Arif Nazir, MD

Under the Patient Protection and Affordable Care Act of 2010, commonly referred to as the Affordable Care Act, hospitals face up to a 3% penalty in Medicare reimbursements for patients readmitted within 30 days of initial discharge, and measures have been proposed for modifying payments to hospitals based on their performance on this metric.[1] Cognitive impairment (CI) is considered a major risk factor for poor postdischarge outcomes including mortality and hospital readmission.[2, 3] Hospitals are seeking strategies to reduce postdischarge mortality and rehospitalization among patients with and without CI.[4] Such strategies include use of transitional care coaches, patient and caregiver education, postdischarge follow‐up, and provision of geriatric consultative services (GCS) for the care of complex patients in the hospital setting.[5, 6, 7]

GCS utilize comprehensive geriatric assessments and multidisciplinary processes to recognize and modify risk factors that may lead to poor outcomes among hospitalized patients.[8, 9, 10, 11] Implementation of GCS models including Acute Care for Elders and, recently, the Mobile Acute Care of the Elderly services have shown many benefits among older patients including a reduction in the hospital length of stay and readmission rates.[12, 13] The benefits of such services among hospitalized elders suffering from CI, however, are not well established. The objective of this article was to evaluate the impact of GCS on the readmission and mortality rates of older adults with CI within 12 months of their hospitalization to an urban, public hospital. We hypothesized that GCS will reduce both 12‐month hospital readmissions and mortality rates among this vulnerable group of older adults.

METHODS

The study was approved by the Indiana University institutional review board, and informed consent for identifiable chart review was obtained from subjects or their legally authorized representatives.

Population

Four hundred fifteen hospitalized patients aged 65 years or older suffering from CI were enrolled into an original, randomized, controlled trial that evaluated the effect of a computerized decision support system on their quality and outcome of care between July 1, 2006 and May 30, 2008.[14] The computerized decision support included reminders for physicians to reduce the prescription of 18 anticholinergics, minimize physical restraints and Foley catheterization, and increase referral to the local GCS.[15] That previous trial neither showed an impact on quality of care nor health utilization among older patients, including mortality and hospital readmission rates. The current study uses the data from the clinical trial cohort to evaluate the effect of GCS on the 12‐month mortality and hospital readmission rates for hospitalized elders with CI (Figure 1).

Figure 1

RESULTS

Between July 1, 2006 and May 30, 2008, 415 CI patients were enrolled in the original trial, with 176 receiving the GCS. As shown in Table 1, the GCS and non‐GCS groups differed significantly. The GCS group was older (79.2 years old, 8.1 standard deviation [SD] vs 75.8 years old, 7.8 SD; P0.001), scored lower on the SPMSQ (4.7, 2.7 SD vs 5.5, 2.7 SD; P=0.002), had fewer chronic conditions with a lower mean Charlson Comorbidity Index Score (2.1, 1.86 SD vs 2.8, 2.6 SD; P=0.023), but a higher percentage of delirium (48.9% vs 29.3%), a lower percentage of being discharged home (37.5% vs 56.1%), and a higher mean length of stay (6.4 days, 6.4 SD vs 5.6 days, 5.9 SD; P=0.004). They also had a lower malignancy rate (6.2% vs 14.6%; P=0.007) and a lower number of hospitalizations in the previous year (0.5 admissions, 0.9 SD vs 0.7 admissions, 1.1 SD; P=0.035). No differences were observed in regard to gender, ethnicity, history of myocardial infarctions, chronic obstructive pulmonary disease, cerebrovascular disease, peripheral vascular disease, diabetes, and use of anticholinergic medicines.

Table 2 describes the association of various factors with receiving GCS. Patients who were positive for delirium (odds ratio [OR]=1.65; 95% confidence interval=0.98‐2.77) and were older (OR=1.04; 95% confidence interval=1.01‐1.08) had a higher propensity to receive GCS, whereas, the presence of metastatic cancer resulted in a lower propensity (OR=0.15; 95% confidence interval=0.02‐1.16) of receiving GCS. The logistic model estimated area under the receiver operating characteristic curve was 0.707.

Table 3 provides results from the Cox models for receiving GCS on readmission and mortality outcomes adjusting for various sets of covariates and with the propensity score adjustment. Model 1 presents unadjusted hazard ratio (HR). Model 2 presents HRs adjusting for a common set of covariates that were significantly associated with at least 1 of the outcomes, whereas model 3 presents the results adjusting for all covariates. All 4 models yielded similar results. As evident from this table, propensity‐adjusted HR for 30‐day readmission was still significantly higher among patients receiving GCS (HR=1.75; 95% confidence interval=1.06‐2.88) but not at 1 year (HR=1.19; 95% confidence interval=0.89‐1.59). There was a trend for decreased mortality for the GCS group at 30 days (HR=0.35; 95% confidence interval=0.09‐1.35), but it disappeared at 1 year (HR=0.91; 95% confidence interval=0.59‐1.40). A composite outcome of readmissions and mortality did not show any difference between the GCS and no‐GCS groups.

DISCUSSION

To our knowledge, this is the first study to analyze the impact of GCS on hospital readmission and mortality rates of CI patients. Our results did not show any short‐term or long‐term benefits of GCS for CI patients. Recent studies exploring cost benefits of the GCS have found trends toward lower readmission, but none focused on patients with CI.[6, 24, 25] It is important to note that our study did not use random allocation to assigning the patient into the GCS or control group, thus raising the possibility that patients who received GCS were sicker and were medically and socially more complex than those who did not receive the consult. Moreover, GCS consultation is preferentially sought for and completed for patients with CI and functional limitations, consistent with our finding that GCS patients more often have delirium and are less‐often discharged home.

The nature of the GCS team is another important consideration. Our GCS model did not include unit cohorting of patients, an important component of other proposed GCS models.[26] A recent meta‐analysis found that the GCS models without unit cohorting of patients did not have an impact on 1‐ or 12‐month readmission rates.[27] Low adherence to consultant recommendations (less than 33%) was thought to be a reason for such results. Importance of cohorting with regard to accomplishing recommendations by primary teams, importance of unit staff expertise in geriatric principles, and impact of a unit model on teamwork has also been highlighted by another review.[28] These findings lend to the hypothesis that unit cohorting and direct order placement by the GCS team may improve outcomes among CI patients, including a reduction in readmission rates.

Although readmissions rates were not statistically different between GCS and control groups at 1‐year postdischarge, 30‐day readmission rates were higher among the GCS group. Previous research among older heart failure patients found that a comprehensive transitional care intervention at the time of hospital discharge significantly shortened the time to readmission in the intervention group (P=0.026).[29] The factors identified by the study authors included enhanced supervision by the transitional healthcare teams along with improved awareness and education among treated patients that may have facilitated early recognition of clinical deterioration.[29] A recent study with intensive outpatient care that resulted in increased admissions among chronically ill adults provided a similar conclusion.[30]

GCS patients showed a trend toward decreased mortality as did patients enrolled in previous studies evaluating GCS models in the inpatient setting, as suggested by a recent review.[27] A caveat to note is that these trends favored ward‐styled GCS services as compared to our open GCS model,[27, 28] although the factors cited in these dedicated units affecting mortality included prompt attention to early rehabilitation, delirium management, and prevention of pressure ulcers and are also frequently implemented for patients in our GCS service model and therefore may have produced similar results.

Our neutral results in regard to the readmissions need to be interpreted with caution. First, this study was conducted in a hospital that supports expert geriatric and palliative care teams, both in the inpatient and the ambulatory settings, that provide consultative services and train medicine teams and hospital nursing staff. On the outpatient side, the presence of a robust geriatrics house‐calls program and the Geriatric Resources for Assessment and Care of Elders team results in above‐average care for the control group, and thus may also impact apparent outcomes.[31, 32] Second, 30‐day readmissions represent a complex outcome. Two recent reviews of hospital‐initiated interventions have shown that evidence regarding best strategies to decrease 30‐day readmissions is unclear.[33] Neither review included studies that targeted patients with CI only. The 2 programs that reduced 30‐day readmissions were multifaceted and included personnel who provide bridging between the hospital and the outpatient setting.[34] The GCS does include a focus on postdischarge resources, but does that on a case‐by‐case basis and no formal posthospital follow‐ups are provided. Moreover, the value of 30‐day readmission rates as a marker of quality, even though used by policymakers as an indicator of hospital quality, remains controversial.[35, 36] Broadening the outcomes of interest to include patient‐centered outcomes including satisfaction with care, that have shown to impact other health outcomes, may help improve understanding the benefits of GCS in hospitals.[37] Other comprehensive transitional care models that failed to show a benefit on 30‐day readmissions in older patients still resulted in higher satisfaction among patients.[38] Unfortunately, our evaluation did not include an assessment of patient satisfaction and quality of transitions.

Since the study period, GCS at our hospital now has incorporated a more robust focus on advance care planning (ACP) and execution of Physician Orders for Scope of Treatment that were legislated in the state in July 2013. The GCS team members are expert in carrying out complex ACP discussions and also partner with the inpatient palliative care team. It is quite possible that a study of more recent outcomes will yield more positive results for the selected outcomes. Thus, for future trials that aim to study the impact of GCS in the inpatient settings, it may be advisable to include important quality markers such as implementation of ACP and patient satisfaction along with the health utilization outcomes.

CONCLUSION

Our results comparing inpatient geriatrics consultative services with usual care in hospitalized elders having cognitive impairment failed to demonstrate an impact on readmissions and mortality. A clinical lesson learned, however, is that much work is still required to reduce readmission and mortality rates in this especially vulnerable patient population.

Under the Patient Protection and Affordable Care Act of 2010, commonly referred to as the Affordable Care Act, hospitals face up to a 3% penalty in Medicare reimbursements for patients readmitted within 30 days of initial discharge, and measures have been proposed for modifying payments to hospitals based on their performance on this metric.[1] Cognitive impairment (CI) is considered a major risk factor for poor postdischarge outcomes including mortality and hospital readmission.[2, 3] Hospitals are seeking strategies to reduce postdischarge mortality and rehospitalization among patients with and without CI.[4] Such strategies include use of transitional care coaches, patient and caregiver education, postdischarge follow‐up, and provision of geriatric consultative services (GCS) for the care of complex patients in the hospital setting.[5, 6, 7]

GCS utilize comprehensive geriatric assessments and multidisciplinary processes to recognize and modify risk factors that may lead to poor outcomes among hospitalized patients.[8, 9, 10, 11] Implementation of GCS models including Acute Care for Elders and, recently, the Mobile Acute Care of the Elderly services have shown many benefits among older patients including a reduction in the hospital length of stay and readmission rates.[12, 13] The benefits of such services among hospitalized elders suffering from CI, however, are not well established. The objective of this article was to evaluate the impact of GCS on the readmission and mortality rates of older adults with CI within 12 months of their hospitalization to an urban, public hospital. We hypothesized that GCS will reduce both 12‐month hospital readmissions and mortality rates among this vulnerable group of older adults.

METHODS

The study was approved by the Indiana University institutional review board, and informed consent for identifiable chart review was obtained from subjects or their legally authorized representatives.

Population

Four hundred fifteen hospitalized patients aged 65 years or older suffering from CI were enrolled into an original, randomized, controlled trial that evaluated the effect of a computerized decision support system on their quality and outcome of care between July 1, 2006 and May 30, 2008.[14] The computerized decision support included reminders for physicians to reduce the prescription of 18 anticholinergics, minimize physical restraints and Foley catheterization, and increase referral to the local GCS.[15] That previous trial neither showed an impact on quality of care nor health utilization among older patients, including mortality and hospital readmission rates. The current study uses the data from the clinical trial cohort to evaluate the effect of GCS on the 12‐month mortality and hospital readmission rates for hospitalized elders with CI (Figure 1).

Figure 1

RESULTS

Between July 1, 2006 and May 30, 2008, 415 CI patients were enrolled in the original trial, with 176 receiving the GCS. As shown in Table 1, the GCS and non‐GCS groups differed significantly. The GCS group was older (79.2 years old, 8.1 standard deviation [SD] vs 75.8 years old, 7.8 SD; P0.001), scored lower on the SPMSQ (4.7, 2.7 SD vs 5.5, 2.7 SD; P=0.002), had fewer chronic conditions with a lower mean Charlson Comorbidity Index Score (2.1, 1.86 SD vs 2.8, 2.6 SD; P=0.023), but a higher percentage of delirium (48.9% vs 29.3%), a lower percentage of being discharged home (37.5% vs 56.1%), and a higher mean length of stay (6.4 days, 6.4 SD vs 5.6 days, 5.9 SD; P=0.004). They also had a lower malignancy rate (6.2% vs 14.6%; P=0.007) and a lower number of hospitalizations in the previous year (0.5 admissions, 0.9 SD vs 0.7 admissions, 1.1 SD; P=0.035). No differences were observed in regard to gender, ethnicity, history of myocardial infarctions, chronic obstructive pulmonary disease, cerebrovascular disease, peripheral vascular disease, diabetes, and use of anticholinergic medicines.

Table 2 describes the association of various factors with receiving GCS. Patients who were positive for delirium (odds ratio [OR]=1.65; 95% confidence interval=0.98‐2.77) and were older (OR=1.04; 95% confidence interval=1.01‐1.08) had a higher propensity to receive GCS, whereas, the presence of metastatic cancer resulted in a lower propensity (OR=0.15; 95% confidence interval=0.02‐1.16) of receiving GCS. The logistic model estimated area under the receiver operating characteristic curve was 0.707.

Table 3 provides results from the Cox models for receiving GCS on readmission and mortality outcomes adjusting for various sets of covariates and with the propensity score adjustment. Model 1 presents unadjusted hazard ratio (HR). Model 2 presents HRs adjusting for a common set of covariates that were significantly associated with at least 1 of the outcomes, whereas model 3 presents the results adjusting for all covariates. All 4 models yielded similar results. As evident from this table, propensity‐adjusted HR for 30‐day readmission was still significantly higher among patients receiving GCS (HR=1.75; 95% confidence interval=1.06‐2.88) but not at 1 year (HR=1.19; 95% confidence interval=0.89‐1.59). There was a trend for decreased mortality for the GCS group at 30 days (HR=0.35; 95% confidence interval=0.09‐1.35), but it disappeared at 1 year (HR=0.91; 95% confidence interval=0.59‐1.40). A composite outcome of readmissions and mortality did not show any difference between the GCS and no‐GCS groups.

DISCUSSION

To our knowledge, this is the first study to analyze the impact of GCS on hospital readmission and mortality rates of CI patients. Our results did not show any short‐term or long‐term benefits of GCS for CI patients. Recent studies exploring cost benefits of the GCS have found trends toward lower readmission, but none focused on patients with CI.[6, 24, 25] It is important to note that our study did not use random allocation to assigning the patient into the GCS or control group, thus raising the possibility that patients who received GCS were sicker and were medically and socially more complex than those who did not receive the consult. Moreover, GCS consultation is preferentially sought for and completed for patients with CI and functional limitations, consistent with our finding that GCS patients more often have delirium and are less‐often discharged home.

The nature of the GCS team is another important consideration. Our GCS model did not include unit cohorting of patients, an important component of other proposed GCS models.[26] A recent meta‐analysis found that the GCS models without unit cohorting of patients did not have an impact on 1‐ or 12‐month readmission rates.[27] Low adherence to consultant recommendations (less than 33%) was thought to be a reason for such results. Importance of cohorting with regard to accomplishing recommendations by primary teams, importance of unit staff expertise in geriatric principles, and impact of a unit model on teamwork has also been highlighted by another review.[28] These findings lend to the hypothesis that unit cohorting and direct order placement by the GCS team may improve outcomes among CI patients, including a reduction in readmission rates.

Although readmissions rates were not statistically different between GCS and control groups at 1‐year postdischarge, 30‐day readmission rates were higher among the GCS group. Previous research among older heart failure patients found that a comprehensive transitional care intervention at the time of hospital discharge significantly shortened the time to readmission in the intervention group (P=0.026).[29] The factors identified by the study authors included enhanced supervision by the transitional healthcare teams along with improved awareness and education among treated patients that may have facilitated early recognition of clinical deterioration.[29] A recent study with intensive outpatient care that resulted in increased admissions among chronically ill adults provided a similar conclusion.[30]

GCS patients showed a trend toward decreased mortality as did patients enrolled in previous studies evaluating GCS models in the inpatient setting, as suggested by a recent review.[27] A caveat to note is that these trends favored ward‐styled GCS services as compared to our open GCS model,[27, 28] although the factors cited in these dedicated units affecting mortality included prompt attention to early rehabilitation, delirium management, and prevention of pressure ulcers and are also frequently implemented for patients in our GCS service model and therefore may have produced similar results.

Our neutral results in regard to the readmissions need to be interpreted with caution. First, this study was conducted in a hospital that supports expert geriatric and palliative care teams, both in the inpatient and the ambulatory settings, that provide consultative services and train medicine teams and hospital nursing staff. On the outpatient side, the presence of a robust geriatrics house‐calls program and the Geriatric Resources for Assessment and Care of Elders team results in above‐average care for the control group, and thus may also impact apparent outcomes.[31, 32] Second, 30‐day readmissions represent a complex outcome. Two recent reviews of hospital‐initiated interventions have shown that evidence regarding best strategies to decrease 30‐day readmissions is unclear.[33] Neither review included studies that targeted patients with CI only. The 2 programs that reduced 30‐day readmissions were multifaceted and included personnel who provide bridging between the hospital and the outpatient setting.[34] The GCS does include a focus on postdischarge resources, but does that on a case‐by‐case basis and no formal posthospital follow‐ups are provided. Moreover, the value of 30‐day readmission rates as a marker of quality, even though used by policymakers as an indicator of hospital quality, remains controversial.[35, 36] Broadening the outcomes of interest to include patient‐centered outcomes including satisfaction with care, that have shown to impact other health outcomes, may help improve understanding the benefits of GCS in hospitals.[37] Other comprehensive transitional care models that failed to show a benefit on 30‐day readmissions in older patients still resulted in higher satisfaction among patients.[38] Unfortunately, our evaluation did not include an assessment of patient satisfaction and quality of transitions.

Since the study period, GCS at our hospital now has incorporated a more robust focus on advance care planning (ACP) and execution of Physician Orders for Scope of Treatment that were legislated in the state in July 2013. The GCS team members are expert in carrying out complex ACP discussions and also partner with the inpatient palliative care team. It is quite possible that a study of more recent outcomes will yield more positive results for the selected outcomes. Thus, for future trials that aim to study the impact of GCS in the inpatient settings, it may be advisable to include important quality markers such as implementation of ACP and patient satisfaction along with the health utilization outcomes.

CONCLUSION

Our results comparing inpatient geriatrics consultative services with usual care in hospitalized elders having cognitive impairment failed to demonstrate an impact on readmissions and mortality. A clinical lesson learned, however, is that much work is still required to reduce readmission and mortality rates in this especially vulnerable patient population.

Under the Patient Protection and Affordable Care Act of 2010, commonly referred to as the Affordable Care Act, hospitals face up to a 3% penalty in Medicare reimbursements for patients readmitted within 30 days of initial discharge, and measures have been proposed for modifying payments to hospitals based on their performance on this metric.[1] Cognitive impairment (CI) is considered a major risk factor for poor postdischarge outcomes including mortality and hospital readmission.[2, 3] Hospitals are seeking strategies to reduce postdischarge mortality and rehospitalization among patients with and without CI.[4] Such strategies include use of transitional care coaches, patient and caregiver education, postdischarge follow‐up, and provision of geriatric consultative services (GCS) for the care of complex patients in the hospital setting.[5, 6, 7]

GCS utilize comprehensive geriatric assessments and multidisciplinary processes to recognize and modify risk factors that may lead to poor outcomes among hospitalized patients.[8, 9, 10, 11] Implementation of GCS models including Acute Care for Elders and, recently, the Mobile Acute Care of the Elderly services have shown many benefits among older patients including a reduction in the hospital length of stay and readmission rates.[12, 13] The benefits of such services among hospitalized elders suffering from CI, however, are not well established. The objective of this article was to evaluate the impact of GCS on the readmission and mortality rates of older adults with CI within 12 months of their hospitalization to an urban, public hospital. We hypothesized that GCS will reduce both 12‐month hospital readmissions and mortality rates among this vulnerable group of older adults.

METHODS

The study was approved by the Indiana University institutional review board, and informed consent for identifiable chart review was obtained from subjects or their legally authorized representatives.

Population

Four hundred fifteen hospitalized patients aged 65 years or older suffering from CI were enrolled into an original, randomized, controlled trial that evaluated the effect of a computerized decision support system on their quality and outcome of care between July 1, 2006 and May 30, 2008.[14] The computerized decision support included reminders for physicians to reduce the prescription of 18 anticholinergics, minimize physical restraints and Foley catheterization, and increase referral to the local GCS.[15] That previous trial neither showed an impact on quality of care nor health utilization among older patients, including mortality and hospital readmission rates. The current study uses the data from the clinical trial cohort to evaluate the effect of GCS on the 12‐month mortality and hospital readmission rates for hospitalized elders with CI (Figure 1).

Figure 1

RESULTS

Between July 1, 2006 and May 30, 2008, 415 CI patients were enrolled in the original trial, with 176 receiving the GCS. As shown in Table 1, the GCS and non‐GCS groups differed significantly. The GCS group was older (79.2 years old, 8.1 standard deviation [SD] vs 75.8 years old, 7.8 SD; P0.001), scored lower on the SPMSQ (4.7, 2.7 SD vs 5.5, 2.7 SD; P=0.002), had fewer chronic conditions with a lower mean Charlson Comorbidity Index Score (2.1, 1.86 SD vs 2.8, 2.6 SD; P=0.023), but a higher percentage of delirium (48.9% vs 29.3%), a lower percentage of being discharged home (37.5% vs 56.1%), and a higher mean length of stay (6.4 days, 6.4 SD vs 5.6 days, 5.9 SD; P=0.004). They also had a lower malignancy rate (6.2% vs 14.6%; P=0.007) and a lower number of hospitalizations in the previous year (0.5 admissions, 0.9 SD vs 0.7 admissions, 1.1 SD; P=0.035). No differences were observed in regard to gender, ethnicity, history of myocardial infarctions, chronic obstructive pulmonary disease, cerebrovascular disease, peripheral vascular disease, diabetes, and use of anticholinergic medicines.

Table 2 describes the association of various factors with receiving GCS. Patients who were positive for delirium (odds ratio [OR]=1.65; 95% confidence interval=0.98‐2.77) and were older (OR=1.04; 95% confidence interval=1.01‐1.08) had a higher propensity to receive GCS, whereas, the presence of metastatic cancer resulted in a lower propensity (OR=0.15; 95% confidence interval=0.02‐1.16) of receiving GCS. The logistic model estimated area under the receiver operating characteristic curve was 0.707.

Table 3 provides results from the Cox models for receiving GCS on readmission and mortality outcomes adjusting for various sets of covariates and with the propensity score adjustment. Model 1 presents unadjusted hazard ratio (HR). Model 2 presents HRs adjusting for a common set of covariates that were significantly associated with at least 1 of the outcomes, whereas model 3 presents the results adjusting for all covariates. All 4 models yielded similar results. As evident from this table, propensity‐adjusted HR for 30‐day readmission was still significantly higher among patients receiving GCS (HR=1.75; 95% confidence interval=1.06‐2.88) but not at 1 year (HR=1.19; 95% confidence interval=0.89‐1.59). There was a trend for decreased mortality for the GCS group at 30 days (HR=0.35; 95% confidence interval=0.09‐1.35), but it disappeared at 1 year (HR=0.91; 95% confidence interval=0.59‐1.40). A composite outcome of readmissions and mortality did not show any difference between the GCS and no‐GCS groups.

DISCUSSION

To our knowledge, this is the first study to analyze the impact of GCS on hospital readmission and mortality rates of CI patients. Our results did not show any short‐term or long‐term benefits of GCS for CI patients. Recent studies exploring cost benefits of the GCS have found trends toward lower readmission, but none focused on patients with CI.[6, 24, 25] It is important to note that our study did not use random allocation to assigning the patient into the GCS or control group, thus raising the possibility that patients who received GCS were sicker and were medically and socially more complex than those who did not receive the consult. Moreover, GCS consultation is preferentially sought for and completed for patients with CI and functional limitations, consistent with our finding that GCS patients more often have delirium and are less‐often discharged home.

The nature of the GCS team is another important consideration. Our GCS model did not include unit cohorting of patients, an important component of other proposed GCS models.[26] A recent meta‐analysis found that the GCS models without unit cohorting of patients did not have an impact on 1‐ or 12‐month readmission rates.[27] Low adherence to consultant recommendations (less than 33%) was thought to be a reason for such results. Importance of cohorting with regard to accomplishing recommendations by primary teams, importance of unit staff expertise in geriatric principles, and impact of a unit model on teamwork has also been highlighted by another review.[28] These findings lend to the hypothesis that unit cohorting and direct order placement by the GCS team may improve outcomes among CI patients, including a reduction in readmission rates.

Although readmissions rates were not statistically different between GCS and control groups at 1‐year postdischarge, 30‐day readmission rates were higher among the GCS group. Previous research among older heart failure patients found that a comprehensive transitional care intervention at the time of hospital discharge significantly shortened the time to readmission in the intervention group (P=0.026).[29] The factors identified by the study authors included enhanced supervision by the transitional healthcare teams along with improved awareness and education among treated patients that may have facilitated early recognition of clinical deterioration.[29] A recent study with intensive outpatient care that resulted in increased admissions among chronically ill adults provided a similar conclusion.[30]

GCS patients showed a trend toward decreased mortality as did patients enrolled in previous studies evaluating GCS models in the inpatient setting, as suggested by a recent review.[27] A caveat to note is that these trends favored ward‐styled GCS services as compared to our open GCS model,[27, 28] although the factors cited in these dedicated units affecting mortality included prompt attention to early rehabilitation, delirium management, and prevention of pressure ulcers and are also frequently implemented for patients in our GCS service model and therefore may have produced similar results.

Our neutral results in regard to the readmissions need to be interpreted with caution. First, this study was conducted in a hospital that supports expert geriatric and palliative care teams, both in the inpatient and the ambulatory settings, that provide consultative services and train medicine teams and hospital nursing staff. On the outpatient side, the presence of a robust geriatrics house‐calls program and the Geriatric Resources for Assessment and Care of Elders team results in above‐average care for the control group, and thus may also impact apparent outcomes.[31, 32] Second, 30‐day readmissions represent a complex outcome. Two recent reviews of hospital‐initiated interventions have shown that evidence regarding best strategies to decrease 30‐day readmissions is unclear.[33] Neither review included studies that targeted patients with CI only. The 2 programs that reduced 30‐day readmissions were multifaceted and included personnel who provide bridging between the hospital and the outpatient setting.[34] The GCS does include a focus on postdischarge resources, but does that on a case‐by‐case basis and no formal posthospital follow‐ups are provided. Moreover, the value of 30‐day readmission rates as a marker of quality, even though used by policymakers as an indicator of hospital quality, remains controversial.[35, 36] Broadening the outcomes of interest to include patient‐centered outcomes including satisfaction with care, that have shown to impact other health outcomes, may help improve understanding the benefits of GCS in hospitals.[37] Other comprehensive transitional care models that failed to show a benefit on 30‐day readmissions in older patients still resulted in higher satisfaction among patients.[38] Unfortunately, our evaluation did not include an assessment of patient satisfaction and quality of transitions.

Since the study period, GCS at our hospital now has incorporated a more robust focus on advance care planning (ACP) and execution of Physician Orders for Scope of Treatment that were legislated in the state in July 2013. The GCS team members are expert in carrying out complex ACP discussions and also partner with the inpatient palliative care team. It is quite possible that a study of more recent outcomes will yield more positive results for the selected outcomes. Thus, for future trials that aim to study the impact of GCS in the inpatient settings, it may be advisable to include important quality markers such as implementation of ACP and patient satisfaction along with the health utilization outcomes.

CONCLUSION

Our results comparing inpatient geriatrics consultative services with usual care in hospitalized elders having cognitive impairment failed to demonstrate an impact on readmissions and mortality. A clinical lesson learned, however, is that much work is still required to reduce readmission and mortality rates in this especially vulnerable patient population.

Delirium is a syndrome of disturbance of consciousness, with reduced ability to focus, sustain, or shift attention, that occurs over a short period of time and fluctuates over the course of the day.1 It encompasses a variety of cognitive, behavioral, and psychological symptoms including inattention, short‐term memory loss, sleep disturbances, agitated behaviors, delusions, and visual hallucinations.2 Delirium complicates the care of 70% to 80% of mechanically ventilated patients in intensive care units (ICUs).3 Of 13 million patients aged 65 and older hospitalized in 2002, 10% to 52% had delirium at some point during their admission.4, 5

Patients experiencing delirium have a higher probability of death during their hospital stay, adjusted for age, gender, race, and comorbidities.3, 6, 7 They are more vulnerable to hospital‐acquired complications leading to prolonged ICU and hospital stay, new institutionalization, and higher healthcare costs.3, 6, 7 Even with such a range of poor outcomes, the rates of delirium recognition are low,8 resulting in inadequate management.9 There has been considerable growth in the number of articles published on delirium in recent years. Therefore, it is of value to provide a state‐of‐the‐art summary of robust evidence in the field to healthcare personnel and delirium investigators.

We systematically reviewed the literature to identify published systematic evidence reviews (SERs), which evaluated the evidence on delirium risk factors, diagnosis, pathogenesis, prevention, treatment, and outcomes. We then summarized the data from the methodologically sound SERs to provide the reader with a clinically oriented summary of delirium literature for patient care. We also identify current gaps in delirium literature, and present future directions for delirium investigators to design studies that will enhance delirium care.

DATA SOURCES AND REVIEW METHODS

The domains of risk factors, diagnosis, pathophysiology, prevention, treatment, and outcomes were selected a priori to capture all relevant SERs regarding delirium based on the framework suggested by the American Delirium Society task force.10 To maximize article retrieval, a 3‐step search strategy was applied. First, we searched the electronic database utilizing OVID Medline, PubMed, the Cochrane Library, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) using the following delirium‐specific search terms: delirium, confusion, agitation, mental status change, inattention, encephalopathy, organic mental disorders, and disorientation. We combined the above terms with the following study design terms: technical report, systematic evidence review, systematic review, meta‐analysis, editorial, and clinical reviews. We limited our search to human subjects. We excluded studies that: a) enrolled patients aged <18; b) enrolled patients with current or past Diagnostic and Statistical Manual of Mental Disorders (DSM) Axis I psychotic disorders; c) did not have standardized delirium evaluation; d) evaluated alcohol or substance abuse‐related delirium; e) did not use a systematic search method for identifying delirium‐related articles; and f) evaluated delirium sub‐types. We searched articles published from January 1966 through April 2011. Second, a manual search of references of the retrieved papers plus an Internet search using Google Scholar was conducted to find additional SERs. Titles and abstracts were screened by 2 reviewers (B.A.K., M.Z.). Authors of the included studies were contacted as necessary. Third, a library professional at the Indiana University School of Medicine independently performed a literature search, and those results were compared with our search to retrieve any missing SERs.

The methodological quality of each SER was independently assessed by 2 reviewers (B.A.K., M.Z.) using the United States Preventive Services Task Force (USPSTF) Critical Appraisal for SER.11 This scale assesses parameters that are critical to the scientific credibility of an SER and categorizes the SER as poor, fair, or good (Table 1). The 2 reviewers (B.A.K., M.Z.) used a data extraction form to record the following information from each SER: primary author, publication year, number and type of studies, number of participants and their mean age, study population, method for delirium diagnosis, risk factors, preventive and therapeutic interventions, and outcomes. Any disagreement between reviewers in SER selection, data extraction, or SER appraisal was resolved through discussion with a third reviewer (M.A.B.). The conflicting findings among SERs were resolved by consensus and by including the findings from a good SER over a fair SER.

RESULTS

Our search yielded 76,060 potential citations, out of which we identified 38 SERs meeting our inclusion criteria (Table 2). Figure 1 outlines our search strategy. Based on the USPSTF criteria, 22 SERs graded as good or fair provided the data to establish our review.

Figure 1

DISCUSSION AND CLINICAL IMPLICATIONS

Our study identified age, cognitive impairment, depression, and mepiridine use for analgesia as risk factors for delirium in surgical patients. Drugs with anticholinergic properties were implicated in delirium development in both medical and surgical patients. The CAM has the best available data to be used as a diagnostic tool for delirium. Multicomponent interventions to prevent delirium occurrence are effective in a non‐cognitively impaired population, and low‐dose haloperidol prophylaxis decreases delirium duration and severity without affecting delirium incidence in hip surgery patients. There is no advantage of using atypical antipsychotics over haloperidol in treating delirium, and low‐dose haloperidol is as effective as a higher dose without unwarranted extrapyramidal side effects. Delirium carries a poor prognosis with an increased risk of death, institutionalization, and dementia.

Hospitals may benefit from implementing multicomponent strategies, focusing on at‐risk elderly medical and surgical patients, administered by a multidisciplinary team to reduce delirium incidence. For ICU physicians and administrators, development of sedation guidelines minimizing the use of benzodiazepines will decrease the risk of delirium development.

A structured approach in diagnosing delirium is required to maximize identification. Use of the CAM, based on best available data is recommended. However, the length of time in doing the CAM (more than 10 minutes with the requisite mental status examination) and insensitivity in nonexpert hands suggest a need for alternative screening tools. Haloperidol should be the preferred first‐line pharmacological therapy for delirium, with atypical antipsychotics reserved for patients with contraindications to haloperidol or those who are refractory to therapy with haloperidol. Figure 2 delineates a clinical model for delirium management derived from the findings in the Results section.

Figure 2

FUTURE RESEARCH DIRECTIONS

We identified multiple areas without clear guidelines that could provide opportunities for future research. A role for routine delirium screening can be clarified through a well‐designed delirium screening trial investigating the benefits of delirium screening, coupled with a multicomponent intervention versus usual care. Use of pharmacotherapy in delirium prevention needs to be explored further in a large randomized trial, with 3 arms to compare typical antipsychotics, atypical antipsychotics, and placebo in patients at risk for delirium with a primary outcome of delirium incidence. In regard to delirium treatment, a large randomized trial to compare haloperidol with atypical antipsychotics, with a placebo arm focusing not only on delirium duration and severity, but also on long‐term outcomes such as rehospitalizations, institutionalization, cognitive impairment, and mortality, is warranted. Figure 3 points out potential areas for researchers to investigate hypotheses generated by our review and thereby improve delirium care.

Figure 3

To our knowledge, our SER presents the first summary of SERs in delirium. Prior to this review, Michaud et al9 and National Institute for Health and Clinical Excellence48 published delirium guidelines, but in both of these guidelines, evidence was collected from a multitude of studies ranging in methodology from scientific review and meta‐analysis to observational studies, and the majority of recommendations were based on expert opinion. On the contrary, our review was limited to rigorously conducted SERs; hence, we utilized the highest level, critically appraised evidence to provide guidance to clinicians and researchers.

Limitations include a diverse group of studies with a heterogeneous population of patients, preventing pooling of results. We did not review each individual study included in the 38 SERs. We excluded non‐English language SERs, studies evaluating delirium subtypes, alcohol or substance abuse‐related delirium, or delirium associated with psychiatric disorders. As we only reviewed SERs, some notable studies not included in the SERs may have been missed.

CONCLUSION

Delirium among hospitalized patients is a common syndrome with a significant burden to the healthcare system and society. The field of delirium has seen considerable advances in diagnosis, prevention, and treatment over the last decade. Even with this advancement, there are still areas of uncertainty, such as: the benefits and costs of delirium screening; the benefits and harms of single or combined pharmacological agents for delirium prevention and treatment; the development of a set of reliable biomarkers for delirium diagnosis, prognosis, and response to therapy; the long‐term effect of delirium‐specific therapeutics on patients' cognitive, physical, and psychological functions; and the relationship between delirium and the development of Alzheimer's disease. As our understanding of delirium's impact on patients and healthcare improves, delirium should be identified as an indicator of poor long‐term prognosis, and should prompt immediate and effective evidence‐based management strategies, like any other critical illness.

Delirium is a syndrome of disturbance of consciousness, with reduced ability to focus, sustain, or shift attention, that occurs over a short period of time and fluctuates over the course of the day.1 It encompasses a variety of cognitive, behavioral, and psychological symptoms including inattention, short‐term memory loss, sleep disturbances, agitated behaviors, delusions, and visual hallucinations.2 Delirium complicates the care of 70% to 80% of mechanically ventilated patients in intensive care units (ICUs).3 Of 13 million patients aged 65 and older hospitalized in 2002, 10% to 52% had delirium at some point during their admission.4, 5

Patients experiencing delirium have a higher probability of death during their hospital stay, adjusted for age, gender, race, and comorbidities.3, 6, 7 They are more vulnerable to hospital‐acquired complications leading to prolonged ICU and hospital stay, new institutionalization, and higher healthcare costs.3, 6, 7 Even with such a range of poor outcomes, the rates of delirium recognition are low,8 resulting in inadequate management.9 There has been considerable growth in the number of articles published on delirium in recent years. Therefore, it is of value to provide a state‐of‐the‐art summary of robust evidence in the field to healthcare personnel and delirium investigators.

We systematically reviewed the literature to identify published systematic evidence reviews (SERs), which evaluated the evidence on delirium risk factors, diagnosis, pathogenesis, prevention, treatment, and outcomes. We then summarized the data from the methodologically sound SERs to provide the reader with a clinically oriented summary of delirium literature for patient care. We also identify current gaps in delirium literature, and present future directions for delirium investigators to design studies that will enhance delirium care.

DATA SOURCES AND REVIEW METHODS

The domains of risk factors, diagnosis, pathophysiology, prevention, treatment, and outcomes were selected a priori to capture all relevant SERs regarding delirium based on the framework suggested by the American Delirium Society task force.10 To maximize article retrieval, a 3‐step search strategy was applied. First, we searched the electronic database utilizing OVID Medline, PubMed, the Cochrane Library, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) using the following delirium‐specific search terms: delirium, confusion, agitation, mental status change, inattention, encephalopathy, organic mental disorders, and disorientation. We combined the above terms with the following study design terms: technical report, systematic evidence review, systematic review, meta‐analysis, editorial, and clinical reviews. We limited our search to human subjects. We excluded studies that: a) enrolled patients aged <18; b) enrolled patients with current or past Diagnostic and Statistical Manual of Mental Disorders (DSM) Axis I psychotic disorders; c) did not have standardized delirium evaluation; d) evaluated alcohol or substance abuse‐related delirium; e) did not use a systematic search method for identifying delirium‐related articles; and f) evaluated delirium sub‐types. We searched articles published from January 1966 through April 2011. Second, a manual search of references of the retrieved papers plus an Internet search using Google Scholar was conducted to find additional SERs. Titles and abstracts were screened by 2 reviewers (B.A.K., M.Z.). Authors of the included studies were contacted as necessary. Third, a library professional at the Indiana University School of Medicine independently performed a literature search, and those results were compared with our search to retrieve any missing SERs.

The methodological quality of each SER was independently assessed by 2 reviewers (B.A.K., M.Z.) using the United States Preventive Services Task Force (USPSTF) Critical Appraisal for SER.11 This scale assesses parameters that are critical to the scientific credibility of an SER and categorizes the SER as poor, fair, or good (Table 1). The 2 reviewers (B.A.K., M.Z.) used a data extraction form to record the following information from each SER: primary author, publication year, number and type of studies, number of participants and their mean age, study population, method for delirium diagnosis, risk factors, preventive and therapeutic interventions, and outcomes. Any disagreement between reviewers in SER selection, data extraction, or SER appraisal was resolved through discussion with a third reviewer (M.A.B.). The conflicting findings among SERs were resolved by consensus and by including the findings from a good SER over a fair SER.

RESULTS

Our search yielded 76,060 potential citations, out of which we identified 38 SERs meeting our inclusion criteria (Table 2). Figure 1 outlines our search strategy. Based on the USPSTF criteria, 22 SERs graded as good or fair provided the data to establish our review.

Figure 1

DISCUSSION AND CLINICAL IMPLICATIONS

Our study identified age, cognitive impairment, depression, and mepiridine use for analgesia as risk factors for delirium in surgical patients. Drugs with anticholinergic properties were implicated in delirium development in both medical and surgical patients. The CAM has the best available data to be used as a diagnostic tool for delirium. Multicomponent interventions to prevent delirium occurrence are effective in a non‐cognitively impaired population, and low‐dose haloperidol prophylaxis decreases delirium duration and severity without affecting delirium incidence in hip surgery patients. There is no advantage of using atypical antipsychotics over haloperidol in treating delirium, and low‐dose haloperidol is as effective as a higher dose without unwarranted extrapyramidal side effects. Delirium carries a poor prognosis with an increased risk of death, institutionalization, and dementia.

Hospitals may benefit from implementing multicomponent strategies, focusing on at‐risk elderly medical and surgical patients, administered by a multidisciplinary team to reduce delirium incidence. For ICU physicians and administrators, development of sedation guidelines minimizing the use of benzodiazepines will decrease the risk of delirium development.

A structured approach in diagnosing delirium is required to maximize identification. Use of the CAM, based on best available data is recommended. However, the length of time in doing the CAM (more than 10 minutes with the requisite mental status examination) and insensitivity in nonexpert hands suggest a need for alternative screening tools. Haloperidol should be the preferred first‐line pharmacological therapy for delirium, with atypical antipsychotics reserved for patients with contraindications to haloperidol or those who are refractory to therapy with haloperidol. Figure 2 delineates a clinical model for delirium management derived from the findings in the Results section.

Figure 2

FUTURE RESEARCH DIRECTIONS

We identified multiple areas without clear guidelines that could provide opportunities for future research. A role for routine delirium screening can be clarified through a well‐designed delirium screening trial investigating the benefits of delirium screening, coupled with a multicomponent intervention versus usual care. Use of pharmacotherapy in delirium prevention needs to be explored further in a large randomized trial, with 3 arms to compare typical antipsychotics, atypical antipsychotics, and placebo in patients at risk for delirium with a primary outcome of delirium incidence. In regard to delirium treatment, a large randomized trial to compare haloperidol with atypical antipsychotics, with a placebo arm focusing not only on delirium duration and severity, but also on long‐term outcomes such as rehospitalizations, institutionalization, cognitive impairment, and mortality, is warranted. Figure 3 points out potential areas for researchers to investigate hypotheses generated by our review and thereby improve delirium care.

Figure 3

To our knowledge, our SER presents the first summary of SERs in delirium. Prior to this review, Michaud et al9 and National Institute for Health and Clinical Excellence48 published delirium guidelines, but in both of these guidelines, evidence was collected from a multitude of studies ranging in methodology from scientific review and meta‐analysis to observational studies, and the majority of recommendations were based on expert opinion. On the contrary, our review was limited to rigorously conducted SERs; hence, we utilized the highest level, critically appraised evidence to provide guidance to clinicians and researchers.

Limitations include a diverse group of studies with a heterogeneous population of patients, preventing pooling of results. We did not review each individual study included in the 38 SERs. We excluded non‐English language SERs, studies evaluating delirium subtypes, alcohol or substance abuse‐related delirium, or delirium associated with psychiatric disorders. As we only reviewed SERs, some notable studies not included in the SERs may have been missed.

CONCLUSION

Delirium among hospitalized patients is a common syndrome with a significant burden to the healthcare system and society. The field of delirium has seen considerable advances in diagnosis, prevention, and treatment over the last decade. Even with this advancement, there are still areas of uncertainty, such as: the benefits and costs of delirium screening; the benefits and harms of single or combined pharmacological agents for delirium prevention and treatment; the development of a set of reliable biomarkers for delirium diagnosis, prognosis, and response to therapy; the long‐term effect of delirium‐specific therapeutics on patients' cognitive, physical, and psychological functions; and the relationship between delirium and the development of Alzheimer's disease. As our understanding of delirium's impact on patients and healthcare improves, delirium should be identified as an indicator of poor long‐term prognosis, and should prompt immediate and effective evidence‐based management strategies, like any other critical illness.

Delirium is a syndrome of disturbance of consciousness, with reduced ability to focus, sustain, or shift attention, that occurs over a short period of time and fluctuates over the course of the day.1 It encompasses a variety of cognitive, behavioral, and psychological symptoms including inattention, short‐term memory loss, sleep disturbances, agitated behaviors, delusions, and visual hallucinations.2 Delirium complicates the care of 70% to 80% of mechanically ventilated patients in intensive care units (ICUs).3 Of 13 million patients aged 65 and older hospitalized in 2002, 10% to 52% had delirium at some point during their admission.4, 5

Patients experiencing delirium have a higher probability of death during their hospital stay, adjusted for age, gender, race, and comorbidities.3, 6, 7 They are more vulnerable to hospital‐acquired complications leading to prolonged ICU and hospital stay, new institutionalization, and higher healthcare costs.3, 6, 7 Even with such a range of poor outcomes, the rates of delirium recognition are low,8 resulting in inadequate management.9 There has been considerable growth in the number of articles published on delirium in recent years. Therefore, it is of value to provide a state‐of‐the‐art summary of robust evidence in the field to healthcare personnel and delirium investigators.

We systematically reviewed the literature to identify published systematic evidence reviews (SERs), which evaluated the evidence on delirium risk factors, diagnosis, pathogenesis, prevention, treatment, and outcomes. We then summarized the data from the methodologically sound SERs to provide the reader with a clinically oriented summary of delirium literature for patient care. We also identify current gaps in delirium literature, and present future directions for delirium investigators to design studies that will enhance delirium care.

DATA SOURCES AND REVIEW METHODS

The domains of risk factors, diagnosis, pathophysiology, prevention, treatment, and outcomes were selected a priori to capture all relevant SERs regarding delirium based on the framework suggested by the American Delirium Society task force.10 To maximize article retrieval, a 3‐step search strategy was applied. First, we searched the electronic database utilizing OVID Medline, PubMed, the Cochrane Library, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) using the following delirium‐specific search terms: delirium, confusion, agitation, mental status change, inattention, encephalopathy, organic mental disorders, and disorientation. We combined the above terms with the following study design terms: technical report, systematic evidence review, systematic review, meta‐analysis, editorial, and clinical reviews. We limited our search to human subjects. We excluded studies that: a) enrolled patients aged <18; b) enrolled patients with current or past Diagnostic and Statistical Manual of Mental Disorders (DSM) Axis I psychotic disorders; c) did not have standardized delirium evaluation; d) evaluated alcohol or substance abuse‐related delirium; e) did not use a systematic search method for identifying delirium‐related articles; and f) evaluated delirium sub‐types. We searched articles published from January 1966 through April 2011. Second, a manual search of references of the retrieved papers plus an Internet search using Google Scholar was conducted to find additional SERs. Titles and abstracts were screened by 2 reviewers (B.A.K., M.Z.). Authors of the included studies were contacted as necessary. Third, a library professional at the Indiana University School of Medicine independently performed a literature search, and those results were compared with our search to retrieve any missing SERs.

The methodological quality of each SER was independently assessed by 2 reviewers (B.A.K., M.Z.) using the United States Preventive Services Task Force (USPSTF) Critical Appraisal for SER.11 This scale assesses parameters that are critical to the scientific credibility of an SER and categorizes the SER as poor, fair, or good (Table 1). The 2 reviewers (B.A.K., M.Z.) used a data extraction form to record the following information from each SER: primary author, publication year, number and type of studies, number of participants and their mean age, study population, method for delirium diagnosis, risk factors, preventive and therapeutic interventions, and outcomes. Any disagreement between reviewers in SER selection, data extraction, or SER appraisal was resolved through discussion with a third reviewer (M.A.B.). The conflicting findings among SERs were resolved by consensus and by including the findings from a good SER over a fair SER.

RESULTS

Our search yielded 76,060 potential citations, out of which we identified 38 SERs meeting our inclusion criteria (Table 2). Figure 1 outlines our search strategy. Based on the USPSTF criteria, 22 SERs graded as good or fair provided the data to establish our review.

Figure 1

DISCUSSION AND CLINICAL IMPLICATIONS

Our study identified age, cognitive impairment, depression, and mepiridine use for analgesia as risk factors for delirium in surgical patients. Drugs with anticholinergic properties were implicated in delirium development in both medical and surgical patients. The CAM has the best available data to be used as a diagnostic tool for delirium. Multicomponent interventions to prevent delirium occurrence are effective in a non‐cognitively impaired population, and low‐dose haloperidol prophylaxis decreases delirium duration and severity without affecting delirium incidence in hip surgery patients. There is no advantage of using atypical antipsychotics over haloperidol in treating delirium, and low‐dose haloperidol is as effective as a higher dose without unwarranted extrapyramidal side effects. Delirium carries a poor prognosis with an increased risk of death, institutionalization, and dementia.

Hospitals may benefit from implementing multicomponent strategies, focusing on at‐risk elderly medical and surgical patients, administered by a multidisciplinary team to reduce delirium incidence. For ICU physicians and administrators, development of sedation guidelines minimizing the use of benzodiazepines will decrease the risk of delirium development.

A structured approach in diagnosing delirium is required to maximize identification. Use of the CAM, based on best available data is recommended. However, the length of time in doing the CAM (more than 10 minutes with the requisite mental status examination) and insensitivity in nonexpert hands suggest a need for alternative screening tools. Haloperidol should be the preferred first‐line pharmacological therapy for delirium, with atypical antipsychotics reserved for patients with contraindications to haloperidol or those who are refractory to therapy with haloperidol. Figure 2 delineates a clinical model for delirium management derived from the findings in the Results section.

Figure 2

FUTURE RESEARCH DIRECTIONS

We identified multiple areas without clear guidelines that could provide opportunities for future research. A role for routine delirium screening can be clarified through a well‐designed delirium screening trial investigating the benefits of delirium screening, coupled with a multicomponent intervention versus usual care. Use of pharmacotherapy in delirium prevention needs to be explored further in a large randomized trial, with 3 arms to compare typical antipsychotics, atypical antipsychotics, and placebo in patients at risk for delirium with a primary outcome of delirium incidence. In regard to delirium treatment, a large randomized trial to compare haloperidol with atypical antipsychotics, with a placebo arm focusing not only on delirium duration and severity, but also on long‐term outcomes such as rehospitalizations, institutionalization, cognitive impairment, and mortality, is warranted. Figure 3 points out potential areas for researchers to investigate hypotheses generated by our review and thereby improve delirium care.

Figure 3

To our knowledge, our SER presents the first summary of SERs in delirium. Prior to this review, Michaud et al9 and National Institute for Health and Clinical Excellence48 published delirium guidelines, but in both of these guidelines, evidence was collected from a multitude of studies ranging in methodology from scientific review and meta‐analysis to observational studies, and the majority of recommendations were based on expert opinion. On the contrary, our review was limited to rigorously conducted SERs; hence, we utilized the highest level, critically appraised evidence to provide guidance to clinicians and researchers.

Limitations include a diverse group of studies with a heterogeneous population of patients, preventing pooling of results. We did not review each individual study included in the 38 SERs. We excluded non‐English language SERs, studies evaluating delirium subtypes, alcohol or substance abuse‐related delirium, or delirium associated with psychiatric disorders. As we only reviewed SERs, some notable studies not included in the SERs may have been missed.

CONCLUSION

Delirium among hospitalized patients is a common syndrome with a significant burden to the healthcare system and society. The field of delirium has seen considerable advances in diagnosis, prevention, and treatment over the last decade. Even with this advancement, there are still areas of uncertainty, such as: the benefits and costs of delirium screening; the benefits and harms of single or combined pharmacological agents for delirium prevention and treatment; the development of a set of reliable biomarkers for delirium diagnosis, prognosis, and response to therapy; the long‐term effect of delirium‐specific therapeutics on patients' cognitive, physical, and psychological functions; and the relationship between delirium and the development of Alzheimer's disease. As our understanding of delirium's impact on patients and healthcare improves, delirium should be identified as an indicator of poor long‐term prognosis, and should prompt immediate and effective evidence‐based management strategies, like any other critical illness.