Discharge

Under current nationwide clinical pressures, hospitals are running at full capacity. Late discharges can lead to poor flow throughout the hospital, overcrowding in the emergency department and out of hours transfers, leading to a poor patient experience and impacts on patient safety. Early morning and afternoon discharges create better flow and improve patient satisfaction, by being home in time for tea. The discharge collaborative within Leeds Teaching Hospitals NHS Trust is a multidisciplinary team (MDT) of junior doctors, pharmacists, nurses and discharge co-ordinators. The aim of the team is to improve discharges in the trust prior to 3pm to 70%. Discharging patients earlier in the day is a complex multifactorial issue which requires an MDT approach. To understand this further a retrospective case note review was conducted to look at avoidable and unavoidable causes of delayed discharges. Each team also received a questionnaire, to discover their perceived barriers to early discharges. This was communicated to teams to empower them to develop their own solutions which were shared within the trust. Run charts of discharges before 3pm are published for each ward in the hospital every two weeks, which is available to wards, but also monitored by the discharge collaborative. Changes to practice include; education of the medical team regarding importance of timely discharge, use of discharge boards, the increase use of discharge lounge, identifying ‘golden patients’ for early morning discharges, prioritisation of community discharges the previous day and achievement recognition for wards with the most improvement. Within the trust, several departments have improved their discharges prior to 3pm through the improvements implemented from the discharge collaborative, including speciality and integrated medicine (SIM), oncology, and trauma services. This project resulted in two step improvements within the Trust with 40% of patients being discharged before 3pm.

Background: Older individuals living with frailty face a heightened risk of experiencing significant deterioration in their mental and physical well-being following seemingly minor health challenges. Our aim was to assess and enhance the practice of the Clinical Frailty Scale (CFS) during inpatient assessments within a large teaching hospital.
Methods: We conducted 2 cycles of retrospective data collection within a single centre setting, screening a total of 600 patients focussing on; age ≥65, level of frailty, location of CFS assessment - Emergency Department (ED), Medical Assessment Unit (MAU); and the health-care professionals involved in CFS practice. We compared practices amongst young-old (65-74), middle-old (75-84), and old-old (≥ 85) age groups.  
Results: The CFS documentation rate for eligible patients was 76.7% in the first cycle, involving 240 patients, and 83% in the second cycle which included 247 patients, whereas the rate for the above-mentioned age sub-groups was 13.8%, 67.7%, 98.3% respectively. The prevalence of frailty amongst the age sub-groups was 74.1%, 84.7%, and 93.9% respectively, while male-to-female prevalence was 88.9% and 89.2%. Overall, 72.7% of the CFS assessments were completed in ED. The Frailty Interface Team (FIT) significantly contributed to the CFS assessment by completing 58.1% of overall assessments.
Conclusion: The results underscore the significance of integrating frailty education into core teachings to enhance CFS practice among junior doctors. Identifying inpatient frailty in the 65-74 age group is crucial, as they are frailer than initially perceived and will further decline with aging. Interdisciplinary collaboration is essential, particularly a specialized FIT, proving pivotal in CFS practice within our hospital. Larger studies into inpatient frailty in the young-old age groups are recommended. 

Background

Nationally, the average rate of discharges drops by over a third over the weekend and prioritising these discharges is recognised by NHS England in improving patient care and facilitating the flow of patients through the hospital.(1)

Aims

To assess the documentation of criteria for discharge in Care of the Elderly wards for patients who were identified as having an estimated date of discharge within 72 hours and could be discharged over the weekend.Guidance from NHS England recommends clear plans to be documented in all patients notes detailing social, physiological and functional criteria for discharge.(1)

Methods

We performed a closed loop audit on the documentation of criteria for discharge for all patients on the Care of The Elderly wards identified as having an estimated date of discharge within 72 hours during the Friday morning multidisciplinary team (MDT) meeting.

We looked at whether criteria for discharge were documented, whether to take out medications (TTOs) were prepared and whether patients identified went on to be discharged. 

Intervention

We provided the pre-existing Criteria-Led Discharge Tool to doctors present at the Friday MDT to document criteria for weekend discharge under the supervision of a senior decision maker.

Results

A total of 100 patients were identified as suitable for weekend discharge over the data collection period. Interim results show that following the intervention, documentation of criteria for discharge rose by 34% (31% - 65%). 

References

1. NHS England. Rapid improvement guide to improving weekend discharges. Available from: https://transform.england.nhs.uk/improvement/100-day-discharge-challeng…

Introduction

We plan fast-track discharges when a person has limited life expectancy and is reaching end of life. When such patients are identified, we use a simple fast-track tool to minimise the delay and reduce the need for in-depth assessments and paperwork. Despite being used very widely, there is very little data in literature regarding the indications for fast-track discharges and life expectancy of patients following discharge. We conducted this observational study to answer these questions.

Methods

We collected data over a three month period from the fast-track applications focusing on indications, length of survival post discharge and what has been communicated to the families.

Results

There were 45 discharges during the three month period. The mean age was 79.6 (range 32 – 98). Most of the applications were made from the medical wards (32), especially from the care of the elderly wards, followed by surgical and the emergency quarter. 10 patients died in the hospital before their discharge could be processed. 17 patients went home, 14 went to a care home and 4 went to a community setting. 23 patients had malignancy, 11 had end organ failure, 6 had advanced dementia, 3 had stroke and 2 had fracture neck of femur. After excluding the patients who died in the hospital, the mean survival following discharge was 15.9 days (1-77 days) and 5 patients were still alive at 90 days. Evidence for good communication with families was lacking from the application forms.

Discussion

Malignancy is the most common reason for fast-track discharges. Even though many patients and families think that end of life means only days or weeks, many survive much longer. We need better documentation regarding communication with patients and families regarding diagnosis and prognosis. 

Introduction : 

The delayed discharge is defined as patient is deemed medically fit to leave hospital but is unable to do so for non-medical reasons. Delayed discharges are associated with mortality, infection, depression, reduction in patients' mobility and their daily activities. 

Aim and Objectives:

1.Recognition of different causes of discharge delays will allow health professionals, hospital administrators to propose potential strategies for minimising delays. 2.To identify causes of prolong delays in discharge among elderly patients.3. To propose strategies for eliminating advisable delays and improving healthcare delivery as well as patient flow process.

Methods:

Total 29 patients' data were collected at the same time. The average length of admission was 32 days. The data were collected to assessed likely presence of delayed discharges and reason for delayed discharges.

Results:

Total 19/29 ( 65% ) were medically fit for discharge (MFFD) and 10/29 ( 35% ) were not MFFD. The average length of time since being declared MFFD was 16days. The reasons for delayed discharges are awaiting POC (32%), awaiting placement (26%), awaiting furniture arrangement at home (10%), awaiting mental capacity assessment from social worker (10%), awaiting equipment delivery (5%), awaiting safeguarding outcomes (5%), awaiting family to find a property to be discharged (5%), family refused equipment (5%).

Recommendations

The recommendations are 1.completing early assessment of onward care needs and recognising the potential needs for either rehabilitation, home assessment for safety and need equipment or residential/nursing home. 2. Early discussion with patients and/or families to reduce the disagreement 3. Early communication with community teams like social worker and CCG by discharge team.

Conclusion

It is important to achieve the correct balance between minimising delays and not discharging patients from hospital before they are clinically ready.

Introduction:

Major trauma including Traumatic Brain Injury (TBI) is an increasingly common cause of hospitalisation in older adults. We studied post-discharge recovery from TBI using a remote healthcare monitoring system that captures data on activity and sleep. We aim to assess the feasibility and acceptability of this technology to monitor recovery at home following a significant acute clinical event in Older adults.

Methods:

We installed Minder, a remote healthcare monitoring system, in recently discharged patients >60 years with moderate-severe TBI. We present descriptive analyses of post-discharge recovery for two males, corroborating data from Minder against verified activities and events. We recorded semi-structured interviews assessing acceptability.

Results:

We present 6 months of sleep and activity data from Minder and feedback from interviews. Data observed from Participant 1 revealed habitual patterns of activity and sleep. These remained stable, despite discrete clinical events. Conversely, Participant 2's data revealed irregular sleep patterns that became increasingly fragmented. Activity was detected in multiple rooms throughout the house at night, consistent with carer reports of night-time wandering. Increased overnight activity coincided with multiple falls, prompting increased care provision. Initial feedback from interviews was the technology helped participants and those involved in their care feel supported.

Conclusions:

As pressure on services mounts, novel approaches to post-discharge care are of increasing importance. Remote healthcare monitoring can provide high temporal resolution data offering ‘real world’ insights into the effects of significant health events in Older adults. Our provisional results support our hypothesis that use of this technology is feasible and acceptable for frail, multi-morbid participants and highlights the substantial potential of this technology to help clinicians improve community-based care and more effectively monitor interventions and chronic conditions.