Improving economic efficiency of operating rooms: production planning approach. Antti Peltokorpi*, Paulus Torkki, Vesa Kämäräinen

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1 Int. J. Services and Standards, Vol. 5, No. 3, Improving economic efficiency of operating rooms: production planning approach Antti Peltokorpi*, Paulus Torkki, Vesa Kämäräinen Institute of Healthcare Engineering, Management and Architecture, Helsinki University of Technology, Otaniementie 17, TKK, Finland *Corresponding author Markku Hynynen Department of Anaesthesia, Helsinki University Central Hospital, Turuntie 150, Espoo, Finland Abstract: Managing surgical services efficiently is essential when maximising the produced health with limited resources. This study aims at understanding the efficiency of operating rooms from the production planning and control point of view. Economic efficiency measure that includes the process costs and output was developed and tested in a real-life context. Daily efficiency was mostly dependent on the number of used operating rooms (beta 0.42, p < 0.01). Speed of surgery, number of delayed surgeries and planned utilisation rate also had an effect on the efficiency. Compared to the previous literature the role of staffing in improving operating room efficiency is emphasised. Keywords: operating room management; production planning; control; efficiency; scheduling; staffing; services; standards. Reference to this paper should be made as follows: Peltokorpi, A., Torkki, P., Kämäräinen, V. and Hynynen, M. (2009) Improving economic efficiency of operating rooms: production planning approach, Int. J. Services and Standards, Vol. 5, No. 3, pp Biographical notes: Antti Peltokorpi is a Researcher at Helsinki University of Technology. He has worked closely with various operations management and process projects in healthcare since He has specialised in analysis and benchmarking of production processes in different healthcare areas including hospitals, healthcare corporations and diagnostics services. Paulus Torkki is a Researcher at Helsinki University of Technology. After graduating as an Industrial Engineer, he has worked with development of IT systems for Instrumentarium and GE Healthcare in Finland and in the USA. He has been involved in numerous research and development projects in healthcare. He is finishing his PhD in Industrial Engineering focusing on surgical processes. Copyright 2009 Inderscience Enterprises Ltd.

2 200 A. Peltokorpi et al. Vesa Kämäräinen is a Research Director at Helsinki University of Technology. He has a wide experience in supply chain management and process development in retail and healthcare sectors. He has worked for private consulting companies as well as academic world serving various organisations. His research interests are mainly in healthcare demand management, process development and capacity management. Markku Hynynen is a Chief Anaesthesiologist in Jorvi Hospital, which belongs to Helsinki University Central Hospital. Previously, Hynynen has worked, e.g. as Professor of Anaesthesia and Intensive Care in Kuopio University and as an Associate Medical Director in Jorvi Hospital. He has been a writer in about 70 peer reviewed academic original publications. 1 Introduction Operating Rooms (ORs) are typically the most cost-intensive part of the hospital. Based on the industry study in several American hospitals, ORs were estimated to account for more than 40% of a hospital s total revenues and a similarly large proportion of their total expenses (HCFMA, 2005). OR also tends to be a bottleneck phase in most patient processes. Hospital that aims at improving the efficiency of operating rooms can also improve the throughput of the whole system. Managing operating rooms efficiently is essential when hospitals and healthcare systems aim at maximising the produced health with limited resources (Berwick, 2005). There is no clear consensus about measures for OR efficiency: Some studies focus on access to care (e.g. Oudhoff et al., 2007) and others underline number of operations (McGowan et al., 2007) or overtime costs (Dexter and Macario, 2002). The main limitations of the extant studies are the used performance measures that lead to a sub-optimisation or can not be used when comparing ORs with different case mix. Proposed efficiency measures are also rarely implemented in hospitals. And even if they are implemented, it has been argued that measures are well below achievable targets at most hospitals (CAB, 2001). In the study about 26 hospitals with different case mixes, the average OR capacity utilisation rate was only 66.0% and the hospital-specific rates ranged between 52.7 and 85.3% (Peltokorpi, 2008). Low performance rates rarely lead to policy improvements. For example in Finland, according to an extensive survey, in half of the hospitals performance indicators never or seldom lead to measures such as notifications, changes in allocations or recruitment (Marjamaa and Kirvelä, 2007). More understanding is needed about the relevant performance measures in ORs and how the performance consists of decisions and events in the planning and execution process. Adopting concepts and principles from industrial engineering and management (Vissers et al., 2001) has made evaluating healthcare service systems much easier. This study suggests that considering ORs and surgical services from the perspective of operations management and production planning and control provides a basis for improving the performance.

3 Improving economic efficiency of operating rooms 201 This study aims at understanding the economic efficiency of the OR process from the production planning and control point of view. The primary research objectives were: 1 Define and describe the operating room production planning and control system 2 Define the relevant measures for the operating room economic efficiency 3 Analyse the existing processes in order to reveal how to improve the economic efficiency in the operating room. This paper is organised as follows: First, the study methods are presented. Secondly, we focus on defining the OR production planning and control system. After that, the more thorough analysis about extant studies in the area of OR management is illustrated. Based on the analysis, the most relevant efficiency measures are selected and revised and after that tested in real-life settings. Finally, the results of the study and their theoretical and practical implications are discussed. 2 Study methods A literature review about theories of operations management and production planning and control and their applications in healthcare systems was conducted in order to define the hierarchy of the operating unit production planning process. After that, previously used OR efficiency measures were evaluated. The most relevant efficiency measures were identified and defined based on the missions and objectives of the ORs. An overall aim to increase the amount of produced health with limited costs was set as a starting point for the measures. The proposed efficiency measure was applied in the real-life context in order to test its applicability and reliability, and to reveal the factors and decisions in the planning process that in the studied hospital significantly affect the efficiency of the ORs. 2.1 Operating room production planning and control system Operations management is the field of study that focuses on the effective planning, scheduling, use and control of a manufacturing or service organisation (APICS, 2004). In the stream of operations management theory, production planning and control focuses on the production part of the organisation or company game plan (Vollman et al., 1997). Vissers et al. (2001) represented a framework for production control in healthcare organisations. They argued that patient groups should be focal units in hospital planning and control systems, and that the time of specialists is the most essential bottleneck resource in the hospital. Based on the previous framework (Vissers et al., 2001), we suggest that the planning and control of surgical services can be described as a hierarchical process (Figure 1). Healthcare organisations define their missions and objectives in a given environment, which consists, e.g. of laws, values, markets and needs relevant in an organisation s area of operation. They define their service range, customers and primary measures for success. Strategic planning is a rough plan about number of operating units and produced operations at each unit. Patient volumes planning and control focuses on estimating future demand and building fixed capacity, such as core personnel and facilities.

4 202 A. Peltokorpi et al. Figure 1 Operating room production planning and control hierarchy System environment (laws, policies, markets, needs, values) Mission and objectives, strategic planning -What to serve and to whom? Primary measures for success? -What produce where? (plants, locations, service mix at each plant) Patient volumes planning & control -Defining future surgery volumes, hiring personnel, engineering facilities to build capacity Resource planning & control -Allocating surgeon-time inside a specialty to different patient groups and departments -Allocating operating room sessions to specialties and patient groups -Daily staffing of operating room sessions Patient planning & control Case scheduling Daily adjustments Execution process Performance monitoring

5 Improving economic efficiency of operating rooms 203 Resource planning and control includes weekly, daily and hourly plans about the use of shared core resources, including the time of specialists and OR sessions. In each specialty, the time of specialists is allocated to different patient groups and departments in the hospital. Daily OR sessions are allocated to the specialties or directly to surgeons and patient groups. Allocated OR sessions are staffed by anaesthesiologists, nurses and other professions. In patient planning and control individual cases are scheduled to OR sessions typically couple of weeks before the day. Last-moment adjustments are forced to be made due to additional cases, especially emergencies. Measuring the performance of the execution is an essential part of the control process. In well-managed organisations, monitored measures are based on organisation s objectives, and performance results have implications for future strategies and plans. 2.2 Evaluation of the previously used efficiency measures A literature review concerning current efficiency measures in surgical services was conducted in order to define how the value chain has been understood historically. The review was conducted by searching the Helsinki University s Vertex database and by utilising a structured bibliography about surgical services maintained by Dexter (2008). The database query found 43 articles where the terms operating room management and efficiency occurred in the title, abstract or text. Efficiency measures were extracted from Vertex articles and those in Dexter s bibliography. If they contained references to other articles relating to the defining efficiency, those articles were also included. The review revealed a variation in efficiency measures used in surgical services. Almost every study concerning OR management defined performance measure(s) for surgical services. The measures can be divided into four efficiency categories in addition into the external and internal measures (Table 1). Most measures used in the reviewed studies of operating room management focus on internal efficiency. The studies emphasise that ORs function in isolation from other hospital units and that ORs are typically bottlenecks in the surgical process (Torkki et al., 2006). Production system quality measures focus on how exactly production plans are realised. Late cancellations are typically the result of poor pre-operative processes and deficiencies in the information process. Shifted surgeries are scheduled or urgent surgeries that are delayed for at least one day due to an overload or the lack of critical resources (Testi et al., 2007). Although shifting a surgery might increase an operating unit s daily efficiency, it incurs extra costs in other units and also typically weakens the patient s condition. Start-time tardiness illustrates the punctuality to start the operation no earlier and later on its planned time (Macario, 2006). Surgery time is another kind of production system measure. Unforeseeable extension of a surgery or OR time can lead to overtime costs or shifted operations. Capacity utilisation and time measures are the performance measures most frequently used in operating room management studies. The OR raw utilisation rate, which is the share of staffed OR hours when there is a patient in the OR, is among the most used measures. Two other commonly used measures include non-operative time between consecutive surgeries and turnover time when there is no patient in the OR. The underlying assumption is that staffed OR time is an expensive bottleneck resource in the surgical process, and must therefore be used efficiently.

6 204 A. Peltokorpi et al. Table 1 Measures used for efficiency of surgical services Production system quality measures Internal Late cancellations measures (Ferschl et al., 2005; McGowan et al., 2007) Shifted operations (Testi et al., 2007) Start-time tardiness (Macario, 2006) Capacity utilisation and time measures Technical efficiency measures OR raw utilisation rate Standardised (Marjamaa and surgery time per Kirvelä, 2007; personnel hours Denton et al., 2007) (Torkki et al., 2006) Non-operative time (Overdyk et al., 1998; Torkki et al., 2006) Turnover time (Marjamaa and Kirvelä, 2007; Macario, 2006) Surgery time First operation (Torkki et al., 2006) start time (Overdyk et al., 1998) Overused OR time (Dexter and Macario, 2002; Testi et al., 2007) External In-hospital waiting measures time (Marjamaa and Kirvelä, 2007) Total waiting time (Oudhoff et al., 2007) Underused OR time (Dexter and Macario, 2002; Peltokorpi et al., 2008) Minimum OR blocks needed with constant throughput (Van Houdenhoven et al., 2007a) Economic efficiency measures Costs of care episode (Hall et al., 2006) Contribution to margin (McIntosh et al., 2006; Macario, 2006) Number of operations Anaesthesia per unit time (Marjamaa workload per labour and Kirvelä., 2007; cost (McIntosh McGowan et al., 2007; et al., al. 2006) Santibanez et al., 2007; Testi et al., 2007) Maximum ward beds needed (Santibanez et al., 2007) Opening hours of ward unit (Testi et al., 2007) Cost per output (Peltokorpi et al., 2008) Underused OR time is defined as the idle time during office hours after the last patient has left the OR. Similarly, overused OR time is the amount of time from the end of office hours until the time the last patient leaves the OR. The sum of underused and overused OR time (Dexter and Macario, 2002) provides information about the balance of scheduling and the use of resources. Overused OR time is typically multiplied by a relative cost factor between 1.5 and 3 (Dexter and Macario, 2002; Peltokorpi et al., 2008). One problem with using underused OR time as an efficiency measure is that it penalises teams that operate quickly. These teams should be rewarded. Underused OR time is a relevant measure when scheduling patients efficiently (Dexter and Epstein, 2005). However, during the day of surgery, underused OR time is typically included in the sunken personnel costs of regular hours. Technical efficiency measures, which take into account the relationship between process output and the amount of used resources, are seldom mentioned in the literature. One example of their use was a study by Torkki et al. (2006), which used standardised surgery time per personnel hours as an efficiency measure. Each procedure was weighted

7 Improving economic efficiency of operating rooms 205 by its historical average duration. The total standardised surgery time of the period was calculated by summing weights of surgeries performed. In some studies, proposed interventions are evaluated by estimating their effects on the number of surgeries performed per unit time with fixed resources (McGowan et al., 2007). In Van Houdenhoven et al. s (2007a) research the approach was reversed: the aim was to find the minimum OR blocks needed with a constant throughput. Regardless of the details in the measures, technical efficiency measures aim at revealing the effect of interventions on the ratio of process output to used resources. Economic efficiency measures are mainly used in competitive environments (McIntosh et al., 2006). Contribution to margin is used when the organisation aims straightforwardly maximising the profit in the OR. Anaesthesia workload per cost hours is used as an economic efficiency measure when billing is based on the workload, such as time used in value-adding tasks. Hall et al. (2006) examined how surgeons affect the variation in total hospital costs per patient. However, they considered only patient- and surgeon-specific factors, not decisions that were made in the operating unit planning process. Economic efficiency measures, such as profit or total costs, are not widely used in non-competitive ORs. One reason for this might be that in a non-competitive environment, increased costs have been added to the prices. In addition, the prices of certain services are not based on the unit costs, but are defined at an upper level so that total costs and profits are in balance. Economic efficiency in ORs could be measured by dividing the personnel costs in the unit by the produced output (Peltokorpi et al., 2008). This measure could be developed by considering also costs that occur by reason of the actions in the operating unit but that are a burden on other units of the hospital. In some studies, total waiting time is used as a primary measure for OR performance (Oudhoff et al., 2007). This viewpoint fits best ORs that serve mainly emergency patients (Torkki et al., 2006). Total waiting time is also widely used in studies where the aim is to consider total costs associated with illnesses, not only the costs for service provider (Peltokorpi and Kujala, 2006). 2.3 Developing a new input-output measure Most production quality, utilisation rate and time measures do not account for the amount and cost of the used resources. They are often used as additional measures to more complex resource related or financial measures (Torkki et al., 2006; Testi et al., 2007). Due to the relatively high cost intensity of ORs compared to other care phases in the surgical care process, economic efficiency measures should be emphasised when examining OR performance. Pure resource utilisation measures, such as OR utilisation rates and turnover times, are insufficient, because they typically focus more on the use of space than the use of more costly personnel, and they do not account for output. Torkki et al. (2006) used a technical efficiency index that takes the used personnel hours as an input and the standardised surgery time as an output of the OR. We suggest that this measure could be extended to an economic efficiency measure which considers the costs of used personnel resources, penalties of the production quality errors and throughput of the system: Cost Economic _ efficiency = = Output n i= 1 cih i + xo + yc + wd, (1) m dn j = 1 j j

8 206 A. Peltokorpi et al. where, c i is the hourly cost of work of profession i during office hours and H i is the daily number of working hours of profession i, x is the hourly cost of operating room overtime, O is the number of overtime hours, y is the cost of shifted elective operations, C is the number of shifted elective operations, w is the cost of delayed emergency operations, D is a number of delayed emergency operations, d j is the standard OR time for surgery type j and N j is the number of surgeries type j performed during the considered period. 2.4 Testing economic efficiency in a real-life setting The developed efficiency measure was tested in Jorvi Hospital, Finland. Jorvi serves 270,000 inhabitants in the Helsinki metropolitan area. The main operating unit has 11 operating rooms in which surgeries are performed per year. Jorvi s surgical specialties are orthopaedics, gastroenterological surgery, vascular surgery, thoracic surgery, plastic surgery, urology, breast surgery, gynaecology and obstetrics and paediatric surgery. Elective operations occur Monday to Friday from 8.00 am to 3.30 pm. For emergency cases, there is one OR resourced in the evenings, at night and on weekends. The OR planning and execution process was modelled using personnel interviews, observations and planning documents (Figure 2). The daily performance of the ORs was a result of the decisions in the planning process and the unplanned events. In the planning phase, capacity allocation, staffing and case scheduling provided initial estimates of daily performance. These estimates could then be adjusted by considering the estimated emergency load. Emergencies remaining from the previous day increased the total emergency load. At the beginning of the office hours, cancellations and new emergency operations changed the balance between load and resources. These occurrences continue throughout the day. The management s response to an overload might be to call in standby personnel or reschedule one or more surgeries, which led to additional personnel and care costs inside and outside the unit. In Jorvi, ORs were allocated to surgical specialties in advance, based on historical demand. Allocations were typically similar from week to week, with each specialty using certain ORs on certain days. ORs were open for 7½ hours on normal weekdays, and 6½ hours on meeting days (Fridays). During the period from January 2007 to May 2007, individual ORs were allocated to one specialty 98% of the time. Specialties scheduled elective surgeries to their allocated OR time blocks and reserved time for emergency cases. The head of anaesthesiology was the manager of the ORs. He was responsible for allocating and coordinating OR time resources and anaesthesiologists. The daily allocation and management of nurses was managed by the head OR nurse. On the day of their surgery, patients were first moved to the operating unit from the ward. They were received in the entrance hall, moved into the OR and then transferred to the operating table. Anaesthesia induction started when the anaesthesiologist entered the OR. After that, surgical preparations were performed and instruments were carried into the OR and placed on the tables. In most cases, the instruments had undergone preliminary preparations in a room next to the OR. This approach meant that cleaning the OR was the only process on the critical pathway between consecutive patients. The surgeon was called during surgical preparation time. After the wound was closed and dressed, the patient was awoken. If the surgery was done using local anaesthesia, the patient went directly back to bed and to the post-anaesthesia care unit.

9 Improving economic efficiency of operating rooms 207 Figure 2 Relationships of planned and unplanned factors to technical and economic efficiency Allocated OR time Planned personnel Estimated OR utilization Planned staff intensity Estimated operations Planned operations Estimated emergency load Emergencies from previous days Planning and estimating Load from previous days Personnel absence Standby personnel Emergencies on the day of surgery Cancelled cases Changes on the day of surgery Realized personnel Technical efficiency Realized operations Delayed elective and emergency cases Performance Overutilized OR time Additional care costs Realized costs Economic efficiency

10 208 A. Peltokorpi et al. The daily economic efficiency and the decisions and events in the planning and execution processes were analysed during 89 weekdays between January and May Standard OR times for output measurement were calculated based on three hospitals database that included 27,871 surgeries. Linear regression models and path analysis were utilised to reveal connections between the planning factors and daily efficiency. During the study period the daily economic efficiency varied between 184 and 377 /h (mean 277 and s.d /h). Decisions in the planning process and less-manageable parameters, such as the average speed of surgery, explained 93.6% (p<0.01) of the daily variation in the economic efficiency. The number of planned personnel per allocated OR had the strongest direct effect on the efficiency. However, path analysis revealed that personnel intensity was highly affected by the amount of allocated OR time. The amount of allocated OR time and the average speed of surgery had the largest total independent effect on the daily efficiency (beta 0.42 and 0.43, respectively, p<0.01) (Figure 3). The effect of the speed of surgery may indicate deficiencies in the definitions of the standard OR and surgery times. The same estimate that was calculated from the three hospitals database was used both in estimating surgery times and defining the output. The more thorough regression analysis revealed that about 68.3% of the effect of the speed of surgery was real and not influenced by the estimated surgery and OR times. The modified standardised beta for the speed of surgery was 0.32 (p<0.01). Shifted operations and planned OR utilisation rate had the next biggest effects (0.21 and 0.20, respectively, p<0.01). Figure 3 Total independent effect of factors on daily operating unit economic efficiency (n = 89 days) Amount of allocated OR time [h] Planned personnel per OR Personnel in education [%] Planned OR utilization [%] Emergencies from previous days Personnel absences [%] Standby personnel [%] Cancellations due to patient [%] Delay in the morning [min] OR turnover time [min] Speed of preparations [% of estim.] Speed of surgery [% of estim.] New emergency patients OR reallocation [h] Cancellations due to system [%] Overused OR time [h] Shifted emergencies [%] -0,5-0,4-0,3-0,2-0,1 0,0 0,1 0,2 0,3 0,4 Total independent effect on the daily ec onomic efficiency [stand. Beta]

11 3 Discussion Improving economic efficiency of operating rooms 209 Operating room production planning and control system consists of several planning levels. Decisions before the day of operation have direct and indirect effects on the daily efficiency. Because the mission of healthcare systems is to maximise the produced health and to minimise the costs, we suggest that economic efficiency measure should be used in the everyday measurement of OR performance. Although the measure does not consider all the costs incurred in the unit, it covers the most expensive personnel costs and penalties that are associated with the poor production quality, and therefore hinders sub-optimisation. In hospitals, overlapping planning decisions are typically made annually, monthly, weekly, daily and even from patient to patient. Despite the higher random variation during one day than during a week or a month, daily performance is nonetheless an important measure. Decisions that were previously made in the planning process are tested daily when OR managers decide whether to shift operations, to call standby personnel or to allow overtime hours. An OR s long-term success depends on daily performance. Therefore, in order to improve the overall performance of ORs, factors that affect the daily economic efficiency must be considered. The amount of OR time allocated to specialties and the speed of surgery had the biggest effect on the daily economic efficiency. The significant effect of the speed of surgery weakened the reliability of the measure. It is suggested that the reliability of the output measurement can be improved by calculating standard OR and surgery times not only based on operation types but also based on the case complexity (e.g. Broka et al., 2003; Lebowitz, 2003). In the OR time allocation, the problem is not in the allocation itself, but in a poor balance between OR staffing and allocation. In a block-scheduling system, where OR lists can be planned in a centralised way, balancing OR allocations between weekdays is typically an easier way to increase efficiency than allowing more variation in staffing. In an open-scheduling system, the question is how to allocate appropriate amounts of OR time and staff for each service and each day (McIntosh et al., 2006). In the blockscheduling system, demand can be more easily managed whereas in the open-scheduling system the focus is more in managing resources flexibly. 3.1 Implications to the research and theory of OR management When compared with previous literature, this study highlights the role of daily staffing when improving OR efficiency. If there is no real flexibility in day-to-day staffing, variation in the allocated OR time leads to variation in efficiency. The developed measure hinders the possibility to hide poor staffing by showing high resource utilisation and non-value added activities during the day of surgery. Similarly than in the previous studies (Dexter and Epstein, 2005; Dexter et al., 2004), the results emphasise that resource flexibility is needed during the day in order to perform both planned and urgent operations, and to maximise the efficiency. It is more profitable to pay 100% extra for overtime than avoid overtime and delay cases to next days. The study also underlines that allocated OR sessions have to be scheduled to the appropriate utilisation rate (Tyler et al., 2003; Van Houdenhoven et al., 2007b). In a unit where overtime is allowed in order to avoid cancelled operations, the optimal raw OR utilisation level would be between 85 90% of the allocated OR time.

12 210 A. Peltokorpi et al. This study illustrates that contrary to other studies, efficiency is not especially sensitive to the start time of the first surgery (Overdyk et al., 1998), OR turnover times (Marjamaa and Kirvelä, 2007; Macario, 2006) and overused OR time (Dexter and Macario, 2002; Testi et al., 2007). Based on the results, it can be argued that those time measures have an effect on the efficiency, but due to their significant role in current control systems, additional improvements can be achieved by focusing on other measures. Staffing issues seem to be quite sensitive, and changes in staffing level are more difficult to implement than changes, e.g. in case scheduling. However, this study suggests, that in the operating room management research, more attention should be paid to the optimal staffing levels and staffing practices and algorithms. 3.2 Implications to the management and administrations of services and standards When managing hospital operations, the efficiency of ORs should be maximised due to its huge contribution to the hospital s efficiency. The daily economic efficiency measure that considers the ratio between the standardised output and used hospital resources should be implemented in everyday management. Other OR efficiency measures, such as planned OR utilisation rate and planned personnel per OR, are suggested to be used as secondary measures that reveal reasons for the high or low economic efficiency. The utilisation of the developed economic efficiency measure is most convenient when the measure is integrated with hospital information management system (HIMS, e.g. Wadhwa et al., 2007). This enables day-to-day efficiency control and feedback to managers and personnel. Integrating personal incentives to this measure promotes the change toward better coordination between stakeholders in the planning and execution processes. In order to achieve a high-performance level, OR managers are recommended to pay more attention to staffing levels and personnel flexibility. More coordination between daily OR time allocations and daily nurse staffing is needed so that both the overcapacity and cancellations due to lack of personnel can be avoided. Based on the study results, ORs are also encouraged to utilise more flexible practices in the end of the day to minimise expensive surgery shifts to the next days. For service administrators and healthcare system managers, the developed measure provides a tool for assessing existing service networks. The economic efficiency measure can also be used when comparing hospitals with different case mixes. In the system level, continuous benchmarking and target levels for efficiency enable dynamic resource and demand allocations between the providers. 3.3 Limitations and future research The study had several limitations that should be avoided in future research. First, the developed measure was tested only in one hospital. The selected hospital had some special characteristics, such as case mix and teaching responsibilities. A hospital with a different service scope or a different scheduling system would have different factors affecting efficiency. As a result, these findings are not generalisable. In future research, economic efficiency should be studied in several hospitals.

13 Improving economic efficiency of operating rooms 211 Secondly, the regression models were built based on the planning process in the case hospital. There may be other factors that were not included in the models but which affected the factors under study and the overall performance. Surgeon s experience, for example, might affect on the surgery times and is therefore recommended to consider in further research. The third limitation relates to the data used in the models. Output for each surgery type was calculated based on historical averages recorded in the databases for the three hospitals. Unfortunately, in 93 cases (5.0%), there were only one or two similar surgeries in the database. A lack of similar cases can distort the output. The reliability of the economic efficiency measure could be improved by increasing the reference database and by considering also a case complexity in the output standardisation. There was no data available in the case hospital about daily complications, infections and readmissions. On the other hand, some of the used variables, such as cancelled and delayed cases, have negative effect both on economic and quality measures. However, in order to avoid conclusions that weaken the medical quality, in future studies, quality parameters should be investigated parallel with economic measures. 4 Conclusions This study illustrates that economic efficiency can be used as an overall efficiency measure in the operating rooms. Decisions about daily staffing, case scheduling and cancelled and shifted surgeries have the most important roles in maintaining high daily efficiency. References APICS (2004) APICS Dictionary, 11th ed., The Association for Operations Management. Berwick, D.M. (2005) Measuring NHS productivity, British Medical Journal, Vol. 330, No. 7498, pp Broka, S., Jamart, J. and Louagie, Y, (2003) Scheduling of elective surgical cases within allocated block-times: can the future be drawn from the experience of the past?, Acta Chirurgica Belgica, Vol. 103, pp CAB (2001) Surgical Services Reform: Executive Briefing for Clinical Leaders, Technical Report, Clinical Advisory Board, Washington, DC. Denton, B., Viapiano, J. and Vogl, A. (2007) Optimization of surgery sequencing and scheduling decisions under uncertainty, Health Care Management Science, Vol. 10, No. 1, pp Dexter, F., Epstein, R., Traub, R. and Xiao, Y. (2004) Making management decisions on the day of surgery based on operating room efficiency and patient waiting times, Anaesthesiology, Vol. 101, No. 6, pp Dexter, F. and Macario, A. (2002) Changing allocations of operating room time from a system based on historical utilization to one where the aim is to schedule as many surgical cases as possible, Anaesthesia and Analgesia, Vol. 94, pp Dexter, F. and Epstein, R. (2005) Operating room efficiency and scheduling, Current Opinion in Anaesthesiology, Vol. 18, No. 2, pp Dexter, F. (2008) Bibliography of operating room management articles. Available on line at: (accessed on 27 July 2009).

14 212 A. Peltokorpi et al. Ferschl, M., Tung, A., Sweitzer, B., Huo, D. and Glick, D. (2005) Preoperative clinic visits reduce operating room cancellations and delays, Anaesthesiology, Vol. 103, No. 4, pp Hall, B., Campbell, D., Phillips, L. and Hamilton, B. (2006) Evaluating individual surgeons based on total hospital costs: evidence for variation in both total costs and volatility of costs, Journal of the American College of Surgeons, Vol. 202, pp HCFMA (2005) Achieving Operating Room Efficiency through Process Integration. Technical Report, Health Care Financial Management Association Report. Available online at: ation.pdf (accessed on 27 July 2009). Lebowitz, P. (2003) Why can t my procedures start on time?, AORN Journal, Vol. 77, pp Macario, A. (2006) Are your hospital operating rooms efficient? A scoring system with eight performance indicators, Anaesthesiology, Vo. 105, No. 2, pp Marjamaa, R. and Kirvelä, O. (2007) Who is responsible for operating room management and how do we measure how well we do it?, Acta Anaesthesiologica Scandinavica, Vol. 51, pp.1 6. McGowan, J., Truwit, J., Cipriano, P., Howell, R., VanBree, M., Garson, Jr. A. and Hanks, J. (2007) Operating room efficiency and hospital capacity: factors affecting operating room use during maximum hospital census, Journal of American College of Surgeons, Vol. 204, No. 5, pp McIntosh, C., Dexter, F. and Epstein, R. (2006) Impact of service-specific staffing, case scheduling, turnovers and first-case starts on anaesthesia group and operating room productivity: tutorial using data from an Australian hospital, Anaesthesia and Analgesia, Vol. 103, No. 6, pp Oudhoff, J., Timmermans, D., Rietberg, M., Knol, D. and Van der Wal, G. (2007) The acceptability of waiting times for elective general surgery and the appropriateness of prioritising patients, BMC Health Services Research, Vol. 7, No. 32. Overdyk, F., Harvey, S., Fishman, R. and Shippey, F. (1998) Successful strategies for improving operating room efficiency at academic institutions, International Anaesthesia Research Society, Vol. 86, No. 4, pp Peltokorpi, A. and Kujala, J. (2006) Time based analysis of total costs of patient episodes: a case study of hip replacement, International Journal of Healthcare Quality Assurance, Vol. 19, No. 2, pp Peltokorpi, A., Lehtonen, J-M., Kujala, J. and Kouri, J. (2008) Operating room cost management in cardiac surgery: a simulation study, International Journal of Healthcare Technology and Management, Vol. 9, No. 1, pp Peltokorpi, A. (2008, 26th June) Managing performance of operating units: international benchmarking study, International Conference of Productivity and Quality Research, Oulu, Finland. Santibáñez, P., Begen, M. and Atkins, D. (2007) Surgical block scheduling in a system of hospitals: an application to resource and wait list management in a British Columbia health authority, Health Care Management Science, Vol. 10, No. 3, pp Testi, A., Tanfani, E. and Torre, G. (2007) A three-phase approach for operating theatre schedules, Health Care Management Science, Vol. 10, No. 2, pp Torkki, P., Alho, A., Peltokorpi, A., Torkki, M. and Kallio, P. (2006) Managing urgent surgery as a process: case study of a trauma centre, International Journal of Technology Assessment in Health Care, Vol. 22, No. 2, pp Tyler, D., Pasquariello, C. and Chen, C-H. (2003) Determining optimum operating room utilization, Anaesthesia and Analgesia, Vol. 96, No. 4, pp Wadhwa, S., Saxena, A. and Wadhwa, B. (2007) Hospital information management system: an evolutionary knowledge management perspective, International Journal of Electronic Healthcare, Vol. 3, No. 2, pp

15 Improving economic efficiency of operating rooms 213 Van Houdenhoven, M., van Oostrum, J., Hans, E., Wullink, G. and Kazemier, G. (2007a) Improving operating room efficiency by applying bin-packing and portfolio techniques to surgical case scheduling, Anaesthesia and Analgesia, Vol. 105, No. 3, pp Van Houdenhoven, M., Hans, E., Klein, J., Wullink, G. and Kazemier, G. (2007b) A norm utilisation for scarce hospital resources: evidence from operating rooms in a Dutch university hospital, Journal of Medical Systems, Vol. 31, No. 4, pp Vissers, J., Bertrand, J. and Vries, G. de (2001) A framework for production control in healthcare organisations, Production Planning and Control, Vol. 12, No. 6, pp Vollman, T., Berry, W., Whybark, D. and Jacobs, F. (2004) Manufacturig Planning and Control for Supply Chain Management, 5th International ed., McGraw-Hill.