Delay of transfer from the intensive care unit: a prospective observational analysis on economic effects of delayed in-house transfer

Application of a Human Factors Systems Approach to Healthcare Control Centres for Managing Patient Flow: A Scoping Review

Over the past decade, healthcare systems have started to establish control centres to manage patient flow, with a view to removing delays and increasing the quality of care. Such centres-here dubbed Healthcare Capacity Command/Coordination Centres (HCCCs)-are a challenge to design and operate. Broad-ranging surveys of HCCCs have been lacking, and design for their human users is only starting to be addressed. In this review we identified 73 papers describing different kinds of HCCCs, classifying them according to whether they describe virtual or physical control centres, the kinds of situations they handle, and the different levels of Rasmussen's [1] risk management framework that they integrate. Most of the papers (71%) describe physical HCCCs established as control centres, whereas 29% of the papers describe virtual HCCCs staffed by stakeholders in separate locations. Principal functions of the HCCCs described are categorised as business as usual (BAU) (48%), surge management (15%), emergency response (18%), and mass casualty management (19%). The organisation layers that the HCCCs incorporate are classified according to the risk management framework; HCCCs managing BAU involve lower levels of the framework, whereas HCCCs handling the more emergent functions involve all levels. Major challenges confronting HCCCs include the dissemination of information about healthcare system status, and the management of perspectives and goals from different parts of the healthcare system. HCCCs that take the form of physical control centres are just starting to be analysed using human factors principles that will make staff more effective and productive at managing patient flow.

Original Research: Breaking Through the Bottleneck: Acuity Adaptability in Noncritical Trauma Care

BACKGROUND

Achieving efficient throughput of patients is a challenge faced by many hospital systems. Factors that can impede efficient throughput include increased ED use, high surgical volumes, lack of available beds, and the complexities of coordinating multiple patient transfers in response to changing care needs. Traditionally, many hospital inpatient units operate via a fixed acuity model, relying on multiple intrahospital transfers to move patients along the care continuum. In contrast, the acuity-adaptable model allows care to occur in the same room despite fluctuations in clinical condition, removing the need for transfer. This model has been shown to be a safe and cost-effective approach to improving throughput in populations with predictable courses of hospitalization, but has been minimally evaluated in other populations, such as patients hospitalized for traumatic injury.

PURPOSE

This quality improvement project aimed to evaluate implementation of an acuity-adaptable model on a 20-bed noncritical trauma unit. Specifically, we sought to examine and compare the pre- and postimplementation metrics for throughput efficiency, resource utilization, and nursing quality indicators; and to determine the model's impact on patient transfers for changes in level of care.

METHODS

This was a retrospective, comparative analysis of 1,371 noncritical trauma patients admitted to a level 1 trauma center before and after the implementation of an acuity-adaptable model. Outcomes of interest included throughput efficiency, resource utilization, and quality of nursing care. Inferential statistics were used to compare patients pre- and postimplementation, and logistic regression analyses were performed to determine the impact of the acuity-adaptable model on patient transfers.

RESULTS

Postimplementation, the median ED boarding time was reduced by 6.2 hours, patients more often remained in their assigned room following a change in level of care, more progressive care patient days occurred, fall and hospital-acquired pressure injury index rates decreased respectively by 0.9 and 0.3 occurrences per 1,000 patient days, and patients were more often discharged to home. Logistic regression analyses revealed that under the new model, patients were more than nine times more likely to remain in the same room for care after a change in acuity and 81.6% less likely to change rooms after a change in acuity. An increase of over $11,000 in average daily bed charges occurred postimplementation as a result of increased progressive care-level bed capacity.

CONCLUSIONS

The implementation of an acuity-adaptable model on a dedicated noncritical trauma unit improved throughput efficiency and resource utilization without sacrificing quality of care. As hospitals continue to face increasing demand for services as well as numerous barriers to meeting such demand, leaders remain challenged to find innovative ways to optimize operational efficiency and resource utilization while ensuring delivery of high-quality care. The findings of this study demonstrate the value of the acuity-adaptable model in achieving these goals in a noncritical trauma care population.

Level of Care Appropriateness in VA Inpatient Surgery Cases

PURPOSE OF STUDY

Within the Veterans Health Administration, utilization management (UM) focuses on reducing unnecessary or inappropriate hospitalizations by applying evidence-based criteria to evaluate whether the patient is placed in the right level of care. This study examined inpatient surgery cases to classify reasons for not meeting criteria and to identify the appropriate level of care for admissions and subsequent bed days of care.

PRIMARY PRACTICE SETTINGS

There were 129 VA Medical Centers in which inpatient UM reviews were performed during that time, of which 109 facilities had UM reviews conducted in Surgery Service.

METHODOLOGY AND SAMPLE

All admissions to surgery service during fiscal year 2019 (October 1, 2018 to September 30, 2019) that had a UM review entered in the national database were extracted, including current level of care, recommended level of care, and reasons for not meeting criteria. The following demographic and diagnostic fields were supplemented from a national data warehouse: age, gender, marital status, race, ethnicity, and service connection status. Data were analyzed with descriptive statistics. Characteristics of patient demographics were compared using the χ2 test for categorical variables and the Student's t test.

RESULTS

A total of 363,963 reviews met conditions to be included in the study: 87,755 surgical admission reviews and 276,208 continued stay reviews. There were 71,274 admission reviews (81.22%) and 198,521 (71.87%) continued stay reviews that met the InterQual criteria. The primary reason for not meeting admission criteria was clinical variance (27.70%), followed by inappropriate level of care (26.85%). The leading reason for not meeting continued stay criteria was inappropriate level of care (27.81%), followed by clinical instability (25.67%). Of the admission reviews not meeting admission criteria, 64.89% were in the wrong level of care and 64.05% of continued stay reviews were also in the wrong level of care. Half of the admission reviews not meeting criteria had a recommended level of care as home/outpatient (43.51%), whereas nearly one-third (28.81%) continued stay reviews showed a recommended level of care of custodial care or skilled nursing.

IMPLICATIONS FOR CASE MANAGEMENT PRACTICE

This study identified system inefficiencies through admission and continued stay reviews of surgical inpatients. Patients admitted for ambulatory surgery or for preoperative testing prior to day of surgery resulted in avoidable bed days of care that may have contributed to patient flow issues and limited the available hospital beds for other patients. Through early collaboration with case management and care coordination professionals, alternatives can be explored that safely address the patient needs, such as temporary lodging options. There may be conditions or complications that can be anticipated on the basis of patient history. Proactive efforts to address these conditions may help avoid unnecessary bed days and extended lengths of stay.

Establishing critical care nursing research priorities for three Australian regional public hospitals: A mixed method priority setting study

OBJECTIVE

To determine key priorities for critical care nursing research in three Australian regional public hospitals, representing the shared priorities of healthcare professionals and patient representatives.

METHODS

A three phase priority setting study, including consensus methods (nominal group), survey, qualitative interviews and focus groups were conducted between May 2021 and March 2022. Healthcare professionals and patient representatives from critical care units in regional public hospitals in Australia participated. A patient representative contributed to research design and co-authored this paper.

RESULTS

In phase one, 29 research topics were generated. In phase two, during a nominal group ranking process, the top 5 priority areas for each site were identified. In the final phase, three themes from focus groups and interviews included patient flow through intensive care, patient care through intensive care journey and intensive care patient recovery.

CONCLUSION

Identifying context specific research priorities through a priority setting exercise provides insight into the topics that are important to healthcare professionals and to patients in critical care. The top research priorities for nursing research in critical care in regional Australian hospitals include patient flow, patient recovery, and evidence based patient care through the intensive care journey, such as delirium management, pain and sedation, and mobilisation. These shared priorities will be used to guide future nursing research in critical care over the next 3-5 years.

IMPLICATIONS FOR CLINICAL PRACTICE

The method we used in identifying the research priorities can be used by other researchers and clinicians; close collaboration among researchers and clinicians will be beneficial for practice improvement; and how we can be reassured that our practice is evidence based is worthy of attention.

Delayed Discharge From the Intensive Care Unit Is Associated With Longer Hospital Lengths of Stay

OBJECTIVE

The study authors sought to determine if delayed discharge from the intensive care unit (ICU) secondary to a lack of floor beds led to longer postoperative hospital length of stay (LOS) or more hospital readmissions.

DESIGN

A retrospective study comparing patients with delayed discharge from the ICU to patients without delayed discharge.

SETTING

At a cardiovascular ICU in a tertiary care university hospital.

PARTICIPANTS

A total of 5,777 patients that were ready for discharge from the ICU after recovering from cardiac surgery.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The authors used linear regression to measure postoperative hospital LOS and logistic regression to measure hospital readmission in patients whose transfer out of the ICU was delayed at least overnight to patients who were transferred out the same day. There were 3,903 patients transferred to the stepdown unit on the same day as the transfer order and 1,874 patients were transferred on a subsequent day. The postoperative LOS was shorter in the no delay group (9 ± 9 v 11 ± 10 days, standardized difference = 0.162), whereas the stepdown unit stay was similar (6 ± 6 v 5 ± 6 days, standardized difference = 0.076). The readmission rates were 15% in the no delay group versus 14% in the delayed discharge group (standardized difference = 0.032). After adjustment, the authors found by linear regression that delayed discharge was associated with an increase (0.72 [95% CI 0.43-1.01] days, p < 0.001) in postoperative LOS but was not associated with readmission.

CONCLUSIONS

The study authors found that patients who had their discharge from the ICU delayed had an increased hospital LOS but a similar rate of hospital readmission.

The impact of tracheostomy delay in intensive care unit patients: a two-year retrospective cohort study

Aims

This study was undertaken to evaluate our tracheostomy service and identify reasons for any delays.

Methods

A retrospective study in an academic tertiary-care hospital in Jeddah, Saudi Arabia. Inclusion criteria were any patients in ICU who required a surgical tracheostomy over a 2-year period (January 2014 to December 2015). The primary outcome was delayed tracheostomy referral and secondary outcomes included the number of days between referral and consultation, days between consultation and tracheostomy placement, and mortality rates.

Results

Ninety-nine patients had a tracheostomy between January 2014 to December 2015 and could be analysed, mean age of 52.7 years, 44.5% females. The average duration from referral to tracheostomy was 5.12 days (SD 6.52). Eighteen patients (18.2%) had delayed tracheostomy (> 7 days from referral). The main reasons for the delay were the patient’s medical condition (50%, n = 9), followed by low haemoglobin (38.9%, n = 7). Administrative reasons were recorded in 5 cases only (28%); 2 due to operating room lack of time, 2 due to multidisciplinary issues, and 1 due to family refusal. Laboratory-confirmed low haemoglobin, a prescription of anti-platelets, or a prescription of anti-coagulation were not associated with a longer duration between referral and tracheostomy placement. An increase of 1 day in the time between referral and tracheostomy corresponded to an increase in delay in discharge from ICU of 1.24 days (95% CI 0.306 to 2.18).

Conclusion

Although most delays related to the clinical condition of the patient, administrative and multidisciplinary factors also play a role. Early tracheostomy (less than 14 days) from intubation increases the survival rates of patients and improves their clinical outcomes. Further prospective evaluation is needed to confirm the impact of delay in performing surgical tracheostomy among ICU patients whose bedside percutaneous tracheostomy is contraindicated.

Evaluation of a Standardized Protocol for Medical Management of Uncomplicated Acute Type B Aortic Dissection

OBJECTIVES

The goals of medical management for uncomplicated acute type B aortic dissection are to prevent expansion of the false lumen and malperfusion syndrome. This is accomplished with antihypertensive agents, but medication selection and titration are typically provider dependent. Given the paucity of data on evidence-based management of this population, we hypothesized that a standardized type B aortic dissection medical management protocol would reduce resource utilization and costs, without compromising patient outcomes.

METHODS

A multidisciplinary team developed a goal-directed protocol to standardize the medical management of uncomplicated acute type B aortic dissection, with an emphasis on early initiation of oral medications, weaning of anti-hypertensive infusions and frequent assessment for de-escalation of care. Implementation was in April 2018. A retrospective review of acute type B aortic dissection patients presenting to our institution from April 2016- April 2020 was performed. Patients requiring aortic or peripheral intervention were excluded. Included patients were analyzed based on treatment before or after protocol implementation. Patient demographics, systolic blood pressure, presence of acute kidney injury at presentation, length of stay, cost metrics, and 30-day mortality were compared.

RESULTS

39 patients were included, 21 pre- and 18 post-protocol implementation. Baseline demographics, systolic blood pressure, and presence of acute kidney injury at presentation were similar between the groups. Post-protocol patients had shorter total (8.6 vs 5.5 days, p=.02) and intensive care unit (3.2 vs 1.8 days, p=.002) length of stay. The protocol was associated with significantly decreased total hospital ($38,928 vs $28,066, p=.04), total variable ($23,115 vs $15,627, p=0.02), and pharmacy ($5,094 vs $1,181, p<.001) costs, while inpatient care costs ($15,152 vs $11,467, p=.09) trended down. Post-protocol patients required fewer oral antihypertensive agents at discharge (3.8 vs 2.7, p=.005). No significant difference in 30-day mortality was observed.

CONCLUSIONS

A goal directed protocol reduces resource utilization and costs without compromising early mortality rates for patients with uncomplicated acute type B aortic dissection. Such a strategy may have broader application in medical management of acute aortic syndromes.

Impact of Intensive Care Unit Discharge Delay on Liver Transplantation Outcomes

Background: For general intensive care unit (ICU) patients, ICU discharge delay (ICUDD) has been associated with an increased hospital length of stay (LOS) and the acquisition of multi-resistant organism (MRO) infections. The impact of ICUDD on liver transplant (LT) recipients is unknown. Methods: We retrospectively studied consecutive adult LT between 2011 and 2019. ICUDD was defined as >8 h between a patient being cleared for discharge to ward and the patient leaving the ICU. Results: 550 patients received LT and the majority (68.5%) experienced ICUDD. The median time between clearance for ward and the patient leaving the ICU was 25.6 h. No donor or recipient variables were associated with ICUDD. Patients cleared for discharge early in the week (Sunday-Tuesday) and those discharged outside routine work hours were more likely to experience ICUDD (p = 0.001 and p < 0.001, respectively). The median hospital LOS was identical (18 days, p = 0.96) and there were no differences in other patient outcomes. Patients who became colonized with MRO in the ICU spent a longer time there compared to those who remained MRO-free (9 vs. 6 days, p < 0.001); however, this was not due to ICUDD. Conclusion: ICUDD post-LT is common and does not prolong hospital LOS. ICUDD is not associated with adverse patient outcomes or MRO colonization.

Reducing PICU-to-Floor Time-to-Transfer Decision in Critically Ill Bronchiolitis Patients using Quality Improvement Methodology

Supplemental Digital Content is available in the text.

Introduction:

Specific criteria for de-escalation from the PICU are often not included in viral bronchiolitis institutional pathways. Variability of transfer preferences can prolong PICU length of stay. We aimed to decrease the time from reaching floor-appropriate heated high flow nasal cannula (HHF) settings to the transfer decision by 20% through standardizing PICU-to-floor transfer assessment in a PICU bronchiolitis cohort.

Methods:

We included PICU bronchiolitis admissions from October 2019 to April 2020, who were 6-months to 2-years-old with no comorbidities nor intubation during their encounter. Our intervention bundle included introduction of transfer criteria and standardization of transfer-readiness assessment. The primary outcome was time from reaching floor-appropriate HHF settings [8 L per minutes (Lpm)] to placement of the transfer order (“time-to-transfer decision”). The secondary outcome was PICU length of stay. The main process measure was the proportion of patients transferred on ≥6 Lpm HHF. Balancing measures included Rapid Response Team activation and unplanned PICU readmission. We assessed admissions meeting inclusion criteria from December, 2018-March, 2019 for the preintervention baseline.

Results:

Special cause variation indicated improvement in our primary outcome and process measures. Comparison of baseline to postintervention revealed a reduction in median time-to-transfer decision (14.4–7.8 hours; P < 0.001) and increase in children transferred on ≥6 Lpm (51%–72%; P < 0.001). We observed no change in PICU length of stay or balancing measures.

Conclusion:

Standardizing de-escalation criteria and transfer-readiness assessment reduced the time-to-transfer decision out of the PICU and increased the proportion transferred on ≥6 Lpm HHF for children with viral bronchiolitis without increasing PICU readmissions.

A scheduling-based methodology for improving patient perceptions of quality of care in intensive care units

Research has found that hospitals with better scores on patient experience of care surveys have better patient safety records and outcomes. Therefore, targeting ways of improving patient experience of care is becoming relevant for hospitals not only for the patient health outcomes but also for the financial implications. Therefore, the goal of this paper is to develop new operation management strategies for improving patient experience of care in intensive care units (ICUs). A new scheduling-based methodology is developed that considers two of the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey dimensions, doctor communication and discharge information. Two hypotheses are studied. The first hypothesis postulates that to improve doctor communication with the patient, a nurse must be present in the patient room when the doctor performs ward rounds. The second hypotheses states that to improve the patient-doctor communication of discharge information aspect, doctors must see the patient expected to be discharged early in the day. A computational study is performed to gather insights and to measure the performance of the scheduling-based methodology on a case study from an intensive care unit located in a hospital in central Texas. The results show hospital improvement in the studied dimensions of the HCAHPS survey after 1 year of the hospital adoption of the study recommendations.

Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources

This paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is developed in order to find the best allocation for ICU beds, considering candidate patients with suspected/confirmed COVID-19. Experts' subjective knowledge and prior probabilities are considered to estimate the input data for the proposed model, considering the particular aspects of the decision problem. Since the chances of survival of patients in several scenarios may not be precisely defined due to the inherent subjectivity of such kinds of information, the proposed model works based on imprecise information provided by users. A Monte-Carlo simulation is performed to build a recommendation, and a robustness index is computed for each alternative according to its performance as evidenced by the results of the simulation.

The Association between Discharge Delay from Intensive Care and Patient Outcomes

Rationale: ICU discharge delay occurs when a patient is considered ready to be discharged but remains in the ICU. The effect of discharge delay on patient outcomes is uncertain.Objectives: To investigate the association between discharge delay and patient outcomes including hospital mortality, readmission to ICU, and length of hospital stay after ICU discharge.Methods: Data were accessed from the Australian and New Zealand Intensive Care Society Adult Patient Database between 2011 and 2019. Descriptive analyses and hierarchical logistic and Cox proportional hazards regression were used to examine association between discharge delay and adjusted outcomes. Patients were stratified and analyzed by categories of mortality risk at ICU admission.Measurements and Main Results: The study included 1,014,540 patients from 190 ICUs: 756,131 (75%) were discharged within 6 hours of being deemed ready, with 137,042 (13%) discharged in the next 6 hours; 17,656 (2%) were delayed 48-72 hours; 31,389 (3.1%) died in hospital; and 45,899 (4.5%) patients were readmitted to ICU. Risk-adjusted mortality declined with increasing discharge delay and was lowest at 48-72 hours (adjusted odds ratio, 0.87; 95% confidence interval, 0.79-0.94). The effect was seen in patients with predicted risk of death on admission to ICU of greater than 5% (adjusted odds ratio, 0.77; 95% confidence interval, 0.70-0.84). There was a progressive reduction in adjusted odds of readmission with increasing discharge delay.Conclusions: Increasing discharge delay in ICUs is associated with reduced likelihood of mortality and ICU readmission in high-risk patients. Consideration should be given to delay the discharge of patients with high risk of death on ICU admission.

Assessment of Costs of Avoidable Delays in Intensive Care Unit Discharge

IMPORTANCE

Delays in transfer for discharge-ready patients from the intensive care unit (ICU) are increasingly described and contribute to strained capacity.

OBJECTIVE

To describe the epidemiological features and health care costs attributable to potentially avoidable delays in ICU discharge in a large integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study was performed in 17 adult ICUs in Alberta, Canada, from June 19, 2012, to December 31, 2016. Participants were patients 15 years or older admitted to a study ICU during the study period. Data were analyzed from October 19, 2018, to May 20, 2020.

EXPOSURES

Avoidable time in the ICU, defined as the portion of total ICU patient-days accounted for by avoidable delay in ICU discharge (eg, waiting for a ward bed).

MAIN OUTCOMES AND MEASURES

The primary outcome was health care costs attributable to avoidable time in the ICU. Secondary outcomes were factors associated with avoidable time, in-hospital mortality, and measures of use of health care resources, including the number of hours in the ICU and the number of days of hospitalization. Multilevel mixed multivariable regression was used to assess associations between avoidable time and outcomes.

RESULTS

In total, 28 904 patients (mean [SD] age, 58.3 [16.8] years; 18 030 male [62.4%]) were included. Of these, 19 964 patients (69.1%) had avoidable time during their ICU admission. The median avoidable time per patient was 7.2 (interquartile range, 2.4-27.7) hours. In multivariable analysis, male sex (odds ratio [OR], 0.92; 95% CI, 0.87-0.98), comorbid hemiplegia or paraplegia (OR 1.47; 95% CI, 1.23-1.75), liver disease (OR 1.20; 95% CI, 1.04-1.37), admission Acute Physiology and Chronic Health Evaluation II score (OR, 1.03; 95% CI, 1.02-1.03), surgical status (OR, 0.90; 95% CI, 0.82-0.98), medium community hospital type (OR, 0.12; 95% CI, 0.04-0.32), and admission year (OR, 1.16; 95% CI, 1.13-1.19) were associated with avoidable time. The cumulative avoidable time was 19 373.9 days, with estimated attributable costs of CAD$34 323 522. Avoidable time accounted for 12.8% of total ICU bed-days and 6.4% of total ICU costs. Patients with avoidable time before ICU discharge showed higher unadjusted in-hospital mortality (1115 [5.6%] vs 392 [4.4%]; P < .001); however, in multivariable analysis, avoidable time was associated with reduced in-hospital mortality (adjusted hazard ratio, 0.74; 95% CI, 0.64-0.85). Results were similar in sensitivity analyses.

CONCLUSIONS AND RELEVANCE

In this study, potentially avoidable discharge delay occurred for most patients admitted to ICUs across a large integrated health system and translated into substantial associated health care costs.