|Year : 2014 | Volume
| Issue : 1 | Page : 1-6
Lean six sigma application in reducing nonproductive time in operation theaters
Sanjeev Singh1, T. Remya1, T. M. Shijo1, Dinesh Nair2, Prem Nair1
1 Department of Medical Administration, Amrita Institute of Medical Sciences, Kochi, Kerala, India
2 Corporate Affairs, Amrita Institute of Medical Sciences, Kochi, Kerala, India
|Date of Web Publication||21-May-2014|
A 12, EKTA, Amrita Institute of Medical Sciences, Ponekara, Kochi - 682 041, Kerala
Source of Support: None, Conflict of Interest: None
Background: Non Productive Time OT causes potential loss or deferment of revenue for the hospital and internal customer dissatisfaction. The quality tool Lean Six Sigma may help to reduce the non-productive time.
Aim: To use elements of a six sigma model to reduce non-productive time in Gastro Intestine Surgery OT. It focuses on the reduction of NPT between Patient In time and Induction Begin time, Induction End time and Incision In time, Patient Out time and OT Readiness Time.
Method: In a five phase study using DMAIC (Define. Measure, Analyze, Implement & Control) model, business case, value analysis, brain storming, FMEA (Failure Mode & Effect Analysis), RPN (Risk Priority Number) calculation identified causes and solutions. In six sigma analysis process sigma, target sigma and achieved sigma was calculated.
Results: The null hypothesis of no difference in old and new Non Productive Time between Patient In time and Induction Begin time, between Induction End time and Incision and between Patient Out Time and OT Readiness Time was rejected using 2test since the p-value was below 0.05 at 95% confidence level. The process sigma was at 0.91, 0.96 and 0.67 which got improved to 2.55, 2.22 and 3.28 which was better than target Six sigma. Overall bottom line improvement was 4.8CR for the study period by bringing efficiency in the system.
Conclusion: The six sigma project in OT resulted in reducing NPTs, helping to take more cases, patient discharge becoming more systematic, and reducing chaos regarding scheduling OT cases.
Keywords: Efficiency, lean, six sigma, operation theater
|How to cite this article:|
Singh S, Remya T, Shijo TM, Nair D, Nair P. Lean six sigma application in reducing nonproductive time in operation theaters. J Nat Accred Board Hosp Healthcare Providers 2014;1:1-6
|How to cite this URL:|
Singh S, Remya T, Shijo TM, Nair D, Nair P. Lean six sigma application in reducing nonproductive time in operation theaters. J Nat Accred Board Hosp Healthcare Providers [serial online] 2014 [cited 2020 Sep 22];1:1-6. Available from: http://www.nabh.ind.in/text.asp?2014/1/1/1/132908
| Introduction|| |
Healthcare, as with any other service operations, requires continuous and systematic innovation to remain cost effective, efficient and provide high quality services. Evidence-based management is particularly important in the area of quality improvement (QI)  in healthcare because of the need to develop and assess practices for better process and outcome measurable.
There are many popular QI tools such as Six Sigma and Lean systems.  Lean  is a philosophy that intends to make business processes quick, to respond to the customer requirements as fast as possible, by helping identify delays in the value chain and helping eliminate waste. Lean Six Sigma (LSS)  is a philosophy and set of management techniques focused on continuous "eliminating waste" so that every process, task or work action is made "value adding" as viewed from customer. Mapping involves clarifying the customer base, listing the process steps, identifying value-add steps, and reworking the process, so the workflow is without interruption. Although, there are many QI tools in healthcare management, LSS are two new and popular tools to be used in the healthcare industry. ,
Operation theaters (OTs) are the key area which involves huge capital investment; it is highly manpower intensive too along with being a high cost center. It is a high priority service area from the management point of view, which requires adequate attention and willingness to improve efficiency for better returns on investment.  The area of application of LSS at our setting was selected based on following parameters; clinical excellence, safety requirements, physician productivity, patient satisfaction, ease of implementation, financial impact, time taken for completion of the project and sustainability.
From the retrospective study on OT utilization, it was evident that there is nonproductive time (NPT), which requires comprehensive correction. The objective of the study includes increasing the efficiency of the OT utilization in order to avoid the NPT in OT, improve efficiency and reduce related financial loss.
| Materials and Methods|| |
A core team was identified who collected data retrospectively in select OT. Based on the above study, a problem statement and a business case were enumerated. The study was carried out during the period of 6 months from July to December 2010.
The Define, Measure, Analysis, Improve and Control (DMAIC)  method was used to achieve the objectives of the study. After in depth study following parameters were defined as measurable.
- NPT1 = Induction begin time - Patient in time in the theater
- NPT2 = Incision in time - Induction end time
- NPT3 = OT readiness time - Patient out time
Though there were other data fields which were also captured during the process but the above three parameters were the most important areas of NPT, which if corrected could lead to better efficiency leading to financial gains.
Voice of customer (VOC)  was done after interviewing key stakeholders such as surgeons, anesthetists and nursing staff, for complete understanding of their difficulties and opportunities of improvement.
Supplier, Input, Process, Output, Customer (SIPOC)  enumerated the understanding of workflow which involved seven processes (wheeling into the theatre, induction of anesthesia, incision for surgery, closure of operating site, rounding from anesthesia, wheeling out of the patient and preparing the theater for the next case). SIPOC gave a bird's eye view toward the OT workflow.
A project charter was prepared with detailing of DMAIC phase with target completion dates and with actual completion dates.
During the process of value stream mapping,  value-add, nonvalue add and operational value-add activities were mapped with voluntarily working toward reduction/removal of nonvalue added activities.
Based on data from the measure phase, the following null hypothesis was formulated:
- H0 = There is no difference between new and old NPT1 (induction begin time - patient in time to OT).
- H0 = There is no difference between new and old NPT2 (incision in time - induction end time)
- H0 = There is no difference between new and old NPT3 (OT readiness time - patient out time)
The definitions of each steps were made clear after the brainstorming of all key stakeholders meeting. An affinity diagram  was drawn along with Ishikawa  (fish bone diagram) for representation of priorities areas. Failure Mode and Effects Analysis (FMEA)  was conducted based on risk priority number (RPN). Mapping of action items with a timeline was charted after pooling in all resources for corrective and preventive measures.
Retrospective data of 44 cases were analyzed to know the NPT. VOC was obtained from by 38 and 45 nurses, surgeons and anesthetists in two stages. NPT of 187 cases was obtained during the analyze phase. Waiting time of 239 patients was obtained during the control phase. All gastrosurgical OT cases scheduled for the study period were taken for statistical analysis excluding the outliers.
The study was done in two theaters of gastrosurgical department.
The indigenously designed data collection sheets were used. VOC  was performed using the standardized questionnaire, OT case tracking sheet and interview of staff and doctors was done on the hospital ISO formats.
MS Excel 2007 and SPSS version 19.0 (IBM) were used for data analysis.
| Results|| |
In the define phase, the problem statement was described as data available on OT utilization for the year 2010 showing 7 min duration between case being wheeled inside the theater and induction of anesthesia time, 17 min was taken between the end of induction of anesthesia and starting of incision for surgery. 37 min was the average turnaround time (TAT) for the next case to be taken in the theatre after the previous case is over, hence the total NPT in a theater was approximately 60 min.
During the measure phase, the analysis of the existing system with various measurement techniques for defects and levels of perfection was done. In this step, accurate metrics were used to define a baseline for further improvements. This step helped in understanding whether any progress was achieved when process improvements were implemented. Value analysis of the value stream analysis was done, 27 were found to be value added activity, 66 were adjudged as operational value-add and 6 were nonvalue added, which were removed during the implementation phase.
Analyze phase was undertaken to determine any disparity that may exist in the goals set and the current performance levels achieved. The understanding of the relationship between cause and the effect was necessary to bring about any improvements, if needed. Brainstorming session was carried out and all the causes were listed in the affinity diagram. The fish bone diagram for controllable causes was prepared [Figure 1]. Analysis and segregation of causes were done; 6 out total 27 were found to be noncontrollable, four were found to direct improvement and 17 as controllable and likely causes [Figure 1].
Modified FMEA , was carried out for occurrence (1 for monthly, 5 for weekly and 9 for daily) and severity (1 for mild, 5 for moderate, and 9 for severe). The top RPN was considered for further analysis, using five WHYs. Accordingly, the area of intervention was planned which were; Rescheduling of OT cases, nonavailability of custodial staff to prepare the OT for the next case, shortage of accessories during the surgery and delay in shifting the patient from OT to intensive care unit (ICU) owing to nonavailability of ICU beds.
In Improvement phase, necessary steps were taken to prepare the organization toward achievement of the goals (target Six Sigma). Creative development of processes  and tools  brought about a new lease on life for the organization's processes and took them nearer to the organizational objectives. Various project management and planning tools were used to implement the new techniques and processes. Appropriate usage of statistical tool was used, which were important to measure the data, leading to understanding of improvements being done and identify any shortcomings that may exist [Table 1].
|Table 1: List of solutions with their respective causes (cause and effect diagram)|
Click here to view
Under the control phase response plan for dealing with the enumerated problems, were formulated. Management support was also be built up for logistical response and sustaining the achievement of the long-term goals of the project. Control phase is the last step in the DMAIC method  and all efforts were made to maintain the motivation levels and engagement of all participants.
Data collected were statistically analyzed and it was hypothesized that there is no difference between new and old NPTs. Two t-test was conducted to ascertain this. With null as NPT is same for both old and new NPT data, it was found that the null can be rejected as the P value was below 0.05 at 95% confidence level for NPT1, NPT2, and NPT3 [Table 2] and [Table 3].
The sigma level calculation covers various levels of process sigma, target sigma and achieved sigma in improved and control phase. The target sigma was set as two for all NPTs and the process sigma level for the three NPTs were below one sigma. After the implementation of LSS, it rose up to 2.5-3 sigma level [Table 4].
| Discussion|| |
The study was done in the gastrointestinal surgery OT, after adequate understanding of intervention in clinical excellence, which involves huge capital investment and manpower.
Common process improvement projects of application of LSS in healthcare have been in improving operating room (OR) throughput, improving emergency department (ED) throughput, reducing medication errors, reducing patient waiting times and reducing TATs etc., thereby following best practice of care.
Van den Heuvel et al.  and Fairbanks et al.  in its study on application of LSS in OR throughput mentioned that several factors impacted OR throughput which included room cleanup, unclear staff assignments and complete case charts, OR planning, scheduling and anesthesia techniques and physician's arrival time. With the use of LSS, all factors such as reduction of start time delays and decrease TAT between surgical cases were targeted. One of the studies also estimated the cost savings to the range of $350,000 to $500,000 annually. 
Ben Tovim et al. and Christianson et al.  examined the outcomes on ED workload or volume, patient wait time, ambulance diversion, patient walk out rate, length of stay, and patient satisfaction. There were similar studies on TAT at laboratory, radiology, lack of available beds, registration and discharge process and staffing patterns. Some of studies estimated the cost savings and revenue generated ranging between $34,000 by reducing the staffing, a 49% decrease in claims costs and increased revenue of $18,000 using LSS application in healthcare.
During our study, with the current implementation of LSS, the organization were able to provide back up for the accessories which have multiple uses, provided a better TAT and bed availability in postoperative recovery for faster shifting of operated patients, TAT also improved by segregating the cases as day care surgeries and tracking each case. The implementation of proper central scheduling at OT which was made transparent and real time also helped significantly. An obvious benefit because of adequate monitoring during the study period was an improvement of the discharge process by alerting and marking the patients and finishing all necessary formalities related to discharge on the previous day basis implemented.
The overall discipline in OT improved during the study period. Responsiveness of each staff towards implementation and better TAT was remarkable. The NPT which was approximately 1 h, reduced to 28 min. The wheeling of patient became smoother with patients being trolleyed at holding bay before time, the induction to wheeling time reduced to 3 min, owing to the ready availability of surgeons and more so senior surgeons, the time between the end of induction and incision time also reduced by 9 min. The trained cleaning crew was ready to clean up the waste, spills (if any) and major surfaces as soon as the patient was wheeled out of the theater. The next case coming in after cleaning reduced to 16 min.
Because of improved efficiency and engagement of all staff, the number of cases being done in the theater improved by 1-2/day (1 long case and 2 if it was day case or laparoscopic case). It leads to an overall increase of 102 cases during the control phase when compared to the similar months in last year.
There was an evident direct and indirect cost savings with application of LSS. Cost saving was approximately Rs. 4,000,000, because of ability to do more cases during the control phase. There was savings on overheads, improved storage of accessories, and lesser cancellation because of proper scheduling and follow-up with patients 48 h in advance plus the opportunity to do more cases. Needless to mention that there was improved internal customer satisfaction and better patient response during the study period.
| Limitation|| |
The challenges during the study were in sensitization and continuously engaging the physicians and anesthetists towards LSS application tool within the theater. Owing to limitation of time, the control phase was limited to the period of 5 months. The resource allocation of providing the accessories required for surgical procedures especially for laparoscopic cases took some time, since it was routed through purchase and technical committee.
| Conclusion|| |
Through the implementation of LSS in OT, it is evident that total NPT has been come down from 60 to 28 min. Overall gain from the implementation of the study was possible because of providing back up for the accessories which have multiple uses, ready availability of the cleaning crew, transparent central OT scheduling, monitoring postponement and cancellation of surgeries and its evaluation, preemptively working on making postoperative beds available for the surgical cases. During this period, owing to engagement of key stakeholders and management, the overall discipline and day care surgeries also improved.
There was an evident benefit of $80,000 by making the system more efficient and performing more surgical cases. Top management gave high priority in reducing the cost and better utilization of theatre during the study period.
| Acknowledgments|| |
The project team is deeply indebted to Mr. Subramaniam (QIMPRO) who hand holded the project team at AIMS at each step during the study period. Institution is also obliged to National Board for Quality Promotion, Quality Council of India for designing National Development Program and including AIMS as one of the institution and to QIMPRO and Mr. Suresh Lulla for giving expert training in LSS during the project period.
| References|| |
|1.||Murphree P, Vath RR, Daigle L. Sustaining Lean Six Sigma projects in health care. Physician Exec 2011;37:44-8. |
|2.||Hurley B, Levett JM, Huber C, Taylor TL. In: Henriksen K, Battles JB, Keyes MA, Grady ML, editors. Using Lean Six Sigma Tools to Compare INR Measurements from Different Laboratories within a Community. Advances in Patient Safety: New Directions and Alternative Approaches. Performance and Tools. Vol. 3. Rockville, MD: Agency for Healthcare Research and Quality (US); 2008. |
|3.||Kuo AM, Borycki E, Kushniruk A, Lee TS. A healthcare Lean Six Sigma System for postanesthesia care unit workflow improvement. Qual Manag Health Care 2011;20:4-14. |
|4.||Pocha C. Lean Six Sigma in health care and the challenge of implementation of Six Sigma methodologies at a Veterans Affairs Medical Center. Qual Manag Health Care 2010;19:312-8. |
|5.||Carboneau C, Benge E, Jaco MT, Robinson M. A lean Six Sigma team increases hand hygiene compliance and reduces hospital-acquired MRSA infections by 51%. J Healthc Qual 2010;32:61-70. |
|6.||DelliFraine JL, Langabeer JR 2 nd , Nembhard IM. Assessing the evidence of Six Sigma and Lean in the health care industry. Qual Manag Health Care 2010;19:211-25. |
|7.||Vest JR, Gamm LD. A critical review of the research literature on Six Sigma, Lean and StuderGroup's hardwiring excellence in the United States: The need to demonstrate and communicate the effectiveness of transformation strategies in healthcare. Implement Sci 2009;4:35. |
|8.||Fischman D. Applying Lean Six Sigma methodologies to improve efficiency, timeliness of care, and quality of care in an internal medicine residency clinic. Qual Manag Health Care 2010;19:201-10. |
|9.||Yamamoto JJ, Malatestinic B, Lehman A, Juneja R. Facilitating process changes in meal delivery and radiological testing to improve inpatient insulin timing using six sigma method. Qual Manag Health Care 2010;19:189-200. |
|10.||Deckard GJ, Borkowski N, Diaz D, Sanchez C, Boisette SA. Improving timeliness and efficiency in the referral process for safety net providers: Application of the Lean Six Sigma methodology. J Ambul Care Manage 2010;33:124-30. |
|11.||Bullas S, Bryant J. Successful systems sustaining change. Stud Health Technol Inform 2007;129 Pt 2:1199-203. |
|12.||Caldwell C. Lean-six sigma: Tools for rapid cycle cost reduction. Healthc Financ Manage 2006;60:96-8. |
|13.||Daley AT. Pro: Lean six sigma revolutionizing health care of tomorrow. Clin Leadersh Manag Rev 2006;20:E2. |
|14.||De Koning H, Verver JP, van den Heuvel J, Bisgaard S, Does RJ. Lean six sigma in healthcare. J Healthc Qual 2006;28:4-11. |
|15.||Van Den Heuvel, Soren Bisgaard, John Verver. Reducing start time delays in Operating Rooms. Journal of Quality Technology 2009;41:95-109. |
|16.||Fairbanks CB. Using Six Sigma and Lean Methodologies to improve OR throughput. AORN Journal 2007;86:73-82. |
|17.||Bahensky JA, Roe J, Bolton R. Lean sigma - Will it work for healthcare? J Healthc Inf Manag 2005;19:39-44. |
|18.||Christianson JB, Warrick JH, Howard R, Vollum J. Deploying Six Sigma in a health care system as a work in progress. Joint Commission Journal on Quality and Patient Safety, 2005;31:603-13. |
[Table 1], [Table 2], [Table 3], [Table 4]
|This article has been cited by|
||Application of six sigma and 5 S to improve medication turnaround time
| ||Ankit Singh,Shraddha Pradhan,Priya Ravi,Srikrishna Dhale |
| ||International Journal of Healthcare Management. 2020; : 1 |
|[Pubmed] | [DOI]|
||Modelling of readiness factors for the implementation of Lean Six Sigma in healthcare organizations
| ||V. Vaishnavi,M. Suresh |
| ||International Journal of Lean Six Sigma. 2020; 11(4): 597 |
|[Pubmed] | [DOI]|
||Assessing the Readiness Level of Healthcare for Implementing Agility Using Fuzzy Logic Approach
| ||V. Vaishnavi,M. Suresh |
| ||Global Journal of Flexible Systems Management. 2020; 21(2): 163 |
|[Pubmed] | [DOI]|
||Assessing the Impact of Lean Healthcare on Inpatient Care: A Systematic Review
| ||Carlos Zepeda-Lugo,Diego Tlapa,Yolanda Baez-Lopez,Jorge Limon-Romero,Sinue Ontiveros,Armando Perez-Sanchez,Guilherme Tortorella |
| ||International Journal of Environmental Research and Public Health. 2020; 17(15): 5609 |
|[Pubmed] | [DOI]|
||Why do surgeons schedule their own surgeries?
| ||David Johnston,Adam Diamant,Fayez Quereshy |
| ||Journal of Operations Management. 2019; |
|[Pubmed] | [DOI]|
||Performance Improvement in Surgery
| ||Rodrigo F. Alban,Emily C. Anania,Tara Cohen,Peter J. Fabri,Bruce L. Gewertz,Monica Jain,Jeffrey K. Jopling,Paul M. Maggio,Juan A. Sanchez,Harry C. Sax |
| ||Current Problems in Surgery. 2019; |
|[Pubmed] | [DOI]|