Transfers from intensive care unit to hospital ward: a multicentre textual analysis of physician progress notes

Factors Associated With Inpatient Hospice Utilization Among Hospitalized Decedents With Comfort Measures Only Status

Background: Patients with serious illness may elect to transition their care to comfort measures only (CMO) while in the hospital. Although studies have shown that routine hospice care is underutilized, the rate of general inpatient hospice (GIP) use among CMO patients during their terminal admission remains unclear. Objectives: We sought to (1) examine the rate of GIP utilization and (2) identify factors associated with its use among hospitalized CMO decedents. Methods: CMO decedents in two academic, tertiary care hospitals in the United States who died between October 1, 2020 and October 31, 2021, were subgrouped based on their primary medical service (GIP vs. non-GIP) at the time of inpatient death. Data abstracted from the electronic health record included demographics, primary diagnosis codes, Rothman Index (RI), time of CMO order, ordering clinician type, time of death, and length of stay (LOS). Multivariable logistic regression analysis was performed, adjusting for relevant covariates. Results: Of 1475 CMO decedents, only 321 (n = 22%) patients received GIP. On multivariable analysis, CMO patients who died in an ICU were five times less likely (odds ratio [OR] = 0.18, confidence interval [95% CI] 0.11-0.29) to receive GIP. Every 10-point increase in RI raised the likelihood of receiving GIP by 59% (OR = 1.59, 95% CI 1.39-1.80). Conclusions: Most CMO decedents died in the hospital without GIP. Compared with GIP decedents, non-GIP decedents were less acutely ill. There was no difference in total LOS between the two groups. CMO decedents were much less likely to receive GIP in an ICU. The RI may help clinicians identify CMO patients who would benefit from GIP earlier in their terminal admission.

Developing a reflection and analysis tool (We-ReAlyse) for readmissions to the intensive care unit: A quality improvement project

BACKGROUND

Readmissions to the intensive care unit are associated with poorer patient outcomes and health prognoses, alongside increased lengths of stay and mortality risk. To improve quality of care and patients' safety, it is essential to understand influencing factors relevant to specific patient populations and settings. A standardized tool for systematic retrospective analysis of readmissions would help healthcare professionals understand risks and reasons affecting readmissions; however, no such tool exists.

PURPOSE

This study's purpose was to develop a tool (We-ReAlyse) to analyze readmissions to the intensive care unit from general units by reflecting on affected patients' pathways from intensive care discharge to readmission. The results will highlight case-specific causes of readmission and potential areas for departmental- and institutional-level improvements.

METHOD

A root cause analysis approach guided this quality improvement project. The tool's iterative development process included a literature search, a clinical expert panel, and a testing in January and February 2021.

RESULTS

The We-ReAlyse tool guides healthcare professionals to identify areas for quality improvement by reflecting the patient's pathway from the initial intensive care stay to readmission. Ten readmissions were analyzed by using the We-ReAlyse tool, resulting in key insights about possible root causes like the handover process, patient's care needs, the resources on the general unit and the use of different electronic healthcare record systems.

CONCLUSIONS

The We-ReAlyse tool provides a visualization/objectification of issues related to intensive care readmissions, gathering data upon which to base quality improvement interventions. Based on the information on how multi-level risk profiles and knowledge deficits contribute to readmission rates, nurses can target specific quality improvements to reduce those rates.

IMPLICATIONS FOR CLINICAL PRACTICE AND RESEARCH

With the We-ReAlyse tool, we have the opportunity to collect detailed information about ICU readmissions for an in-depth analysis. This will allow health professionals in all involved departments to discuss and either correct or cope with the identified issues. In the long term, this will allow continuous, concerted efforts to reduce and prevent ICU readmissions. To obtain more data for analysis and to further refine and simplify the tool, it may be applied to larger samples of ICU readmissions. Furthermore, to test its generalizability, the tool should be applied to patients from other departments and other hospitals. Adapting it to an electronic version would facilitate the timely and comprehensive collection of necessary information. Finally, the tool's emphasis comprises reflecting on and analyzing ICU readmissions, allowing clinicians to develop interventions targeting the identified problems. Therefore, future research in this area will require the development and evaluation of potential interventions.

Understanding medication safety involving patient transfer from intensive care to hospital ward: a qualitative sociotechnical factor study

OBJECTIVE

To understand the sociotechnical factors affecting medication safety when intensive care patients are transferred to a hospital ward. Consideration of these medication safety factors would provide a theoretical basis, on which future interventions can be developed and evaluated to improve patient care.

DESIGN

Qualitative study using semistructured interviews of intensive care and hospital ward-based healthcare professionals. Transcripts were anonymised prior to thematic analysis using the London Protocol and Systems Engineering in Patient Safety V.3.0 model frameworks.

SETTING

Four north of England National Health Service hospitals. All hospitals used electronic prescribing in intensive care and hospital ward settings.

PARTICIPANTS

Intensive care and hospital ward healthcare professionals (intensive care medical staff, advanced practitioners, pharmacists and outreach team members; ward-based medical staff and clinical pharmacists).

RESULTS

Twenty-two healthcare professionals were interviewed. We identified 13 factors within five broad themes, describing the interactions that most strongly influenced the performance of the intensive care to hospital ward system interface. The themes were: Complexity of process performance and interactions; Time pressures and considerations; Communication processes and challenges; Technology and systems and Beliefs about consequences for the patient and organisation.

CONCLUSIONS

The complexity of the interactions on the system performance and time dependency was clear. We make several recommendations for policy change and further research based on improving: availability of hospital-wide integrated and functional electronic prescribing systems, patient flow systems, sufficient multiprofessional critical care staffing, knowledge and skills of staff, team performance, communication and collaboration and patient and family engagement.

A Multiple Baseline Trial of an Electronic ICU Discharge Summary Tool for Improving Quality of Care

OBJECTIVE

Effective communication between clinicians is essential for seamless discharge of patients between care settings. Yet, discharge summaries are commonly not available and incomplete. We implemented and evaluated a structured electronic health record-embedded electronic discharge (eDischarge) summary tool for patients discharged from the ICU to a hospital ward.

DESIGN

Multiple baseline trial with randomized and staggered implementation.

SETTING

Adult medical-surgical ICUs at four acute care hospitals serving a single Canadian city.

PATIENTS

Health records of patients 18 years old or older, in the ICU 24 hours or longer, and discharged from the ICU to an in-hospital patient ward between February 12, 2018, and June 30, 2019.

INTERVENTION

A structured electronic note (ICU eDischarge tool) with predefined fields (e.g., diagnosis) embedded in the hospital-wide electronic health information system.

MEASUREMENTS AND MAIN RESULTS

We compared the percent of timely (available at discharge) and complete (included goals of care designation, diagnosis, list of active issues, active medications) discharge summaries pre and post implementation using mixed effects logistic regression models. After implementing the ICU eDischarge tool, there was an immediate and sustained increase in the proportion of patients discharged from ICU with timely and complete discharge summaries from 10.8% (preimplementation period) to 71.1% (postimplementation period) (adjusted odds ratio, 32.43; 95% CI, 18.22-57.73). No significant changes were observed in rapid response activation, cardiopulmonary arrest, death in hospital, ICU readmission, and hospital length of stay following ICU discharge. Preventable (60.1 vs 5.7 per 1,000 d; p = 0.023), but not nonpreventable (27.3 vs 40.2 per 1,000d; p = 0.54), adverse events decreased post implementation. Clinicians perceived the eDischarge tool to produce a higher quality discharge process.

CONCLUSIONS

Implementation of an electronic tool was associated with more timely and complete discharge summaries for patients discharged from the ICU to a hospital ward.

Impact of customised ICU handover protocol on the quality of ICU discharge reports

Background

The aim of this investigation was to evaluate the impact of implementing a handover protocol, based on a standardised mnemonic tool specific for a cardiovascular intensive care unit (ICU), on the quality of information transferred during ICU discharge.

Methods

In this prospective pre–post study, we evaluated the implementation of an ICU discharge handover protocol in 168 patients who underwent coronary artery bypass graft surgery. The primary outcome was the quality of the information. In the preintervention phase, 84 ICU standard discharge reports were evaluated. During the intervention period, a new handover protocol which included a written discharge report based on the I-PASS (illness severity, patient summary, action list, situation awareness and contingency plans, and synthesis by receiver) mnemonic tool was implemented. After the intervention, 84 new reports were assessed. The reports were evaluated by the ward physicians and by an external independent examiner using a standardised questionnaire. ICU discharge time and postoperative length of stay were also analysed.

Results

The overall quality of the reports was evaluated as ‘completely understood’ by the ward physicians in 17 patients (21%) in the preintervention phase compared with 45 patients (54.9%) in the postintervention phase (p<0.001). The independent examiner classified one report (1.2% of the total number) as ‘excellent’ in the preintervention phase and 30 (35.7%) in the postintervention phase (p<0.001). After protocol implementation, patients were released from the ICU 58 min later (p<0.001). There was no difference in the length of postoperative hospital stay.

Conclusion

Implementation of a customised handover protocol when discharging patients from the ICU was associated with improvement in the quality of the information transferred but also with ICU discharge occurring at a later time of day.

Long-term Safety of Directly Discharging Patients Home from the ICU Compared to Ward Transfer

Purpose: To evaluate the long-term safety of directly discharging intensive care unit (ICU) survivors to their home. Methods: A retrospective observational cohort of 341 ICU survivors who were directly discharged home from the ICU ("direct discharge") or discharged home ≤72 hours after ICU transfer to the ward ("ward transfer") was conducted in Regina, Saskatchewan ICUs between September 1, 2016 and September 30, 2018. The primary outcome was 90-day hospital readmission. Secondary outcomes included 30-day, 90-day, and 365-day emergency department (ED) visits, 30-day and 365-day hospital readmissions, and 365-day mortality. All outcomes were evaluated by multivariable Cox regression after adjustment for demographic and clinical characteristics. Results: Of 341 survivors (25.5% of total ICU visits), 148 (43.4%) patients were direct discharges and 193 (56.6%) were ward transfers. The median age was 46 years (interquartile range, 34-62), 38.4% were female, and 61.8% resided in Regina. Compared to the ward transfer cohort, more patients in the direct discharge cohort had at least one 90-day hospital readmission (30.4% versus 17.1% of patients, adjusted hazard ratio 2.09, 95% confidence interval 1.28-3.40, P = .003), after adjustment. Additionally, there were more 90-day ED visits (P = .045), and 30-day (P = .049) and 365-day hospital readmissions (P = .03), after adjustment. Conclusions: In Saskatchewan, direct discharge compared to ward transfer was associated with an increase in 90-day hospital readmissions, and potentially other clinical outcomes. Further study is necessary.

Identification of data elements for blood gas analysis dataset: a base for developing registries and artificial intelligence-based systems

Background

One of the challenging decision-making tasks in healthcare centers is the interpretation of blood gas tests. One of the most effective assisting approaches for the interpretation of blood gas analysis (BGA) can be artificial intelligence (AI)-based decision support systems. A primary step to develop intelligent systems is to determine information requirements and automated data input for the secondary analyses. Datasets can help the automated data input from dispersed information systems. Therefore, the current study aimed to identify the data elements required for supporting BGA as a dataset.

Materials and methods

This cross-sectional descriptive study was conducted in Nemazee Hospital, Shiraz, Iran. A combination of literature review, experts’ consensus, and the Delphi technique was used to develop the dataset. A review of the literature was performed on electronic databases to find the dataset for BGA. An expert panel was formed to discuss on, add, or remove the data elements extracted through searching the literature. Delphi technique was used to reach consensus and validate the draft dataset.

Results

The data elements of the BGA dataset were categorized into ten categories, namely personal information, admission details, present illnesses, past medical history, social status, physical examination, paraclinical investigation, blood gas parameter, sequential organ failure assessment (SOFA) score, and sampling technique errors. Overall, 313 data elements, including 172 mandatory and 141 optional data elements were confirmed by the experts for being included in the dataset.

Conclusions

We proposed a dataset as a base for registries and AI-based systems to assist BGA. It helps the storage of accurate and comprehensive data, as well as integrating them with other information systems. As a result, high-quality care is provided and clinical decision-making is improved.

Prescribing errors in post - COVID-19 patients: prevalence, severity, and risk factors in patients visiting a post - COVID-19 outpatient clinic

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has challenged healthcare globally. An acute increase in the number of hospitalized patients has necessitated a rigorous reorganization of hospital care, thereby creating circumstances that previously have been identified as facilitating prescribing errors (PEs), e.g. a demanding work environment, a high turnover of doctors, and prescribing beyond expertise. Hospitalized COVID-19 patients may be at risk of PEs, potentially resulting in patient harm. We determined the prevalence, severity, and risk factors for PEs in post–COVID-19 patients, hospitalized during the first wave of COVID-19 in the Netherlands, 3 months after discharge.

Methods

This prospective observational cohort study recruited patients who visited a post-COVID-19 outpatient clinic of an academic hospital in the Netherlands, 3 months after COVID-19 hospitalization, between June 1 and October 1 2020. All patients with appointments were eligible for inclusion. The prevalence and severity of PEs were assessed in a multidisciplinary consensus meeting. Odds ratios (ORs) were calculated by univariate and multivariate analysis to identify independent risk factors for PEs.

Results

Ninety-eight patients were included, of whom 92% had ≥1 PE and 8% experienced medication-related harm requiring an immediate change in medication therapy to prevent detoriation. Overall, 68% of all identified PEs were made during or after the COVID-19 related hospitalization. Multivariate analyses identified ICU admission (OR 6.08, 95% CI 2.16–17.09) and a medical history of COPD / asthma (OR 5.36, 95% CI 1.34–21.5) as independent risk factors for PEs.

Conclusions

PEs occurred frequently during the SARS-CoV-2 pandemic. Patients admitted to an ICU during COVID-19 hospitalization or who had a medical history of COPD / asthma were at risk of PEs. These risk factors can be used to identify high-risk patients and to implement targeted interventions. Awareness of prescribing safely is crucial to prevent harm in this new patient population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00588-7.

Safety Influencing Factors and Management Countermeasures of Patients Transferred from ICU in Transition Period Based on Intelligent Processor Three-Dimensional Quality Model

With the development of science and technology of the times, the level of medical care is constantly improving. For patients transferred from ICU, the intelligent processor 3D quality model technology has gradually played an important role in clinical treatment and has become a new type of attention. In order to understand the implementation status of transitional care and the feelings of transitional care for patients transferred from ICU and understand the views of transitional care-related department doctors on transitional patient care and the role that the intelligent processor three-dimensional quality model can play, this article passed a review of the city ICU transferred patients from a hospital that conducted related investigations, reviewed related literature, conducted interviews with professionals, etc., collected relevant information, constructed case templates, and created a clinical research model using comprehensive quantitative and qualitative analysis methods. The results of the study found that, after treatment, patients transferred from the ICU based on the intelligent processor's three-dimensional quality model have higher physical activity than patients treated by other methods, the ratio is more than 20%, and the postoperative recovery efficiency of patients is higher than 15% and more. This shows that the three-dimensional quality model based on the intelligent processor can improve the important role in the transition period of patients transferred from ICU.

Quality of hospital discharge letters for patients at the end of life: A retrospective medical record review

Objective

For patients who are discharged to go home after a hospitalisation, timely and adequately informing their general practitioner is important for continuity of care, especially at the end of life. We studied the quality of the hospital discharge letter for patients who were hospitalised in their last year of life.

Methods

A retrospective medical record review was performed. Included patients had been admitted to the hospital during the period 1 January to 1 July 2017 and had died within a year after discharge.

Results

Data were collected from records of 108 patients with cancer or other diseases. For 57 patients (53%), the discharge letter included information that related to their limited life expectancy (e.g., agreements about treatment limitations), whereas the patient's limited life expectancy was addressed in the medical record in 76 cases (70%). We found related information in discharge letters for 36 patients (66%) who died <3 months compared to 21 patients (40%) who died 3–12 months after hospitalisation (p < 0.01).

Conclusion

For patients with a limited life expectancy going home after a hospitalisation, one out of two hospital discharge letters lacked any information addressing their limited life expectancy. Specific guidelines for medical information exchange between care settings are needed.

Asking "Meaning Questions" in Evidence-Based Reviews and the Utility of Qualitative Findings in Practice

Evidence-based practice (EBP) systematic reviews are mostly conducted using etiology, diagnosis, therapy, prevention, and prognosis question format. "Meaning" or qualitative questions are very rarely used. The purpose of this article is to discuss qualitative findings' contribution to EBP through asking "meaning questions" in conducting systematic reviews and the utilization of the results to practice. Two EBP systematic review exemplars using meaning questions including the relevance and utilization of qualitative findings in health care decision-making, practice, and policy are presented. There is a need to instill an evidence-based mindset into systematic reviews that balance scientific knowledge gained through empirical research and evidence from qualitative studies. This is turn will increase awareness among clinicians and decision makers on the different ways in which qualitative evidence can be used and applied in practice.

Adverse Events After Transition From ICU to Hospital Ward: A Multicenter Cohort Study

OBJECTIVES

To examine adverse events and associated factors and outcomes during transition from ICU to hospital ward (after ICU discharge).

DESIGN

Multicenter cohort study.

SETTING

Ten adult medical-surgical Canadian ICUs.

PATIENTS

Patients were those admitted to one of the 10 ICUs from July 2014 to January 2016.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Two ICU physicians independently reviewed progress and consultation notes documented in the medical record within 7 days of patient's ICU discharge date to identify and classify adverse events. The adverse event data were linked to patient characteristics and ICU and ward physician surveys collected during the larger prospective cohort study. Analyses were conducted using multivariable logistic regression. Of the 451 patients included in the study, 84 (19%) experienced an adverse event, the majority (62%) within 3 days of transfer from ICU to hospital ward. Most adverse events resulted only in symptoms (77%) and 36% were judged to be preventable. Patients with adverse events were more likely to be readmitted to the ICU (odds ratio, 5.5; 95% CI, 2.4-13.0), have a longer hospital stay (mean difference, 16.1 d; 95% CI, 8.4-23.7) or die in hospital (odds ratio, 4.6; 95% CI, 1.8-11.8) than those without an adverse event. ICU and ward physician predictions at the time of ICU discharge had low sensitivity and specificity for predicting adverse events, ICU readmissions, and hospital death.

CONCLUSIONS

Adverse events are common after ICU discharge to hospital ward and are associated with ICU readmission, increased hospital length of stay and death and are not predicted by ICU or ward physicians.

Adverse events experienced with intrahospital transfer of critically ill patients: A national survey

ABSTRACT

Research that focuses on transfers to and from the intensive care unit (ICU) could highlight important patients' safety issues. This study aims to describe healthcare workers' (HCWs) practices involved in patient transfers to or from the ICU.This cross-sectional study was conducted among HCWs during the Saudi Critical Care Society's annual International Conference, April 2017. Responses were assessed using Likert scales and frequencies. Bivariate analysis was used to evaluate the significance of different indicators.Overall, 312 HCWs participated in this study. Regarding transfer to ICUs, the most frequently reported complications were deterioration in respiratory status (51.4%), followed by deterioration in hemodynamic status (46.5%), and missing clinical information (35.5%). Regarding transfers from ICUs to the general ward, the most commonly reported complications were changes in respiratory status (55.6%), followed by incomplete clinical information (37.9%), and change in hemodynamic conditions (29%). The most-used models for communicating transfers were written documents in electronic health records (69.3%) and verbal communication (62.8%). One-fourth of the respondents were not aware of the Situation, Background, Assessment, Recommendation (SBAR) method of patients' handover. Pearson's test of correlation showed that the HCW's perceived satisfaction with their hospital transfer guidelines showed significant negative correlation with their reported transfer-related complications (r = -0.27, P < .010).Hemodynamic and respiratory status deterioration is representing significant adverse events among patients transferred to or from the ICU. Factors controlling the perceived satisfaction of HCWs involved in patients, transfer to and from the ICU need to be addressed, focusing on their compliance to the hospital-wide transfer and handover policies. Quality improvement initiatives could improve patient safety to transfer patients to and from the ICU and minimize the associated adverse events.

Effectiveness of an Electronic Communication Tool on Transitions in Care From the Intensive Care Unit: Protocol for a Cluster-Specific Pre-Post Trial

BACKGROUND

Transitions in care are vulnerable periods in health care that can expose patients to preventable errors due to incomplete or delayed communication between health care providers. Transitioning critically ill patients from intensive care units (ICUs) to other patient care units (PCUs) is particularly risky, due to the high acuity of the patients and the diversity of health care providers involved in their care. Instituting structured documentation to standardize written communication between health care providers during transitions has been identified as a promising means to reduce communication breakdowns. We developed an evidence-informed, computer-enabled, ICU-specific structured tool-an electronic transfer (e-transfer) tool-to facilitate and standardize the composition of written transfer summaries in the ICUs of one Canadian city. The tool consisted of 10 primary sections with a user interface combination of structured, automated, and free-text fields.

OBJECTIVE

Our overarching goal is to evaluate whether implementation of our e-transfer tool will improve the completeness and timeliness of transfer summaries and streamline communications between health care providers during high-risk transitions.

METHODS

This study is a cluster-specific pre-post trial, with randomized and staggered implementation of the e-transfer tool in four hospitals in Calgary, Alberta. Hospitals (ie, clusters) were allocated randomly to cross over every 2 months from control (ie, dictation only) to intervention (ie, e-transfer tool). Implementation at each site was facilitated with user education, point-of-care support, and audit and feedback. We will compare transfer summaries randomly sampled over 6 months postimplementation to summaries randomly sampled over 6 months preimplementation. The primary outcome will be a binary composite measure of the timeliness and completeness of transfer summaries. Secondary measures will include overall completeness, timeliness, and provider ratings of transfer summaries; hospital and ICU lengths of stay; and post-ICU patient outcomes, including ICU readmission, adverse events, cardiac arrest, rapid response team activation, and mortality. We will use descriptive statistics (ie, medians and means) to describe demographic characteristics. The primary outcome will be compared within each hospital pre- and postimplementation using separate logistic regression models for each hospital, with adjustment for patient characteristics.

RESULTS

Participating hospitals were cluster randomized to the intervention between July 2018 and January 2019. Preliminary extraction of ICU patient admission lists was completed in September 2019. We anticipate that evaluation data collection will be completed by early 2021, with first results ready for publication in spring or summer 2021.

CONCLUSIONS

This study will report the impact of implementing an evidence-informed, computer-enabled, ICU-specific structured transfer tool on communication and preventable medical errors among patients transferred from the ICU to other hospital care units.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03590002; https://www.clinicaltrials.gov/ct2/show/NCT03590002.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18675.

Pediatric Inpatient Problem List Review and Accuracy Improvement

BACKGROUND AND OBJECTIVES

The problem list (PL) is a meaningful use-incentivized criterion for electronic health record documentation. Inconsistent use or inaccuracy of the PL can create communication gaps among providers, potentially leading to diagnostic delays and serious safety events. The objective of the study was to increase the rate of PL review by attending physicians for inpatients discharged from hospital pediatrics and infectious disease services from a baseline of 70% to 80% by June 2018 and to sustain the rate for 6 months. The secondary aim was to improve PL accuracy by decreasing the rate of duplicate codes and red code diagnoses that should resolve before discharge from a baseline of 12% and 11%, respectively, to 5% and sustaining the rate for 6 months.

METHODS

A quality improvement team used the Institute for Healthcare Improvement Model for Improvement. We tracked duplicate codes and red codes as surrogate markers of PL quality. Rates of PL review and PL quality were analyzed monthly via statistical process control charts (p-charts) with 3-σ control limits to identify special cause variation.

RESULTS

PL review improved from a baseline of 70% to 90%, and the change was sustained for 1 year. PL quality improved as duplicate codes at the time of discharge decreased from 12% to 6% and as red codes decreased from a baseline of 11% to 6%.

CONCLUSIONS

The PL is an important communication tool that is underused. By engaging and educating stakeholders, incentivizing compliance, standardizing PL management, leveraging electronic health record enhancements, and providing physician feedback, we improved PL meaningful use and quality.

Transition of care at discharge from the Intensive Care Unit: a scoping review

OBJECTIVE

to map the available evidence on the components of the transition of care, practices, strategies, and tools used in the discharge from the Intensive Care Unit (ICU) to the Inpatient Unit (IU) and its impact on the outcomes of adult patients.

METHOD

a scoping review using search strategies in six relevant health databases.

RESULTS

37 articles were included, in which 30 practices, strategies or tools were identified for organizing and executing the transfer process, with positive or negative impacts, related to factors intrinsic to the Intensive Care Unit and the Inpatient Unit and cross-sectional factors regarding the staff. The analysis of hospital readmission and mortality outcomes was prevalent in the included studies, in which trends and potential protective actions for a successful care transition are found; however, they still lack more robust evidence and consensus in the literature.

CONCLUSION

transition of care components and practices were identified, in addition to factors intrinsic to the patient, associated with worse outcomes after discharge from the Intensive Care Unit. Discharges at night or on weekends were associated with increased rates of readmission and mortality; however, the association of other practices with the patient's outcome is still inconclusive.

Improving Transitions of Care between the Intensive Care Unit and General Internal Medicine Ward. A Demonstration Study

Background: In-hospital transfers such as from the intensive care unit (ICU) to the general internal medicine (GIM) ward place patients at risk of adverse events. A structured handover tool may improve transitions from the ICU to the GIM ward. Objective: To develop, implement, and evaluate a customized user-designed transfer tool to improve transitions from the ICU to the GIM ward. Methods: This was a pre-post intervention study at a tertiary academic hospital. We developed and implemented a user-designed, structured, handwritten ICU-to-GIM transfer tool. The tool included active medical issues, functional status, medications and medication changes, consulting services, code status, and emergency contact information. Transfer tool users included GIM physicians, ICU physicians, and critical care rapid response team nurses. An implementation audit and mixed qualitative and quantitative analysis of pre-post survey responses was used to evaluate clinician satisfaction and the perceived quality of patient transfers. Results: The pre-post survey response rate was 51.8% (99/191). Respondents included GIM residents (58.5%), ICU rapid response team physicians and nurses (24.2%), and GIM attending physicians (17.2%). Less than half of clinicians (48.8%) reported that the preintervention transfer process was adequate. Clinicians who used the transfer tool reported that the transfer process was improved (93.3% vs. 48.8%, P = 0.03). Clinician-reported understanding of medication changes in the ICU increased (69.2% vs. 29.1%, P = 0.004), as did their ability to plan for a safe hospital discharge (69.2% vs. 31.0%, P = 0.01). However, only 64.2% of audited transfers used the tool. Frequently omitted sections included home medications (missing in 83.4% of audits), new medications (33.3%), and secondary diagnosis (33.3%). Thematic analysis of free-text responses identified areas for improvement including clarifying the course of ICU events and enhancing tool usability. Conclusion: A user-designed, structured, handwritten transfer tool may improve the perceived quality of patient transfers from the ICU to the GIM wards.

Going back to the ward-transitioning care back to the ward team

Transition of care from the intensive care unit (ICU) to the ward is usually an indication of the patient's improving clinical status, but is also a time when patients are particularly vulnerable. The transition between care teams poses a higher risk of medical error, which can be mitigated by safe and complete patient handoff and medication reconciliation. ICU readmissions are associated with increased mortality as well as ICU and hospital length of stay (LOS); however tools to accurately predict ICU readmission risk are limited. While there are many mechanisms in place to carefully identify patients appropriate for transfer to the ward, the optimal timing of transfer can be affected by ICU strain, limited resources such as ICU beds, and overall hospital capacity and flow leading to suboptimal transfer times or delays in transfer. The patient and family perspectives should also be considered when planning for transfer from the ICU to the ward. During times of transition, families will meet a new care team, experience uncertainty of future care plans, and adjust to a different daily routine which can lead to increased stress and anxiety. Additionally, a subset of patients, such as those with new technology, require additional multidisciplinary support, education and care coordination which can contribute to longer hospital LOS if not addressed proactively early in the hospitalization while the patient remains in the ICU. In this review article, we describe key components of the transfer from ICU to the ward, discuss current strategies to optimize timing of patient transfers, explore strategies to partner with patients and families during the transfer process, highlight patient populations where additional considerations are needed, and identify future areas of exploration which could improve the care transition from the ICU to the ward.