Risk-adjusted policies to minimise perioperative staffing shortages during a pandemic: An agent-based simulation study.

Healthcare workers' (HCWs) safety and availability to care for patients are critical during a pandemic such as the one caused by severe acute respiratory syndrome coronavirus 2. Among providers of different specialities, it is critical to protect those working in hospital settings with a high risk of infection. Using an agent-based simulation model, various staffing policies were developed and simulated for 90 days using data from the largest health systems in South Carolina. The model considers staffing policies that include geographic segregation, interpersonal contact limits, and a combination of factors, including the patient census, transmission rates, vaccination status of providers, hospital capacity, incubation time, quarantine period, and interactions between patients and providers. Comparing the existing practices to various risk-adjusted staffing policies, model predictions show that restricted teaming and rotating schedules significantly (p-value <0.01) reduced weekly HCW unavailability and the number of infected HCWs by 22% and 38%, respectively, when the vaccination rates among HCWs were lower (<75%). However, as the vaccination rate increases, the benefits of risk-adjusted policies diminish; and when 90% of HCWs were vaccinated, there were no significant (p-value = 0.09) benefits. Although these simulated outcomes are specific to one health system, our findings can be generalised to other health systems with multiple locations.

A data driven policy to minimise the tuberculosis testing cost among healthcare workers.

INTRODUCTION: The Centres for Disease Control and Prevention (CDC) mandates that healthcare employees at high-risk exposure to Tuberculosis (TB) undergo annual testing. Currently, two methods of TB testing are used: a two-step skin test (TST) or a whole-blood test (IGRA). Healthcare leadership's test selection must account for not only direct costs such as procedure and resources but also indirect costs, including employee workplace absence. METHODS: A mathematical model based on Upstate South Carolina's largest health system affecting over 18,000 employees on six campuses was developed to investigate the value loss perspective of these testing methods and assist in decision-making. A process flow map identified the varied direct and indirect costs for each test for four employee types, and 6 travel-to-testing-site times were calculated. RESULTS: The switching point between testing procedures that minimised total system costs was most influenced by employee salary compared to travel distance. Switching from the current hospital policy to an integrated TST/IGRA testing could reduce TB compliance costs by 28%. CONCLUSIONS: This study recommends an integrated approach as cost-effective for large health systems with multiple campuses while considering the direct and indirect costs. When accounting for 'inconvenience costs' (stress, etc.) associated with visits, IGRAs are recommended irrespective of employee salary.

First Case On-Time Starts Measured by Incision On-Time and No Grace Period: A Case Study of Operating Room Management.

EXECUTIVE SUMMARY: A delay in first case on-time starts (FCOTS) can lead to less operating room (OR) utilization, greater facility costs, and dissatisfaction among staff and patients. FCOTS is usually measured by the patient in-room metric with a small grace period. For this study, the partnering hospital elected to target and improve delays by aggressively defining FCOTS as time of incision with no grace period. Metric standardization, goal setting, and organizational focus contributed to a 9-month implementation plan to improve the newly defined FCOTS metric. The target was achieved during implementation, with 73.6% of first cases starting on time. Annual impact showed 80,587 min, or 1,343 hr, of saved OR time, which led to $771,000 in annual savings for variable OR labor costs. This redefined metric and related interventions contributed to significant reduction in delays and savings to the hospital. Engaged physician leadership played a key role in this improvement initiative, as well. The methods employed here can be used in other hospitals looking to improve FCOTS metrics in their procedural areas.

Allocating operating room block time using historical caseload variability.

Operating room (OR) allocation and planning is one of the most important strategic decisions that OR managers face. The number of ORs that a hospital opens depends on the number of blocks that are allocated to the surgical groups, services, or individual surgeons, combined with the amount of open posting time (i.e., first come, first serve posting) that the hospital wants to provide. By allocating too few ORs, a hospital may turn away surgery demand whereas opening too many ORs could prove to be a costly decision. The traditional method of determining block frequency and size considers the average historical surgery demand for each group. However, given that there are penalties to the system for having too much or too little OR time allocated to a group, demand variability should play a role in determining the real OR requirement. In this paper we present an algorithm that allocates block time based on this demand variability, specifically accounting for both over-utilized time (time used beyond the block) and under-utilized time (time unused within the block). This algorithm provides a solution to the situation in which total caseload demand can be accommodated by the total OR resource set, in other words not in a capacity-constrained situation. We have found this scenario to be common among several regional healthcare providers with large OR suites and excess capacity. This algorithm could be used to adjust existing blocks or to assign new blocks to surgeons that did not previously have a block. We also have studied the effect of turnover time on the number of ORs that needs to be allocated. Numerical experiments based on real data from a large health-care provider indicate the opportunity to achieve over 2,900 hours of OR time savings through improved block allocations.

Work systems analysis of sterile processing: assembly.

BACKGROUND: Sterile processing departments (SPDs) play a crucial role in surgical safety and efficiency. SPDs clean instruments to remove contaminants (decontamination), inspect and reorganise instruments into their correct trays (assembly), then sterilise and store instruments for future use (sterilisation and storage). However, broken, missing or inappropriately cleaned instruments are a frequent problem for surgical teams. These issues should be identified and corrected during the assembly phase. OBJECTIVE: A work systems analysis, framed within the Systems Engineering Initiative for Patient Safety (SEIPS) model, was used to develop a comprehensive understanding of the assembly stage of reprocessing, identify the range of work challenges and uncover the inter-relationship among system components influencing reliable instrument reprocessing. METHODS: The study was conducted at a 700-bed academic hospital in the Southeastern United States with two reprocessing facilities from October 2017 to October 2018. Fifty-six hours of direct observations, 36 interviews were used to iteratively develop the work systems analysis. This included the process map and task analysis developed to describe the assembly system, the abstraction hierarchy developed to identify the possible performance shaping factors (based on SEIPS) and a variance matrix developed to illustrate the relationship among the tasks, performance shaping factors, failures and outcomes. Operating room (OR) reported tray defect data from July 2016 to December 2017 were analysed to identify the percentage and types of defects across reprocessing phases the most common assembly defects. RESULTS: The majority of the 3900 tray defects occurred during the assembly phase; impacting 5% of surgical cases (n=41 799). Missing instruments, which could result in OR delays and increased surgical duration, were the most commonly reported assembly defect (17.6%, n=700). High variability was observed in the reassembling of trays with failures including adding incorrect instruments, omitting instruments and failing to remove damaged instrument. These failures were precipitated by technological shortcomings, production pressures, tray composition, unstandardised instrument nomenclature and inadequate SPD staff training. CONCLUSIONS: Supporting patient safety, minimising tray defects and OR delays and improving overall reliability of instrument reprocessing require a well-designed instrument tracking system, standardised nomenclature, effective coordination of reprocessing tasks between SPD and the OR and well-trained sterile processing technicians.

Simulating the effects of operating room staff movement and door opening policies on microbial load.

OBJECTIVE: To identify factors that increase the microbial load in the operating room (OR) and recommend solutions to minimize the effect of these factors. DESIGN: Observation and sampling study. SETTING: Academic health center, public hospitals. METHODS: We analyzed 4 videotaped orthopedic surgeries (15 hours in total) for door openings and staff movement. The data were translated into a script denoting a representative frequency and location of movements for each OR team member. These activities were then simulated for 30 minutes per trial in a functional operating room by the researchers re-enacting OR staff-member roles, while collecting bacteria and fungi using settle plates. To test the hypotheses on the influence of activity on microbial load, an experimental design was created in which each factor was tested at higher (and lower) than normal activity settings for a 30-minute period. These trials were conducted in 2 phases. RESULTS: The frequency of door opening did not independently affect the microbial load in the OR. However, a longer duration and greater width of door opening led to increased microbial load in the OR. Increased staff movement also increased the microbial load. There was a significantly higher microbial load on the floor than at waist level. CONCLUSIONS: Movement of staff and the duration and width of door opening definitely affects the OR microbial load. However, further investigation is needed to determine how the number of staff affects the microbial load and how to reduce the microbial load at the surgical table.

Work systems analysis of sterile processing: decontamination.

BACKGROUND: Few studies have explored the work of sterile processing departments (SPD) from a systems perspective. Effective decontamination is critical for removing organic matter and reducing microbial levels from used surgical instruments prior to disinfection or sterilisation and is delivered through a combination of human work and supporting technologies and processes. OBJECTIVE: In this paper we report the results of a work systems analysis that sought to identify the complex multilevel interdependencies that create performance variation in decontamination and identify potential improvement interventions. METHODS: The research was conducted at a 700-bed academic hospital with two reprocessing facilities decontaminating approximately 23 000 units each month. Mixed methods, including 56 hours of observations of work as done, formal and informal interviews with relevant stakeholders and analysis of data collected about the system, were used to iteratively develop a process map, task analysis, abstraction hierarchy and a variance matrix. RESULTS: We identified 21 different performance shaping factors, 30 potential failures, 16 types of process variance, and 10 outcome variances in decontamination. Approximately 2% of trays were returned to decontamination from assembly, while decontamination problems were found in about 1% of surgical cases. Staff knowledge, production pressures, instrument design, tray composition and workstation design contributed to outcomes such as reduced throughput, tray defects, staff injuries, increased inventory and equipment costs, and patient injuries. CONCLUSIONS: Ensuring patients and technicians' safety and efficient SPD operation requires improved design of instruments and the decontamination area, skilled staff, proper equipment maintenance and effective coordination of reprocessing tasks.

Minor flow disruptions, traffic-related factors and their effect on major flow disruptions in the operating room.

BACKGROUND: Studies in operating rooms (OR) show that minor disruptions tend to group together to result in serious adverse events such as surgical errors. Understanding the characteristics of these minor flow disruptions (FD) that impact major events is important in order to proactively design safer systems OBJECTIVE: The purpose of this study is to use a systems approach to investigate the aetiology of minor and major FDs in ORs in terms of the people involved, tasks performed and OR traffic, as well as the location of FDs and other environmental characteristics of the OR that may contribute to these disruptions. METHODS: Using direct observation and classification of FDs via video recordings of 28 surgical procedures, this study modelled the impact of a range of system factors-location of minor FDs, roles of staff members involved in FDs, type of staff activities as well as OR traffic-related factors-on major FDs in the OR. RESULTS: The rate of major FDs increases as the rate of minor FDs increases, especially in the context of equipment-related FDs, and specific physical locations in the OR. Circulating nurse-related minor FDs and minor FDs that took place in the transitional zone 2, near the foot of the surgical table, were also related to an increase in the rate of major FDs. This study also found that more major and minor FDs took place in the anaesthesia zone compared with all other OR zones. Layout-related disruptions comprised more than half of all observed FDs. CONCLUSION: Room design and layout issues may create barriers to task performance, potentially contributing to the escalation of FDs in the OR.

Modelling and forecasting daily surgical case volume using time series analysis.

Hospitals and outpatient surgery centres are often plagued by a recurring staff management question: "How can we plan our nursing schedule weeks in advance, not knowing how many and when patients will require surgery?" Demand for surgery is driven by patient needs, physician constraints, and weekly or seasonal fluctuations. With all of these factors embedded into historical surgical volume, we use time series analysis methods to forecast daily surgical case volumes, which can be extremely valuable for estimating workload and labour expenses. Seasonal Autoregressive Integrated Moving Average (SARIMA) modelling is used to develop a statistical prediction model that provides short-term forecasts of daily surgical demand. We used data from a Level 1 Trauma Centre to build and evaluate the model. Our results suggest that the proposed SARIMA model can be useful for estimating surgical case volumes 2-4 weeks prior to the day of surgery, which can support robust and reliable staff schedules.

Assessing operating room turnover time via the use of mobile application.

BACKGROUND: Improving operating room (OR) utilization is crucial to hospitals. This study examines the effectiveness of a mobile application co-developed with hospital staff to track OR turnover time (TOT). METHODS: An Android-based app, named ORTimer, was used by staff in two OR units (GI-Lab and D-Core) of Greenville Memorial Hospital (GMH) in South Carolina. The staff used the app to record milestones and note delay reasons (if applicable). A total of 1,782 turnover observations from the GI-Lab and 694 turnover observations from the D-Core were collected for the study. Using data collected from the app and additional information from GMH's electronic medical record system, a two-sample proportionality test was conducted to test the hypothesis that the use of the app improved OR turnover performance (i.e., the TOT is equal to or less than the allotted time). RESULTS: The result of the hypothesis test indicates that a higher percentage of observations in the GI-Lab and D-Core met their turnover target time when the ORTimer app was used. Additionally, multiple regression analysis was used to identify significant factors that contribute to prolonged OR TOT and to estimate their impacts. CONCLUSIONS: The app serves as both a visual management tool as well as a TOT data collection tool. By identifying barriers to the on-time completion of the turnaround, the app allows for continuous improvement of the turnover process.

Effect of Resident Involvement on Operative Time and Operating Room Staffing Costs.

OBJECTIVE: The operating room (OR) is a major driver of hospital costs; therefore, operative time is an expensive resource. The training of surgical residents must include time spent in the OR, but that experience comes with a cost to the surgeon and hospital. The objective of this article is to determine the effect of surgical resident involvement in the OR on operative time and subsequent hospital labor costs. DESIGN: The Kruskal-Wallis statistical test is used to determine whether or not there is a difference in operative times between 2 groups of cases (with residents and without residents). This difference leads to an increased cost in associated hospital labor costs for the group with the longer operative time. SETTING: Cases were performed at Greenville Memorial Hospital. Greenville Memorial Hospital is part of the larger healthcare system, Greenville Health System, located in Greenville, SC and is a level 1 trauma center with up to 33 staffed ORs. PARTICIPANTS: A total of 84,997 cases were performed at the partnering hospital between January 1st, 2011 and July 31st, 2015. Cases were only chosen for analysis if there was only one CPT code associated with the case and there were more than 5 observations for each group being studied. This article presents a comprehensive retrospective analysis of 29,134 cases covering 246 procedures. RESULTS: The analysis shows that 45 procedures took significantly longer with a resident present in the room. The average increase in operative time was 4.8 minutes and the cost per minute of extra operative time was determined to be $9.57 per minute. OR labor costs at the partnering hospital was found to be $2,257,433, or $492,889 per year. CONCLUSIONS: Knowing the affect on operative time and OR costs allows managers to make smart decisions when considering alternative educational and training techniques. In addition, knowing the connection between residents in the room and surgical duration could help provide better estimates of surgical time in the future and increase the predictability of procedure duration.

Prioritization strategies for patient evacuations.

Evacuation from a health care facility is considered last resort, and in the event of a complete evacuation, a standard planning assumption is that all patients will be evacuated. A literature review of the suggested prioritization strategies for evacuation planning-as well as the transportation priorities used in actual facility evacuations-shows a lack of consensus about whether critical or non-critical care patients should be transferred first. In addition, it is implied that these policies are "greedy" in that one patient group is given priority, and patients from that group are chosen to be completely evacuated before any patients are evacuated from the other group. The purpose of this paper is to present a dynamic programming model for emergency patient evacuations and show that a greedy, "all-or-nothing" policy is not always optimal as well as discuss insights of the resulting optimal prioritization strategies for unit- or floor-level evacuations.