Delirium is a sudden acute mental change accompanying acute illness. Characterized by disturbances of consciousness, attention, cognition, psychomotor behavior and emotions [1, 2], it affects 10 to 60% of all patients treated in medical, surgical, medical-surgical mixed or general wards [3–5], and up to 80% of those treated in intensive care units (ICUs) [3, 6–10]. More than two dozen predisposing and precipitating delirium risk factors have been identified, including male gender, older age (> 65 years), prior delirium, co-morbidities (i.e., dementia, depression) and severe illness [3, 11–13].

Delirium is linked to negative patient and institutional outcomes including prolonged ICU and hospital length of stay (LOS) [7, 14–17], higher mortality rates [14, 16, 18–20], cognitive decline or impaired cognitive functions [20–23], restrictions in motor functionality [23, 24], ongoing need for care in long-term care institutions [14, 15] and a higher likelihood of discharge to destinations other than home [23, 25].

From an economic perspective, delirium is strongly associated with additional healthcare costs [17]. In the United States (US), annual additional delirium-related healthcare costs are estimated to range from 6.6 to 20.4 billion USD (mean: 9014 USD per case) in ICU patients [26] and 38 to 152 billion USD per year in non-ICU patients aged 70 years and older (range: 16,303 to 64,421 USD per case) [27].

The large number of patients affected by delirium during hospitalization, the negative clinical outcomes, and the severe economic consequences all call for action. In recent years, several delirium management guidelines and / or standardized programs were developed for the prevention, early recognition, and / or treatment of delirium across all hospital departments [28–32]. The results indicate that multicomponent delirium management guidelines or programs are most efficient to reduce the delirium rates and the delirium-linked negative outcomes, i.e., decreasing LOS and institutionalization [31, 33, 34].

In 2012, in response to the delirium burden at the study hospital –a Swiss university hospital–the multi-professional Delir-Path (Detect Evaluate Control Inpatient Risk factors, Prevent And Treat Hospital Acquired Deliriums) project was started. It includes a practice development part and a health service research (HSR) part.

Delir-Path has five primary purposes: 1) to develop a standardized multi-professional, multicomponent delirium management guideline for the prevention, early recognition and treatment of delirium; 2) to implement the delirium management guideline throughout the study hospital and to monitor and evaluate the implementation process based on defined outcomes; 3) to evaluate the effectiveness, efficiency, and benefits of the implemented multiprofessional delirium management protocol, both as a whole and as single components, e.g., pharmacological delirium treatment; 4) to develop and implement a system for monitoring delirium incidence rates and the courses of the underlying diseases (duration); 5) to develop and establish a multicenter, multiprofessional Health Care Service Research Program for effective, efficient and cost-effective delirium management.

As a first step in a form of a pilot study an interprofessional multicomponent delirium management guideline was developed. The developed guideline contains interventions for delirium prevention, risk stratification, screening and diagnostics, non-pharmacological and pharmacological treatment, as well as a multi-professional training program (see Additional file 1). The guideline was implemented on nine surgical and neurological wards and ICUs and its benefits evaluated [35, 36]. Based on that pilot’s promising results, the standardized delirium management guideline was adapted and implemented hospital-wide in 2013 / 2014 [35, 36]. Concurrently, the HSR program was developed further. In the study hospital, as of April 2018, this includes a main study, more than 10 sub-studies [6, 36–43]. Furthermore, the program includes a multicenter study in ICU settings. This study refers to the main study, which uses a longitudinal cohort design.

To date, delirium management programs and / or delirium bundles and related research have focused on the best-known high delirium risk patient groups – predominately ICU, cardiac and orthopaedic patients [3]. A small number have also focused on medical and / are palliative care groups [44, 45]. However, the literature shows no delirium management programs implemented, e.g., for haemato-oncological patients, although, based on the typical courses of their conditions, fulfil the criteria for a high delirium risk [46].

Because significant risk groups may remain undetected, the Delir-Path main study included an entire university hospital cohort of acute care patients. This allowed us to study both delirium’s prevalence and the effect of the implemented guideline across acute care patient groups.

Of all eligible adult patients hospitalized in 2014, almost a third was identified as at risk for delirium and screened accordingly. Of those screened, nearly one-third yielded a DOS and / or ICDSC score indicating a delirium. In accordance with available evidence, delirium was more frequent in males and patients hospitalized for cardiac surgery [3, 6, 59, 60], neurosurgery, traumatology, radiotherapy, and neurological care, with period-prevalences from 36.2 to 40.5%. Elsewhere, with period-prevalence’s ranging from 21.6 to 28.6%, delirium also occurred frequently in patients treated in geriatric and internal / general medicine, as well as in visceral surgery. Similar prevalences were found in patients recovering from visceral surgery, reconstructive plastic surgery, cranio-maxillo-facial surgery, and oral surgery. This new finding underscores the importance of a standard delirium management guideline for use across patient groups.

The comparison of the delirium point-prevalence rate by ICD-10 diagnosis chapter and the presence of delirium in patients within and between groups partly reflected these rates. Delirious states were most frequent in patients with main diagnoses referring to the ICD-10 chapters on mental / behavioral disorders, infections, injuries, poisoning, or diseases of the nervous, circulatory, digestive, blood and endocrine /nutritional /metabolic systems. The high prevalence of delirious states in patients with diagnoses related to Chapter V (mental / ‘behavioral disorders) can be explained by that chapter’s direct focus on psychiatric disorders. The other diagnosis chapters refer to diseases such as infections or abnormal laboratory values, e.g., abnormal creatinine, serum sodium, glucose or potassium levels and metabolic acidosis, which are known precipitating factors of delirium [11, 61, 62].

Our subgroup analysis by ICD-10 diagnosis chapter indicated not only that delirious patients were significantly more likely to die, but that they required roughly twice most non-delirious groups’ nursing hours, ICU days, hospital stay, and overall financial expenditure per case. The one exception was the category of non-delirious patients with infections and respiratory diseases, whose ICU stays were not significantly lower (Table 2). These demonstrated negative outcomes in patients with delirium correspond with recent findings of significant differences between delirious and non-delirious patients’ mortality rates [14, 19, 63–65], ICU LOS [14, 16, 19, 66, 67], hospital LOS [14, 16, 17, 19, 66, 67], nursing hours per case [68] and total cost [17, 26, 67]. The demonstrated variation in these outcomes regarding the seven top ICD-10 diagnosis groups adds to the current evidence. Such marked differences between main outcomes suggest that group-specific characteristics and risk factors influence delirium-related outcomes and consequences. Still, it remains unclear whether delirium contributes to poorer outcomes, impacts the underlying illness’s trajectory [69], or simply indicates greater disease severity.

As our results show, compared to non-delirious patients, those with delirium were more often admitted from other hospitals and less frequently discharged home. In addition, they were treated in the ICU more frequently (table1). This suggests that, compared to their non-delirious counterparts, the delirious were more seriously ill or had more exacerbated functional health status impairment. Since serious disease and functional impairment are known predictors of delirium [3, 11, 12], despite controlling for all known confounders in the first set of models, which we run for the comparison of the non-delirious and delirious patients, we cannot exclude the possibility that these factors contributed to the outcome differences discussed above.

This study has a number of notable strengths and limitations. One strength is that its analyses covered all eligible patients treated in the study hospital over one full calendar year. The sample included a broad range of surgical, medical, and mixed surgical-medical patient groups – several of which, to our knowledge, were studied for the first time in this context. Two analyses were particularly important: that of the patient subgroup identified as at risk for delirium; and, within this group, the separate analysis of only the older at-risk patients by ICD-10 main diagnosis chapter. Both provided important insights regarding the occurrence of delirium in diverse subgroups. Limitations include an observational design and the inclusion of only a single center, both of which limit the generalizability of the results and allow no inferences regarding causal relations. Another limitation is that our chosen approach to identifying delirious patients – classing a patient as delirious if he/she had at least once an DOS score ≥ 3 and / or a ICDSC score of ≥4 - might have been too sensitive, i.e., it might have led to delirium rate overestimation. Further, the use of existing clinical data restricted both the number of variables and the overall adequacy of the dataset regarding our needs. This and the large sample size, for example, made a precise calculation of delirium intensity and duration unfeasible. Finally, in the study hospital, roughly 2′000 clinicians participated in delirium screening. Although these clinicians’ delirium training covered interrater reliability, a smaller research team may have yielded more reliable assessment results. I.e., while the use of validated screening tools ensured that detection of patients with delirium was reliable within acceptable tolerances. Further studies, ideally of a prospective nature, will be necessary to confirm our findings.

The results reported here indicate not only high numbers of patients identified as at risk for a delirium but also high delirium prevalence across most patient groups. This underscores the relevance of this topic and the need for systematic delirium management to prevent, recognize, and treat delirium across patient groups.

In both the unadjusted and adjusted models, compared to the patients without delirium, delirious patients’ ≥ 65 year had a significantly higher mortality rate and longer ICU and hospital LOS. They also required more nursing hours and generated much higher cost per case. In the subgroup analysis conducted by ICD-10 diagnosis chapter, for the unadjusted models, each diagnostic group’s delirious patients had worse outcomes compared to those with no delirium. However, considering that, as discussed above, the current study cannot indicate causality, is it essential to test these findings with a study design that allows causal inferences.

Our subgroup analyses highlighted striking variations in delirium period-prevalence across patient groups. Several of these differences, e.g., the frequent occurrence of delirium in cardiac surgery or geriatric patients, support previous findings. One new finding – which requires further attention – is the high prevalence of delirium in radiotherapy, visceral surgery, reconstructive plastic surgery, and cranio-maxillo-facial or oral surgery patients – all groups who have thus far fallen either outside or only marginally within the scope of clinical delirium management.

In the subgroup analysis according to the ICD-10 diagnosis chapters, patient diagnoses referring to known delirium precipitating factors, e.g., infection/parasites, injury, poisoning, or endocrine /nutritional /metabolic diseases, were linked with elevated delirium prevalence. Therefore, in addition to patients currently in the focus of standard delirium management (i.e., ICU, cardiac and orthopaedic patients), it is recommended to expand that focus to include those treated in care centers for radiotherapy, visceral surgery, reconstructive plastic surgery, cranio-maxillo-facial and oral surgery.

Finally, the used approach described above to identify patients at risk for a delirium, timely screening, detection and identification of delirious patients can easily be added to standard clinical practice. From a scientific perspective, this approach allows quick classification of patients into three groups with significant and clinically relevant outcomes: (1) those not at risk, for whom delirium screening is unnecessary; (2) those at risk and screened, who do not develop a delirious state; and (3) those at risk and screened and who develop a delirious state.