scholarly journals https://staging.acutemedjournal.co.uk/investigating-for-pulmonary-embolism-in-pregnancy-five-year-retrospective-review-of-referrals-to-the-acute-medical-unit-of-a-large-teaching-hospital/

2016 ◽  
Vol 15 (2) ◽  
pp. 51-57
Author(s):  
T Brougham ◽  
C Gillett ◽  
L Powter ◽  
Keyword(s):  
Data Collection ◽  
Quality Indicators ◽  
Patient Flow ◽  
Waiting Times ◽  
Electronic System ◽  
Acute Medicine ◽  
Bed Management ◽  
Acute Medical Unit ◽  
Large Teaching Hospital ◽  
Medicine Quality

Aims: To create a system to co-ordinate the medical take, bed management and track patient flow. To use the system to continuously audit against Society for Acute Medicine Quality Indicators. To use the data to model patient flow and optimize working patterns to improve waiting times. Method: An online whiteboard and underlying database system were designed, tested and implemented. Data from this system were used to audit against SAM Quality Indicators and then analysed to optimise both trainee and consultant working patterns. Results: The online whiteboard proved effective and popular as a working tool. Data collection improved using the electronic system. Optimising junior doctor working patterns to match demand led to a reduction of average waiting time to see a doctor from 190 minutes to 71 minutes (p < 0.0001), and a reduction in the proportion of patients waiting over 4 hours from 40% to 10% (p < 0.0001). Optimising consultant working patterns did not produced significant changes in waiting times. Conclusions: The online whiteboard improved day-to-day working and data collection, when compared to the previous paper-based system. Better data facilitated analysis of working patterns leading to a significant improvement in patient waiting times.

scholarly journals Meeting the challenges of Acute Care Quality Indicators

2011 ◽  
Vol 10 (2) ◽  
pp. 91-94
Author(s):  
Kate Evans ◽  
◽  
Ben Fulton ◽  
Keyword(s):  
Acute Care ◽  
Quality Indicators ◽  
Waiting Times ◽  
Working Hours ◽  
Management Plan ◽  
Care Quality ◽  
Patient Assessment ◽  
Acute Medicine ◽  
Out Of Hours ◽  
Acute Medical Unit

The Royal College of Physicians and Society of Acute Medicine have proposed the introduction of Acute Care Quality Indicators. These include the need for rapid initial patient assessment and instigation of a management plan.1 Reductions in junior doctor working hours may impact on our ability to meet these standards. We present the result of a service review of 297 consecutive admissions to a large acute medical unit. This has identified a marked dichotomy between waiting times during daytime and out-of-hours, despite appropriate response to initial triage. We conclude that further service redevelopment is required to reach the standards proposed in the current Acute Care Quality Indicators.

scholarly journals 365 Arrival to Decision: Improving Waiting Times in Surgical Ambulatory Care

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
F Mahmood ◽  
P Patel ◽  
O Islam
Keyword(s):  
Quality Improvement ◽  
Data Collection ◽  
Ambulatory Care ◽  
Patient Flow ◽  
Waiting Times ◽  
Improvement Project ◽  
Team Members ◽  
Referral Form ◽  
Flow Through ◽  
Clear Communication

Abstract Introduction An audit of the newly established Surgical Emergency Ambulatory Care Unit (SEAC) at Furness General Hospital found perceived patient waiting times were high. This Quality Improvement Project assessed the patient flow through the SEAC unit and aimed to improve the average time from arrival in the department to senior review by 10%. Method The Plan Do Study Act (PDSA) methodology for quality improvement was used, the time from arrival in the unit to senior decision was recorded for each patient seen over one-week data collection periods. Analysis of the data allowed for a patient process map to be created to visualise bottlenecks in patient flow. The findings were discussed with all team members and an agreed intervention was implemented and tested. Results Over three PDSA cycles, a significant improvement in the overall time from arrival to decision was achieved, from an average time of 193 minutes to 150 minutes. This was achieved by introducing a referral form, which altered how and when members of the multidisciplinary team communicated with each other. Conclusions Clear communication at the appropriate time between all members of the SEAC team significantly improved the average time from arrival to decision.

Principles of capacity management, applied in the mental health context

2018 ◽  
Vol 42 (4) ◽  
pp. 438
Author(s):  
Kathryn Zeitz ◽  
Darryl Watson
Keyword(s):  
Mental Health ◽  
Mental Health Problems ◽  
Average Length ◽  
Patient Flow ◽  
Waiting Times ◽  
Capacity Management ◽  
Mental Health Setting ◽  
Mental Health Consumer ◽  
Mental Health Consumers ◽  
Flow Improvement

Objective The aim of the paper was to describe a suite of capacity management principles that have been applied in the mental health setting that resulted in a significant reduction in time spent in two emergency departments (ED) and improved throughput. Methods The project consisted of a multifocal change approach over three phases that included: (1) the implementation of a suite of fundamental capacity management activities led by the service and clinical director; (2) a targeted Winter Demand Plan supported by McKinsey and Co.; and (3) a sustainability of change phase. Descriptive statistics was used to analyse the performance data that was collected through-out the project. Results This capacity management project has resulted in sustained patient flow improvement. There was a reduction in the average length of stay (LOS) in the ED for consumers with mental health presentations to the ED. At the commencement of the project, in July 2014, the average LOS was 20.5 h compared with 8.5 h in December 2015 post the sustainability phase. In July 2014, the percentage of consumers staying longer than 24 h was 26% (n = 112); in November and December 2015, this had reduced to 6% and 7 5% respectively (less than one consumer per day). Conclusion Improving patient flow is multifactorial. Increased attendances in public EDs by people with mental health problems and the lengthening boarding in the ED affect the overall ED throughput. Key strategies to improve mental health consumer flow need to focus on engagement, leadership, embedding fundamentals, managing and target setting. What is known about the topic? Improving patient flow in the acute sector is an emerging topic in the health literature in response to increasing pressures of access block in EDs. What does this paper add? This paper describes the application of a suite of patient flow improvement principles that were applied in the mental health setting that significantly reduced the waiting time for consumers in two EDs. What are the implications for practitioners? No single improvement will reduce access block in the ED for mental health consumers. Reductions in waiting times require a concerted, multifocal approach across all components of the acute mental health journey.

scholarly journals Rhythmicity of patient flow in an acute medical unit: relationship to hospital occupancy, seven-day working, and the effect of COVID-19

QJM ◽  
2021 ◽  
Author(s):  
S J Dauncey ◽  
P A Kelly ◽  
D Baykov ◽  
A C Skeldon ◽  
M B Whyte
Keyword(s):  
Hospital Admissions ◽  
Fourier Transforms ◽  
Patient Flow ◽  
Cohort Analysis ◽  
Information Management System ◽  
Hospital Performance ◽  
Bed Occupancy ◽  
Urban Hospital ◽  
Medical Unit ◽  
Acute Medical Unit

Abstract Background The Acute Medical Unit (AMU) provides care for unscheduled hospital admissions. Seven-day Consultant presence and morning AMU discharges have been advocated to improve hospital bed management. Aims To determine whether a later time of daily peak AMU occupancy correlates with measures of hospital stress; whether seven-day Consultant presence, for COVID-19, abolished weekly periodicity of discharges. Design Retrospective cohort analysis Methods Anonymised AMU admission and discharge times were retrieved from the Profile Information Management System (PIMS), at a large, urban hospital from 14th April 2014—31st December 2018 and 20th March—2nd May 2020 (COVID-19 peak). Minute-by-minute admission and discharge times were combined to construct a running total of AMU bed occupancy. Fourier transforms were used to determine periodicity. We tested association between i) average AMU occupancy and ii) time of peak AMU occupancy, with measures of hospital stress (total medical bed occupancy and ‘medical outliers’ on non-medical wards). Results Daily, weekly and seasonal patterns of AMU bed occupancy were evident. Timing of AMU peak occupancy was unrelated to each measure of hospital stress: total medical inpatients (Spearman’s rho, rs=0.04, P = 0.24); number of medical outliers (rs=-0.06, P = 0.05). During COVID-19, daily bed occupancy was similar, with continuation of greater Friday and Monday discharges than the weekend. Conclusions Timing of peak AMU occupancy did not alter with hospital stress. Efforts to increase morning AMU discharges are likely to have little effect on hospital performance. Seven-day Consultant presence did not abolish weekly periodicity of discharges – other factors influence weekend discharges.

scholarly journals Assessing DNA rates within first time psychiatric referrals and the extent to which DNA rates are reduced by an SMS reminder service

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S315-S315
Author(s):  
Henry Coates
Keyword(s):  
Data Collection ◽  
Waiting Time ◽  
Text Messaging ◽  
Positive Impact ◽  
Waiting Times ◽  
National Guidelines ◽  
Medical Specialties ◽  
Number Of Patients ◽  
First Time ◽  
Communication Preference

Aims1) To assess the average wait time for patients to be offered an appointment and to establish any correlations between longer waiting times and 'Did not attend (DNA)' rates 2) To assess the number of patients who have opted into the text message appointment reminder service and whether this had an effect on DNA rates.BackgroundResearch has indicated that the Did Not Attend (DNA) rate in Psychiatry is estimated at 20%, twice that of other medical specialties (1). With NHS Digital estimating that DNAs cost the NHS £1 Billion per annum, there has been much interest in reducing the rate of DNAs within Psychiatry (2). Findings have shown that short waiting times are associated with higher rates of attendance (3). In addition, poor appointment attendance within Psychiatry is also associated with increased disease severity and higher rates of hospital admission (4).MethodWe conducted retrospective data collection on 99 patients referred to Professor Oyebode between January 2018 and August 2019. Our data collection involved assessing time the referral was received, time to first appointment and the patient's communication preference (e.g. whether they opted in to the SMS alert service). All data collection was conducted through use of RIO and coded/ammonized into a Excel spreadsheet. No sampling methods were employed and our population only consisted of first-time referrals to Professor Oyebodes clinic.Result1) We found no correlation between a longer waiting time to first appointment and an increased DNA rate.2) All patient waiting times between 1st January - 31st August were within the maximum limit set by national guidelines3) Opting into the text messaging service remains severely low. Of the patients audited, 95% had not completed a communication preference form. Overall, it is still unclear whether the text messaging service has a positive impact on DNA rates.ConclusionOur data have shown no significant correlation between a longer waiting time and an increased DNA rate for first time Psychiatry appointments. Secondly, we have concluded that between the audited period, waiting times were still within the maximum 18 week wait set by the Mental Health Standards. Finally, we can conclude that uptake of the text messaging service remains very low at 4%. Due to a limited sample size of only 4 patients, it is still unclear from this audit whether opting into the text messaging services will have a positive decrease on the number of DNA's.

scholarly journals Robust capacity planning for accident and emergency services

2020 ◽  
Vol 54 (6) ◽  
pp. 1757-1773
Author(s):  
Elvan Gökalp
Keyword(s):  
Capacity Planning ◽  
Emergency Services ◽  
Simulation Optimization ◽  
Patient Flow ◽  
Waiting Times ◽  
Model Parameters ◽  
Planning Problem ◽  
Accident And Emergency ◽  
Number Of Patients ◽  
The Impact

Accident and emergency departments (A&E) are the first place of contact for urgent and complex patients. These departments are subject to uncertainties due to the unplanned patient arrivals. After arrival to an A&E, patients are categorized by a triage nurse based on the urgency. The performance of an A&E is measured based on the number of patients waiting for more than a certain time to be treated. Due to the uncertainties affecting the patient flow, finding the optimum staff capacities while ensuring the performance targets is a complex problem. This paper proposes a robust-optimization based approximation for the patient waiting times in an A&E. We also develop a simulation optimization heuristic to solve this capacity planning problem. The performance of the approximation approach is then compared with that of the simulation optimization heuristic. Finally, the impact of model parameters on the performances of two approaches is investigated. The experiments show that the proposed approximation results in good enough solutions.

scholarly journals How to limit the burden of data collection for Quality Indicators based on medical records? The COMPAQH experience

2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Clément Corriol ◽  
Valentin Daucourt ◽  
Catherine Grenier ◽  
Etienne Minvielle
Keyword(s):  
Data Collection ◽  
Quality Indicators ◽  
Medical Records

Patient-Data Collection System Used During Medical Operations After the 1994 San Fernando Valley-Northridge Earthquake

1995 ◽  
Vol 10 (3) ◽  
pp. 178-183 ◽  
Author(s):  
Ralph B. (Monty) Leonard ◽  
Lew W. Stringer ◽  
Roy Alson
Keyword(s):  
Data Collection ◽  
Patient Flow ◽  
Patient Data ◽  
Northridge Earthquake ◽  
Collection System ◽  
Data Collection System ◽  
Support Unit ◽  
Disaster Assistance ◽  
Major Disaster ◽  
Flow Information

AbstractIntroduction:In large disasters, such as earthquakes and hurricanes, rapid, adequate and documented medical care and distribution of patients are essential.Methods:After a major (magnitude 6.7 Richter scale) earthquake occurred in Southern California, nine disaster medical assistance teams and two Veterans Administration (VA) buses with VA personnel responded to staff four medical stations, 19 disaster-assistance centers, and two mobile vans. All were under the supervision of the medical support unit (MSU) and its supervising officer. This article describes the patient-data collection system used. All facilities used the same patient encounter forms, log sheets, and medical treatment forms. Copies of these records accompanied the patients during every transfer. Centers for Disease Control and Prevention data classifications were used routinely. The MSU collected these forms twice each day so that all facilities had access to updated patient flow information.Results:Through the use of these methods, more than 11,000 victims were treated, transferred, and their cases tracked during a 12-day period.Conclusions:Use of this system by all federal responders to a major disaster area led to organized care for a large number of victims. Factors enhancing this care were the simplicity of the forms, the use of the forms by all federal responders, a central data collection point, and accessibility of the data at a known site available to all agencies every 12 hours.

Enhancing patient flow in emergency department (ED) using lean strategies–an integrated voice of customer and voice of process perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Alowad ◽  
Premaratne Samaranayake ◽  
Kazi Ahsan ◽  
Hisham Alidrisi ◽  
Azharul Karim
Keyword(s):  
Waiting Time ◽  
Emergency Services ◽  
Single Case ◽  
Patient Flow ◽  
Waiting Times ◽  
Small Sample ◽  
Content Type ◽  
Lean Tools ◽  
And Performance ◽  
Voice Of Customer

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.

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