1. INTRODUCTION:

The healthcare sector faces a challenge to deliver more and better patient care with less manpower and less financial resources¹. Also, the hospitals as many organizations want to eliminate waste, reduce costs, improve the working processes, reduce the waiting time and have satisfied customers, which in this case patients². So, there is a need to look outside of health care for inspiration about new and more efficient ways of providing care for quality improvement. From this perspective, many healthcare organizations adopt the Toyota Production System as the performance improvement approach, often called the Lean healthcare management system^3,4. Lean system, also called “Lean Thinking” and “Toyota Production System” is a process reengineering philosophy composed of strategic guiding principles and a set of tools at the operational level exemplified by the best practices of Toyota Corporation^5,6.

Lean system (LS) is defined as a philosophy and a set of tools for improving quality and reducing costs by eliminating all non-value added activities ''waste'' in work processes⁷. In this context, there is an opportunity in supporting front-line staff to identify and remove non value added steps from their everyday work. This is the essence of Lean, and it has been employed in manufacturing industries for decades. It is now becoming a critical tool for healthcare leaders⁸. In this context, nurses are ideal leaders of Lean because leading a complex lean transformation of a large hospital department is a natural role for nurses who have experienced leading multidisciplinary teams, are trained in assessment and are system thinkers⁹.

All health care organizations are composed of a series of processes each includes set of actions or steps each of which must be accomplished properly in the proper sequence at the proper time to create value to the patient. Every process involves an amount of different steps which can be value-added or non-value-added (Type1, Type 2). Value added steps are any activities that are essential to deliver the service to the patient. Type 1 non-value-added step does not provide value to the patient but it is necessary or required by the system for the functioning process that should be reduced. Type 2 non-value-added step is considered waste include actions that consume resources, cost, time, effort and not provide value to the service or the customer and is not required by rules and regulations that should be eliminated¹⁰.

Lean system defined eight types of waste. These definitions have been adopted as a useful framework for viewing waste in hospitals¹¹. So identification of non- value added steps (Wastes) is facilitated by classifying wastes in specific types; overproduction, waiting, transportation, over processing, unnecessary inventory, unnecessary motion, defects, and waste of non-utilized people^10-12. In this context, there are five principles for lean system; specifying value by determining what the values in a service provided to the patient, identification of the value stream which includes identification and evaluation of all activities and steps of process needed to produce a service, creating flow for the value-added activities and removing non value added activities, creating a pull system, and striving for perfection by combining the previous four principles with each other¹³. Lean system offers the organization a set of tools and techniques that can be used to help achieve the LS objectives and the organization will be able to follow the five principles effectively such as process map, value stream map, 5S, kaizen, 5 Whys, standardization of work, visual management, etc^9-17.

The need for advanced quality approaches such as Lean system in health care that focuses on identification and elimination of process wastes is urgent to improve quality, safety, and efficiency of health care delivery. Lean system begins with driving out wastes so that all work adds value and serves the patient' needs. Identifying value added and non value added a step in every process is the beginning of the journey toward lean. The total health care in hospitals encompasses many different, dependent processes; a step by step approach is needed, this research will focuses on patient admission process.

2. THE OBJECTIVE OF THE STUDY:

The purpose of this study is to investigate Lean wastes in health services (Admission process) and develop a proposed improvement process.

3. MATERIALS AND METHODS:

3.1 Study design:

Descriptive design utilized in this study.

3.2 Study Setting:

The study was conducted in outpatient department and four surgical units with bed capacity (100 beds) at Alexandria Main University Hospital namely; hepatic-biliary, Gastro Intestinal Tract (G.I.T), head and neck and urology which were selected through simple random sampling to identify Lean wastes in health services process flow.

3.3 Study Subject:

For observation of process flow and lean waste identification; 50% of total patient number who were involved in processes flow (N=50).

3.4 Study tool:

Lean Wastes Identification Tool(LWI):

This tool composed of two forms. The first is an observation record developed by Sanders (2014)which is a modified version of original hospital inpatient waste identification tool¹². It was used for recording the observation of each process tasks which includes: name of unit for selected process, date of process observed, name of selected process observed, description of tasks for observed process, duration (time consumed) for each task, classification for each task of observed process if value adding or not, classification for eight types of lean wastes in relation to each task of observed process in form of (over production, over processing, unnecessary motion, unnecessary inventory, unnecessary transportation, defect, waiting, and non-utilized people), classification for waste level; either type 1 non-value-added or Type 2 non-value-added. It was used concurrently with the second form; an observation sheet developed by Armstrong (2010)¹¹as a guide to identify waste of an existing selected process which consists of eight types of Lean wastes, definition for each type of waste, and examples in healthcare.

3.5 Data Collection:

Lean waste identification tool was submitted to five panel of experts from the Faculty of Nursing, Alexandria University to review and test content validity. Accordingly, modification was done based on their comments which is adding time consumed item for each task observed in observation sheet. Identification of lean waste was conducted by the researcher using continuous direct observation to patients who were going through process using observation record and observation sheet as a guide (Lean waste identification tool) to record the detailed flow of admission process. Each unit was observed for the current state for two weeks (observation time for each unit = 72 hours, total observation for the four units =288 hours for two months. After that, each task of observed process was analyzed in term of value added and non value added; as well as eight types of lean waste according to the guide. Then value stream map was developed.

After data collection and analysis, discussion through group interview was done with nurse directors of hospital and outpatient department, First Line Nurse

Managers, Nurse supervisor, staff nurses, physicians, and registration employees, who were involved in process and worked in morning shift to identify root causes of lean wastes in admission process through 5 Whys technique and suggested process improvement ideas was generated to eliminate non value added activities level 2 and reduce time of non value added activities level 1, then proposed future value stream map was developed with decreased process lead time based on mean, SD, and confidence limit (95%) of sample responses related to time of non value added level 1. The time of discussion was one month, six days per week, 2 hours per day starting from 19/2/2016 to 19/3/2016.

Based on that, improved admission process was proposed and developed through removal of NVA time level 2 and reducing non value added time level 1 as well as reducing lead time of process and increase process cycle efficiency. A total time for data collection was five months started from 17 th October 2015 to 19th March 2016.

3.6. Ethical Consideration:

The Ethics Committee of the Faculty of Nursing, Alexandria University approved the study protocol. Informed consent was obtained from study subjects for collecting needed data. The right to refuse to participate was assured in this study.

3.7. Data management:

Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. The evaluation of the study findings was handling statistically analyzed by using both descriptive and. Mean, SD, confidence limit was employed to represent the descriptive statistics.

Table2. Lean wastes (Non-value-added tasks) in current admission process flow

Types of Lean wastes in admission process (NVA)	NVA: Level 1 No of tasks observed =305					NVA: Level 2 No of tasks observed = 1109
	No	% of NVA	% of total VA/ NVA	Time in minutes		No	% of NVA	% of total VA/ NVA	Time in minutes
	No	% of NVA	% of total VA/ NVA	M	SD	No	% of NVA	% of total VA/ NVA	M	SD
1. Overproduction	27	1.9	1.1	2.06	0.43	0	0	0	0	0
2. Waiting	82	5.8	3.3	62.93	22.62	258	18.2	10.5	61.72	16.81
3. Defect	31	2.2	1.3	7.15	3.09	112	7.9	4.5	1.52	0.42
4. Transportation	50	3.5	2	7.89	2.00	243	17.2	9.9	10.55	1.46
5. Inventory	0	0	0	0	0	9	0.6	0.4	0.63	0.05
6. Non utilized staff	0	0	0	0	0	18	1.3	0.7	0.83	0.12
7. Motion	15	1.1	0.6	0.45	0.03	282	20	11.4	20.99	0.97
8. Over processing	100	7.1	4.1	1.33	0.02	187	13.2	7.6	0.49	0.05
Total	305	21.6	12.4	81.81	13.91	1109	78.4	45	96.73	19.12

Continew Table2

Types of Lean wastes in admission process (NVA)	Total No of NVA tasks observed =1414 Total No of VA/ NVA tasks observed =2462
	No	% of NVA	% of total VA/ NVA	Time in minutes
	No	% of NVA	% of total VA/ NVA	M	SD
1. Overproduction	27	1.9	1.1	2.06	0.43
2. Waiting	340	24	13.8	124.65	20.54
3. Defect	143	10.1	5.8	8.67	3.09
4. Transportation	293	20.7	11.9	18.44	2.52
5. Inventory	9	0.6	0.4	0.63	0.05
6. Non utilized staff	18	1.3	0.7	0.83	0.12
7. Motion	297	21.1	12	21.44	0.90
8. Over processing	287	20.3	11.7	1.82	0.56
Total	1414	100	57.4	178.54	21.99

Table 2 illustrate number and percent of lean wastes (non-value-added tasks) of all process tasks; value added and non value added tasks (VA /NVA) as well as of non value added tasks (NVA) with mean time in minutes.

As can be seen, Lean wastes constitute more than half (57.4%) of whole process with mean time 178.54 minutes. Waiting is the predominant waste in admission process which represent the highest percentage 13.8% of total VA /NVA and 24% of NVA with the highest mean time 124.65+20.54 min distributed as 3.3% of total VA /NVA in level 1 with mean time 62.93+22.62 min and 10.5% of total VA /NVA in level 2 with mean time 61.72+16.81 min, followed by the waste of motion, transportation, over processing.Related to the waste of motion, it represent 12 % of total VA/ NVA and 21.1% of NVA with mean time 21.44+0.90 min distributed as 0.6% of total VA/NVA in level 1 with mean time 0.45+0.03 min and 11.4% of total VA/NVA in level 2 with mean time 20.99+0.97 min.

The waste of transportation represents 11.9% of VA/NVA and 20.7% of NVA with mean time 18.44+2.52 min distributed as 2% of total VA/NVA in level 1 with mean time 7.89+2.00 min and 9.9% of VA/ NVA in level 2 with mean time 10.55+1.46 min. Regarding the waste of over processing, it constitute 11.7% of VA/NVA and 20.3% of NVA with mean time 1.82+0.56min, out of which 4.1% of total VA/NVA them observed as level 1 with mean time 1.33+0.03min and 7.6% of total VA/NVA with mean time 0.49+0.05 min.

On contrary, the waste of defect, overproduction, non utilized staff and inventory represented the least percent and mean time; where defect represent 5.8% of total VA/NVA and 10.1% of NVA with mean time 8.67+3.09min; distributed as 1.3% of total VA/NVA with mean time 7.15+3.09min in level 1 and 4.5% of total VA/NVA with mean time 1.52+0.42 in level 2. Overproduction represent 1.1 of total VA/NVA and 1.9% of NVA with mea time 2.06+0.43min that are observed only as level 1. Non-utilized staff consumes 0.7% of total VA/ NVA and 1.3% of NVA with mean time 0.83+0.12min as level 2. The waste of inventory represent the least percent 0.4% of total VA/NVA and 0.6% of NVA with mean time 0.63+0.05min as level 2.

Current state value stream map:

Figure 1 reflect the current state value stream map of the major operations in admission process. The mean lead time of current admission process equal to 211.83+22.55 min divided into value added time equal to 33.29+5.20 min and 178.54+21.99 min non-value-added time divided into non-value-added level 1 (NVA1) 81.81+13.91min and non value added level 2 (NVA 2) 96.73+19.12min.

Figure 1 current state value stream map of the major operations in admission process

Table 3 Mean time in minutes and Process cycle efficiency (PCE) between current and proposed future admission process flow:

Table 3 illustrates the comparison in mean time in minutes and PCE between current and proposed future state of admission process in relation to its major operations (value added and non value added tasks) as reflected in proposed future value stream map of admission process in figure 2. From the table, non value added tasks but not required (level2) (NVA2) was eliminated from the process and non value added tasks but required by regulations (level 1) (NVA1) was reduced based on discussion with nurses, physicians, and registration employees.

Regarding outpatient registration in clinic; NVA1 was reduced from 0.68+0.07 min to 0.21+0.04 min. In outpatient consultation, NVA1 was reduced from 54.73 +26.72 min to 28.82+9.54 min. Also, NVA 1 in patient arrival to the unit was reduced from 7.89+2.00 min to 3.61+1.09. In relation to preparation of patient chart; NVA1 was reduced from 7.15+3.09 min to 4.12+0.93 min. Concerning patient examination and investigation NVA1 was reduced from 9.3+3.60 to 4.00+2.66. Finally, NVA1 in medication prescription was reduced from 2.06+0.43 min to 0.76+0.19 min. So, The mean lead time of admission process was reduced from 211.83 + 22.55 min to 74.8+5.81 as well as process cycle efficiency was improved to be more than 25%.

To evaluates the efficiency of admission process; the researcher use process cycle efficiency (PCE), which is the ratio of value added to lead time that revealed efficiency of process to be more than 25% (World class efficiency)

Value added time

PCE =--------------------- X 100

Lead time

Table 3. Mean time in minutes and Process cycle efficiency (PCE) between current and proposed future admission process flow

Operations	Current state			Future state
	Value added	Non value added (NVA1)	Non value added (NVA2)	Value added	Non value added (NVA1)	Non value added (NVA2)	Total NVA1/2
	Mean ±SD	Mean ±SD	Mean±SD	Mean±SD	Mean±SD	Mean±SD	Mean±SD
1. Outpatient Registration in clinic	1.05±0.35	0.68±0.07	0	1.05±0.35	0.21±0.04	0	0.21+0.04
2. Outpatient consultation	11.62±3.49	54.73±26.72	7.27±2.52	11.62±3.49	28.82±9.54	0	28.82+9.54
3. Registration for hospital admission	2.28±0.51	0	56.94±21.89	2.28±0.51	0	0	0
4. Patient arrival to the unit	0.3±0.01	7.89±2.00	0	0.3±0.01	3.61±1.09	0	3.61+1.09
5. Patient placement in unit	1.03±0.28	0	5.28+0.92	1.03±0.28	0	0	1.03+0.28
6. Patient handover and registration in admission log book	0.65±0.15	0	3.31±0.55	0.65±0.15	0	0	0.65+0.15
7. Measurement of vital signs	5.52±1.68	0	5.63±0.79	5.52±1.68	0	0	5.52+1.68
8. Preparation of patient' chart	0.62±0.08	7.15±3.09	5.58±1.21	0.62±0.08	4.12±0.93	0	0.62+0.08
9. Patient examination and investigation	9.43±2.28	9.3±3.60	11.41±2.28	9.43±2.28	4.00 ±2.66	0	9.43+2.28
10. Medication prescription	0.79±0.16	2.06±0.43	1.31±0.36	0.79±0.16	0.76± 0.19	0	0.79+0.16
Total	33. 29±5.20	81.81±13.91	96.73±19.12	33.29±5.20	41.52±9.64	0
Lead time	211.83+ 22.55			74.8 + 5.81
Process cycle efficiency (PCE)	PCE = 33.29 X100 = 15.7% 211.83			PCE = 33.29 X100 = 44.5% 74.8

Figure 2: Proposed future state value stream map for major operations of admission process

4. DISCUSSION:

Process lead time and lean wastes in process flow:

The findings of present study showed that, the average lead time of admission process was 211.83 min (3.53 h). This is related to Lean wastes (non value added tasks) that were identified in admission such as, waiting, overproduction, defect transportation, inventory, non utilized staff, motion, and over processing wastes as revealed from study findings.

Waiting is the predominant lean wastes in admission process which consumes 124.65 (2.07h) min. This is related to delay for clinic consultation, due to unplanned and inappropriate registration system in outpatient clinic, large number of patients arrived at the same time, limited consultation rooms, working hours, and days in outpatient clinic, as well as patients waiting for some procedures or tests by physician and nurse, shortage of equipment and supplies, some equipment are not functioning well, shortage of staff, sending admitted patient to inpatients units as a group, absence of guidelines for health care providers, delay in receiving some information related to patient condition, inflexible work force, workload, and miscommunication.

This results is supported by Graban et al (2012, 2009), da Silva et al (2014), Bercaw (2010), Ajami et al (2007) who elaborated that, waiting and delay in health services process due to waiting for health professionals, waiting for supplies, defect in communication, poor equipment effectiveness, waiting in hallway to be admitted, as well as ineffective information system in hospital, and absence of standard guidelines for personnel involved in process^{6,17 -19}.

This is in agreement with Capital (2004) who clarified that, when time is being used ineffectively, then the waste of waiting occurs²⁰. Parr (2010) explained this type of waste in form of waiting for other co-workers to give report²¹. In addition Armstrong (2010) elaborated that the waste of waiting is the easiest of wastes to identify such as delays in receiving information, delays for bed assignments, admission delays, waiting for equipment to be repaired, depending on or waiting for others to complete tasks¹¹. Moreover, Gill (2011) stated that the waste of waiting result form poor scheduling, uneven workloads²².

Oche (2013) who found that more than half of the patients waited in admission process more than 1 h, with high patient load coupled with few doctors and nurses being the main causes of this long waiting time²³. Also Ofilli (2007) and (2005) revealed waiting time of 173 min in admission process of teaching hospital^24,25.

In this essence, Mohebbifar et al (2014) revealed waiting time in admission process equal 161 minutes due to lack of human resources and professional workers in the hospitals such as physicians, licensed nurses and other professional staff, most of the hospitals use the same old admission systems on the same day, patients themselves and their attitudes are involved in the increased waiting time, and registration process²⁶. Moreover, Saeed et el (2016) found waiting time in patient admission process 210 minutes²⁷.

The waste of overproduction consumes 2.06 min which is related to current documentation system that require writing additional admission record lead to duplicate charting, excess paperwork due to lack of standardized documentation system. This interpretation is congruent with Armstrong (2010) who stated that, making extra copies is overproduction¹¹. Moreover, Parr (2010) illustrated that overproduction caused by duplicate charting and multiple forms with the same information²¹. Furthermore, Bush (2007), and Teich et al (2015) elaborated that providing something in excess, earlier, or faster than the next process is overproduction^28,29.

The waste of defect consumes 8.67 min that is occurred in form of documentation problems, insufficient number of records and reports, incomplete information, and incomplete nursing procedures due to staff workload, shortage of staff who provide direct patient care, large number of nurse patient ratio, work interruptions, lack of standardized work, poor assignment methods, lack of training and ineffective supervision, defect in equipment,, lack of awareness about zero defect principles, staff negligence.

This result goes in the same line David (2016) who found defect in documentation of information related to admission process³⁰. Also, Bercaw (2013) illustrated that defects create waste because they result in work needing to be completely redone or corrected³¹. Brady et al (2009) stated that defect related to personal negligence³².

The waste of transportation consumes 18.44 min that is in form of patients searching about consultation room and walk outside outpatients department and waiting for hospital admission. Also, unnecessary moving patient to nursing room to for nursing procedures, patient moving between unit room search about nurse for bed assignment, as well as search about physician. This is related to poor understanding of patient flow in process, staff negligence, carless, lack of supervision, lack of awareness with patients’ needs and rights, unclear work instructions and guidelines, multiple registration methods, staff workload, shortage of staff, lack of guidance with patient’ movement in process, limited resources as elevators in hospital setting as well as delayed maintenance for them.

In this context, The interpretation of this findings is supported by Teich et al (2013) who clarified that the waste of transportation in healthcare this can be evident when moving patients in healthcare process²⁹. Manos et al (2006) elaborated that transportation in healthcare is caused by moving patients³³.

The waste of motion 21.44 min which occurred in form of staff searching for something such as patient' file, equipment and supplies, records, and as well as other staff in unit. Lack of records that are needed to be prepared in patient' file, disorganized workplace, shortage of materials, extra hand off of anything, multiple storage locations. This is related to poor workplace organization, shortage of unit supplies and paperwork, ineffective equipment, excessive medical records pick up and deliveries between staff in unit, extra handoff of materials, multiple storage locations in some units as well as fixed, limited storage location in some units, work supplies and equipment are not where work occur.

This findings is supported by Graban et al (2012), Parr (2010) who stated that, walking to get equipment and medications, walking to get charts, searching for things: supplies, equipment, patient charts, records, other care team members, etc are causes for motion waste^17,21. In the same line, David (2016) identified the waste of motion in admission process in form of unnecessary staff movement³⁰.

Over processing waste consumes 1.82 min which is attributed to multiple registration methods in outpatient clinic as well as extra process steps such as guiding patients for waiting areas as well as to nursing room for nursing procedures. In addition to re correction of documentation errors. This related to unclear work instructions and guidelines, errors, lack of double checking, extra copies and excessive information required, staff negligence, ineffective supervision, large number of patients request services, improper assignment, and staff workload. This results is supported by Tufts (2015) who explained that, generating the same information in several formats lead to over processing wastes³⁴. In addition, Graban et al (2012), Armstrong (2010), Manos et al (2006) who elaborated that, over processing caused by effort that adds no value to the service, as well as unnecessary work and unclear work instructions, miscommunication, over processing to accommodate scheduling or workload issues, and lack of standard work protocol training^16,11,33. In this essence, David (2016) found over processing wastes in administrative activities of admission process due to in effective documentation and registration system³⁰.

The waste of inventory consumes 0.63 min that is related to excessive stock of equipment that are not functioning well and take place, poor quality of materials, and lack of periodic check up and maintenance to materials. This finding is consistent with David (2016) who found inventory waste in admission process³⁰. In this respect, Armstrong (2010) stated that excessive and malfunctioning inventory takes up space, consumes resources to move, store and stock it and costs money to remove inventory when it becomes obsolete¹¹. Also, Graban et al (2012) explained that outdated supplies lead to inventory waste¹⁶.

The waste of non utilized staff consumes 0.83 min that is related nurses working below their skill level in form of cleaning environment around patient bed due to unavailability of workers or nurses. This results goes in the same line with David (2016) who found waste of under-utilization of people’s capabilities in admission process inform of staff performing duties below their skill level³⁰.

Proposed improvement and process cycle efficiency:

The present study provided a proposed future value stream map with reduction in lead process time through elimination of non value added tasks and not required (NVA2) and reduction in non value added tasks but required by regulations (NVA1). Subsequently process cycle efficiency could be improved to be more than 25%. This is related to proposed improvements that were generated through discussion with staff involved in process including; nurse directors, nurse supervisor, First Line Nurse Managers, staff nurses, physicians, technicians and employees.

This improvement method is supported by Alsmadi et al. (2012) Di Pietro et al (2013) who stressed on staff (stakeholders) such nurses, physicians, and process owners (facility manager, supervisor) involvement in process improvement and they should be empowered to solve problems, and help in understanding the future state better, and their input/suggestions will give for alternate methods of conducting the process^35,36. In addition Graban (2009) emphasized on ideas and solutions should flow from the bottom up, with the assumption that frontline or value-adding employees are closest to the process⁶.

The proposed improvement related to admission process showed that process cycle time (lead time) could be reduced from 211.83 min (3.53 h), to 74.8 min (1.24 h), the time of non-value added activities (NVA) reduced from 178.54 min to 41.51 min and PCE was increased from 15.7% to 44.5%. The time of NVA reduced due to elimination of NVA2 activities and reduction of NVA1, based on proposed areas of improvements such as; planning and scheduling of registration system, modification in working hours / days. Plan clear assignment to workers duties and effective supervision on their performance. Design communication system between hospital registration office and units by phone calling to give information about patients number and initial diagnosis. Specify elevators specially to for patients only and put visual sign for illustration. Simplify manual documentation. As well as Organization of space, equipment, supplies, people, work areas, records, patient’ files.

This results go in the same line with Patel et el (2014) who revealed that the admission waiting time reduction program contributed to an increase in patients being admitted to the hospital within 60 minutes³⁷.Also, Haron (2015) improve the process flow of patient in clinic by reducing lead time and waste and revealed that lead time is decreased from 93.35 minutes to 86.41 minutes by reducing waiting time from 60 minutes to 53.1 minutes³⁸.

This is in agreement with Al Khani 2015 who streamlined patient's flow through process mapping along with time measuring and waiting time data were done after observing patient’s journey in clinic and the average waiting time was reduced from 120 minutes to 60 minutes³⁹.

5. CONCLUSIONS AND RECOMMENDATION:

The findings of the study concluded that, the percent of value added tasks in admission represent less than half of whole process tasks as well as consuming less than half of process lead time. Compared to non value added tasks (Lean wastes) that constitute more than half of whole process tasks and consuming more than half of process lead time. So The process cycle efficiency (PCE) was less than 25% to be less efficient. The predominant wastes in health process were waiting, overproduction, motion, transportation, defect, and over processing. In addition, the process cycle efficiency for process studied was improved after proposed improvements to be higher than 25%. Therefore, the study recommended that hospital managers, physicians, nursing administrators and staff nurses work together to improve current health service process flow as well as reduce non value added activities (lean wastes) in admission process through increase working days and working hours of clinic for each specialty, Designing communication system between hospital registration office and units by phone calling to give information about patients number and initial diagnosis. Specifying elevators specially to be used by patients only and put visual sign for illustration.

6. REFERENCES:

1. Rosmulder R. Improving healthcare delivery with Lean thinking: Action research in an emergency department. Published Master Thesis. University of Twente.2011. Available at https://www.research.utwente.nl/en/publications/improving-healthcare-delivery-with-lean-thinking-action-research. Retrieved on 20/10/2017

2. Alwan F. Lean implementation problems in the healthcare system: A Case study conducted at Torsby Hospital. Published Master Thesis. Karlstad Business School. Karlstad University.2012.

3. Poksinska B. The current state of lean implementation in health care: literature review. Quality Management in Health Care 2010; 4 (19): 319-29.

4. Machado VC, Leitner U. Lean tools and lean transformation process in health care. International Journal of Management Science and Engineering Management 2010; 5(5): 383-92.

5. Balushi A, Sohal P, Singh A, Hajri YM, Farsi R. Readiness factors for lean implementation in healthcare settings: A literature review". Journal of Health Organization and Management 2014; 28(2): 135 – 153.

6. Graban M. Lean Hospitals Improving Quality, Patient Safety, Employee Satisfaction, 2009.

7. Liker JK. The Toyota way: 14 management principles from the world's greatest manufacturer. New York: McGraw-Hill. 2004.

8. Fine B, Golden B, Hannam R, Morra D. Leading Lean: A Canadian Healthcare Leader’s Guide. Healthcare Quarterly 2009; 12(3): 32-41.

9. Johnson J, Smith A, Mastro K. From Toyota to the Bedside Nurses: Can Lead the Lean Way in Health Care Reform. Nursing Administration Quarterly 2012; 36(3):234-42.

10. Dick K. Lean Implementation and Pediatric Intensive Care Unit Bed Availability Analysis via Simulation at the Winnipeg Children’s Hospital. Published Master Thesis. Faculty of Graduate Studies. University of Manitoba. 2011. Available at: www. mspace.lib.umanitoba.ca/handle/1993/4990. Retrieved on 20/10/2017.

11. Armstrong P. Lean implementation manual for reducing cost in health care throughout the application of lean principles. Published Master Thesis. California State University.2010. Available at: www.gradworks.umi.com/14/84/1484854.html. Retrieved on 2010/2017.

12. Sanders J H. Strengthening the IHI waste identification tool with lean waste 2014. Available at www.xcdsystem.com/iie2014/.../finalpapers/I1291.pdf. Retrieved on 20/10/2017

13. Womack J, Jones D. Lean Thinking: Simon and Schuster New York, NY; 1996.

14. Bridge O.A Guide to Process Mapping 2015. Available at https://www.thefis.org/.../2015/.../Best-Practice-A-Guide-to-Process-... Retrieved on 20/10/2017

15. Luna, l. Klökner B. Ferreira J. Applying Value Stream Mapping to Identify and Evaluate Waste in a Company of the Ceramic Sector. Springer: Switzerland 2013.

16. Graban, M. Lean Hospitals, CRC Press, Taylor and Francis Group, FL 2012

17. Da Silva S. Valácio R. Botelho F. Amaral. Reasons for discharge delays in teaching hospitals. Rev Saode Poblica 2014;48(2):1-7.

18. Bercaw R G. Lean Leadership for Healthcare Approaches to Lean Transformation Taylor and Francis Group 2013. Available at http:www.m-bikeshop.com/library/download/asin=1466515546andtype=stream Retrieved on 20/10/2017.

19. Ajami s, Ketabi S. An analysis of the average waiting time during the patient discharge process at Kashani Hospital in Esfahan, Iran: a case study. Health information Management Journal 2007; 36 (2): 37-42.

20. Capital, M Introduction to Lean Manufacturing for Vietnam 2004. Available at http.www.industrvweek.com/Current Articles/asp/articles.asp?. Retrieved on 20/10/2017.

21. Parr J. Patient Flows to Improve Hospital Performance.2010. Available at http: www.digitalcommons.bryant.edu/cgi/viewcontent.cgi?article=1008.. Retrieved on 20/10/2017.

22. Gill S. Application of Lean principles in the Emergency department within resources constrained environment. Published Doctorate Dissertation. University of California.2011.Available at https://www.emergencymedicinekenya.org/990/. Retrieved on 20/10/2017

23. Oche M, Adamu H. Determinants of Patient Waiting Time in the General Outpatient Department of a Tertiary Health Institution in North Western Nigeria. Ann Med Health SCi Res 2013; 3(4): 588-592.

24. Ofilli AN, Ofowve CE. What patients want: A content analysis of key qualities that influence patient satisfaction. J Med Pract Manage. 2007;22: 255–61.

25. Ofilli AN, Ofowve CE. Patient's assessment of efficiency of services at a teaching hospital in a developing country. Ann Afr Med. 2005;4: 150–3.

26. Mohebbifar R, Hasanpoor E, Mohseni M, Sokhanvar M, Khosravizadeh O, Isfahani H. Outpatient Waiting Time in Health Services and Teaching Hospitals: A Case Study in Iran. Global Journal of Health Science2014; 6(1): 172-180.

27. Saeed A, Ahmed B, Jamil S, Marzyeh S, Zahra T, Hasan A, Negar F. Measuring and Analyzing Waiting Time Indicators of Patients’ Admitted in Emergency Department: A Case Study. Glob J Health Sci 2016; 8(1): 143–149

28. Bush RW. Reducing waste in US health care systems. JAMA 2007;297: 871–4.

29. Teich ST, Faddoul FF. Lean Management: The Journey from Toyota to Healthcare. RMMJ 2013;4 (2): 1-9.

30. David B. Reducing waste in administrative services with lean principles. Published Master Thesis. University of Twente. 2016

31. Lazarus I, Neely C. Six sigma raising the bar. Managed Healthcare executive 2003;13(1):31-33

32. Brady A, Malone A, Fleming S. A literature review of an individual and systems factors that contribute to medication errors in nursing practice. Journal of Nursing Management 2009; 17:679-97

33. Manos A, Sattler M, Alukal G. Make healthcare lean. Qual Prog 2006;39 (7):24-30.

34. Tufts J. Lean Healthcare: Continually Eliminating Waste to Reach Value To Patients 2015. Available at www.icetechnologies.com/.../lean-healthcare-continually-eliminating... Retrieved on 20/10/2017

35. Alsmadi M, Almani, A, Jerisat, R. A comparative analysis of Lean practices and performance in the UK manufacturing and service sector firms. Total Quality Management, Business Excellence 2012; 23(3-4): 381–396.

36. Di Pietro L, Mugion, R. G, Renzi, M. F. An integrated approach between Lean and customer feedback tools: An empirical study in the public sector. Total Quality Management andBusiness Excellence 2013;24(7-8): 899–917.

37. Patel PB, Combos MA, Vinson DR. Reduction of admit wait times: the effect of a leadership-based program.2014. Acad Emerg Med. 2014 Mar;21(3):266-73.

38. Haron S. Patient Process Flow Improvement: Value Stream Mapping. Journal of Management Research 2015; 7(2): 495- 505.

39. Al Khani R. Improving Waiting Time and Patients' Experience in a Medical Retina Clinic. Published Master Thesis. Royal College of Surgeons in Ireland, 2015.Avaialble at http://epubs.rcsi.ie/mscttheses/64/. Retrieved on 20/10/2017.

Received on 12.12.2020 Modified on 24.01.2021

Int. J. of Advances in Nur. Management. 2021; 9(2):151-159.

DOI: 10.5958/2454-2652.2021.00035.4

Tasks in current admission process flow	No of tasks observed			Time in minutes
Tasks in current admission process flow	No=2462	%	Mean±SD	Mean	SD	% of lead time
Value added tasks	1048	42.6	20.69±2.21	33.29	5.20	15.7
Non-value added (NVA) tasks	1414	57.4	28.28 ± 4.15	178.54	21.99	84.3
NVA 1	305	12.4	6.1±1.44	81.81	13.91	38.6
NVA 2	1109	45	22.18±4.00	96.73	19.12	45.7
Total value added and non-value added tasks in process flow / lead time	2462	100	49.24±4.8	211.83	22.55	100