Optimal sequencing of urgent surgical cases. Scheduling cases using operating room information systems

Managing capacity for urgent surgery: staffing, staff scheduling in-house or on-call from home, and work assignments

Parmar and colleagues developed and validated a graphical method for choosing the number of operating theatres to set aside for urgent surgical cases. We address appropriate usage of their new method for calculating anaesthesia staffing, including comparison with previously published techniques. Parmar and colleagues' method is based on all staff scheduled in-house, rather than some on-call from home. We review that this is not nearly as large a limitation as it may seem because of behavioural factors of staff assignment.

A graphical assessment of emergency surgical list efficiency to determine operating theatre capacity needs

BACKGROUND

Unlike elective lists, full utilisation of an emergency list is undesirable, as it could prevent patient access. Conversely, a perpetually empty emergency theatre is resource wasteful. Separately, measuring delayed access to emergency surgery from time of booking the urgent case is relevant, and could reflect either deficiencies in patient preparation or be because of an occupied (over-utilised) emergency theatre.

METHODS

We developed a graphical method recognising these two separate but linked elements of performance: (i) delayed access to surgery and (ii) operating theatre utilisation. In a plot of one against the other, data fell into one of four quadrants, with delays associated with high utilisation signifying the need for more emergency capacity. However, delays associated with low utilisation reflect process deficiencies in the emergency patient pathway. We applied this analysis to 73 consecutive lists (>300 cases) from two UK hospitals.

RESULTS

Although both hospitals experienced similar rates of delayed surgery (21.8% vs 21.0%; P=0.872), in one hospital 83% of these were associated with low emergency theatre utilisation (suggesting predominant process deficiencies), whereas in the other 73% were associated with high utilisation (suggesting capacity deficiency; P<0.0001). Increasing emergency capacity in the latter resulted in shorter delays (just 6.7% cases excessively delayed; P<0.0001 for effect of intervention).

CONCLUSIONS

This simple graphical analysis indicates whether more emergency capacity is necessary. We discuss potential applications in managing emergency surgery theatres.

Importance of operating room case scheduling on analyses of observed reductions in surgical site infections from the purchase and installation of capital equipment in operating rooms

BACKGROUND

We review the impact of the consequences of operating room (OR) management decision making on power analyses for observational studies of surgical site infections (SSIs) among patients receiving care in ORs with interventions versus without interventions involving physical changes to ORs. Examples include ventilation systems, bactericidal lighting, and physical alterations to ORs.

METHODS

We performed a narrative review of operating room management and surgical site infection articles. We used 10-years of operating room data to estimate parameters for use in statistical power analyses.

RESULTS

Creating pivot tables or monthly control charts of SSI per case by OR and comparing among ORs with or without intervention is not recommended. This approach has low power to detect a difference in SSI rates among the ORs with or without the intervention. The reason is that appropriate OR case scheduling decision making causes risk factors for SSI to differ among ORs, even when stratifying by surgical specialty. Such risk factors include case duration, urgency, and American Society of Anesthesiologists' Physical Status. Instead, analyze SSI controlling for the OR, where the patient had surgery, and matching patients using these variables is preferable. With α = 0.05, 600 cases per OR, 5 intervention ORs, and 5 or 1 control patients for each intervention patient, reasonable power (≅94% or 78%, respectively) can be achieved to detect reductions (3.6% to 2.4%) in the incidence of SSI between ORs with or without the intervention.

CONCLUSIONS

By using this matched cohort design, the effect of the purchase and installation of capital equipment in ORs on SSI can be evaluated meaningfully.

Mortality effects of timing alternatives for hip fracture surgery

BACKGROUND

The appropriate timing of hip fracture surgery remains a matter of debate. We sought to estimate the effect of changes in timing policy and the proportion of deaths attributable to surgical delay.

METHODS

We obtained discharge abstracts from the Canadian Institute for Health Information for hip fracture surgery in Canada (excluding Quebec) between 2004 and 2012. We estimated the expected population-average risks of inpatient death within 30 days if patients were surgically treated on day of admission, inpatient day 2, day 3 or after day 3. We weighted observations with the inverse propensity score of surgical timing according to confounders selected from a causal diagram.

RESULTS

Of 139 119 medically stable patients with hip fracture who were aged 65 years or older, 32 120 (23.1%) underwent surgery on admission day, 60 505 (43.5%) on inpatient day 2, 29 236 (21.0%) on day 3 and 17 258 (12.4%) after day 3. Cumulative 30-day in-hospital mortality was 4.9% among patients who were surgically treated on admission day, increasing to 6.9% for surgery done after day 3. We projected an additional 10.9 (95% confidence interval [CI] 6.8 to 15.1) deaths per 1000 surgeries if all surgeries were done after inpatient day 3 instead of admission day. The attributable proportion of deaths for delays beyond inpatient day 2 was 16.5% (95% CI 12.0% to 21.0%).

INTERPRETATION

Surgery on admission day or the following day was estimated to reduce postoperative mortality among medically stable patients with hip fracture. Hospitals should expedite operating room access for patients whose surgery has already been delayed for nonmedical reasons.

Protocol for Urgent and Emergent Cases at a Large Academic Level 1 Trauma Center

Background

Level 1 trauma centers are capable of caring for every aspect of injury and contain 24-hour in-house coverage by general surgeons, with prompt availability of nearly all other disciplines upon request. Despite the wide variety of trauma, currently reported protocols often focus on a single surgical service and studies describing their implementation are lacking. The aim of the current study was to characterize all urgent and emergent cases at a large academic Level 1 trauma center, characterize the specialty and nature of emergent operative cases, and assess the efficacy of the institutional trauma protocol on timing of surgery.

Methods

For this retrospective review, all urgent and emergent cases treated at a single institution, during a 34-month period (January 1, 2015–October 31, 2017), were identified. All included cases were subject to the Institutional Guidelines for Operative Urgent/Emergent Cases. Demographic characteristics for non-elective surgical emergent cases were compiled by level of urgency and operating room (OR) waiting times were compared by year, department, and Level.

Results

A total of 11,206 urgent and emergent operative cases were included, among over 16 surgical departments. Level 2 cases represented the majority of urgent/emergent cases (33%–36%), followed by Level 3 (25%–26%), Level 1 (21%–22%), Level 4 (12%–16%), and Level 5 (2%–4%). Univariate analysis demonstrated that the proportion of urgent and emergent cases, by level of urgency, did not significantly differ between each year. Operating room waiting time decreased significantly over each year from 2015, 2016, and 2017: 193.40 ± 4.78, 177.20 ± 3.29, and 82.01 ± 2.98 minutes, respectively.

Conclusions

To the authors’ knowledge, this is the first study to characterize all urgent and emergent cases at a large academic Level 1 trauma center, outline the specialty and nature of emergent operative cases, and assess the efficacy of the institutional trauma protocol on surgical waiting times over a 34-month period.

Survey and Classification of Operational Control Problems in Discrete Event Logistics Systems (DELS)

This paper reviews and classifies literature on operational control of discrete event logistics systems (DELS). Operational control manipulates the flow of items through a DELS. Each control problem addressed in the surveyed literature is classified based on the control decision that the analysis model is formulated to support. These control decisions are defined by abstract functional definitions focusing on analysis model inputs, outputs, and variables. This classification of control problems shows that five kinds of atomic control decisions are needed to cover the literature, either by themselves or in combination. Standard functional definitions of operational control decisions enable discovery and interoperability of decision-support analysis models.

Mortality by Timing of Hip Fracture Surgery: Factors and Relationships at Play

In hip fracture care, it is disputed whether mortality worsens when surgery is delayed. This knowledge gap matters when hospital managers seek to justify resource allocation for prioritizing access to one procedure over another. Uncertainty over the surgical timing-death association leads to either surgical prioritization without benefit or the underuse of expedited surgery when it could save lives. The discrepancy in previous findings results in part from differences between patients who happened to undergo surgery at different times. Such differences may produce the statistical association between surgical timing and death in the absence of a causal relationship. Previous observational studies attempted to adjust for structure, process, and patient factors that contribute to death, but not for relationships between structure and process factors, or between patient and process factors. In this article, we (1) summarize what is known about the factors that influence, directly or indirectly, both the timing of surgery and the occurrence of death; (2) construct a dependency graph of relationships among these factors based explicitly on the existing literature; (3) consider factors with a potential to induce covariation of time to surgery and the occurrence of death, directly or through the network of relationships, thereby explaining a putative surgical timing-death association; and (4) show how age, sex, dependent living, fracture type, hospital type, surgery type, and calendar period can influence both time to surgery and occurrence of death through chains of dependencies. We conclude by discussing how these results can inform the allocation of surgical capacity to prevent the avoidable adverse consequences of delaying hip fracture surgery.

A Literature Review on Validated Simulations of the Surgical Services

The surgical department is a critical unit that oversees multiple surgical-based clinical pathways and works with various other units in a hospital. This department faces numerous challenges relating to variability in demand and management of resources. The aim of this article is to review the application of validated simulation models on hospital-wide surgical services. Each of these models is broadly classified by (i) simulation method and (ii) level of detail given to the management of "patient pathways" and "staff workflows". We remark that very few studies have given attention to the management of staff workflows in their validated simulation models.

Impact of changed management policies on operating room efficiency

Background

To increase operating room (OR) efficiency, a new resource allocation strategy, a new policy for patient urgency classification, and a new system for OR booking was implemented at a tertiary referral hospital. We investigated the impact of these interventions.

Methods

We carried out a before-and-after study using OR data. A total of 23 515 elective (planned) and non-elective (unplanned) orthopaedic and general surgeries were conducted during calendar year 2007 (period 1) and July 2008 to July 2009 (period 2). The Wilcoxon–Mann–Whitney test was used to calculate statistical significance.

Results

An increased amount of case time (7.1%, p < 0.05) was conducted without any increase in out-of-hours case time. Despite having three fewer ORs for electives, slightly more elective case time was handled with 26% less use of overtime (p < 0.05). Mean OR utilization was 56% for the 17 mixed ORs, 60% for the 14 elective ORs, and 62% for the 3 dedicated ORs. A 20% growth (p < 0.05) of non-elective case time was primarily absorbed through enhanced daytime surgery, which increased over 48% (p < 0.05). As a result, the proportions of case time on evenings and nights decreased. Specifically, case time at night decreased by 26% (p < 0.05), and the number of nights without surgery increased from 55 to 112 (out of 315 and 316, respectively). Median waiting time for the middle urgencies increased with 1.2 hours, but over 90% received treatment within maximum acceptable waiting time (MAWT) in both periods. Median waiting time for the lowest urgencies was reduced with 12 hours, and the proportion of cases treated within MAWT increased from 70% to 89%. The proportion of high urgency patients (as a proportion of the total) was reduced from 20% to 12%. Consequently, almost 90% of the operations could be planned at least 24 hours in advance.

Conclusions

The redesign facilitated effective daytime surgery and a more selective use of the ORs for high urgency patients out of hours. The synergistic effect probably exceeded the sum of the individual effects of the changes, because the effects of each intervention facilitated the successful implementation of others.

A traffic-light coding system to organize emergency surgery across surgical disciplines

BACKGROUND

Emergency surgery is associated with night-time procedures and disruption of elective surgery. An analysis was undertaken of the effect of classifying emergency operations uniformly with a three-tier urgency colour code and the use of dedicated daytime operating rooms.

METHODS

Observed changes from 2001 to 2012 in the number, timing and ability to meet the urgency-designated colour code deadline were retrieved from the computer-based operating theatre organization system for all emergency operations.

RESULTS

The number of emergency operations performed annually ranged from 3330 to 4341, with an increasing trend. The proportion of night-time emergency operations decreased from 27.4 per cent (2563 of 9347) before to 23.5 per cent (7731 of 32,959) after introduction of the colour coding system in 2004 (χ2  = 61.94, 1 d.f., P < 0.001). In 2007, owing to long preoperative delays in patients with acute appendicitis and acute cholecystitis, colour codes for these patients were upgraded from 'orange' to 'red' and from 'yellow' to 'orange' respectively. The proportion of patients operated on with a red code before and after this change increased from 45.2 per cent (5831 of 12,907 operations) to 62.7 per cent (13,020 of 20,778 operations; χ2  = 986.99, 1 d.f., P < 0.001). In 2012, the office-hours raw utilization time for the principal emergency operation theatre was 85.4 per cent.

CONCLUSION

The structural separation of elective and emergency surgery, the use of dedicated daytime operating theatres and the implementation of a universal classification of emergency operations reduced night-time surgery, improved the efficiency of operating theatre utilization during daytime, shortened preoperative delay in patients requiring urgent surgery, and enabled monitoring and corrective actions for providing emergency surgery services.

Decision support system for the operating room rescheduling problem

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

The enhanced postoperative care system

The perioperative care system is a continuum that includes preoperative patient evaluation, operating room scheduling, the operation itself, and postoperative care. This costly fast-paced system requires its various components to function efficiently and interact effectively. This review explores the interrelation between the operational elements of the enhanced care postoperative care system (intensive care units, intermediate care units, postanesthesia care units, and monitored floor beds) and other perioperative care activities. This care system provides patients with enhanced (from routine floor) nursing and medical care, continuous physiological monitoring, and sophisticated treatments (eg, continuous infusion of vasoactive substances). A management, rather than clinical, approach is used to provide insight into the operations of the perioperative care system so that bottlenecks to patient flow may be identified and eliminated. Emphasis is placed on the need to switch from a "fiefdom" mentality, where each component of the system acts independently and defensively, to systems thinking, in which complex interrelated patterns are identified, analyzed, and optimized.

Zuweisung und Planung von Operationsraumkapazit�ten

During the past decade many scientific advances have been made concerning the development of methodologies to maximize efficiency of surgical facilities through allocating and scheduling of operating rooms. In this article such a methodology is described. Using the analysis of historical data of surgical activity in a facility, future demand is predicted and planned. Part of the methodology includes principles and rules needed for the daily organization and operative management of surgical facilities. They are also derived from the same science and therefore the basis for rational and structured decision making. Medical aspects such as patient safety and free choice of day for surgery have higher priority than the economic goal of maximizing operating room efficiency.

Use of Operating Room Information System Data to Predict the Impact of Reducing Turnover Times on Staffing Costs

Potential benefits to reducing turnover times are both quantitative (e.g., complete more cases and reduce staffing costs) and qualitative (e.g., improve professional satisfaction). Analyses have shown the quantitative arguments to be unsound except for reducing staffing costs. We describe a methodology by which each surgical suite can use its own numbers to calculate its individual potential reduction in staffing costs from reducing its turnover times. Calculations estimate optimal allocated operating room (OR) time (based on maximizing OR efficiency) before and after reducing the maximum and average turnover times. At four academic tertiary hospitals, reductions in average turnover times of 3 to 9 min would result in 0.8% to 1.8% reductions in staffing cost. Reductions in average turnover times of 10 to 19 min would result in 2.5% to 4.0% reductions in staffing costs. These reductions in staffing cost are achieved predominantly by reducing allocated OR time, not by reducing the hours that staff work late. Heads of anesthesiology groups often serve on OR committees that are fixated on turnover times. Rather than having to argue based on scientific studies, this methodology provides the ability to show the specific quantitative effects (small decreases in staffing costs and allocated OR time) of reducing turnover time using a surgical suite's own data.

IMPLICATIONS

Many anesthesiologists work at hospitals where surgeons and/or operating room (OR) committees focus repeatedly on turnover time reduction. We developed a methodology by which the reductions in staffing cost as a result of turnover time reduction can be calculated for each facility using its own data. Staffing cost reductions are generally very small and would be achieved predominantly by reducing allocated OR time to the surgeons.

Weekend operating room on call staffing requirements

This article describes a statistical method used to determine the minimum number of OR teams that should be on call for urgent procedures, in-house versus on standby from home, to minimize labor costs. The OR manager obtains the number of ORs staffed at each hour of the 24-hour period of interest (e.g., 7 AM Saturday to 7 AM Sunday) from the surgical suite's information system. The minimum number of total staffed hours needed to care for patients is calculated for a prespecified level of the acceptable risk of inadequate staffing. A method used to determine whether each staff member should work in-house or on standby from home then is introduced. This method enumerates all possible combinations of shifts to find the one with the lowest cost, and it ensures a prespecified service level. An example based on 248 weeks of data collected from a large surgical suite is presented, and staffing for emergency procedures is reviewed.