Are we able to predict who needs a bed the most?

2018 ◽  
Vol 17 (3) ◽  
pp. 120-120
Author(s):  
MNT (Marjolein) Kremers ◽  
◽  
Prabath WB Nanayakkara ◽  

In recent years we indeed have witnessed an increasing demand on healthcare services coupled with spiraling healthcare costs forcing us towards identifying factors and interventions leading to greater healthcare efficiency. The case mix of our ED patients is changing with an increase in the number of the elderly needing acute (hospital) care, often suffering from multiple comorbidities leading to simple problems becoming easily complex and demanding admission. Partly due to this changing case mix, acute bed capacity is under serious pressure leading to ED stagnation and increased waiting times internationally. When the ED is at its capacity, acute physicians have to make choices how to divide the few available beds. Are we able to predict who needs a bed the most and make justified decisions? Which patient can wait at the ED before admission and which ones can’t? The study of Byrne et al. in this issue focused on the association between ED waiting times and clinical outcomes in Ireland, measured by 30 days mortality, using patient data of admitted acute medical patients collected from 2002 until 2017. High Risk Score patients with a longer waiting time at the ED, appear to have an increased risk on mortality. It is therefore necessary to identify these patients early and prioritize their hospital admission. However, to our knowledge, the used risk score isn’t implemented in daily practice. In 2012 the National Early Warning Score (NEWS) has been broadly implemented and it would be of interest to know whether the used retrospective Risk Score using laboratory data accord to the NEWS. Curiously, in this study, patients in all three MTS urgent categories with <4 hours waiting time, have a higher risk on mortality than patients experiencing a longer waiting time. What’s the cause of this effect? Are patients so severely ill that urgent treatment and admission can’t change the adverse outcome? Or is it possible that all three urgent MTS categories identify patients who are sicker with a higher chance of dying? Intriguingly, in Ireland the mortality amongst admitted acute medical patients decreased since 2002 by 1.3%. An important question remained unanswered by Byrne et al: why has this mortality decreased? Has the severity of the diseases by urgently admitted patients diminished? Has the treatment for acute medical patients been improved? Don’t severely ill patients come to the ED anymore, due to proper advanced care planning? In contrast to the decreased mortality, the median waiting times >6 hours have increased by 50%, from 10 to 15 hours. What caused this increase? What happened in the acute care in Ireland? Have other European countries experienced the same effect or can’t the Irish results not being extrapolated to other European acute care systems? For example, in the Netherlands, the total number of patients being seen at the ED has decreased and stabilised in the last years, although the number of acute medical patients, especially elderly, is increasing. During the last flu season patients we were faced with ED closures, long length of stay and overnight ED stays due to the lack of beds in-hospital. However, waiting hours >12 hours at the ED are rare in Dutch EDs. A key factor in constraining the patient flow to the ED is the well-functioning primary care system with adequate out of office hours care by GP-posts. When a GP post is placed at an ED, GPs treat 75% of the self-referred patient, which is safe and cost-effective. Due to this the ED`s can concentrate on the sick patients who need urgent care. Despite the decreased patient flow to the ED in the Netherlands, the organisation of the acute care has gained much attention of policy makers, media and health care professionals due to frequent ED closures and stagnation in some regions in the Netherlands. Recently, a prediction model for hospital admission in a mixed ED population has been established by using data directly available after triage, aiming to use for shortening the Length of Stay (LOS) at the ED. A computerised tool calculates admission probability for any patient at the time of triage by using age, triage category, arrival mode and main symptom. It demonstrates that different European countries are facing the same issues and are trying to optimize the acute care with some overlapping focus. We believe that at a time where the demand on acute care is increasing, it’s essential to pay attention to the organisation of acute care so that high-quality care is guaranteed and the available resources should be handled efficiently. Studies such as executed by Byrne et al. contribute to this topic and provide lessons which can be learned internationally. We need tools to identify sick patients who need properly care on time and acute physicians can play a central role in developing these tools.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Alowad ◽  
Premaratne Samaranayake ◽  
Kazi Ahsan ◽  
Hisham Alidrisi ◽  
Azharul Karim

PurposeThe purpose of this paper is to systematically investigate the patient flow and waiting time problems in hospital emergency departments (EDs) from an integrated voice of customer (VOC) and voice of process (VOP) perspective and to propose a new lean framework for ED process.Design/methodology/approachA survey was conducted to better understand patients' perceptions of ED services, lean tools such as process mapping and A3 problem-solving sheets were used to identify hidden process wastes and root-cause analysis was performed to determine the reasons of long waiting time in ED.FindingsThe results indicate that long waiting times in ED are major concerns for patients and affect the quality of ED services. It was revealed that limited bed capacity, unavailability of necessary staff, layout of ED, lack of understanding among patients about the nature of emergency services are main causes of delay. Addressing these issues using lean tools, integrated with the VOC and VOP perspectives can lead to improved patient flow, higher patient satisfaction and improvement in ED capacity. A future value stream map is proposed to streamline the ED activities and minimize waiting times.Research limitations/implicationsThe research involves a relatively small sample from a single case study. The proposed approach will enable the ED administrators to avoid the ED overcrowding and streamline the entire ED process.Originality/valueThis research identified ED quality issues from the integration of VOC and VOP perspective and suggested appropriate lean tools to overcome these problems. This process improvement approach will enable the ED administrators to improve productivity and performance of hospitals.


2006 ◽  
Vol 30 (4) ◽  
pp. 525 ◽  
Author(s):  
Debra O'Brien ◽  
Aled Williams ◽  
Kerrianne Blondell ◽  
George A Jelinek

Objective: Fast track systems to stream emergency department (ED) patients with low acuity conditions have been introduced widely, resulting in reduced waiting times and lengths of stay for these patients. We aimed to prospectively assess the impact on patient flows of a fast track system implemented in the emergency department of an Australian tertiary adult teaching hospital which deals with relatively few low acuity patients. Methods: During the 12-week trial period, patients in Australasian Triage Scale (ATS) categories 3, 4 and 5 who were likely to be discharged were identified at triage and assessed and treated in a separate fast track area by ED medical and nursing staff rostered to work exclusively in the area. Results: The fast track area managed 21.6% of all patients presenting during its hours of operation. There was a 20.3% (?18 min; 95%CI, ?26 min to ?10 min) relative reduction in the average waiting time and an 18.0% (?41 min; 95%CI, ?52 min to ?30 min) relative reduction in the average length of stay for all discharged patients compared with the same period the previous year. Compared with the 12-week period before the fast track trial, there was a 3.4% (?2.1 min; 95%CI, ?8 min to 4 min) relative reduction in the average waiting time and a 9.7% (?20 min; 95%CI, ?31 min to ?9 min) relative reduction in the average length of stay for all discharged patients. There was no increase in the average waiting time for admitted patients. This was despite major increases in throughput and access block in the study period. Conclusion: Streaming fast track patients in the emergency department of an Australian tertiary adult teaching hospital can reduce waiting times and length of stay for discharged patients without increasing waiting times for admitted patients, even in an ED with few low acuity patients.


1996 ◽  
Vol 15 (11) ◽  
pp. 915-919 ◽  
Author(s):  
Shl Thomas ◽  
S. Lewis ◽  
L. Bevan ◽  
S. Bhattacharyya ◽  
MG Bramble ◽  
...  

1 Poisoning is a common reason for presentation to hospital and hospital admission but there is no agreed policy for managing these patients. This study exam ined the management of patients presenting with poisoning and the factors affecting the probability of hospital admission and prolonged stay. 2 Data on all cases of poisoning presenting to six Accident and Emergency departments in the North East of England over 12 weeks in 1994 was collected prospectively from A&E notes. Length of stay and outcome were recorded from hospital computer records. 3 Overall, 73% of patients were admitted to a medical ward. Probability of admission was not independently affected by age or gender but was increased in those with intentional poisoning (Odds Ratio (OR) 3.3 [95% CI 1.8, 6.1]), a history of self harm (OR 1.7, [1.0, 2.9]) or potentially hazardous poisoning (OR 3.7 [2.1, 6.6]). There were significant variations between hospitals (50 - 80%) which could not be attributed to case mix. 4 Prolonged stay ( > 2 nights) was more common in patients over 65 years (OR 6.8 [2.9, 16.1]), those with intentional poisoning (OR 2.7 [1.1, 6.6]) and those with potentially hazardous poisoning (OR 2.6 [1.4, 4.9]). Mean hospital stay was 1.5 days and varied signifi cantly between hospitals from 0.8 to 2.1 days and this was independent of case mix. 5 There are appreciable variations in the management of poisoning between hospitals which are not explained by patient characteristics. Savings would occur if rates of admission and duration of stay were reduced by those hospitals where admission is more frequent or hospital stay is longer. However, the impact of this on long term morbidity is unknown.


Author(s):  
Yngvar Nilssen ◽  
Odd T Brustugun ◽  
Bjørn Møller

Abstract Background International and national differences exist in survival among lung cancer patients. Possible explanations include varying proportions of emergency presentations (EPs), unwanted differences in waiting time to treatment and unequal access to treatment. Methods Case-mix-adjusted multivariable logistic regressions the odds of EP and access to surgery, radiotherapy and systemic anticancer treatment (SACT). Multivariable quantile regression analyzed time from diagnosis to first treatment. Results Of 5713 lung cancer patients diagnosed in Norway in 2015–16, 37.9% (n = 2164) had an EP before diagnosis. Higher age, more advanced stage and more comorbidities were associated with increasing odds of having an EP (P &lt; 0.001) and a lower odds of receiving any treatment (P &lt; 0.001). After adjusting for case-mix, waiting times to curative radiotherapy and SACT were 12.1 days longer [95% confidence interval (CI): 10.2, 14.0] and 5.6 days shorter (95% CI: −7.3, −3.9), respectively, compared with waiting time to surgery. Patients with regional disease experienced a 4.7-day shorter (Coeff: −4.7, 95% CI:−9.4, 0.0) waiting time to curative radiotherapy when compared with patients with localized disease. Patients with a high income had a 22% reduced odds [odds ratio (OR) = 0.78, 95% CI: 0.63, 0.97] of having an EP, and a 63% (OR = 1.63, 95% CI: 1.20, 2.21) and a 40% (OR = 1.40, 95% CI: 1.12, 1.76) increased odds of receiving surgery and SACT, respectively. Conclusion Patients who were older, had advanced disease or increased comorbidities were more likely to have an EP and less likely to receive treatment. While income did not affect the waiting time for lung cancer treatment in Norway, it did affect the likelihood of receiving surgery and SACT.


2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 89s-89s
Author(s):  
H. Alkhatib

Background: Prolonged patient stay in ER is an issue frequently raised with regards to patient safety. In addition to patient complains and dissatisfaction, it increases the risk of healthcare associated infections, increases pressure on ER staff, increases waiting time and eventually impacts bed utilization. Oncology patients frequently visits ER due to their disease nature, progression and treatment protocols (radiotherapy, chemotherapy, and hormonal therapy), in which they come in with multiple serious medical complains that need early and immediate interventions. Septic shock, neutropenic fever and electrolyte imbalance are some of these serious conditions. Aim: To decrease the length of stay of ER patients at an oncology center. Methods: Lean improvement methodology was adopted to eliminate the unnecessary waste during ER workflow. Lean improvement team was trained on lean concepts and methodology by an expert staff. ER value stream map was drawn and an initial data were collected by outside volunteers to eliminate data collection bias, then lean interactions were deployed on multidisciplinary dimensions, followed by quarterly data collection to measure the success of the interventions. It was a cycle of training, collecting data, meeting ER physicians, pharmacy, laboratory, radiology, support services, and nursing. Then implementing the proposed interventions and finally collecting data. Results: ER patients' length of stay gradually decreased by 42% from 377 minutes to 221 minutes. There were remarkable deductions in radiology procedures turn-around time by 62%, and pharmacy by 57%. Improvement in patient flow, decreasing waiting time and ultimately improved patient and family satisfaction were measured outcomes to lean project. Conclusion: Lean improvement methodology is an excellent tool to reduce the nonvalue added time and ultimately improves the patient's safety.


2017 ◽  
Vol 6 (1) ◽  
pp. u212356.w7916 ◽  
Author(s):  
Milfi Al-Onazi ◽  
Ahmed Al Hajri ◽  
Angela Caswell ◽  
Maria Leizl Hugo Villanueva ◽  
Zuhair Mohammed ◽  
...  

2019 ◽  
Vol 8 (3) ◽  
pp. e000542 ◽  
Author(s):  
Alexandra von Guionneau ◽  
Charlotte M Burford

BackgroundLong waiting times in accident and emergency (A&E) departments remain one of the largest barriers to the timely assessment of critically unwell patients. In order to reduce the burden on A&Es, some trusts have introduced ambulatory care areas (ACAs) which provide acute assessment for general practitioner referrals. However, ACAs are often based on already busy acute medical wards and the availability of clinical space for clerking patients means that these patients often face long waiting times too. A cheap and sustainable method to reducing waiting times is to evaluate current space utilisation with the view to making use of underutilised workspace. The aim of this quality improvement project was to improve accessibility to pre-existing clinical spaces, and in doing so, reduce waiting times in acute admissions.MethodsData were collected retrospectively from electronic systems and used to establish a baseline wait time from arrival to having blood taken (primary outcome). Quality improvement methods were used to identify potential implementations to reduce waiting time, by increasing access to clinical space, with serial measurements of the primary outcome being used to monitor change.ResultsData were collected over 54 consecutive days. The median wait time increased by 55 min during the project period. However, this difference in waiting time was not deemed significant between the three PDSA cycles (p=0.419, p=0.270 and p=0.350, Mann-Whitney U). Run chart analysis confirmed no significant changes occurred.ConclusionIn acute services, one limiting factor to seeing patients quickly is room availability. Quality improvement projects, such as this, should consider facilitating better use of available space and creating new clinical workspaces. This offers the possibility of reducing waiting times for both staff and patients alike. We recommend future projects focus efforts on integration of their interventions to generate significant improvements.


Public Health ◽  
2020 ◽  
Vol 189 ◽  
pp. 6-11 ◽  
Author(s):  
A.A. Butt ◽  
A.B. Kartha ◽  
N.A. Masoodi ◽  
A.M. Azad ◽  
N.A. Asaad ◽  
...  

2021 ◽  
Vol 2 (3) ◽  
pp. 412-417
Author(s):  
S. Assetzadeh

Patient flow analysis was used to assess the waiting time of patients referred to a large paediatric outpatient department, and also the lengths of the consultations of the paediatricians and interns. The average waiting times to see the paediatricians and interns were 77 minutes and 7.8 minutes, respectively. The average lengths of consultation for the paediatricians and interns were 3.4 minutes, and 7.7 minutes, respectively


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