Discharge planning predicting patients' needs.

The elderly are at higher risk for longer and more frequent lengths of hospital stay than other adults. Comprehensive discharge planning programs, including early identification of those at risk, can alter these statistics. Screening inventories to identify patients at risk have been available for many years, but they are not specific to the needs of the elderly. The Blaylock Risk Assessment Screen (BRASS) is administered on admission and identifies patients at risk for prolonged hospital stay and in need of discharge planning resources. The nurse can use the data BRASS provides to improve care outcomes while the patient is in the hospital and in the transition to home care. It shows promise for use as the first phase of a discharge planning program.     

Predictive validity of the BRASS index in screening patients with post-discharge problems. Blaylock Risk Assessment Screening Score

RATIONALE: Discharge planning is a nursing intervention that aims to ensure continuity of care; it consists of several steps of which selecting patients in need of it is the first one. The Blaylock Risk Assessment Screening Score (BRASS) index is a risk screening instrument which can be used early after admission to identify those patients in need of discharge planning. AIM: To test the predictive validity of the BRASS index in screening patients with post-discharge problems. DESIGN: Prospective longitudinal design with prediction instrument measured at admission, and outcomes measured at discharge and 7 and 30 days after discharge. OUTCOME MEASURES: length of stay, discharge destination, status after discharge. INSTRUMENTS: BRASS index, Problems after discharge Questionnaire, Nottingham Health Profile, COOP/WONCA charts. RESEARCH METHOD: 503 elderly patients were screened at admission with the BRASS index. Length of stay and discharge destination were measured at discharge in these same patients. Outcomes after discharge were gathered only in patients who were discharged home and with length of stay of more than 3 days (n=226); outcomes were measured by postal questionnaires at day 7 and day 30 after discharge. RESULTS: patients identified by the BRASS index as high risk are frequently not discharged home and have a longer length of stay. The BRASS scores correlate significantly with the outcome scores after discharge: the higher the BRASS score, the higher the difficulty score after discharge on all domains. However, the sensitivity of the BRASS index is rather low. CONCLUSION: This study demonstrates that the BRASS index is a good predictor instrument for indicating patients who are not discharged home, that the BRASS scores correlate significantly with problems experienced after discharge and that it has high specificity to predict patients with problems after discharge. Clinical use, however, is limited due to the low sensitivity. The BRASS index is a promising case-finding instrument for discharge planning, but needs further development.     

Clinical utility of scores on the Blaylock Risk Assessment Screen (BRASS): An analysis of administrative data

PurposeProject was undertaken to examine the utility of the Blaylock Risk Assessment Screen (BRASS) in identifying patients who may experience discharge complications as indicated by longer hospital stays or readmission within 30-days of a discharge to home.BackgroundBefore measures can be put in place to facilitate discharge planning and to prevent unplanned readmission by recently discharged patients, those at risk of such events must be identified.MethodsProject involved an analysis of 13-months of administrative data from one tertiary care hospital. Utility of the BRASS was examined in terms of its sensitivity and specificity as well as its positive and negative predictive values.ResultsMajority (83%) of hospital discharges were to home. Approximately 7% of patients experienced at least one readmission within 30-days of being discharged to home. Using scores of 10 or higher as an indicator of risk, BRASS exhibited a high degree of specificity suggesting it is useful for ‘ruling in’ those who have the outcomes-of-interest. However low sensitivity indicates many who experienced the outcomes were incorrectly classified by the BRASS as low risk. The low positive predictive value for 30-day readmission also suggests many who were classified by the BRASS as being ‘at risk’ were not readmitted.ConclusionThe observed rate of 30-day readmission is likely conservative as the analysis involved data from only one acute care facility. One explanation for the low positive predictive value for 30-day readmission is that completion of the BRASS on admission enabled the implementation of preventive measures.     

Intensive care unit survivors have fewer hospital readmissions and readmission days than other hospitalized patients in British Columbia

OBJECTIVE: Intensive care unit (ICU) patients who survive their hospital admission have a long-term survival that is similar to that of hospitalized patients who do not require ICU admission. The risk of future readmission to the hospital for these two patient groups is unknown. The objective of this study was to determine the association between ICU admission and number of readmissions to the hospital and number of readmission days. DESIGN: Cohort study for 3 yrs between 1994 and 1997. SETTING: All acute care hospitals in British Columbia, Canada. PATIENTS: A total of 23,859 patients admitted to the ICU and 40,052 patients admitted to the hospital but not the ICU (5% random sample of total). INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We measured the number of readmissions to the hospital and the number of readmission days after discharge from the first admission to the hospital during the study period. For survivors to the end of the study period, patients who had been in the ICU had 0.66 readmissions per year and 5.29 readmission days per year compared with 0.73 readmissions per year and 5.48 readmission days per year for control subjects. After controlling for age, sex, socioeconomic status, number of previous ICU and hospital admissions, major clinical category during index admission, comorbidity score during index admission, length of hospital stay during index admission, size of index hospital, and period of follow-up, ICU admission was associated with fewer readmissions (survivors: rate ratio, 0.80; 95% confidence interval, 0.77-0.82; nonsurvivors: rate ratio, 0.85; 95%, confidence interval, 0.82-0.89) and readmission days (survivors: rate ratio, 0.91; 95% confidence interval, 0.87-0.95; nonsurvivors: rate ratio, 0.87; 95%, confidence interval, 0.81-0.92) than admission to the hospital but not the ICU. CONCLUSIONS: Survivors of a hospital stay that includes admission to an ICU have fewer hospital readmissions and readmission days after their discharge than do survivors of a hospital stay without intensive care.     

Exploring the capacity to ambulate after a period of prolonged mechanical ventilation

Purpose

The purposes were to assess the functional recovery of those who survived a prolonged intensive care unit (ICU) stay by reporting the proportion who were able to ambulate independently at hospital discharge and also to examine if the time duration between admission and when the patient first stood impacted on their capacity to ambulate at discharge.

Materials and Methods

A retrospective review was conducted of medical records of ICU patients in 2007 to 2008, who were mechanically ventilated for 168 hours or more, and survived their acute care stay. Main outcome measures were (1) ambulation status before admission and at time of hospital discharge and (2) time between admission to the ICU and when the patient first stood.

Results

A total of 190 patients were included. Before admission, 189 (99%; 95% confidence interval [CI], 98%-100%) were ambulating independently, of whom 180 (95%) did not require a gait aid. On discharge from acute care, 89 (47%; 95% CI, 40%-54%) were ambulating independently, of whom 54 (61%) did not require a gait aid. Compared with those who stood within 30 days of ICU admission, a delay in standing of between 30 and 60 days increased the odds 5-fold (95% CI, 2-11) of being unable to ambulate independently at the time of discharge.

Conclusions

After a prolonged ICU admission, more than 50% of patients were unable to ambulate independently by hospital discharge, with the time between admission and first stand, being an important predictor of this outcome.     

Long-term outcome in ICU patients: what about quality of life?

Objective Analysis of mortality and quality of life (QOL) after intensive care unit (ICU) discharge.Design Prospective, observational study.Setting Mixed, 31-bed, medico-surgical ICU.Patients Consecutive adult ICU admissions between June 25 and September 10, 2000, except admissions for uncomplicated elective postoperative surveillance.Interventions None.Measurements and results Age, past history, admission APACHE II, SOFA score (admission, maximum, discharge), ICU and hospital mortality were recorded. A telephone interview employing the EuroQol 5D system was conducted 18 months after discharge. Of 202 patients, 34 (16.8%) died in the ICU and 23 (11.4%) died in the hospital after ICU discharge. Of the 145 patients discharged alive from hospital, 22 could not be contacted and 27 (13.4%) had died after hospital discharge. Of the 96 patients (47.5%) who completed the questionnaire, 38% had a worse QOL than prior to ICU admission, but only 8.3% were severely incapacitated. Twenty-three patients (24%) had reduced mobility, 15 (15.6%) had limited autonomy, 24 (25%) had alteration in usual daily activities, 29 (30.2%) expressed more anxiety/depression, and 42 (44%) had more discomfort or pain. Twenty-eight (62.2% of those who worked previously) patients had returned to work 18 months after ICU discharge.Conclusions Comparing QOL after discharge with that before admission, patients more frequently report worse QOL for the domains of pain/discomfort and anxiety/depression than for physical domains. Factors commonly associated with a change in QOL were previous problems in the affected domains, prolonged hospital length of stay (LOS), greater disease severity at admission and degree of organ dysfunction during ICU stay.     

Long-term survival and functional capacity in cardiac surgery patients after prolonged intensive care

OBJECTIVE: To determine whether hospital discharge alone represents a good outcome for patients who had prolonged intensive care after cardiac surgery by studying their postdischarge survival and functional outcome. The secondary objective is to estimate the proportion of intensive care unit (ICU) resources used by the long-stay (> or = 10 initial consecutive ICU days) patients and to identify preoperative patient characteristics that are associated with a prolonged ICU stay and hospital and long-term survival. DESIGN: Inception cohort study. SETTING: The Cleveland Clinic Foundation, a tertiary care, academic teaching institution. PATIENTS: Cardiac surgery patients with an initial ICU stay of 10 or more consecutive days. INTERVENTIONS: Data were collected daily during hospitalization on every adult who underwent coronary artery bypass graft and/or valve surgery at one institution in 1993. Discharged patients who spent >10 initial consecutive days in the ICU after surgery were contacted by telephone to determine vital status and functional capacity using the Duke Activity Status Index. Total ICU and total hospital direct costs were obtained for each patient. MEASUREMENTS AND MAIN RESULTS: The primary outcome measurements were ICU length of stay, hospital mortality, after-surgery and postdischarge mortality and functional capacity, and relative resource utilization. Of the 2,618 cardiac surgery patients who met the inclusion criteria, 142 (5.4%) had an initial ICU length of stay of 10 or more consecutive days. Of these, 47 (33.1%) died in the hospital. Ninety-four of the 95 discharged patients were followed up (median follow-up, 30.6 months), and 44 of the 94 (46.8%) died during the follow-up period. The median Duke Activity Status Index for the 50 survivors was 26 out of a possible 58.2. The 142 long-stay patients used 50% of the total ICU days and 48% of the total ICU direct cost for all 2,618 patients. CONCLUSIONS: Many survivors of prolonged intensive care die soon after hospital discharge and many longer term survivors have a poor functional state. Therefore, hospital discharge is an incomplete measure of outcome for these patients, and longer follow-up is more appropriate. The relatively small number of patients who require prolonged intensive care consumes a disproportionate amount of the total ICU and total hospital direct cost.     

Early indicators of prolonged intensive care unit stay: impact of illness severity,physician staffing,and pre-intensive care unit length of stay

OBJECTIVE: Scoring systems that predict mortality do not necessarily predict prolonged length of stay or costs in the intensive care unit (ICU). Knowledge of characteristics predicting prolonged ICU stay would be helpful, particularly if some factors could be modified. Such factors might include process of care, including active involvement of full-time ICU physicians and length of hospital stay before ICU admission. DESIGN: Demographic data, clinical diagnosis at ICU admission, Simplified Acute Physiology Score, and organizational characteristics were examined by logistic regression for their effect on ICU and hospital length of stay and weighted hospital days (WHD), a proxy for high cost of care. SETTING: A total of 34 ICUs at 27 hospitals participating in Project IMPACT during 1998. PATIENTS: A total of 10,900 critically ill medical, surgical, and trauma patients qualifying for Simplified Acute Physiology Score assessment. INTERVENTIONS: None. RESULTS: Overall, 9.8% of patients had excess WHD, but the percentage varied by diagnosis. Factors predicting high WHD include Simplified Acute Physiology Score survival probability, age of 40 to 80 yrs, presence of infection or mechanical ventilation 24 hrs after admission, male sex, emergency surgery, trauma, presence of critical care fellows, and prolonged pre-ICU hospital stay. Mechanical ventilation at 24 hrs predicts high WHD across diagnostic categories, with a relative risk of between 2.4 and 12.9. Factors protecting against high WHD include do-not-resuscitate order at admission, presence of coma 24 hrs after admission, and active involvement of full-time ICU physicians. CONCLUSIONS: Patients with high WHD, and thus high costs, can be identified early. Severity of illness only partially explains high WHD. Age is less important as a predictor of high WHD than presence of infection or ventilator dependency at 24 hrs. Both long ward stays before ICU admission and lack of full-time ICU physician involvement in care increase the probability of long ICU stays. These latter two factors are potentially modifiable and deserve prospective study.     

Impact of intensive care unit discharge time on patient outcome

OBJECTIVE: To determine the impact of nighttime intensive care unit (ICU) discharge on patient outcome. DESIGN: Multiple-center, retrospective observational cohort study. SETTING: Canadian hospitals. PATIENTS: We used a prospectively collected dataset containing information on 79,090 consecutive admissions from 31 Canadian community and teaching hospitals. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients were categorized according to the time of ICU discharge into daytime (07:00-20:59) and nighttime (21:00-06:59). Admissions were excluded if the patients were a) 相似文献   

Post-intensive care unit pediatric hospital stay and estimated costs

OBJECTIVE: For pediatric intensive care unit (ICU) survivors, to determine the proportion of hospital stay and estimated hospital costs accounted for by post-ICU care. DESIGN: Prospective study. SETTING: University teaching hospital. PATIENTS: Pediatric patients who survive an ICU admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Estimated relative daily costs were assumed as follows: ICU, with ventilator/ICU, not on ventilator/intermediate care unit/general pediatric hospital day, at 2:1:0.7:0.3, respectively. Estimated costs were expressed in arbitrary units as (number of days at each level of care) x (relative cost per day). The ICU phase was defined as the patient's first ICU admission only, and the post-ICU phase included intermediate care unit and general pediatric hospital days, as well as ICU readmission during the same hospitalization. Pre-ICU hospital activity was excluded from analysis. For 341 ICU survivors, post-ICU days (median, 4 days per patient) accounted for 62% of the total hospital stay. Post-ICU care accounted for one third of the total estimated hospital costs for ICU survivors. Patients with longer post-ICU stays could not be reliably identified at the time of ICU discharge according to their ICU length of stay, duration of mechanical ventilation in the ICU, age, ICU day 1 mortality probability, or diagnostic group (p>.05). CONCLUSIONS: Post-ICU care accounts for a substantial proportion of hospital stay and estimated costs for ICU survivors. These observations suggest that developing strategies to optimize hospital utilization at the time of ICU discharge may be important for controlling costs of recovery from critical illness.     

ICU患者抑郁焦虑发生的危险因素分析

目的探讨ICU患者住院期间抑郁焦虑的发病率及出院后抑郁焦虑的危险因素。方法前瞻性研究,入选在我院ICU进行治疗的250例神志清楚及智力正常的患者,记录患者的性别、年龄、教育程度、原发病的严重程度[以Charlson Co-morbidity index(CCI)量表评估]、APACHEⅡ评分、呼吸机使用天数、每日睡眠时间、入住ICU的时间等10项资料,在入院4 d后以医院焦虑抑郁量表(HADS)来测评其住院期间抑郁焦虑的发病率;在患者出院2个月内,成功随访195例,以HADS量表再次测评患者出院后抑郁焦虑的发生情况,采用多元线性回归分析找出与患者出院后抑郁焦虑发生的有关危险因素。结果 ICU患者住院期间抑郁焦虑的发生率为24%;多元线性回归分析表明:CCI评分(P<0.01),住院期间HADS评分(P<0.05),入住ICU时间(P<0.01)3项为患者出院后抑郁发病的危险因素;CCI评分(P<0.01),APACHEⅡ评分(P<0.05),住院期间出现谵妄(P<0.05),住院期间HADS评分(P<0.05),入住ICU时间(P<0.01)5项因素为患者出院后焦虑发生的危险因素。结论 ICU患者住院期间抑郁焦虑的发病率较高。原发病较重,住院期间出现精神症状,入住ICU时间长是患者出院后出现抑郁症状的危险因素;原发病较重,APACHEⅡ评分较高,且住院期间出现精神、谵妄症状,入住ICU时间长是患者出院后出现焦虑症状的危险因素。     

Determinants of outcome for patients admitted to a long-term ventilator unit

BACKGROUND: This prospective cohort study was done to identify determinants of successful weaning from mechanical ventilation among patients admitted to the 10-bed long-term ventilator unit (LTVU) of a teaching hospital. METHODS: Prospective patient surveillance and data collection were done on 472 patients admitted to the LTVU over a 4-year period (January 1996 to December 1999). RESULTS: Multiple logistic regression analysis showed that the absence of home mechanical ventilation at the time of hospital admission, absence of intensive care unit (ICU) readmission, and admission to the LTVU from a nonmedical service were independently associated with successful weaning. No statistical difference between hospital survivors and nonsurvivors was associated with length of stay in the LTVU and length of stay in the hospital. CONCLUSIONS: Patients admitted to an LTVU require prolonged hospitalizations and intensive resource utilization. These data suggest that improved methods for identifying patients who are unlikely to benefit from prolonged mechanical ventilation may assist physicians in their discussions with patients and family members as they consider various treatment options.     

Admission factors associated with prolonged (> 14 days) intensive care unit stay

Purpose

To describe the admission factors associated with prolonged (> 14 days) intensive care unit (ICU) stay (PIS).

Materials and Methods

Retrospective analysis of 3257 admissions during a 1.5-year period in a tertiary hospital. We tested the association between clinically relevant variables and PIS (> 14 days) through binary logistic regression using the backward method. A Kaplan-Meier curve and the log-rank test were used to compare hospital outcomes for ICU survivors between patients with and without PIS.

Results

In total, 6.6% of all admissions had a prolonged stay, consuming over 40% of all ICU bed-days. Illness severity; respiratory support at admission; performance status; readmission; admission from a ward, emergency room or other hospital; admission due to intracranial mass effect; severe chronic obstructive pulmonary disease; and the temperature at admission were all associated with PIS in a multivariate analysis. The created model had a good area under the curve (0.82) and was calibrated (Hosmer-Lemeshow test p = 0.431). Post hoc analysis on ICU survivors on in patients with at least two days of ICU stay yielded similar results. Hospital survival after ICU discharge was similar for patients with and without PIS (log-rank test p = 0.50).

Conclusion

A small number of ICU admissions consume a great proportion of ICU bed-days. Illness severity, a need for support and performance status are important predictors of PIS. Patients who survive a PIS have similar hospital mortality to patients with a shorter stay.     

Long-stay patients in the pediatric intensive care unit

OBJECTIVE: Length of stay in the pediatric intensive care unit (PICU) is a reflection of patient severity of illness and health status, as well as PICU quality and performance. We determined the clinical profiles and relative resource use of long-stay patients (LSPs) and developed a prediction model to identify LSPs for early quality and cost saving interventions. DESIGN: Nonconcurrent cohort study. SETTING: A total of 16 randomly selected PICUs and 16 volunteer PICUs. PATIENTS: A total of 11,165 consecutive admissions to the 32 PICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: LSPs were defined as patients having a length of stay greater than the 95th percentile (>12 days). Logistic regression analysis was used to determine which clinical characteristics, available within the first 24 hrs after admission, were associated with LSPs and to create a predictive algorithm. Overall, LSPs were 4.7% of the population but represented 36.1% of the days of care. Multivariate analysis indicated that the following factors are predictive of long stays: age <12 months, previous ICU admission, emergency admission, no CPR before admission, admission from another ICU or intermediate care unit, chronic care requirements (total parenteral nutrition and tracheostomy), specific diagnoses including acquired cardiac disease, pneumonia, and other respiratory disorders, having never been discharged from the hospital, need for ventilatory support or an intracranial catheter, and a Pediatric Risk of Mortality III score between 10 and 33. The performance of the prediction algorithm in both the training and validation samples for identifying LSPs was good for both discrimination (area under the receiver operating characteristics curve of 0.83 and 0.85, respectively), and calibration (goodness of fit, p = .33 and p = .16, respectively). LSPs comprised from 2.1% to 8.1% of individual ICU patients and occupied from 15.2% to 57.8% of individual ICU bed days. CONCLUSIONS: LSPs have less favorable outcomes and use more resources than non-LSPs. The clinical profile of LSPs includes those who are younger and those that require chronic care devices. A predictive algorithm could help identify patients at high risk of prolonged stays appropriate for specific interventions.     

Outcome of children requiring admission to an intensive care unit after bone marrow transplantation

OBJECTIVE: To review the outcome of bone marrow transplant (BMT) recipients admitted to a pediatric intensive care unit (ICU) and attempt to identify admission characteristics that might accurately predict a poor outcome. DESIGN: Retrospective case-note review. SETTING: Pediatric ICU of a tertiary teaching hospital. PATIENTS: A total of 40 BMT recipients, accounting for 57 admissions to the ICU, in the 5 yrs between 1994 and 1998 were identified. MEASUREMENTS AND MAIN RESULTS: Median time to ICU admission after BMT was 42 days. Of the 40 patients admitted to ICU, 11 (22.5%) are still alive, with a median time of follow-up since their most recent ICU admission of 587 days (absolute range, 308-1803 days). A total of 32 of 57 admissions (56.1%) resulted in the patient's discharge from the ICU, and 21 admissions (36.8%) resulted in survival to at least 30 days after discharge. There was no difference between the survivors and nonsurvivors in terms of underlying diagnoses, age at BMT, or time to ICU admission after BMT. Type of BMT, conditioning regimen, and presence of significant graft vs. host disease was not found to influence outcome. Although patients who died in the ICU had a significantly longer length of stay compared with the survivors (median, 7.9 days, vs. 2.1 days, p =.02), 11 of 21 admissions (52.4%) associated with survival to 30 days post-ICU discharge were of >or=2 days of duration, the longest being 22.8 days. Thirty-one of 40 patients (77.5%) required intubation and mechanical ventilation during 36 of the 57 admissions, and 15 of these episodes (41.6%) ended with the patient's discharge from the ICU. Of ten patients with respiratory failure associated with pulmonary infection, there were no survivors among those who remained ventilated at 48 hrs (n = 8). Four patients who required mechanical ventilation (12.9%) were alive at the 6-month follow-up. The majority of patients who died in the ICU did so after either withdrawal (65%) or limitation (22%) of treatment. CONCLUSIONS: Despite the generally poor prognosis for pediatric patients admitted to the ICU after BMT, intensive care continues to play an important role in the care of these patients. Although it is clear that patients who require mechanical ventilation have a worse prognosis, we were unable to identify factors that accurately predict with 100% sensitivity which patients will not survive. Those patients requiring mechanical ventilation due to pneumonitis have a particularly poor outcome, and our findings support the limitation of intensive care in certain circumstances. Decisions regarding treatment options and limitation of care in this group of patients should be based on ongoing outcome research in this field.     

Long-term outcomes and clinical predictors of hospital mortality in very long stay intensive care unit patients: a cohort study

Introduction  

Little information is available on prognosis and outcomes of very long stay intensive care unit (ICU) patients. The purpose of this study was to identify long-term outcomes after hospital discharge and readily available clinical predictors of hospital mortality for patients requiring prolonged care in the ICU.     

Long-term outcomes in patients requiring stay of more than 48 hours in the intensive care unit following coronary bypass surgery

BACKGROUND: The primary objective of this study was to determine the long-term outcomes of all patients requiring prolonged intensive care unit (ICU) stay following coronary bypass surgery (CABG) surgery. METHODS: All patients undergoing CABG surgery between 1998 and 2002 were reviewed. Prolonged ICU stay was defined as more than 48 hours. Short-term (in-hospital) and long-term (postdischarge) outcomes were evaluated using available databases. RESULTS: Of 3139 patients who underwent CABG surgery, 598 required an ICU stay of more than 48 hours (19%). The in-hospital mortality for patients requiring prolonged ICU stay was 10.0% as compared with 1.2% for the remainder of patients (P < .0001). The median length of hospitalization for patients requiring prolonged stay was 11 days (IQR 7-18) as compared to 6 days (IQR 5-7). The median follow-up of patients who survived to discharge was 31 months with a 100% follow-up. Using Cox proportional hazard ratio, patients who required a prolonged ICU stay were found to have a significant lower survival and freedom from cardiac readmission to the hospital. Prolonged ICU stay was an independent predictor of composite outcome (death + readmission) with a hazard ratio of 1.8 (1.5-2.1). CONCLUSIONS: Prolonged ICU stay following CABG resulted in increased early and late mortality and lower freedom from readmission to hospital for cardiac reasons.     

Healthcare utilization and mortality outcomes in patients with pre-existing psychiatric disorders after intensive care unit discharge: A population-based retrospective cohort study

PurposePre-existing psychiatric disorders may lead to negative outcomes following intensive care unit (ICU) discharge. We evaluated the association of pre-existing psychiatric disorders with subsequent healthcare utilization and mortality in patients discharged from ICU.Materials and methodsWe retrospectively studied adult patients admitted to 14 medical-surgical ICUs (January 2014–June 2016) with ICU length stay ≥24 h who survived to hospital discharge. Pre-existing psychiatric disorders were identified using algorithms for diagnostic codes captured ≤5 years before ICU admission. Outcomes were healthcare utilization (emergency department visit, hospital or ICU readmission) and mortality. We used logistic regression models with propensity scores to estimate associations, converted to risk ratios (RR).ResultsWe included 10,598 patients. 37.6% (n = 3982) had a psychiatric history. Patients with pre-existing psychiatric disorders were at higher risk of subsequent emergency department visits (RR 1.49, 95%CI 1.29–1.71), hospital readmission (RR 1.49, 95%CI 1.34–1.66), ICU readmission (RR 2.64, 95%CI 1.55–4.49) one-year post-ICU discharge, compared to patients without pre-existing psychiatric disorders. Patients with pre-existing psychiatric disorders had a higher risk of mortality (RR 1.31, 95%CI 1.00–1.71) six-months post-ICU discharge.ConclusionCritically ill patients with pre-existing psychiatric disorders have an increased risk of healthcare utilization and mortality outcomes following an ICU stay.     

Discharge from hospital with newly administered antipsychotics after intensive care unit delirium – Incidence and contributing factors

PurposeDelirium in the intensive care unit (ICU) is often treated with haloperidol or atypical antipsychotics. Antipsychotic treatment can lead to severe adverse effects and excess mortality. After initiation in the ICU, patients are at risk of having their antipsychotics continued unnecessarily at ICU and hospital discharge. This study aims to determine the incidence of, and risk factors for antipsychotic continuation at hospital discharge after ICU delirium.MethodsThis retrospective observational study was performed in a tertiary care center. Adult patients who received antipsychotics for ICU delirium during 2016 were included. Data was extracted from patient records. After univariate testing, a multivariate binary logistic regression model was used to identify independent risk factors for antipsychotic continuation.ResultsA total of 196 patients were included, of which 104 (53.1%) and 41 (20.9%) had their antipsychotics continued at ICU and hospital discharge respectively. Medical ICU admission (odds ratio [95% confidence interval] 2.97 [1.37–6.41]) and quetiapine treatment (5.81 [1.63–20.83]) were independently associated with antipsychotic continuation at hospital discharge.ConclusionsApproximately one in five patients were discharged from the hospital with continued antipsychotics. Hospital policies should implement strategies for systematic antipsychotic tapering and better follow-up of antipsychotics at transitions of care.