CHAPTER 1: INTRODUCTION

Problem introduction, relevance and significance:

The experiment focuses at the research on existing problems or possible causes of the falling relative income generated in proportion to the inputs. The experiment is based on the determination of problems faced by nine Al Habib Medical Laboratories and accomplishing the optimised solutions on the improvement of their respective incomes including the decisive factors responsible for the same. It is done using software like Minitab and Excel along with the use of a few equations. This experiment can benefit the laboratories in automation of currently average testing systems, improving the emergency services so as to offer simultaneous results to the patients.

Problem and research statement:

This case study will be aimed explicitly at relative analysis of incomes of the laboratories in terms of their productivity. The experiment would encapsulate the study, comparison and analysis of each parameter or constraint on the laboratory so as to effectively evaluate the factors affecting the income. The experimental design would be done in such a way to ensure the presence of all the four control variables from the laboratories such that their data sheets are ready for analysis and offering the best possible income enhancing techniques by frugal engineering and management of the available resources in the best possible way. The comparative evaluation of response variable will help in controlling the income generated by nine labs as this project aims to establish empirical relationships amongst the factors.

Scope and limitations:

These nine laboratories are already under CAP standards and approvals, there is still some room to better the best and this experiment yearns to achieve the same. This experiment aims to boost the income/profit to the laboratories and hospitals by saving their times in testing or emergency cases in various departments. The assumptions in this study would be the consideration of a fact that employees are equally skilled or experienced and the apparatus or equipment’s used and handled by nine laboratories are pretty similar from technological point of view. Although, the efficiency of tests, operating time and capacity may vary as per their inputs in the context of man, machine, material or money.

There are two significant response variables to the income generated by a laboratory i.e. the number of patients and improvement of income. In case of any missing or contradictory data available from the credible sources, a nuisance factor will be used to account the information needed for experimental analysis of incomes of the laboratory.

Control Parameters:

• Staff
• Working hours and productivity
• Time for result
• Quality of equipment
• Laboratory location

There are a few control variables which may be of constant factors, restraint type or dynamic control factors type. These include:

• Quality of equipment
• Amicable location
• Approachable, skillful and experienced staff

Background:

Gilbreth gave ‘Therbligs Principles’ to understand the psychological and physiological factors contributing to productivity and efficiency of a workplace. The patients or people who seek the lab services would be under observation in the test trials and the working procedures would be strongly studied microscopically to identify and then rectify the flaws in their working if any so as to achieve the aforementioned objectives. The concepts of work study and motion study will be used to observe the trends in the labs. The work sequence of tests and treatments if done on the best adopted standards, it can lead to improvement. This experiment can benefit the laboratories in automation of currently average testing systems, improving the emergency services so as to offer simultaneous results to the patients and working on the application of point care systems as a technique to optimize the critical cases such that their documentation is sped up by automatic control of the tests. The factors influencing their income are the laboratory staff, quality of equipment, time and location where most of them are constant constraints but the time taken as per SOP (Standard Operating Procedure) can be reduced as per the targets. This experiment is a dedicated attempt to provide the best possible solution of the laboratories’ variations in income.

Literature Review

Automation, Efficiency, and Workflow

The establishment of an efficient and effective laboratory and its personnel is tantamount to attaining positive clinical outcomes for patients. It calls for the introduction of automation coordination for perianalytical robotic is attributed to the significant improvement in efficiency in production, in addition to decreased costs of operations (International FAIM Conference & Azevedo, 2013). Keohane (2015) maintain that the computerization of laboratory processes enables modern laboratories to increase the workload with a reduced number of employees (Najmabadi, 2006). Moreover, the handling of stats is lessened while at the same time offering extra benefits, such as enhanced sample identification and safe working environment, which can be quantified using other forms (Vincent, 2010).

Vincent (2010) categorically states that the redesign of the workflow and lab processes can lead to a great outcome as far as the capacity of any clinical laboratory to achieve more with fewer resources is concerned. In order for such a phenomena to occur, there is need to place a vital attention to every unit dollar invested (Keohane, 2015). It is crucial to adopt the perspective of a consultant while managing a clinical laboratory by undertaking procedures such as periodic product evaluation, repeated procedures, task analysis, safety measures and standards, and some of the best practices responsible for transforming a clinical laboratory to attain more productivity and enhance quality and efficiency (Najmabadi, 2006).

Automation is considered one of the best ways for improving clinical laboratory processes. The main goal is to undertake a high level of tasks, or achieve as many goals and objectives as possible, while using the minimum resources possible. Clinical laboratories dictate that efficiency focus on reducing the level of procedures and processes. When such a ventured (automation) is designed while referring to the needs of the laboratory, workflow effectiveness and optimization is guaranteed (Keohane, 2015). The equipment should be swiftly combined with the personnel, while still seeking to reduce hazards by limiting the staff to critical and abnormal results only (Keohane, 2015).

Aside from the enhancement of operational efficiency through the decrease of the number of personnel-intensive care and the probability of hazards, the introduction of automated systems can improve parameters and the service level that they represent (Keohane, 2015).  Such metrics include the turnaround time (TAT) and the consistency of TAT (International FAIM Conference & Azevedo, 2013). A laboratory that reflects extensive reruns necessitated by questionable results, persistent downtime, and/ or a manual with high degrees of vagueness can undergo significant transformation if automated systems are introduced to replace the manual processes (Vincent, 2010). Consequently, the improvements will build confidence in the capacity of such a laboratory to deliver accurate and consistent results within the set deadline (Najmabadi, 2006).

Four major issues influence the ability of a laboratory to deliver predictable and timely results. They include transportation of samples, post analytic storage, TAT, and the management of STAT samples (International FAIM Conference & Azevedo, 2013). Clinical laboratories that introduce automated systems tend to enhance efficiency in the sections aforementioned. The following sections of this section is committed to examining various discussions on how automation reinforce effectiveness and quality production in the management of STAT samples, TAT, the post analytic storage, and the transportation of samples (International FAIM Conference & Azevedo, 2013).

TAT

Medical healthcare personnel and the institutions they work in depend on predictable, fast turnaround time to manage control costs and optimize healthcare processes (Najmabadi, 2006). There are times when TAT’s reliability is questionable, for instance, during moments when is delayed or fluctuates. In such occurrences, timely therapeutic intervention and diagnosis becomes complicated and difficult to achieve (International FAIM Conference & Azevedo, 2013). Further, it questions the institutional standing and capacity of the medical center under question (Keohane, 2015). When there is an appropriate configuration, a complete laboratory automated system boasts of a measurable capacity to shorten and streamline TAT, as well as its vulnerability. It includes during peak and low periods and hours (Keohane, 2015).

STATs

The efficiency of the workflow directly affects the effective management of samples (STATs) (The National Research Council (U.S.), 2011). Due to the critical nature of the information that is also time sensitive, there is need to improve the management and handling of such samples (Najmabadi, 2006). Such an initiative leads to increased speed and quality in the delivery of results, and present positive healthcare outcomes (Najmabadi, 2006). One common way of achieving such a status includes the introduction of automated systems that guarantee genuine STAT optimization throughout the whole process (Keohane, 2015). The outcome is that a single process will be maintained for every sample, whether STAT or routine. Moreover, it also allows STAT samples to bypass the other types of samples that do not qualify as urgent (Keohane, 2015).

The Transportation of Samples

When samples are handled in an automated manner, there are probable benefits that are likely to be achieved, such as time saving and minimal human supervision and intervention (Najmabadi, 2006). Such systems ensure that a personnel touch a sample only once, after which the system handles it for the rest of the processes. Vincent (2010) proposes that when a transportation system is installed between the analytics and the pre-analytics, and between the storage and the analytics, then it directly translates to high efficiency level (Keohane, 2015). In addition, there is a likelihood of manual handling by about 80%, aside from other benefits (International FAIM Conference & Azevedo, 2013). In order to increase laboratory efficiency, it is vital to take note of the route that is reserved for traffic while considering the nature and design of the transport line. It is advisable to construct the transport system in a bi-directional manner (Najmabadi, 2006). Consequently, when it is availed, it should be multi-leveled. Such a design ensures that the empty samples are separated from the full ones in dedicated lanes to offer reliable and fast results for laboratory tests, even when the workload is extremely high (Keohane, 2015).

Storage

            Keohane (2015) maintains that manual handling result in delays when the staff is locating stored and archived specimen for reflex or add-on testing. One way to eliminate or reduce latent workflow disruptions is through the automation of the retrieval and storage systems. It is because a manual procedure requires that each specimen be logged  into their rack location using an Excel spreadsheet. In other instances, they call for the placement of the samples into a plastic container/rack and allocate accession numbers for each specimen (Najmabadi, 2006).

Various types of automation systems exist that are designed to eliminate or minimize such manual procedures and offer a rapid access in cases of retrieval (Keohane, 2015). The automation can also enable the immediate transportation of the samples to the analytics for testing (Najmabadi, 2006). Some clinical laboratories have semi-automated systems (Najmabadi, 2006). One of their main tasks is to archive samples that are arranged in trays with the aim of eliminating the manual process that entail a laboratory staff carrying the samples to the refrigerator. When it comes to fully automated systems, such steps are advanced further, including automated delivery towards the storage unit where they are automatically retrieved when a personnel orders a subsequent test (Keohane, 2015).

Important Considerations

The International FAIM Conference and Azevedo (2013) provide that upto 70% of healthcare decisions rely on laboratory test outcomes. In this effect, there is need to give laboratory processes and equipment special attention. Whereas diagnostic testing features as a critical procedure with respect to improving the outcome of healthcare steps, the majority of laboratories are marred with limited resources and tight budgets (Keohane, 2015). Consequently, purchasing automation, replacing, and other improvement initiatives are made complex (Keohane, 2015). Such management perceives the automation of laboratory tasks a daunting encounter that seeks to get them out of their comfort zones (Najmabadi, 2006). In contrast, the advancement of the internet technology infrastructure has appreciated the growing demand to automate test procedures to deal with the ever-growing complexities (Keohane, 2015).

The International FAIM Conference and Azevedo (2013) further provide that about 17% of the laboratory personnel in the world over are preparing for retirement in the near future. The current aging population persistently piles pressure on the need to adopt and expand laboratory automation (Keohane, 2015). With reference to such a growing reality, laboratory managers should be armed with a clear vision that outlines the best way to carry out their laboratory potentials into the coming years (Najmabadi, 2006). There are three major steps that laboratories should adopt in their quest to improve their capacity to adequately affect patient care (Najmabadi, 2006). The first step is to integrate an information and technology system that focuses on maximizing the benefits associated with automation (Vincent, 2010). Secondly, there is need to maximize on the flexibility of the automation system, and thirdly, improve the efficiency and management of test tubes (Vincent, 2010).

References

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International FAIM Conference, & Azevedo, A. (2013). Advances in sustainable and competitive manufacturing systems: 23rd International Conference on Flexible Automation and Intelligent Manufacturing. Cham: Springer.

Keohane, E. (2015). Rodak’s hematology: Clinical principles and applications. S.l.: Elsevier Saunders.

Khan, M. N., & Findlay, J. W. A. (2010). Ligand-binding assays: Development, validation, and implementation in the drug development arena. Hoboken, N.J: Wiley.

Kottke-Marchant, K., & Davis, B. H. (2012). Laboratory hematology practice. Chichester, West Sussex, UK: Wiley-Blackwell/International Society for Laboratory Hematology.

Najmabadi, P. (2006). New laboratory automation system architectures for biotechnology applications.

National Research Council (U.S.). (2009). An assessment of the National Institute of Standards and Technology Chemical Science and Technology Laboratory: Fiscal year 2009. Washington, D.C: National Academies Press.

National Research Council (U.S.). (2011). Prudent practices in the laboratory: Handling and management of chemical hazards. Washington, D.C: National Academies Press.

Vincent, C. (2010). Patient Safety. New York, NY: John Wiley & Sons.

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