Integrated Lean Six Sigma approach for patient flow improvement in hospital emergency department

Because of increased competition between healthcare providers, higher customer expectations, stringent checks on insurance payments and new government regulations, it has become vital for healthcare organisations to enhance the quality of the care they provide, to increase efficiency, and to improve the cost effectiveness of their services. Consequently, a number of quality management concepts and tools are employed in the healthcare domain to achieve the most efficient ways of using time, manpower, space and other resources. Emergency departments are designed to provide a high-quality medical service with immediate availability of resources to those in need of emergency care. The challenge of maintaining a smooth flow of patients in emergency departments is a global problem. This study attempts to improve the patient flow in emergency departments by considering Lean techniques and Six Sigma methodology in a comprehensive conceptual framework. The proposed research will develop a systematic approach through integration of Lean techniques with Six Sigma methodology to improve patient flow in emergency departments. The results reported in this paper are based on a standard questionnaire survey of 350 patients in the Emergency Department of Aseer Central Hospital in Saudi Arabia. The results of the study led us to determine the most significant variables affecting patient satisfaction with patient flow, including waiting time during patient treatment in the emergency department; effectiveness of the system when dealing with the patient’s complaints; and the layout of the emergency department. The proposed model will be developed within a performance evaluation metric based on these critical variables, to be evaluated in future work within fuzzy logic for continuous quality improvement.

Measuring patient flow variations : a cross-organisational process mining approach

Variations that exist in the treatment of patients (with similar symptoms) across different hospitals do substantially impact the quality and costs of healthcare. Consequently, it is important to understand the similarities and differences between the practices across different hospitals. This paper presents a case study on the application of process mining techniques to measure and quantify the differences in the treatment of patients presenting with chest pain symptoms across four South Australian hospitals. Our case study focuses on cross-organisational benchmarking of processes and their performance. Techniques such as clustering, process discovery, performance analysis, and scientific workflows were applied to facilitate such comparative analyses. Lessons learned in overcoming unique challenges in cross-organisational process mining, such as ensuring population comparability, data granularity comparability, and experimental repeatability are also presented.

Integrated lean six sigma approach for patient flow improvement in hospital emergency department

This research aims to develop an Integrated Lean Six Sigma approach to investigate and resolve the patient flow problems in hospital emergency departments. It was proposed that the voice of the customer and the voice of the process should be considered simultaneously to investigate the current process of patient flow. Statistical analysis, visual process mapping with A3 problem solving sheet, and cause and effect diagrams have been used to identify the major patient flow issues. This research found that engaged frontline workers, long-term leadership obligation, an understanding of patients' requirements and the implementation of a systematic integration of lean strategies could continuously improve patient flow, health care service and growth in the emergency departments.

Length of Stay-Based Patient Flow Models: Recent Developments and Future Directions

Modelling patient flow in health care systems is vital in understanding the system activity and may therefore prove to be useful in improving their functionality. An extensively used measure is the average length of stay which, although easy to calculate and quantify, is not considered appropriate when the distribution is very long-tailed. In fact, simple deterministic models are generally considered inadequate because of the necessity for models to reflect the complex, variable, dynamic and multidimensional nature of the systems. This paper focuses on modelling length of stay and flow of patients. An overview of such modelling techniques is provided, with particular attention to their impact and suitability in managing a hospital service.

A systematic review of triage-related interventions to improve patient flow in emergency departments

Background Overcrowding in emergency departments is a worldwide problem. A systematic literature review was undertaken to scientifically explore which interventions improve patient flow in emergency departments. Methods A systematic literature search for flow processes in emergency departments was followed by assessment of relevance and methodological quality of each individual study fulfilling the inclusion criteria. Studies were excluded if they did not present data on waiting time, length of stay, patients leaving the emergency department without being seen or other flow parameters based on a nonselected material of patients. Only studies with a control group, either in a randomized controlled trial or in an observational study with historical controls, were included. For each intervention, the level of scientific evidence was rated according to the GRADE system, launched by a WHO-supported working group. Results The interventions were grouped into streaming, fast track, team triage, point-of-care testing (performing laboratory analysis in the emergency department), and nurse-requested x-ray. Thirty-three studies, including over 800,000 patients in total, were included. Scientific evidence on the effect of fast track on waiting time, length of stay, and left without being seen was moderately strong. The effect of team triage on left without being seen was relatively strong, but the evidence for all other interventions was limited or insufficient. Conclusions Introducing fast track for patients with less severe symptoms results in shorter waiting time, shorter length of stay, and fewer patients leaving without being seen. Team triage, with a physician in the team, will probably result in shorter waiting time and shorter length of stay and most likely in fewer patients leaving without being seen. There is only limited scientific evidence that streaming of patients into different tracks, performing laboratory analysis in the emergency department or having nurses to request certain x-rays results in shorter waiting time and length of stay.

Emergency nurse practitioner care and emergency department patient flow: case-control study

Objective: The present study aimed to compare ED waiting times (for medical assessment and treatment), treatment times and length of stay (LOS) for patients managed by an emergency nurse practitioner candidate (ENPC) with patients managed via traditional ED care. Methods: A case–control design was used. Patients were selected using the three most common ED discharge diagnoses for ENPC managed patients: hand/wrist wounds, hand/wrist fractures and removal of plaster of Paris. The ENPC group (n = 102) consisted of patients managed by the ENPC who had ED discharge diagnoses as mentioned above. The control group (n = 623) consisted of patients with the same ED discharge diagnoses who were managed via traditional ED care. Results: There were no significant differences in median waiting times, treatment times and ED LOS between ENPC managed patients and patients managed via traditional ED processes. There appeared to be some variability between diagnostic subgroups in terms of treatment times and ED LOS. Conclusion: Patient flow outcomes for ENPC managed patients are comparable with those of patients managed via usual ED processes.

A model for stakeholder interactions in hospitals : towards understanding the patient flow process

The aim of this research is to understand how stakeholder interactions can facilitate the patient flow process within a hospital. An analysis of the findings reveals that nurses are in a perfect position to be a conduit between doctors and managers. This is due to several factors including the nurses understanding of both the clinical and control worlds, as well as nurses ability to form networks based on their pivotal characteristics. As a result of these findings, a model for better understanding stakeholder relationships is developed. In this research, a mixed methods approach was used by undertaking a cultural assessment via survey questionnaire, complemented by observations of interactions between organisational actors, including formal semi-structured interviews and reflections of many hours of observation. Glouberman and Mintzberg’s four world’s models is used as a foundation for the arguments of this paper. Mitchell, Agle and Wood’s (1997) model is used to discuss the three stakeholder groups of this research including doctors, nurses, and managers.

Improving patient privacy and confidentiality in one regional Emergency Department – a quality project

Background: Patient privacy and confidentiality (PPaC) is an important consideration for nurses and other members of the health care team. Can a patient expect to have confidentiality and in particular privacy in the current climate of emergency health care? Do staff who work in the Emergency Department (ED) see confidentiality as an important factor when providing emergency care? These questions are important to consider. Methods: This is a two phased quality improvement project, developed and implemented over a six month period in a busy regional, tertiary referral ED. Results: Issues identified for this department included department design and layout, overcrowding due to patient flow and access block, staff practices and department policies which were also impacted upon by culture of the team, and use of space. Conclusions: Changes successful in improving this issue include increased staff awareness about PPaC, intercom paging prior to nursing handover to remove visitors during handover, one visitor per patient policy, designated places for handover, allocated bed space for patient reviews/assessment and a strategy to temporarily move the patient if procedures would have been undertaken in shared bed space. These are important issues when considering policy, practice and department design in the ED.

Tracking the patient journey by combining multiple hospital database systems

With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

Forecasting daily patient outflow from a ward having no real-time clinical data

OBJECTIVE: Our study investigates different models to forecast the total number of next-day discharges from an open ward having no real-time clinical data.

METHODS: We compared 5 popular regression algorithms to model total next-day discharges: (1) autoregressive integrated moving average (ARIMA), (2) the autoregressive moving average with exogenous variables (ARMAX), (3) k-nearest neighbor regression, (4) random forest regression, and (5) support vector regression. Although the autoregressive integrated moving average model relied on past 3-month discharges, nearest neighbor forecasting used median of similar discharges in the past in estimating next-day discharge. In addition, the ARMAX model used the day of the week and number of patients currently in ward as exogenous variables. For the random forest and support vector regression models, we designed a predictor set of 20 patient features and 88 ward-level features.

RESULTS: Our data consisted of 12,141 patient visits over 1826 days. Forecasting quality was measured using mean forecast error, mean absolute error, symmetric mean absolute percentage error, and root mean square error. When compared with a moving average prediction model, all 5 models demonstrated superior performance with the random forests achieving 22.7% improvement in mean absolute error, for all days in the year 2014.

CONCLUSIONS: In the absence of clinical information, our study recommends using patient-level and ward-level data in predicting next-day discharges. Random forest and support vector regression models are able to use all available features from such data, resulting in superior performance over traditional autoregressive methods. An intelligent estimate of available beds in wards plays a crucial role in relieving access block in emergency departments.