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.

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.

A Work Systems Analysis of Sterile Processing: Sterilization and Case Cart Preparation.

Achieving reliable instrument reprocessing requires finding the right balance among cost, productivity, and safety. However, there have been few attempts to comprehensively examine sterile processing department (SPD) work systems. We considered an SPD as an example of a socio-technical system - where people, tools, technologies, the work environment, and the organization mutually interact - and applied work systems analysis (WSA) to provide a framework for future intervention and improvement. The study was conducted at two SPD facilities at a 700-bed academic medical center servicing 56 onsite clinics, 31 operating rooms (ORs), and nine ambulatory centers. Process maps, task analyses, abstraction hierarchies, and variance matrices were developed through direct observations of reprocessing work and staff interviews and iteratively refined based on feedback from an expert group composed of eight staff from SPD, infection control, performance improvement, quality and safety, and perioperative services. Performance sampling conducted focused on specific challenges observed, interruptions during case cart preparation, and analysis of tray defect data from administrative databases. Across five main sterilization tasks (prepare load, perform double-checks, run sterilizers, place trays in cooling, and test the biological indicator), variance analysis identified 16 failures created by 21 performance shaping factors (PSFs), leading to nine different outcome variations. Case cart preparation involved three main tasks: storing trays, picking cases, and prioritizing trays. Variance analysis for case cart preparation identified 11 different failures, 16 different PSFs, and seven different outcomes. Approximately 1% of cases had a tray with a sterilization or case cart preparation defect and 13.5 interruptions per hour were noted during case cart preparation. While highly dependent upon the individual skills of the sterile processing technicians, making the sterilization process less complex and more visible, managing interruptions during case cart preparation, improving communication with the OR, and improving workspace and technology design could enhance performance in instrument reprocessing.

The use of a mobile application to track process workflow in perioperative services.

This article discusses the data collection tool developed to investigate how patient flow is affected by the delivery of different types of care within Perioperative Services. To better understand the Perioperative Services processes, this study tracked staff members as they perform their activities. A challenging aspect of documenting the processes observed while tracking the Perioperative Services staff is to record the specific times and order in which the activities took place. The Perioperative Services is a fast-paced, dynamic environment where the staff members often perform multiple tasks that may also be interrupted, and each staff member may perform these tasks in their own sequence. To meet the needs of accurate data gathering, an iPhone/iPod Touch application was developed. It provides several advantages over the traditional paper/pencil method: (1) time stamps are instantaneous and consistent among the data collectors, (2) activities are entered via swipe-and-click capability, (3) multiple active tasks and interruptions can be tracked, and (4) collected data can be output to Microsoft Excel or Access for analysis. The "app" has proven to be useful in capturing data for our study. This technology can be customized and applied to similar settings at other hospitals.