Journal of Health Organization and Management Preoperative cross functional teams improve OR performance Justin Bitter Elizabeth van Veen-Berkx Pierre van Amelsvoort Hein Gooszen
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To cite this document: Justin Bitter Elizabeth van Veen-Berkx Pierre van Amelsvoort Hein Gooszen , (2015),"Preoperative cross functional teams improve OR performance", Journal of Health Organization and Management, Vol. 29 Iss 3 pp. 343 - 352 Permanent link to this document: http://dx.doi.org/10.1108/JHOM-07-2013-0145 Downloaded on: 30 January 2016, At: 14:40 (PT) References: this document contains references to 30 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 212 times since 2015*
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Preoperative cross functional teams improve OR performance
CFTs improve OR performance
Justin Bitter OR Department, Bernhoven Hospital, Uden, The Netherlands
Elizabeth van Veen-Berkx OR Department, Erasmus University Medical Center, Rotterdam, The Netherlands
Pierre van Amelsvoort
343 Received 12 July 2013 Revised 27 March 2014 Accepted 8 April 2014
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Catholic University Leuven, Leuven, Belgium, and
Hein Gooszen OR Department, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands Abstract Purpose – The purpose of this paper is to present the effect of the introduction of cross-functional team (CFT)-based organization, rather than, on planning and performance of OR teams. Design/methodology/approach – In total, two surgical departments of the Radboud University Nijmegen Medical Center (RUNMC) in the Netherlands were selected to illustrate the effect on performance. Data were available for a total of seven consecutive years from 2005 until 2012 and consisted of 4,046 OR days for surgical Department A and 1,154 OR days for surgical Department B on which, respectively 8,419 and 5,295 surgical cases were performed. The performance indicator “raw utilization” of the two surgical Departments was presented as box-and-whisker plots per year (2005-2011). The relationship between raw utilization (y) and years (x) was analyzed with linear regression analysis, to observe if performance changed over time. Findings – Based on the linear regression analysis, raw utilization of surgical Department A showed a statistically significant increase since 2006. The variation in raw utilization reduced from IQR 33 percent in 2005 to IQR 8 percent in 2011. Surgical Department B showed that raw utilization increased since 2005. The variation in raw utilization reduced from IQR 21 percent in 2005 to IQR 8 percent in 2011. Social implications – Hospitals need to improve their productivity and efficiency in response to higher societal demands and rapidly escalating costs. The RUNMC increased their OR performance significantly by introduction of CFT-based organization in the operative process and abandoning the so called functional silos. Originality/value – The stepwise reduction of variation – a decrease of IQR during the years – indicates an organizational learning effect. This study demonstrates that introducing CFTs improve OR performance by working together as a team. Keywords Performance, The Netherlands, Teamwork, OR, Self-managing teams Paper type Case study
Introduction Hospitals are continuously exploring ways to simultaneously improve patient safety, quality of care and efficiency. Hospitals need to improve their productivity and efficiency in response to higher societal demands and rapidly escalating costs. In Dutch hospitals most of the growth in costs is being driven by increased health care consumption, partly as a result of medical advances that lead to more diseases at an earlier age so patients can be treated earlier and longer (Kuenen et al., 2011). Efficient use of OR capacity is crucial since it is considered a high-cost environment continuously
Journal of Health Organization and Management Vol. 29 No. 3, 2015 pp. 343-352 © Emerald Group Publishing Limited 1477-7266 DOI 10.1108/JHOM-07-2013-0145
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challenging the limited hospital resources (Marjamaa et al., 2008). To respond to these challenges, the Radboud University Nijmegen Medical Centre (RUNMC) in the Netherlands opted for a redesign consisting of a cross-functional team (CFT)-based organization in the operative process. In this study we focus on the performance indicator “OR utilization” (for definition: see “Methods”). Professionalization of multidisciplinary collaboration and improving planning are ways to improve on this indicator. Mathieu et al. (2008) show that effective collaboration between professionals is based on attitude, culture and structure (division of tasks and roles). In this study we describe the effect of the introduction of multidisciplinary teams. In our process of ongoing improvement of performance, we decided that once a CFT structure has been implemented and has shown its effectiveness and added value, the focus will be shifted to culture and attitude. Background theory self-organizing teams The roots for the developing theories about CFTs can be found in the socio-technical systems theory (Argyris, 1976; de Sitter et al., 1997). Starting point is that organizations have to cope with growing uncertainty and variety. The internal complexity of hospital organizations architecture, caused by traditional functional specialization, is an amplifier for external complexity and a source for interference, errors, variance and accidents. These are difficult to handle due to defects in effective collaboration of autonomous individual professionals. Organizational redesign will revitalize the organization (Achterbergh and Vriens, 2009; de Sitter et al., 1997). Decreasing organizational complexity by reducing the functional concentration and increasing local control is necessary to create optimal conditions for cross-functional teamwork. CFTs with a high level of self-organizing capabilities and mandate can handle variety, interference and upcoming errors (Achterbergh and Vriens, 2009; Bitter et al., 2013). Integration of tasks by a cross-functional team-based organization is supposed to reduce the sources of interference, like X-ray equipment not being available or inadequately consulted schedule deviation. Furthermore, cross-functional teams with full mandate are equipped to regulate interference, errors and learn to improve planning under circumstances of scarce resources and large variety. In this paper we describe the relationship between the implementation of CFTs and OR performance in the RUNMC in the Netherlands. We have chosen to investigate two surgical Departments (A and B) based on their differences in working environment and organizational learning effects. Department A is a surgical department performing highly complex, often (sub)acute surgical procedures, frequently demanding intensive care treatment. Department B is a surgical department performing mostly (semi)-elective procedures of mixed complexity, rarely demanding intensive care treatment. While surgical Department B operated in a stable environment during the seven years of investigation, surgical Department A went through a turbulent phase of reorganization with strong focus on building a new team with the assignment to improve team performance and patient safety. Surgical Department B is a department characterized by a stable – mostly – elective patient population of intermediate and low complexity. On the contrary, surgical Department A is characterized by an unstable highly complex and patient population with a large proportion of non-elective procedures. In addition, this population is characterized by a long duration of surgical procedures.
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The baseline Prior to redesign, the OR schedule was prepared and controlled by the surgeon in charge. The anesthesiologist approved the schedule the day before. Cancellations regularly occurred due to missing data and other causes, e.g. lack of OR time due to over-utilization at the end of the day. To live up to appointments made with patients, doctor’s commitment also needed improvement. To optimize these pitfalls in the planning and scheduling process, CFTs were formed in 2004. These CFTs were called “cross-functional OR scheduling teams” and every surgical Department (i.e. orthopedics department, cardiothoracic surgery department, etc.) using OR facilities, implemented such a team. The team was supervised by a dedicated anesthesiologist and further consisted of a surgeon, a scheduler, an OR nurse, an anesthesia nurse, a recovery room nurse and a nurse from the ward. Once a week the team meets to discuss the OR schedule of the following week and to evaluate the OR performance of the previous week, in terms of utilization, cancellations and other factors interfering with smooth planning and performance. The cross-functional team deliberates the complete program, day by day and members inform their colleagues about all relevant issues needed for optimal planning and safety. The CFT is fully responsible for optimal preparation and continuity of the OR program for the week to come. The anesthesiologist as the chairman of the team, chairs the meeting. Besides their role in optimizing OR scheduling, CFTs draw attention to imminent conflicts. Methods Data was prospectively collected from 2005 until 2012 and analyzed retrospectively for the purpose of this study. All data were registered electronically by the OR nursing staff in the Hospital Information System and validated by the surgeon and anesthesiologist in charge. Data used in this longitudinal study involved repeated and continuous measurement of the same performance indicators over a long period of time; in this study raw utilization was focussed on. The performance of one OR day, which is generally equal to eight hours of block time (usually from 8:00 h until 16:00 h) allocated to a specific surgical department, is commonly evaluated by this indicator. It is a measure for efficiency and relates to whether staffed operating rooms are under – or overutilized. An OR is considered underutilized when OR time is staffed but not used for surgery, setup or clean up, which can occur if cases finish earlier than scheduled, there are prolonged delays between cases or a case is cancelled unexpectedly. An OR is regarded overutilized when it is staffed at overtime wages (Macario, 2007). OR utilization can be calculated in two ways, raw and adjusted. Raw utilization is defined as the total hours of elective cases performed within OR block time divided by the hours of allocated block time per day x 100 percent. Adjusted utilization uses the total hours of elective cases performed within OR block time, including “credit” for the turnover time necessary to set up and clean up ORs × 100 percent (Dexter, 2003; Donham et al., 1996; Van Veen-Berkx et al., 2013). This study considered raw utilization, excluding turnover time. To define a consistent dataset for analysis, all non-elective (emergency) cases and all outpatient cases, were excluded. In RUNMC outpatient surgical cases are allocated to a specific organizational OR unit (a separate “day surgery centre”). The outpatient surgery workflow varies from the in-patient surgery workflow. This study focussed on elective in-patient surgical cases.
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A national independent data management center was employed to facilitate the collection and processing of the data. This center provided professional expertise to facilitate the collection and processing of data records. Data reliability checks were performed before data were ready for analysis. Reliability refers to the accuracy and completeness of data, given the intended purpose for use (Bowling, 2009). Reliability checks for this research consisted of: •
a check for missing values (e.g. are all months included; are all OR locations included; are all required data elements included);
•
a consistency check to determine if data is in accordance with earlier data deliveries (is the number of surgical cases comparable with the number of cases during the month of the previous year?);
•
the correctness of data was studied to check if values are outside of a designated range (e.g. time patient leaves OR o time patient enters OR; date o W date patient enters OR); and
•
outliers were removed from the dataset according to outlier filtering rules (e.g. surgeon-controlled time 0 W x ⩽ 1,400 minutes; OR utilization 25 ⩾ x ⩽110 percent; cumulative turnover time 0 W x ⩽ 120 minutes).
This study evaluated the effect of CFTs in both surgical Departments A and B on OR performance. Surgical Department A was chosen because this department went through a rapid and meticulous introduction of this redesign process including optimization of patient safety and surgical scheduling. Moreover, their patient case mix is multifaceted with a relatively high percentage of complex and acute or semi-acute cases, which makes scheduling a demanding process. The Surgical Department B was opted for because this is a relatively small group with a high percentage of elective cases. Data analysis was performed using SPSS Statistics 19. Normality of distribution was determined using the Kolmogorov-Smirnov test. The relationship between raw utilization (y) and years (x), concerning the two surgical departments, was analyzed with linear regression analysis. Violations of the basic regression assumptions were diagnosed by means of the residual plot; a graph with the residuals (y − ŷ) plotted on the vertical axe and the predicted values of raw utilization (ŷ) on the horizontal axe. The box plot, also called a box-and-whisker plot, was introduced by Tukey (1977). The graph consists of a box extending from the first quartile (Q1) to the third quartile (Q3), a mark (black horizontal line) at the median with whiskers extending from the first quartile to the minimum value and from the third quartile to the maximum value. The interquartile range (IQR) is also called the “middle 50” and is a measure of dispersion. It is calculated by subtracting the upper and lower quartiles: IQR ¼ Q3 − Q1 (Dawson, 2011; Munro, 2005). Results Data were available for a total of seven consecutive years from 2005 until 2012. After excluding day care surgery and non-elective surgical cases, the collected data consisted of 4,046 OR days for surgical Department A and 1,154 OR days for surgical Department B on which, respectively 8,419 and 5,295 surgical cases were performed. Outliers (mean ±3 SD) were excluded, based on the SPSS output “Casewise Diagnostics”. This left 4,009 OR days for surgical Department Aand 1,127 OR days for surgical Department B, for statistical analysis.
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Surgical Department A Figure 1 shows that raw utilization of surgical Department A demonstrated an increase since 2006. Most of this increase was effectuated in the lower quartile (Q1 from 62 percent in 2005 to 91 percent in 2011) and the median (from 82 percent in 2005 to 97 percent in 2011). The variation in raw utilization reduced from IQR 33 percent in 2005 to IQR 8 percent in 2011. Results of linear regression analysis showed mean raw utilization significantly increased 3.077 percent every year (p o 0.0005). Surgical Department B Figure 1 shows that raw utilization of surgical Department B demonstrated an increase since 2005. The main part of this increase was effectuated in the lower quartile (Q1 from 74 percent in 2005 to 86 percent in 2011). The variation in raw utilization reduced from IQR 21 percent in 2005 to IQR 8 percent in 2011. Results of linear regression analysis showed mean raw utilization significantly increased 0.899 percent every year (p o 0.0005). year 2005 2006 2007 2008 2009 2010 2011
120
100 Raw Utilization Rate (%)
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Data of each year and each department showed that raw utilization was not normally distributed (Kolmogorov-Smirnov test, p o 0.0005). However, normality of data are not an assumption in linear regression analysis. With reference to the basic regression assumptions; interval measure level of variables, independence of the errors, homoscedasticity (or constant variance) of the errors were not violated. Normality of the error distribution was dishonored, however, this assumption did not lead to biased results because the assumption of normality is not important for large sample sizes (n ⩾ 1,000), which was the case in this study.
80
60
40
20
0 Surgical Department A
Surgical Department B
Source: Database Nationwide OR Benchmark University Medical Centers, specifically RUNMC
Figure 1. Box-and-whisker plots raw utilization (percent) surgical Departments A and B (2005 – 2011)
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Discussion The purpose of this study was to identify the relationship between the implementation of cross-functional teams and OR performance. This study shows a long-term perspective and a gradual improvement in OR utilization. Our data are insufficient to prove not that this is a direct result of introduction of the CFTs, however, since this was the only major change in the OR organization in the time period of the study, it is highly likely that the improvement can, to a great extent, be ascribed to the systematic work of the two teams. The effects of single loop and double loop learning, as well as focussing on OR scheduling are well-documented helpsin the process of organizational learning that we have gone through (Argyris, 1976; Bitter et al., 2013). Improving OR performance by the introduction of a CFT-based organization in the operative process contributes to more focus on OR scheduling and better collaboration in a team. Abandoning the so-called “functional silos” results in less variation in raw utilization. This redesign is based on the principle that a cross-functional team has the ability to attenuate variability, unpredictability and politics (Achterbergh and Vriens, 2009). In other words, cross-functional teams are assumed to have a self-regulating capacity. It is crucial that the OR management facilitates the CFTs and backs them up, in essence, under any circumstances. Applying socio-technical systems theory design principles has shown to not only lead to improvements in the quality of working life, but can also contribute to an increase in organizational productivity and patient safety as well as better collaboration between professionals (Argyris, 1976; Achterbergh and Vriens, 2009; Bitter et al., 2013). We decided that once this structure is in place and has shown to be effective, the attention will be focussed on culture and attitude, as the next step. This study showed a significant reduction in variation of raw utilization since the implementation of cross-functional OR scheduling teams in 2004, with a gradual improvement over the years. Regarding to the linear regression analysis, we can conclude a significant increase in mean raw utilization every year, with 3.077 percent for surgical Department A and 0.899 percent for surgical Department B. We expect that this increase will stabilize during the time. There are two potential explanations for these findings; one is the organizational learning effect and the other is more efficient utilization of OR capacity in the strict sense as a result of focusing on the utilization process by the whole OR organization. The stepwise reduction of variation – a decrease of IQR during the years – indicates an organizational learning effect, whereas an increase of raw utilization, reduction of uncertainty and reliability in scheduling are indicators of more efficient utilization of OR capacity (Murray and Berwick, 2003; Reason, 2005). This indicates a stable process and positive learning effect in both surgical departments. The redesign in our study is based on the principle that a CFT has the ability to attenuate variability, reduce unpredictability, the impact of local politics and the effect of personal preference and input of the individual staff members of both departments on the OR schedule. Reduction of uncertainties – by means of optimizing multidisciplinary collaboration – will improve OR scheduling (Harders et al., 2006). In other words, CFTs are assumed to have a self-regulating capacity to identify bottlenecks and to improve continuity. The effect of CFTs can also be endorsed by Donabedian’s traditional structure-processoutcome model (Donabedian, 1966). This model claims a causal relationship between structure, process (CFTs) and outcome (raw utilization). The structure of the context in
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which health services are delivered, has an effect on processes and outcomes. Outcomes indicate the combined effects of structure and process. CFTs have several indicators to score their performance. Based on previous work of others on improvement of OR scheduling (Stepaniak et al., 2009; Strum, 2000), raw utilization was chosen in this study since we wanted to analyze over-all performance in a straightforward fashion. CFTs have shown to progressively learn how to deal with their new role and improve their performance continuously through collaboration and better use of checks and balances (Achterbergh and Vriens, 2009; Argyris, 1976; Overdyk et al., 1998). Systems that are highly differentiated generally require correspondingly high degrees of integration (Berg et al., 2005; Glouberman and Mintzberg, 2001). As for surgery, accurate scheduling of operations is a crucial factor, complicated by the uncertainty regarding the adequate preparation of the patients on the tentative list and unpredictability of the duration of surgical procedures. Modeling that variability by continuous registration, in turn, provides a mechanism to generate tools for accurate time estimation (Stepaniak et al., 2009). OR professionals are conservative and have a tendency to remain within their comfort zone. Introducing CFTs is a multi-factorial and multi-consequential intervention with emphasis on multidisciplinary collaboration. Multidisciplinary teamwork is an important foundation for an effective organization (Parker, 2002). Effective CFTs are characterized by setting and accepting common operational and safety goals (Mathieu et al., 2008). In effective CFTs there is a strong collective responsibility for these results in which individual interests are subordinate to the interests of the team. (Mathieu et al., 2008; Parker, 2002; Gittell, 2009) Effective CFTs are well organized (Bitter et al., 2013), and use single-loop and double-loop learning, as well as feedback processes to continuously learn and improve their performance (Argyris, 1976; Achterbergh, Vriens, 2009). Gittell (2009) describes the critical concept of relational coordination. Coordinating work through shared goals, shared knowledge and mutual respect. Because of the way healthcare is organized, weak links exist throughout the chain of communication. Relational coordination strengthens those weak links, enabling providers to deliver high quality, efficient care to their patients. The result of this study suggest that both the surgical teams have gone successfully through this phase of adaptation to a different planning and control process. In this study, OR performance was investigated. For reasons explained in the method section, we have chosen to investigate the effect of introduction of CFTs in the two selected surgical Departments A and B based on their differences in case mix, urgency and scheduling challenges. The performance of both departments over the years showed that there is a learning curve and further improvement can be anticipated. Surgical Department A showed a stronger organizational learning effect, which was attributed to their unstable relationship to safety, incidents and changes of management over the years. Due to the stable situation of surgical Department B a weaker learning effect occurred (Pfeffer and Salancik, 2003). The analysis of several additional separate performance indicators, e.g. over-utilized time and case cancellations, can identify areas of further improvement. Other performance indicators – e.g. first-case tardiness, turnover time between cases and under-utilized time – could also further improve utilization of the available OR time. The RUNMC did not specifically formulate goal-settings or standards for OR performance indicators in advance. Even though the Audit Commission (2002) in the UK has tried to formulate a standard for utilization, a general global standard has not
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yet been found for performance indicators in OR scheduling. Through benchmarking with other Dutch University Medical Centres, we might be able to substantiate the added value of CFTs to all other on-going improvement programs. A limitation of this study was the longitudinal and retrospective nature. During the seven years of investigation other developments parallel to the introduction of CFTs, e.g. more focus on patient safety issues, and increased awareness of costs and efficiency by national developments in health care, could have influenced the outcome. The data set of RUNMC was not compared to the other seven University Medical Centres in the Netherlands and no information about their performance is available yet. To further specify the separate role of CFTs, the data of this study need to be compared to performance data in the other UMC’s in the Netherlands in the near future. Moreover, there is a difference in patient case mix between the two surgical departments investigated. However, it is unlikely that difference in case mix fully explains the differences in OR performance. This study that set out to analyse the effects of a new strategy to improve OR efficiency, demonstrates that introducing CFTs improves OR performance by working together as a team. The results need to be extended and supported by multi-center research. Glossary CFT OR RUNMC IQR
Cross-Functional Team(s) Operating Room Radboud University Nijmegen Medical Centre Interquartile Range
References Achterbergh, J. and Vriens, D. (2009), Organizations: Social Systems Conducting Experiments. Springer-Verlag Berlin Heidelberg. Argyris, C. (1976), “Single-loop and double-loop models in research on decision making”, Administrative Science Quaterly, Vol. 21 No. 3, pp. 363-375. Audit Commission (2002), Operating Theatres, A Bulletin for Health Bodies, Audit Commission. Berg, M., Schellekens, W. and Bergen, C. (2005), “Bridging the quality chasm: integrating professional and organizational approaches to quality”, International Journal for Quality in Health Care, Vol. 17 No. 1, pp. 75-82. Bitter, J., van Veen-Berkx, E., Gooszen, H.G. and van Amelsvoort, P. (2013), “Multidisciplinary teamwork is an important issue to healthcare professionals”, Team Performance Management, Vol. 19 Nos 5/6, pp. 263-278. Bowling, A. (2009), Research Methods in Health. Investigating Health and Health Services, Open University Press, Bershire. Dawson, R. (2011), “How significant is a boxplot outlier?”, Journal of Statistics Education, Vol. 19 No. 2, pp. 1-13. de Sitter, L.U., den Hertog, J.F. and Dankbaar, B. (1997), “From complex organizations with simple jobs to simple organizations with complex job”, Human Relations, Vol. 50 No. 5, pp. 497-534. Dexter, F. (2003), “Operating room utilization alone is not an accurate metric for the allocation of operating room block time to individual surgeons with low caseloads”, Anesthesiology, Vol. 98 No. 5, pp. 1243-1249.
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Donabedian, A. (1966), “Evaluating the quality of medical care”, Milbank Mem Fund Q, Vol. 44, Supplement, pp. 166-206. Donham, R.T., Mazzei, W.J. and Jones, R.L. (1996), “Procedural times glossary”, American Journal Anesthesiology, Vol. 23 No. S5, pp. 4-12. Gittell, J.H. (2009), High Performance Healthcare: Using the Power of Relationships to Achieve Quality, Efficiency and Resilience, The McGraw-Hill companies, New York, NY. Glouberman, S. and Mintzberg, H. (2001), “Managing the care of health and the cure of disease-part 1: differentiation”, Health Care Management Review, Vol. 26 No. 1, pp. 56-71. Glouberman, S. and Mintzberg, H. (2001), “Managing the care of health and the cure of diseasepart 2: integration”, Health Care Management Review, Vol. 26 No. 1, pp. 72-86, . Harders, M., Malangoni, M.A., Weight, S. and Sidhu, T. (2006), “Improving operation room efficiency through process redesign”, Journal of Surgery, Vol. 140 No 4, pp. 509-516. Kuenen, J.W., Geurts, M., Van Leeuwen, W. and Nolst Trenité, T. (2011), “Provide value. More quality for less money: what the Dutch health care can learn from Sweden”, The Boston Consulting Group. Macario, A. (2007), “Are your operating rooms ‘efficient’?”, OR Manager, Vol. 23 No. 12, pp. 16-18. Marjamaa, R., Vakkuri, A. and Kirvela, O. (2008), “Operating room management: why, how and by whom?”, Acta Anaesthesiology Scandinavia, Vol. 52 No. 5, pp. 596-600. Mathieu, J., Maynard, M.T., Rapp, T. and Gilson, L. (2008), “Team effectiveness 1997-2007: a review of recent advancements and a glimpse into the future”, Journal of Management, Vol. 34 No. 3, pp. 410-476. Munro, B.H. (2005), Statistical Methods for Healthcare Research, 5th ed., Lippincott Williams & Wilkins, Philadelphia, PA. Murray, M. and Berwick, D.M. (2003), “Innovations in primary care. Advance access: reducing waiting and delays in primary care”, JAMA, February 26, Vol. 289 No. 8, pp. 1035-1040. Overdyk, F.J., Harvey, S.C., Fishman, R.L. and Shippey, F. (1998), “Successful srategies for improving operating room efficiency at academic institutions”, Anesth Analg, Vol. 86 No. 4, pp. 896-906. Parker, G.M. (2002), Cross Functional Teams. Working with Allies, Enemies and Other Strangers, 2nd ed., Jossey-Bass. An Imprint of Wiley, San Francisco, CA. Pfeffer, J. and Salancik, G.R. (2003), The External Control Of Organizations. A Resource Dependence Perspective, Stanford University Press, Stanford. Reason, J. (2005), “Safety in the operating theatre part 2: human error and organizational failure”, Qual Saf Health Care, Vol. 14 No. 1, pp. 56-60. Stepaniak, P., Heij, C., Mannaerts, G.H., de Quelerij, M. and de Vries, G. (2009), “Modeling procedure and surgical times for CPT-anesthesia-surgeon combinations and evaluation in terms of case duration prediction and OR efficiency”, Anesth Analg, Vol. 109 No. 4, pp. 1232-1245. Strum, D.P. (2000), “Surgeon and type of anesthesia predict variability in surgical procedure times”, Anesthesiology, Vol. 92, pp. 1454-1466. Tukey, J.W. (1977), Exploratory Data Analysis, 1st ed., Pearson PLC, New York, NY. Van Veen-Berkx, E., Elkhuizen, S.G., Kalkman, C.J., Buhre, W.F. and Kazemier, G. (2013), “Successful Interventions to Reduce First-Case Tardiness in Dutch University Medical Centers. Results of a Nationwide Operating Room Benchmark Study, American Journal of Surgery, doi:10.1016/j.amjsurg.2013.09.025. Further reading Mainz, J. (2003), “Defining and classifying clinical indicators for quality improvement”, Int J Qual Health Care, Vol. 15 No. 6, pp. 523-30.
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About the authors Justin Bitter is a PhD Fellow at the Radboud University Medical Center Nijmegen, the Netherlands, and a Manager Operating Rooms at the Bernhoven Hospital in Uden, the Netherlands, and is preparing a PhD study about teamwork in OR in academic hospitals. Justin Bitter is the corresponding author and can be contacted at: [email protected] Elizabeth van Veen-Berkx is a PhD Fellow OR Benchmarking Collaboration at the Department of Operating Rooms at the Erasmus University Medical Center Rotterdam, the Netherlands. Pierre van Amelsvoort is a Consultant at the STGroup (Netherlands) and a Professor Social Innovation at the Catholic University in Leuven, Belgium. Hein Gooszen is a Professor at the Faculty of Medical Sciences of the Radboud University Nijmegen in the Netherlands, teaching academization of operative processes. Hein Gooszen is also a Professor of Surgery at the Radboud University and the Head of the Department of Evidence Based Surgery at the Radboud University Medical Center Nijmegen, the Netherlands.
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To cite this document: Justin Bitter Elizabeth van Veen-Berkx Pierre van Amelsvoort Hein Gooszen , (2015),"Preoperative cross functional teams improve OR performance", Journal of Health Organization and Management, Vol. 29 Iss 3 pp. 343 - 352 Permanent link to this document: http://dx.doi.org/10.1108/JHOM-07-2013-0145 Downloaded on: 30 January 2016, At: 14:40 (PT) References: this document contains references to 30 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 212 times since 2015*
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Preoperative cross functional teams improve OR performance
CFTs improve OR performance
Justin Bitter OR Department, Bernhoven Hospital, Uden, The Netherlands
Elizabeth van Veen-Berkx OR Department, Erasmus University Medical Center, Rotterdam, The Netherlands
Pierre van Amelsvoort
343 Received 12 July 2013 Revised 27 March 2014 Accepted 8 April 2014
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Catholic University Leuven, Leuven, Belgium, and
Hein Gooszen OR Department, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands Abstract Purpose – The purpose of this paper is to present the effect of the introduction of cross-functional team (CFT)-based organization, rather than, on planning and performance of OR teams. Design/methodology/approach – In total, two surgical departments of the Radboud University Nijmegen Medical Center (RUNMC) in the Netherlands were selected to illustrate the effect on performance. Data were available for a total of seven consecutive years from 2005 until 2012 and consisted of 4,046 OR days for surgical Department A and 1,154 OR days for surgical Department B on which, respectively 8,419 and 5,295 surgical cases were performed. The performance indicator “raw utilization” of the two surgical Departments was presented as box-and-whisker plots per year (2005-2011). The relationship between raw utilization (y) and years (x) was analyzed with linear regression analysis, to observe if performance changed over time. Findings – Based on the linear regression analysis, raw utilization of surgical Department A showed a statistically significant increase since 2006. The variation in raw utilization reduced from IQR 33 percent in 2005 to IQR 8 percent in 2011. Surgical Department B showed that raw utilization increased since 2005. The variation in raw utilization reduced from IQR 21 percent in 2005 to IQR 8 percent in 2011. Social implications – Hospitals need to improve their productivity and efficiency in response to higher societal demands and rapidly escalating costs. The RUNMC increased their OR performance significantly by introduction of CFT-based organization in the operative process and abandoning the so called functional silos. Originality/value – The stepwise reduction of variation – a decrease of IQR during the years – indicates an organizational learning effect. This study demonstrates that introducing CFTs improve OR performance by working together as a team. Keywords Performance, The Netherlands, Teamwork, OR, Self-managing teams Paper type Case study
Introduction Hospitals are continuously exploring ways to simultaneously improve patient safety, quality of care and efficiency. Hospitals need to improve their productivity and efficiency in response to higher societal demands and rapidly escalating costs. In Dutch hospitals most of the growth in costs is being driven by increased health care consumption, partly as a result of medical advances that lead to more diseases at an earlier age so patients can be treated earlier and longer (Kuenen et al., 2011). Efficient use of OR capacity is crucial since it is considered a high-cost environment continuously
Journal of Health Organization and Management Vol. 29 No. 3, 2015 pp. 343-352 © Emerald Group Publishing Limited 1477-7266 DOI 10.1108/JHOM-07-2013-0145
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challenging the limited hospital resources (Marjamaa et al., 2008). To respond to these challenges, the Radboud University Nijmegen Medical Centre (RUNMC) in the Netherlands opted for a redesign consisting of a cross-functional team (CFT)-based organization in the operative process. In this study we focus on the performance indicator “OR utilization” (for definition: see “Methods”). Professionalization of multidisciplinary collaboration and improving planning are ways to improve on this indicator. Mathieu et al. (2008) show that effective collaboration between professionals is based on attitude, culture and structure (division of tasks and roles). In this study we describe the effect of the introduction of multidisciplinary teams. In our process of ongoing improvement of performance, we decided that once a CFT structure has been implemented and has shown its effectiveness and added value, the focus will be shifted to culture and attitude. Background theory self-organizing teams The roots for the developing theories about CFTs can be found in the socio-technical systems theory (Argyris, 1976; de Sitter et al., 1997). Starting point is that organizations have to cope with growing uncertainty and variety. The internal complexity of hospital organizations architecture, caused by traditional functional specialization, is an amplifier for external complexity and a source for interference, errors, variance and accidents. These are difficult to handle due to defects in effective collaboration of autonomous individual professionals. Organizational redesign will revitalize the organization (Achterbergh and Vriens, 2009; de Sitter et al., 1997). Decreasing organizational complexity by reducing the functional concentration and increasing local control is necessary to create optimal conditions for cross-functional teamwork. CFTs with a high level of self-organizing capabilities and mandate can handle variety, interference and upcoming errors (Achterbergh and Vriens, 2009; Bitter et al., 2013). Integration of tasks by a cross-functional team-based organization is supposed to reduce the sources of interference, like X-ray equipment not being available or inadequately consulted schedule deviation. Furthermore, cross-functional teams with full mandate are equipped to regulate interference, errors and learn to improve planning under circumstances of scarce resources and large variety. In this paper we describe the relationship between the implementation of CFTs and OR performance in the RUNMC in the Netherlands. We have chosen to investigate two surgical Departments (A and B) based on their differences in working environment and organizational learning effects. Department A is a surgical department performing highly complex, often (sub)acute surgical procedures, frequently demanding intensive care treatment. Department B is a surgical department performing mostly (semi)-elective procedures of mixed complexity, rarely demanding intensive care treatment. While surgical Department B operated in a stable environment during the seven years of investigation, surgical Department A went through a turbulent phase of reorganization with strong focus on building a new team with the assignment to improve team performance and patient safety. Surgical Department B is a department characterized by a stable – mostly – elective patient population of intermediate and low complexity. On the contrary, surgical Department A is characterized by an unstable highly complex and patient population with a large proportion of non-elective procedures. In addition, this population is characterized by a long duration of surgical procedures.
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The baseline Prior to redesign, the OR schedule was prepared and controlled by the surgeon in charge. The anesthesiologist approved the schedule the day before. Cancellations regularly occurred due to missing data and other causes, e.g. lack of OR time due to over-utilization at the end of the day. To live up to appointments made with patients, doctor’s commitment also needed improvement. To optimize these pitfalls in the planning and scheduling process, CFTs were formed in 2004. These CFTs were called “cross-functional OR scheduling teams” and every surgical Department (i.e. orthopedics department, cardiothoracic surgery department, etc.) using OR facilities, implemented such a team. The team was supervised by a dedicated anesthesiologist and further consisted of a surgeon, a scheduler, an OR nurse, an anesthesia nurse, a recovery room nurse and a nurse from the ward. Once a week the team meets to discuss the OR schedule of the following week and to evaluate the OR performance of the previous week, in terms of utilization, cancellations and other factors interfering with smooth planning and performance. The cross-functional team deliberates the complete program, day by day and members inform their colleagues about all relevant issues needed for optimal planning and safety. The CFT is fully responsible for optimal preparation and continuity of the OR program for the week to come. The anesthesiologist as the chairman of the team, chairs the meeting. Besides their role in optimizing OR scheduling, CFTs draw attention to imminent conflicts. Methods Data was prospectively collected from 2005 until 2012 and analyzed retrospectively for the purpose of this study. All data were registered electronically by the OR nursing staff in the Hospital Information System and validated by the surgeon and anesthesiologist in charge. Data used in this longitudinal study involved repeated and continuous measurement of the same performance indicators over a long period of time; in this study raw utilization was focussed on. The performance of one OR day, which is generally equal to eight hours of block time (usually from 8:00 h until 16:00 h) allocated to a specific surgical department, is commonly evaluated by this indicator. It is a measure for efficiency and relates to whether staffed operating rooms are under – or overutilized. An OR is considered underutilized when OR time is staffed but not used for surgery, setup or clean up, which can occur if cases finish earlier than scheduled, there are prolonged delays between cases or a case is cancelled unexpectedly. An OR is regarded overutilized when it is staffed at overtime wages (Macario, 2007). OR utilization can be calculated in two ways, raw and adjusted. Raw utilization is defined as the total hours of elective cases performed within OR block time divided by the hours of allocated block time per day x 100 percent. Adjusted utilization uses the total hours of elective cases performed within OR block time, including “credit” for the turnover time necessary to set up and clean up ORs × 100 percent (Dexter, 2003; Donham et al., 1996; Van Veen-Berkx et al., 2013). This study considered raw utilization, excluding turnover time. To define a consistent dataset for analysis, all non-elective (emergency) cases and all outpatient cases, were excluded. In RUNMC outpatient surgical cases are allocated to a specific organizational OR unit (a separate “day surgery centre”). The outpatient surgery workflow varies from the in-patient surgery workflow. This study focussed on elective in-patient surgical cases.
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A national independent data management center was employed to facilitate the collection and processing of the data. This center provided professional expertise to facilitate the collection and processing of data records. Data reliability checks were performed before data were ready for analysis. Reliability refers to the accuracy and completeness of data, given the intended purpose for use (Bowling, 2009). Reliability checks for this research consisted of: •
a check for missing values (e.g. are all months included; are all OR locations included; are all required data elements included);
•
a consistency check to determine if data is in accordance with earlier data deliveries (is the number of surgical cases comparable with the number of cases during the month of the previous year?);
•
the correctness of data was studied to check if values are outside of a designated range (e.g. time patient leaves OR o time patient enters OR; date o W date patient enters OR); and
•
outliers were removed from the dataset according to outlier filtering rules (e.g. surgeon-controlled time 0 W x ⩽ 1,400 minutes; OR utilization 25 ⩾ x ⩽110 percent; cumulative turnover time 0 W x ⩽ 120 minutes).
This study evaluated the effect of CFTs in both surgical Departments A and B on OR performance. Surgical Department A was chosen because this department went through a rapid and meticulous introduction of this redesign process including optimization of patient safety and surgical scheduling. Moreover, their patient case mix is multifaceted with a relatively high percentage of complex and acute or semi-acute cases, which makes scheduling a demanding process. The Surgical Department B was opted for because this is a relatively small group with a high percentage of elective cases. Data analysis was performed using SPSS Statistics 19. Normality of distribution was determined using the Kolmogorov-Smirnov test. The relationship between raw utilization (y) and years (x), concerning the two surgical departments, was analyzed with linear regression analysis. Violations of the basic regression assumptions were diagnosed by means of the residual plot; a graph with the residuals (y − ŷ) plotted on the vertical axe and the predicted values of raw utilization (ŷ) on the horizontal axe. The box plot, also called a box-and-whisker plot, was introduced by Tukey (1977). The graph consists of a box extending from the first quartile (Q1) to the third quartile (Q3), a mark (black horizontal line) at the median with whiskers extending from the first quartile to the minimum value and from the third quartile to the maximum value. The interquartile range (IQR) is also called the “middle 50” and is a measure of dispersion. It is calculated by subtracting the upper and lower quartiles: IQR ¼ Q3 − Q1 (Dawson, 2011; Munro, 2005). Results Data were available for a total of seven consecutive years from 2005 until 2012. After excluding day care surgery and non-elective surgical cases, the collected data consisted of 4,046 OR days for surgical Department A and 1,154 OR days for surgical Department B on which, respectively 8,419 and 5,295 surgical cases were performed. Outliers (mean ±3 SD) were excluded, based on the SPSS output “Casewise Diagnostics”. This left 4,009 OR days for surgical Department Aand 1,127 OR days for surgical Department B, for statistical analysis.
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Surgical Department A Figure 1 shows that raw utilization of surgical Department A demonstrated an increase since 2006. Most of this increase was effectuated in the lower quartile (Q1 from 62 percent in 2005 to 91 percent in 2011) and the median (from 82 percent in 2005 to 97 percent in 2011). The variation in raw utilization reduced from IQR 33 percent in 2005 to IQR 8 percent in 2011. Results of linear regression analysis showed mean raw utilization significantly increased 3.077 percent every year (p o 0.0005). Surgical Department B Figure 1 shows that raw utilization of surgical Department B demonstrated an increase since 2005. The main part of this increase was effectuated in the lower quartile (Q1 from 74 percent in 2005 to 86 percent in 2011). The variation in raw utilization reduced from IQR 21 percent in 2005 to IQR 8 percent in 2011. Results of linear regression analysis showed mean raw utilization significantly increased 0.899 percent every year (p o 0.0005). year 2005 2006 2007 2008 2009 2010 2011
120
100 Raw Utilization Rate (%)
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Data of each year and each department showed that raw utilization was not normally distributed (Kolmogorov-Smirnov test, p o 0.0005). However, normality of data are not an assumption in linear regression analysis. With reference to the basic regression assumptions; interval measure level of variables, independence of the errors, homoscedasticity (or constant variance) of the errors were not violated. Normality of the error distribution was dishonored, however, this assumption did not lead to biased results because the assumption of normality is not important for large sample sizes (n ⩾ 1,000), which was the case in this study.
80
60
40
20
0 Surgical Department A
Surgical Department B
Source: Database Nationwide OR Benchmark University Medical Centers, specifically RUNMC
Figure 1. Box-and-whisker plots raw utilization (percent) surgical Departments A and B (2005 – 2011)
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Discussion The purpose of this study was to identify the relationship between the implementation of cross-functional teams and OR performance. This study shows a long-term perspective and a gradual improvement in OR utilization. Our data are insufficient to prove not that this is a direct result of introduction of the CFTs, however, since this was the only major change in the OR organization in the time period of the study, it is highly likely that the improvement can, to a great extent, be ascribed to the systematic work of the two teams. The effects of single loop and double loop learning, as well as focussing on OR scheduling are well-documented helpsin the process of organizational learning that we have gone through (Argyris, 1976; Bitter et al., 2013). Improving OR performance by the introduction of a CFT-based organization in the operative process contributes to more focus on OR scheduling and better collaboration in a team. Abandoning the so-called “functional silos” results in less variation in raw utilization. This redesign is based on the principle that a cross-functional team has the ability to attenuate variability, unpredictability and politics (Achterbergh and Vriens, 2009). In other words, cross-functional teams are assumed to have a self-regulating capacity. It is crucial that the OR management facilitates the CFTs and backs them up, in essence, under any circumstances. Applying socio-technical systems theory design principles has shown to not only lead to improvements in the quality of working life, but can also contribute to an increase in organizational productivity and patient safety as well as better collaboration between professionals (Argyris, 1976; Achterbergh and Vriens, 2009; Bitter et al., 2013). We decided that once this structure is in place and has shown to be effective, the attention will be focussed on culture and attitude, as the next step. This study showed a significant reduction in variation of raw utilization since the implementation of cross-functional OR scheduling teams in 2004, with a gradual improvement over the years. Regarding to the linear regression analysis, we can conclude a significant increase in mean raw utilization every year, with 3.077 percent for surgical Department A and 0.899 percent for surgical Department B. We expect that this increase will stabilize during the time. There are two potential explanations for these findings; one is the organizational learning effect and the other is more efficient utilization of OR capacity in the strict sense as a result of focusing on the utilization process by the whole OR organization. The stepwise reduction of variation – a decrease of IQR during the years – indicates an organizational learning effect, whereas an increase of raw utilization, reduction of uncertainty and reliability in scheduling are indicators of more efficient utilization of OR capacity (Murray and Berwick, 2003; Reason, 2005). This indicates a stable process and positive learning effect in both surgical departments. The redesign in our study is based on the principle that a CFT has the ability to attenuate variability, reduce unpredictability, the impact of local politics and the effect of personal preference and input of the individual staff members of both departments on the OR schedule. Reduction of uncertainties – by means of optimizing multidisciplinary collaboration – will improve OR scheduling (Harders et al., 2006). In other words, CFTs are assumed to have a self-regulating capacity to identify bottlenecks and to improve continuity. The effect of CFTs can also be endorsed by Donabedian’s traditional structure-processoutcome model (Donabedian, 1966). This model claims a causal relationship between structure, process (CFTs) and outcome (raw utilization). The structure of the context in
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which health services are delivered, has an effect on processes and outcomes. Outcomes indicate the combined effects of structure and process. CFTs have several indicators to score their performance. Based on previous work of others on improvement of OR scheduling (Stepaniak et al., 2009; Strum, 2000), raw utilization was chosen in this study since we wanted to analyze over-all performance in a straightforward fashion. CFTs have shown to progressively learn how to deal with their new role and improve their performance continuously through collaboration and better use of checks and balances (Achterbergh and Vriens, 2009; Argyris, 1976; Overdyk et al., 1998). Systems that are highly differentiated generally require correspondingly high degrees of integration (Berg et al., 2005; Glouberman and Mintzberg, 2001). As for surgery, accurate scheduling of operations is a crucial factor, complicated by the uncertainty regarding the adequate preparation of the patients on the tentative list and unpredictability of the duration of surgical procedures. Modeling that variability by continuous registration, in turn, provides a mechanism to generate tools for accurate time estimation (Stepaniak et al., 2009). OR professionals are conservative and have a tendency to remain within their comfort zone. Introducing CFTs is a multi-factorial and multi-consequential intervention with emphasis on multidisciplinary collaboration. Multidisciplinary teamwork is an important foundation for an effective organization (Parker, 2002). Effective CFTs are characterized by setting and accepting common operational and safety goals (Mathieu et al., 2008). In effective CFTs there is a strong collective responsibility for these results in which individual interests are subordinate to the interests of the team. (Mathieu et al., 2008; Parker, 2002; Gittell, 2009) Effective CFTs are well organized (Bitter et al., 2013), and use single-loop and double-loop learning, as well as feedback processes to continuously learn and improve their performance (Argyris, 1976; Achterbergh, Vriens, 2009). Gittell (2009) describes the critical concept of relational coordination. Coordinating work through shared goals, shared knowledge and mutual respect. Because of the way healthcare is organized, weak links exist throughout the chain of communication. Relational coordination strengthens those weak links, enabling providers to deliver high quality, efficient care to their patients. The result of this study suggest that both the surgical teams have gone successfully through this phase of adaptation to a different planning and control process. In this study, OR performance was investigated. For reasons explained in the method section, we have chosen to investigate the effect of introduction of CFTs in the two selected surgical Departments A and B based on their differences in case mix, urgency and scheduling challenges. The performance of both departments over the years showed that there is a learning curve and further improvement can be anticipated. Surgical Department A showed a stronger organizational learning effect, which was attributed to their unstable relationship to safety, incidents and changes of management over the years. Due to the stable situation of surgical Department B a weaker learning effect occurred (Pfeffer and Salancik, 2003). The analysis of several additional separate performance indicators, e.g. over-utilized time and case cancellations, can identify areas of further improvement. Other performance indicators – e.g. first-case tardiness, turnover time between cases and under-utilized time – could also further improve utilization of the available OR time. The RUNMC did not specifically formulate goal-settings or standards for OR performance indicators in advance. Even though the Audit Commission (2002) in the UK has tried to formulate a standard for utilization, a general global standard has not
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yet been found for performance indicators in OR scheduling. Through benchmarking with other Dutch University Medical Centres, we might be able to substantiate the added value of CFTs to all other on-going improvement programs. A limitation of this study was the longitudinal and retrospective nature. During the seven years of investigation other developments parallel to the introduction of CFTs, e.g. more focus on patient safety issues, and increased awareness of costs and efficiency by national developments in health care, could have influenced the outcome. The data set of RUNMC was not compared to the other seven University Medical Centres in the Netherlands and no information about their performance is available yet. To further specify the separate role of CFTs, the data of this study need to be compared to performance data in the other UMC’s in the Netherlands in the near future. Moreover, there is a difference in patient case mix between the two surgical departments investigated. However, it is unlikely that difference in case mix fully explains the differences in OR performance. This study that set out to analyse the effects of a new strategy to improve OR efficiency, demonstrates that introducing CFTs improves OR performance by working together as a team. The results need to be extended and supported by multi-center research. Glossary CFT OR RUNMC IQR
Cross-Functional Team(s) Operating Room Radboud University Nijmegen Medical Centre Interquartile Range
References Achterbergh, J. and Vriens, D. (2009), Organizations: Social Systems Conducting Experiments. Springer-Verlag Berlin Heidelberg. Argyris, C. (1976), “Single-loop and double-loop models in research on decision making”, Administrative Science Quaterly, Vol. 21 No. 3, pp. 363-375. Audit Commission (2002), Operating Theatres, A Bulletin for Health Bodies, Audit Commission. Berg, M., Schellekens, W. and Bergen, C. (2005), “Bridging the quality chasm: integrating professional and organizational approaches to quality”, International Journal for Quality in Health Care, Vol. 17 No. 1, pp. 75-82. Bitter, J., van Veen-Berkx, E., Gooszen, H.G. and van Amelsvoort, P. (2013), “Multidisciplinary teamwork is an important issue to healthcare professionals”, Team Performance Management, Vol. 19 Nos 5/6, pp. 263-278. Bowling, A. (2009), Research Methods in Health. Investigating Health and Health Services, Open University Press, Bershire. Dawson, R. (2011), “How significant is a boxplot outlier?”, Journal of Statistics Education, Vol. 19 No. 2, pp. 1-13. de Sitter, L.U., den Hertog, J.F. and Dankbaar, B. (1997), “From complex organizations with simple jobs to simple organizations with complex job”, Human Relations, Vol. 50 No. 5, pp. 497-534. Dexter, F. (2003), “Operating room utilization alone is not an accurate metric for the allocation of operating room block time to individual surgeons with low caseloads”, Anesthesiology, Vol. 98 No. 5, pp. 1243-1249.
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Donabedian, A. (1966), “Evaluating the quality of medical care”, Milbank Mem Fund Q, Vol. 44, Supplement, pp. 166-206. Donham, R.T., Mazzei, W.J. and Jones, R.L. (1996), “Procedural times glossary”, American Journal Anesthesiology, Vol. 23 No. S5, pp. 4-12. Gittell, J.H. (2009), High Performance Healthcare: Using the Power of Relationships to Achieve Quality, Efficiency and Resilience, The McGraw-Hill companies, New York, NY. Glouberman, S. and Mintzberg, H. (2001), “Managing the care of health and the cure of disease-part 1: differentiation”, Health Care Management Review, Vol. 26 No. 1, pp. 56-71. Glouberman, S. and Mintzberg, H. (2001), “Managing the care of health and the cure of diseasepart 2: integration”, Health Care Management Review, Vol. 26 No. 1, pp. 72-86, . Harders, M., Malangoni, M.A., Weight, S. and Sidhu, T. (2006), “Improving operation room efficiency through process redesign”, Journal of Surgery, Vol. 140 No 4, pp. 509-516. Kuenen, J.W., Geurts, M., Van Leeuwen, W. and Nolst Trenité, T. (2011), “Provide value. More quality for less money: what the Dutch health care can learn from Sweden”, The Boston Consulting Group. Macario, A. (2007), “Are your operating rooms ‘efficient’?”, OR Manager, Vol. 23 No. 12, pp. 16-18. Marjamaa, R., Vakkuri, A. and Kirvela, O. (2008), “Operating room management: why, how and by whom?”, Acta Anaesthesiology Scandinavia, Vol. 52 No. 5, pp. 596-600. Mathieu, J., Maynard, M.T., Rapp, T. and Gilson, L. (2008), “Team effectiveness 1997-2007: a review of recent advancements and a glimpse into the future”, Journal of Management, Vol. 34 No. 3, pp. 410-476. Munro, B.H. (2005), Statistical Methods for Healthcare Research, 5th ed., Lippincott Williams & Wilkins, Philadelphia, PA. Murray, M. and Berwick, D.M. (2003), “Innovations in primary care. Advance access: reducing waiting and delays in primary care”, JAMA, February 26, Vol. 289 No. 8, pp. 1035-1040. Overdyk, F.J., Harvey, S.C., Fishman, R.L. and Shippey, F. (1998), “Successful srategies for improving operating room efficiency at academic institutions”, Anesth Analg, Vol. 86 No. 4, pp. 896-906. Parker, G.M. (2002), Cross Functional Teams. Working with Allies, Enemies and Other Strangers, 2nd ed., Jossey-Bass. An Imprint of Wiley, San Francisco, CA. Pfeffer, J. and Salancik, G.R. (2003), The External Control Of Organizations. A Resource Dependence Perspective, Stanford University Press, Stanford. Reason, J. (2005), “Safety in the operating theatre part 2: human error and organizational failure”, Qual Saf Health Care, Vol. 14 No. 1, pp. 56-60. Stepaniak, P., Heij, C., Mannaerts, G.H., de Quelerij, M. and de Vries, G. (2009), “Modeling procedure and surgical times for CPT-anesthesia-surgeon combinations and evaluation in terms of case duration prediction and OR efficiency”, Anesth Analg, Vol. 109 No. 4, pp. 1232-1245. Strum, D.P. (2000), “Surgeon and type of anesthesia predict variability in surgical procedure times”, Anesthesiology, Vol. 92, pp. 1454-1466. Tukey, J.W. (1977), Exploratory Data Analysis, 1st ed., Pearson PLC, New York, NY. Van Veen-Berkx, E., Elkhuizen, S.G., Kalkman, C.J., Buhre, W.F. and Kazemier, G. (2013), “Successful Interventions to Reduce First-Case Tardiness in Dutch University Medical Centers. Results of a Nationwide Operating Room Benchmark Study, American Journal of Surgery, doi:10.1016/j.amjsurg.2013.09.025. Further reading Mainz, J. (2003), “Defining and classifying clinical indicators for quality improvement”, Int J Qual Health Care, Vol. 15 No. 6, pp. 523-30.
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About the authors Justin Bitter is a PhD Fellow at the Radboud University Medical Center Nijmegen, the Netherlands, and a Manager Operating Rooms at the Bernhoven Hospital in Uden, the Netherlands, and is preparing a PhD study about teamwork in OR in academic hospitals. Justin Bitter is the corresponding author and can be contacted at: [email protected] Elizabeth van Veen-Berkx is a PhD Fellow OR Benchmarking Collaboration at the Department of Operating Rooms at the Erasmus University Medical Center Rotterdam, the Netherlands. Pierre van Amelsvoort is a Consultant at the STGroup (Netherlands) and a Professor Social Innovation at the Catholic University in Leuven, Belgium. Hein Gooszen is a Professor at the Faculty of Medical Sciences of the Radboud University Nijmegen in the Netherlands, teaching academization of operative processes. Hein Gooszen is also a Professor of Surgery at the Radboud University and the Head of the Department of Evidence Based Surgery at the Radboud University Medical Center Nijmegen, the Netherlands.
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