Group’s Specialised Register ‐ on 23 April 2013. The search was as sensitive as possible to identify all studies on ALOIS relating to delirium.
ALOIS is maintained by the Trials Search Co‐ordinator of the Cochrane Dementia and Cognitive Improvement Group and contains dementia and cognitive improvement studies identified from:
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Monthly searches of a number of major healthcare databases: MEDLINE, EMBASE, PsycINFO, CINAHL, and LILACS.
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Monthly searches of a number of trial registers: meta Register of Controlled Trials; Umin Japan Trial Register; WHO portal (which covers ClinicalTrials.gov; ISRCTN; Chinese Clinical trials Register; German Clinical trials register; Iranian Registry of Clinical trials; Netherlands National Trials Register, plus others).
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Quarterly search of the Central Register of Controlled Trials (CENTRAL) on The Cochrane Library.
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Monthly searches of a number of grey literature sources: ISI Web of Knowledge Conference Proceedings; Index to Theses; Australasian Digital Theses.
To view a list of all sources searched for ALOIS see About ALOIS on the ALOIS website.
We ran additional separate searches in Medline (OVID SP), EMBASE (OVID SP), PschInfo (OVID SP), CINAHL (EBSCO host), Web of Science and conference proceedings (Web of Knowledge), LILACS (BIREME), CENTRAL (The Cochrane Library), Clinicaltrials.gov (www.clinicaltrials.gov) and ICTRP Search Portal (apps.who.int/trialsearch) to ensure that the search was as comprehensive as possible. All search strategies and the number of hits retrieved can be viewed in Appendix 1.
Searching other resources
We checked the reference lists of all papers of included studies for further potentially eligible studies.
Data collection and analysis
Selection of studies
Two independent review authors (AC and AH) examined the titles and abstracts of citations identified by the search for eligibility, with any disagreements settled by consensus. We retrieved full‐text copies and two review authors (AC and AH) independently assessed them for inclusion on the basis of the stated eligibility criteria. We settled any disagreements by consensus.
Data extraction and management
Two review authors (AC and AH) independently extracted data from included trials using a piloted data extraction form, and settled any disagreements by consensus. We created Characteristics of included studies tables and summary of findings Table for the main comparison and summary of findings Table 2 using GRADEpro and Review Manager 5 software (RevMan 2012).
Assessment of risk of bias in included studies
Two review authors (AC and AH) independently assessed risks of bias using Cochrane criteria as described in the Cochrane Handbook for Systematic Reviews of Interventions (Cochrane 2011). We assessed included trials for adequacy of sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting and other potential sources of bias. For each domain, we made a judgement of low risk, high risk or unclear risk of bias. We settled any disagreements by consensus. We generated 'Risk of bias' summary figures using Review Manager 5 (RevMan) software (RevMan 2012).
Measures of treatment effect
We used risk ratios (RR) as measures of treatment effect for dichotomous outcomes. We used hazard ratios (HR) when time to event data were reported.
Unit of analysis issues
Both included trials were cluster‐randomised. Where the authors reported analyses which had adjusted for the effects of clustering, we extracted the adjusted effect measures (RR, HR) and their 95% confidence intervals (CIs) directly. If unadjusted analyses had been performed, we sought to calculate approximately correct analyses by extracting data on number of clusters, mean size of each cluster, primary outcome data and estimates of the intra‐cluster correlation coefficient (ICC). If an approximately correct analysis was not possible, then we extracted primary data and calculated risk ratios with 95% CIs.
Dealing with missing data
Where data were missing due to loss of participants or clusters from follow‐up, we recorded this with reasons where possible. We preferred Intention‐to‐treat data. If these were not available, we recorded per protocol data.
Assessment of heterogeneity
We anticipated that national and international models of LTC may lead to clinical heterogeneity. For example, in the UK residential homes and nursing homes comprise residents who have different levels of dependence and associated care needs. Furthermore, different interventions for preventing delirium in older people in long term care were likely to lead to methodological and statistical heterogeneity. For example, there may be heterogeneity between strategies targeting LTC residents or LTC facilities, or heterogeneity due to timing of the delirium prevention intervention.
We planned separate categorisation and analysis of non‐pharmacological/pharmacological single/multicomponent interventions to help address trial heterogeneity. Due to clear clinical heterogeneity (see Included studies), we did not conduct any meta‐analysis of the included trials.
Assessment of reporting biases
We sought clinical trial registration databases and trial protocols to assess potential reporting biases, and documented the funding source for all trials to assist the assessment.
Data synthesis
Where adjusted hazard ratios were presented, we analysed data using generic inverse variance methods, deploying natural logarithms of hazard ratios and associated standard errors. We did not perform a meta‐analysis because of clinical and methodological differences between the trials.
Subgroup analysis and investigation of heterogeneity
Sensitivity analysis
Results
Description of studies
See: Characteristics of included studies; Characteristics of excluded studies; Characteristics of ongoing studies.
Results of the search
The results of the search are outlined in a PRISMA diagram (Figure 1). We retrieved 15 full‐text studies, 13 of which we excluded (see Excluded studies), leaving two eligible for inclusion (see Included studies). One potentially eligible trial is ongoing (see Ongoing studies).
Study flow diagram.
Included studies
We include two trials that recruited 3636 participants (Culp 2003; Lapane 2011). Both trials were complex single‐component non‐pharmacological delirium prevention interventions.
The first trial (Culp 2003) was a cluster‐RCT of a four‐week hydration management intervention that recruited 98 residents across seven nursing homes in the United States. All residents were considered eligible for inclusion; those with acute confusion at baseline, terminal illness, uncontrolled diabetes, nasogastric or gastrostomy tube, severe renal failure, severe congestive heart failure, current urinary tract infection or serum sodium < 135 mEq/L were excluded. The intervention was a hydration management programme whereby an individual fluid intake goal was calculated according to participant body weight. Seventy‐five per cent of the fluid intake goal was delivered with meals, and the remaining 25% during non‐meal times. Nursing staff were instructed on the treatment regimen. A research assistant calculated the fluid goal and measured fluid intake randomly to ensure protocol compliance. No individual fluid intake goal was calculated for control arm participants. Follow‐up was at four weeks post‐randomisation.
The second trial (Lapane 2011) was a cluster‐RCT of the Geriatric Risk Assessment MedGuide (GRAM) software programme that included 3538 residents across 25 care homes in the United States. Medicare‐ and Medicaid‐certified nursing homes with contracts with Omnicare pharmacies, 50 or more geriatric beds and few short‐stay residents were considered for inclusion. All residents were considered eligible; individual resident consent was assessed as not required on the basis that the intervention involved a wholesale change in clinical and administrative practices at the nursing home. The GRAM was used to identify medications that may contribute to delirium and falls risk for individual residents. Pharmacy automatically generated a GRAM report within 24 hours of nursing home admission. For those identified as being on medication contributing to risk of delirium or falls, an automatic report was sent to the pharmacist to coincide with a monthly visit to the nursing home. A medication review was then undertaken at the visit and a proactive monitoring plan was initiated by the care‐home staff to assess for medication side effects. Control nursing homes did not receive the triggered pharmacist visit or proactive monitoring plan. All outcomes were recorded electronically by participating care‐home staff over a 12‐month period. The trial used resident months rather than individuals as its unit of outcome measurement. Results apply only to new admissions during 2004.
Excluded studies
We excluded 13 trials: 11 were not delirium prevention trials (Greendyke 1986; Hofferberth 1989; Mittal 2004; Moretti 2004; Ushijima 2008; Kim 2010; Overshott 2010; Pellfolk 2010; Tahir 2010; Grover 2011; Yoon 2011), with the focus either on delirium treatment or on health conditions other than delirium; two were not conducted in a long term care setting (Isaia 2009; Marcantonio 2010).
Risk of bias in included studies
Our assessment of risk of bias in the two included trials is presented in the 'Characteristics of included studies' table and is summarised here in the text and in Figure 2. Neither trial was assessed as being at low risk of methodological bias across all domains. Notably, there was no evidence of blinding of trial participants or assessors in either trial. Risk of bias for many domains was unclear because insufficient information was reported.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Allocation
Neither trial reported sufficient information on sequence generation or allocation concealment, so risk of selection bias was assessed as unclear.
Blinding
There was no evidence of participant or assessor blinding in either trial, so both were assessed as being at high risk of bias. Culp 2003 reported that the study was not blinded and members of the research team who were not blind to allocation completed outcome assessments. Similarly, Lapane 2011 reported that participants and personnel were aware of allocated intervention. The minimum data set (MDS) was used for outcome data and was completed by care staff with knowledge of allocation.
Incomplete outcome data
Culp 2003 did not report information on losses to follow‐up and did not perform an intention‐to‐treat analysis, so was assessed as being at high risk of attrition bias. Lapane 2011 did not report an intention‐to‐treat analysis, so risk of attrition bias was assessed as unclear.
Selective reporting
There was no evidence of selective outcome reporting in either trial, so both were assessed as being at low risk of reporting bias.
Other potential sources of bias
Culp 2003 reported that staff alerted researchers to change in cognition, so identification of delirium was partly dependent on staff knowledge. The nursing facility director recommended which unit should be used in the study, which may have introduced further potential for bias. There was a significantly higher baseline blood urea nitrogen (BUN):creatinine ratio in the intervention group, indicating that this group were more dehydrated at baseline and results were not adjusted to account for this. No adjustments were made for the potential effects of clustering. There may have been potential for between‐cluster contamination of the relatively simple hydration‐based intervention, and measures to prevent this were not reported by the investigators. On the basis of these additional considerations, Culp 2003 was assessed as being at high risk of bias in this domain.
Lapane 2011 reported that only one cluster was lost and Poisson regression was used to account for the cluster design. This trial was therefore assessed as being at low risk of bias for this domain.
Effects of interventions
See: Summary of findings for the main comparison Single‐component medication monitoring and adjustment intervention versus control for preventing delirium in older people in institutional long term care; Summary of findings 2 Single‐component hydration intervention versus control for preventing delirium in older people in institutional long term care
Primary outcomes
Both trials reported data on one of the primary outcome measures, incidence of delirium. Culp 2003 reported no effect of a hydration‐based intervention on delirium incidence (risk ratio (RR) 0.85, 95% confidence interval (CI) 0.18 to 4.00). No adjustment was made for the effects of clustering and it was not possible to calculate an approximately correct analysis due to limitations in data reporting.
Lapane 2011 reported that the introduction of the intervention (GRAM report, pharmacist‐led medication review and subsequent proactive monitoring plan) was associated with a significant reduction in delirium incidence, compared to control (12‐month hazard ratio (HR) 0.42, CI 0.34 to 0.51). Adjustments were made for the effects of clustering. No data were reported on the other primary outcomes.
Secondary outcomes
Culp 2003 did not report data for any of the secondary outcomes. Lapane 2011 reported adjusted analyses for additional outcomes of unplanned hospitalisation, mortality and falls. There was no clear evidence of reduction in unplanned hospitalisation (HR 0.89, CI 0.72 to 1.10), in mortality (HR 0.88, CI 0.66 to 1.17) or in falls (HR 1.03, CI 0.92 to 1.15). Neither study reported data on direct costs or cost effectiveness of the interventions.
Clear intervention heterogeneity precluded synthesis of data for meta‐analysis. Limitations of data reporting precluded subgroup analysis for participants with and without dementia.
Discussion
Summary of main results
Our review has identified two randomised controlled trials (RCTs) of delirium prevention interventions for older people in institutional long term care, recruiting 3636 participants. One small cluster‐RCT (n = 98) of a hydration‐based intervention reported no reduction in delirium incidence in the intervention group compared to control. Results were imprecise, not adjusted for the effects of clustering and with serious limitations evident in trial design. Importantly, the investigators reported that both intervention and control groups were consuming approximately the same volume of fluids over the follow‐up period, but only 51% of intervention participants had 90% or greater compliance with the fluid goal. Previous research has identified that many LTC residents do not consume adequate fluid (Armstrong‐Esther 1996) and this result may indicate that achieving target fluid intake in care‐home residents is challenging, even in the context of a clinical trial.
One large cluster‐RCT (n = 3538) of a computerised system to identify medications that may contribute to delirium risk and trigger a pharmacist‐led medication review reported a large reduction in delirium incidence but no clear evidence of reductions in hospital admissions, mortality or falls. Although the analysis was adjusted for the effects of clustering, there were limitations evident in trial design, notably an absence of either participant or assessor blinding.
Overall completeness and applicability of evidence
The very small number of included trials identify a limited body of evidence on the effectiveness of interventions for preventing delirium in older people in institutionalised long term care. We identified only two single‐component non‐pharmacological interventions with methodological limitations. We did not find any multicomponent non‐pharmacological delirium prevention interventions or pharmacological delirium prevention interventions for this population. Both trials were conducted in the United States and international differences in the organisation of long term care mean that the results may not be directly applicable to other settings.
Quality of the evidence
We used GRADEpro software to inform the generation of evidence quality statements.
On the basis of one large RCT there is moderate‐quality evidence that a single component medication monitoring and adjustment intervention may reduce the incidence of delirium in older people in institutional LTC (see summary of findings Table for the main comparison). Notably, personnel, participants and outcome assessors were not blinded in this trial.
On the basis of one large RCT there is moderate‐quality evidence that a single component medication monitoring and adjustment intervention does not appear to be associated with reduced hospitalisation, mortality or falls for older people in institutional LTC (summary of findings Table for the main comparison). Notably, personnel, participants and outcome assessors were not blinded in this trial.
On the basis of a single RCT with serious limitations in trial design and very imprecise results, there is very low‐quality evidence on the effectiveness of hydration‐based interventions for reducing the incidence of delirium in older people in institutional LTC. It is therefore not possible to draw firm conclusions about this intervention (summary of findings Table 2).
Potential biases in the review process
This review has followed Cochrane procedures and there were only a small number of minor amendments to the review protocol following initial publication. The very small number of included trials precluded an accurate assessment of consistency of results or a statistical assessment of reporting bias.
Agreements and disagreements with other studies or reviews
To our knowledge there are no previous systematic reviews on the effectiveness of delirium prevention interventions for older people in institutional long term care.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Comparison 1 Single component hydration intervention versus control, Outcome 1 Incidence of delirium.
Comparison 2 Single component medication monitoring and adjustment intervention versus control, Outcome 1 Incidence of delirium.
Comparison 2 Single component medication monitoring and adjustment intervention versus control, Outcome 2 Unplanned hospitalisation.
Comparison 2 Single component medication monitoring and adjustment intervention versus control, Outcome 3 Mortality.
Comparison 2 Single component medication monitoring and adjustment intervention versus control, Outcome 4 Falls.
| Single‐component medication monitoring and adjustment intervention versus control for preventing delirium in older people in institutional long term care | ||||||
| Patient or population: People at risk of delirium in institutional long term care | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No of resident months | Quality of the evidence | Comments | |
| Assumed risk | Corresponding risk | |||||
| Control | Single‐component medication monitoring and adjustment intervention versus control | |||||
| Incidence of delirium1 | Study population | HR 0.42 | 7311 | ⊕⊕⊕⊝ | ||
| 104 per 1000 | 45 per 1000 | |||||
| Medium risk population | ||||||
| 99 per 1000 | 43 per 1000 | |||||
| Unplanned hospitalisation1 | Study population | HR 0.89 | 7599 | ⊕⊕⊕⊝ | ||
| 55 per 1000 | 49 per 1000 | |||||
| Medium risk population | ||||||
| 57 per 1000 | 51 per 1000 | |||||
| Mortality1 | Study population | HR 0.88 | 9412 | ⊕⊕⊕⊝ | ||
| 25 per 1000 | 22 per 1000 | |||||
| Medium risk population | ||||||
| 25 per 1000 | 22 per 1000 | |||||
| Falls1 | Study population | RR 1.03 | 2275 | ⊕⊕⊕⊝ | ||
| 523 per 1000 | 539 per 1000 | |||||
| Medium risk population | ||||||
| 523 per 1000 | 539 per 1000 | |||||
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| 1Assumed risk based on control group risk in included study. | ||||||
| Single‐component hydration intervention versus control for preventing delirium in older people in institutional long term care | ||||||
| Patient or population: People at risk of delirium in institutional long term care | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | No of Participants | Quality of the evidence | Comments | |
| Assumed risk | Corresponding risk | |||||
| Control | Single‐component hydration intervention versus control | |||||
| Incidence of delirium1 | Study population | RR 0.85 | 98 | ⊕⊝⊝⊝ | ||
| 67 per 1000 | 57 per 1000 | |||||
| Medium risk population | ||||||
| 67 per 1000 | 57 per 1000 | |||||
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| 1Assumed risk based on control group risk in included study. | ||||||
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 1 Incidence of delirium Show forest plot | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 1 Incidence of delirium Show forest plot | 1 | Hazard Ratio (Random, 95% CI) | Subtotals only | |
| 2 Unplanned hospitalisation Show forest plot | 1 | Hazard Ratio (Random, 95% CI) | Subtotals only | |
| 3 Mortality Show forest plot | 1 | Hazard Ratio (Random, 95% CI) | Subtotals only | |
| 4 Falls Show forest plot | 1 | Hazard Ratio (Random, 95% CI) | Subtotals only | |
