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ISRN Stroke
Volume 2013 (2013), Article ID 620186, 7 pages
http://dx.doi.org/10.1155/2013/620186
Research Article

Delirium in Acute Stroke: A Survey of Screening and Diagnostic Practice in Scotland

1School of Health Sciences, Queen Margaret University, Queen Margaret University Drive, Edinburgh EH21 6UU, UK
2Institute for Applied Health Research and School of Health and Life Sciences, Glasgow Caledonian University, Cowcaddens Road, Glasgow G0 4BA, UK
3Geriatric Medicine, Clinical and Surgical Sciences, The University of Edinburgh, Room S1642, Royal Infirmary of Edinburgh, Little France Crescent, Edinburgh EH16 4SA, UK

Received 5 June 2013; Accepted 16 July 2013

Academic Editors: R. P. Kessels, P. A. Nyquist, and J. Van Der Grond

Copyright © 2013 Gail Carin-Levy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aims. To survey the use of delirium screening and diagnostic tools in patients with acute stroke across Scotland and to establish whether doctors and nurses felt the tools used were suitable for stroke patients. Methods. An invitation to participate in a web-based survey was e-mailed to 217 doctors and nurses working in acute stroke across Scotland. Descriptive statistics were used to report nominal data, and content analysis was used to interpret free text responses. Results. Sixty-five responses were logged (30% return rate). 48% of the respondents reported that they routinely screened newly admitted patients for delirium. Following initial screening, 38% reported that they screened for delirium as the need arises. 43% reported using clinical judgment to diagnose delirium, and 32% stated that they combined clinical judgment with a standardised tool. 28% of the clinicians reported that they used the Confusion Assessment Method; however, only 13.5% felt that it was suitable for stroke patients. Conclusions. Screening for delirium is inconsistent in Scottish stroke services, and there is uncertainty regarding the suitability of screening tools with stroke patients. As the importance of early identification of delirium on stroke outcomes is articulated in recent publications, validating a screening tool to detect delirium in acute stroke is recommended.

1. Introduction

Delirium is a common neuropsychiatric condition affecting 20–30% of elderly patients across most hospital settings [1]. In acute stroke, the incidence of delirium reported by individual studies ranges from 10% [2] to 48% [3], and meta analyses recently performed placed the incidence around 26%–28% [4, 5]. Delirium is associated with increased mortality, morbidity, and length of hospital stay [58], and it has been strongly associated with development of cognitive impairment in the long term in the general medical setting [9, 10]. In acute stroke, recent studies have clearly demonstrated that patients who develop delirium are more likely to die within 12 months, have poorer functional outcomes, and are at higher risk of developing dementia [4, 5, 11, 12]. There are calls in the literature for clinicians to place an emphasis on early identification of delirium in stroke patients, using a tool validated specifically for this population, as early intervention may minimise the aforementioned unfavourable outcomes [5, 13, 14]. The most recent guidance published in the United Kingdom (UK) by both the National Institute for Health and Clinical Excellence (NICE) and the Royal College of Physicians (RCP) do not mention delirium as a specific complication of stroke [15, 16]; however, both refer to cognitive impairment and inattention. The word “confusion” is mentioned in the Scottish Intercollegiate Guidelines Network document “Management of Patients with Stroke” (SIGN 118), but there is no specific guidance about how to screen for or manage this “confusion” [17]. Clinical guidelines from other English speaking countries were examined for comparison: Australian guidelines [18] do not mention delirium in stroke patients; American Heart Association (AHA) guidelines mention delirium in the context of screening for psychiatric sequelae to stroke in the end of life care [19]; Canadian guidelines were the most detailed, and they contained a clear message about the importance of delirium as a complication in acute stroke. This was discussed in relation to screening for cognitive impairment or a change in cognitive function, and there is a clear call to screen patients at risk, using a validated screening tool [20]. Screening for delirium in other clinical settings is considered important across several countries. Clinical guidelines published in the UK [7], United States of America [21], Australia [22], and Canada [23] all guide clinicians to screen for delirium in services which are known to have a high prevalence of the condition. This is in order to ensure that delirium is not missed or misdiagnosed and thus to decrease the length of hospital stay and the unfavourable outcomes and ultimately generate cost savings for the organization [7, 23]. As for the method of diagnosis, the UK and Canadian documents specifically recommend the use of the Confusion Assessment Method (CAM) [24] as the diagnostic tool of choice.

2. Description of Screening/Diagnostic Tools

Our systematic review [4] identified a number of tools commonly mentioned in the literature; however, the most frequently cited are the Delirium Rating Scale (DRS) [25] and the CAM [24], both of which are based on the American Psychiatric Association diagnostic and statistical manual (DSM) criteria and designed to identify delirium across a variety of medical settings. The DRS was designed to be used by medical staff with specific training [25]. It comprises of 10 items, the highest possible score is 32, with a cut-off score of ten indicating the presence of delirium, thus it is a useful tool to rate the severity of delirium [13]. The CAM comprised four features (acute onset, fluctuating course, and inattention with either disorganised thinking or altered level of consciousness); it was originally developed for use by any health professional, and it has high sensitivity, specificity, and reliability and is easy to administer [24]. Other tools mentioned in the literature are the mini mental state examination (MMSE) [26]: it is a screening test for cognitive impairment and not specifically designed for the detection of delirium [27]; nonetheless, it seems to be used in some studies as a means of identifying delirium in a stroke patient [4]. Levkoff et al. [27] provide a useful review of instruments available for the detection of delirium in hospital patients.

In summary, a variety of screening and diagnostic tools for the detection of delirium exist; screening for delirium is important in a variety of settings, but there is no clear guidance about how, when, and how often to screen patients for delirium after stroke. Although studies of delirium in acute stroke describe how delirium is identified [4], it is unclear what happens in clinical practice; namely, how delirium is identified and diagnosed and by whom. The literature from the general medical/geriatric settings gives an indication that, in practice, delirium is under-recognised, and staff do not routinely use screening tools in daily practice [28, 29].

The aims of this web-based survey were to investigate the use of delirium screening and diagnostic tools in patients with acute stroke. We sought to identify whether and if so, how doctors and nurses across Scotland screen for and diagnose delirium in acute stroke.

The survey explored the following questions: (i)Is delirium screened for in routine clinical practice? (ii)How often does screening for delirium in acute stroke take place and what is the method of screening and or diagnosis in clinical practice? (iii)Who is most likely to identify delirium in acute stroke? (iv)Which delirium identification tools (if any) are used?(v)What are clinicians’ views about the suitability of screening tools as they are used within acute stroke care?

3. Methods

3.1. Survey Questionnaire

The Bristol Online Survey Tool was used to set up, collect, and subsequently analyse the survey data. This tool is widely used by universities and other public bodies in the UK [30]. Web surveys are inexpensive; they increase the ease of administration for the research team and allow data to be analysed as soon as it is logged on the online survey tool [31]. Web-based surveys yield the same findings as paper surveys in terms of content [32, 33] although online surveys may yield a slightly lower response rate [34]. We attempted to maximise response by keeping the length of the survey as short as possible, maintaining a clear structure, and using clear language [34]. A scrolling design (rather than the questions set over several webpages) was chosen to maximise ease of use and minimise potential technical difficulties. This design is reputed to increase response rate as it reduces the time taken to complete the survey [35]. Survey questions were constructed based on published guidance on effective question writing [36] and effective design for web-based response options such as minimising “drop down boxes” as they are burdensome to respondents [37]. Following questionnaire development, the survey tool was distributed to three clinicians: a stroke physician, a stroke nurse specialist, and a psychiatrist. This process was used to check for language, structure, and sequence of the questions presented [38], but no data were collected during this process. Two minor difficulties related to the ambiguity of questions were identified and rectified prior to the survey being distributed among stroke clinicians practising throughout Scotland.

3.2. Sample and Recruitment

The survey was distributed to 217 clinicians (doctors and nurses) working in the acute stroke setting in Scotland by the administrators of the British Association of Stroke Physicians (BASP) and the Scottish Stroke Research Network (SSRN), and the first author contacted all ( ) members of the Scottish Stroke Nurses Forum (SSNF) directly. The first author cross checked the complete distribution lists of SSRN and SSNF and removed duplicate names and email addresses. The BASP database was not shared with the first author; therefore, it was not possible to check for duplicates with other databases, and we were informed by the administrator that the approximate number of BASP members in Scotland is 60. The initial invitations were sent by email in July 2012. Two further email reminders were sent two weeks apart, in August 2012. In order to be able to calculate response rate as accurately as possible, respondents were asked not to disseminate the email invitation among their colleagues.

3.3. Data Analysis

Descriptive statistics were used to report nominal data. Free text comments were analysed by the first author using qualitative content analysis methodology: the first author read and reread the words used in the responses and then classified them into small sets of categories or codes of shared meaning. The codes were counted to determine how frequently they appear within the text responses and patterns relating to the key themes emerged [3941]. Data regarding size of stroke unit and number of stroke beds of all hospitals across Scotland were obtained via Information Service Division Scotland [42]; these are presented in Table 1 to categorise respondent characteristics.

tab1
Table 1: Respondent characteristics.
3.4. Ethics

This study did not require ethical approval as it an opinion survey seeking the views of NHS staff on service delivery. A letter of confirmation was obtained from the South East Scotland Research Ethics Service. Ethical approval was gained from Queen Margaret University.

4. Results

Sixty-five (30%) responses were received following an initial email and two reminders. A total of 36/90 (40%) of doctors replied; 29/127 (23%) of nurses replied. The characteristics of the respondents are summarised in Table 1.

4.1. Screening for Delirium

In response to the question: “Does your ward have a policy on screening new patients for delirium?”, 21/65 (32%) respondents selected “yes,” 35 respondents (53.5%) replied “no,” and 9 respondents (14%) responded “unsure.” In response to the question: “Do you routinely screen for delirium on admitting new patients to the ward?,” 31(48%) selected “yes” and 34 (52%) selected “no.” The following question: “Do you screen patients for delirium on a regular basis during admission?” yielded the same result, with 31 (48%) selecting “yes” and 34 (52%) selecting “no.” Of the 31 respondents who selected “yes,” 25 (81%) reported screening “as the need arises”; two (6.5%) selected “once weekly”; and four (13%) selected “other” and provided a short text explanation: two respondents stated that screening occurred during ward rounds or if a concern is raised by a staff member. One respondent stated that they screened daily, and, one respondent stated that they screened on admission (which answers the original question: “Do you routinely screen for delirium on admitting new patients to the ward?”).

4.2. Diagnostic Methods

In response to the question: “How do you normally diagnose delirium in stroke patients?,” 28 respondents (43%) reported applying their clinical judgement, two respondents (3%) reported using a standardised tool, and the remaining respondents reported combining clinical judgement with the application of a standardised tool ( , 32.3%). Two respondents selected “other”: one reported using “AMT (abbreviated mental test) and urine testing and observations” and the other reported using the CAM [24] to diagnose delirium. Twelve respondents (18.5%), all of whom were nurses, stated that they do not diagnose delirium in their practice and selected the option “I have not been trained to use a standardised tool”. Table 2 summarises these results.

tab2
Table 2: Questions regarding diagnostic practices and tools utilised.
4.3. Clinicians’ Choice of Diagnostic Tool

Table 2 outlines the structure of the questions relating to the choice of diagnostic tool. Free text comments made in response to the question on clinicians’ choice of diagnostic tool revealed that six (9%) respondents used a tool developed by a local collaboration between Liaison Psychiatry and Geriatrics known as “4AT” [43]. Four respondents reported using either the abbreviated mental test (AMT) [44] or the MMSE [26].

4.4. Suitability of the Diagnostic Tool in a Stroke Population

Respondents were asked “Do you think the tool you use is suitable for a stroke population?.” A total of 52 (80%) of the 65 respondents answered this question. Seven respondents selected “yes” (13.5%), 16 respondents selected “no” (31%), and the remaining 29 selected “not sure” (56%). Figure 1 cross-references those who selected their tool of choice with clinicians’ opinion regarding suitability for stroke patients. 15 (23%) participants gave free text comments. The majority ( ; 53%) of comments related to the difficulty using a generic screening tool with persons who experience communication difficulties such as receptive or expressive aphasia. Four respondents questioned the validity of the tool in a stroke population and discussed in particular cognitive or “neurological abnormalities” arising from the stroke. One respondent felt that the tool they used had “reasonable face validity,” and one further respondent advocated the use of the CAM [24].

620186.fig.001
Figure 1: Is the tool you use suitable for use in stroke patients?

5. Discussion

Our survey results highlight a number of key findings that reveal current delirium diagnostic and screening practice in Scottish stroke services. Most stroke units either did not have a screening policy for the identification of delirium in acute stroke, or the clinicians were unaware of such policy. Almost half of respondents to this survey stated that they did not routinely screen for delirium in acute stroke. The diagnosis of delirium was reportedly made mainly by doctors, in most cases by means of clinical judgement and in some cases combined with the use of a standardised tool. Interestingly, the majority (41%) of nurses who responded to this survey ( ) claimed that they do not diagnose delirium in their practice, citing lack of training to use a standardised tool as the main reason for this. This finding supports the findings of a survey of nurses across intensive care and general medical/surgical units which highlights that nurses have only modest confidence levels in identifying delirium in clinical practice [45]. Other authors have reported infrequent use of standardised tools for the screening and/or diagnosis of delirium: nurses reportedly rely largely on clinical judgement when it comes to diagnosing delirium. In these studies, the clinicians surveyed had recognised the importance of delirium as an underdiagnosed condition of potentially serious consequences; however, routine screening and utilisation of standardised observation tools were still the exceptions in a variety of studies [4547]. Surveys of doctors highlight similar concerns. A survey of Brazilian critical care physicians found that less than 15% of respondents used validated delirium assessment tools [48]. An American survey of ICU clinicians found that despite the belief that the literature supported routine screening for delirium, only 40% of respondents did so, and of those, only a small number used specific delirium screening tools [49]. Furthermore, a finding from a survey of junior doctors working in a variety of medical settings in the UK revealed that the fundamental cause of under-recognition and undertreatment of delirium lies in the lack of knowledge of the diagnostic criteria and standardised screening tools [50].

Within our own survey, a small number of respondents reported using a variety of tools to diagnose delirium in their practice, citing tools which have not been validated for the use in acute stroke [26, 43]. Some studies found a degree of usefulness in detecting cognitive changes using the AMT [44] and the MMSE [26] which might be due to delirium [5153]; however, these tools are not specifically designed to detect delirium [27, 49, 54]. Some of our respondents reported difficulties in using diagnostic tools in stroke patients because of aphasia. Our systematic review highlights that previous studies have excluded patients with aphasia from their cohorts for the same reason [4]. In our survey, only two respondents reported using the CAM-ICU, which might increase the proportion of patients with language difficulties who may be assessable [55] as the CAM-ICU does not rely on language for the diagnosis of delirium [49, 56]. This tool has recently been validated for use in stroke patients, demonstrating high sensitivity, specificity, overall accuracy, and inter-rater reliability [14, 57]. Various authors, in both nursing and medical literature are calling for clinicians to take a key role in the identification of delirium in practice, advocating the use of validated instruments to facilitate accurate and timely recognition, leading to prompt treatment and better outcomes for patients [5, 14, 28, 58].

Our response rate was 30%, a rate lower than a number of surveys (both online and traditional) of delirium identification published within the last five years [4648, 50]. Our response rate seems to be influenced by the notable difference between doctors and nurses response to our invitation to participate: only 23% of nurses approached actually completed the survey. Eley et al. [59] identified the main barrier to nurses’ access to computers in the ward environment as lack of time due to other demands of the job. This may be a reason why the response rate from the nurses in this survey was comparatively low.

6. Strengths, Limitations, and Future Research

We were keen to explore practice within Scotland only at this stage, and we would plan to roll out the same survey throughout the UK. Our response rate was moderate but consistent with the literature on online surveys return rates [34, 60]. Other surveys examining delirium identification utilised a variety of methods of survey distribution which yielded better response rates, for example, using a combined approach of both paper and online options [47] or using the traditional postal questionnaire design [46, 50]. We were keen to be able to calculate our response rate; therefore, we used convenience sampling and approached specific individuals in the clinical field and avoided snowballing, but this may have introduced a selection bias. Nevertheless, our data are of interest because this is, to the best of our knowledge, the first survey of diagnostic and screening practice in relation to delirium in acute stroke services in the UK. Our survey contributes to a growing body of knowledge on delirium in acute stroke. This field of research is steadily growing as more publications are generated on the various aspects of identification [14, 52] and potential treatment [61, 62] of the condition.

It was interesting to note the inconsistent screening and diagnostic practice identified by this survey, which is perhaps related to the lack of guidance or policy regarding screening and diagnosis of delirium in stroke. It would be beneficial for UK best practice guidelines in stroke care [15, 17] to incorporate information on delirium and perhaps consider establishing a standardised way of identifying the condition in this population. This would require further research to be conducted, not only to validate a tool to detect delirium in stroke patients, but also to establish the most effective time intervals for screening patients. Another avenue for further research is to identify the barriers to regular and effective screening for delirium across all members of the multidisciplinary team. In light of the fact that both this survey and others have identified the need for training and increasing awareness of delirium among staff working with stroke patients, we would like to reiterate the importance of this and call for more staff to become familiar with the risk factors and outcomes associated with delirium. Increasing the amount of correctly identified cases of delirium may lead to better outcomes for these patients and may yield cost benefits to the organisation [7].

Acknowledgment

The authors declare that they have no conflict of interests. This project received no external funding; however, it forms part of Ms Carin-Levy’s Doctoral studies which are funded by Queen Margaret University, Edinburgh.

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