Excerpts from interviews.
\r\n\t
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Nurse and medical staff starts‐up advanced life support (ALS) maneuvers. The primary and emerging interventions are to permeabilize the airway accessing the trachea through an endotracheal tube. Not being possible to access it by the usual routes, the only solution is to perform a tracheotomy or cricothyrotomy, using a tracheotomy surgical tray (TST) or an emergency cricothyrotomy kit (ECK). However, the health team most of the times do not know its existence, location, or has difficulties in accessing it in due time, what could have as consequence the loss of a life.
\nPortuguese Directorate‐General of Health (DGS) points out on the Circular Normative no. 15/ DQS/DQCO of 22/06/2010 [1] that “patients who are admitted in hospitals believe that they are being admitted to a safe environment. They feel confident that if their clinical condition gets worse, they are in the best place for a prompt and effective intervention. However, there is some evidence that this does not always happen” (p. 1). This Circular also states, “ALL inpatient areas should have easy and immediate access to equipment, supplies and emergency drugs. They should be organized and stored in a standardized way… throughout the health unit” (p.6). However, compliance with these recommendations depends, above all, on political and management decisions of legislators, regulators, managers, and industry providers, and it is at the health institutions jurisdiction to “adequate resources and create the structures that leads to quality professional practice” [2]. For the Portuguese Republic Government (Governo da República Portuguesa—GRP) is “fundamental, that the available resources are better used, avoiding waste, that is, improving management, transparency, and accountability for the use of money from the citizens” [3]. Corvi [4] draws attention to the “waste epidemic in health care,” as acknowledge by the GRP, and so a great opportunity to improve, being fundamental a spirit of continuous learning as part of “implementing a lean management system” [4].
\nThe Intensive Care Society [5] recommends “all critical care areas should have their own, appropriately stocked and checked difficult airway trolley to deal with airway and tracheostomy emergencies” (p.11). The absence or inaccessibility to this kind of equipment can lead to adverse events with huge impact on the safety and lives of patients, mainly the critical ones. To the matter of the impact of layout configurations in hospital environment, Soriano‐Meier et al. [6] points out that “inadequate facility layout negatively affects the performance of the service staff, the quality of care provision and the service temporally over time” (p. 255).
\nAt a particular neurosurgery high dependency unit (NHDU) of a central hospital in Lisbon, problems related to design, layout, architectural barriers, accessibility to life support equipment (LSE) and wastes of time, handling, and transport were identified. Those that may infer greater impact on patients and on the provision of care taken by nurses are as follows: (a) accessibility to LSE, (b) difficulty/inexperience in the use of the resuscitation trolley (RT), and (c) lack of knowledge of ECK and TST existence and location. This chapter summarizes the action research study embarked with the purpose of testing the application of Lean methodologies at NHDU for a quality and safety provision of care to acute neuropatients and to reduce at least by half, time, steps, and distance travelled by nurses’ accessing LSE. Gemba walk, value stream mapping, spaghetti diagrams, 5S, and JIT (just‐in‐time) were the main Lean methodologies used.
\nGemba is the Japanese term used for Shop floor, where products are produced, or where the services are provided [7, 8]. To start an improvement project, it is critical to analyze the current and real situation of an organization or its workplace. Therefore, the gemba should analyze processes, time of setups, physical layout and surroundings with an open mind, to detect where, how, and why clients and staff experience problems [7–9].
\nThe value stream mapping (VSM) is one of the main lean methodologies that engages waste elimination in any organization [10]. VSM will help to identify and analyze, for example, problems experienced by stakeholders, errors in medicine, flow of processes and work, financial analysis, among others. VSM allows checking (visual and graphically) the current state of a particular procedure, its productive time (value‐added), and the non‐productive time (non‐value‐added) [11].
\nJackson [12] argues that 5S is the foundation of the Toyota production system (TPS). What this methodology tries to ensure is an orderly organized workspace for an efficient and safe work environment [10], increased productivity, fewer errors, and less waste [8]. 5S represents the five levels of this methodology starting with the letter “S”. In Japanese vocabulary: SEIRI (sort), SEITON (set in order), SEISO (shine), SEIKETSU (standardize), and SHITSUKE (sustain). Smart [13] summarizes this methodology with the expression “a place for everything and everything in its place” (p. 62).
\nJIT is a production process that targets the optimization of the process as a whole in a continuous flow improvement and tries to answer to the organization or service needs. Briefly, it means producing no sooner, no later, neither more or less, only and just the necessary [8, 10].
\nAnother Lean methodology is the spaghetti diagram. This diagram consists on a graphic reproduction of the architectural floor plan of a structure, where you draw lines from one space to another, representing the path taken by employees, customers, and objects along a particular process (round trip) [12, 14]. It allows documenting and visualizing the physical flow, in order to identify waste motion or transportation, architectural barriers, and improvement opportunities to expedite process flow [15].
\nThis chapter is organized as follows: Following the introduction, a literature review on Lean philosophy is performed, then the methodology used in the research, and the results of the action research are described. Finally, some discussion and conclusions are drawn.
\nIt was through Krafcik [16] that the Lean term was released thus referring to the TPS as a lean production system: A system that uses less resources compared to the mass production systems. Less effort, less capital investment, less space, and less time [17]. The Lean philosophy is essentially focused on waste reduction as a means to increase actual value‐added, in order to fulfill customer needs and maintain profitability [17]. The fundamental focuses of Lean are respect for people, teamwork, waste elimination, continuous improvement, value, quality, and safety [8, 16–18]. Several authors have highlighted this and other key principles of Lean philosophy, such as follows: (i) customer relationship [19]; (ii) total quality management (TQM) [20]; (iii) JIT [21, 22]; (iv) pull production/flow [19, 20]; (v) supplier relationships/long‐term business relationship [21]; (vi) mistake‐proofing [23]; (vii) total productive maintenance (TPM) [22]; and (viii) physical layout [6]. At the operational level, the Lean paradigm is implemented using a number of techniques such as kanban, 5S, visual control, takt‐time, poke‐yoke, and single minute exchange of die (SMED) [24].
\nTo Imai [8], the importance of applying a Lean philosophy in an organization has at least three components: (1) any activity or process that does not add value is waste, independently of being practiced by people or machines; (2) the reduction or elimination of waste may be the most cost‐effective way for improving productivity and reduce operating costs instead of increasing investment in the hope of adding value. Moreover, investing in new equipment is expensive while eliminating waste, in most cases, has no costs. (3) Standardization of processes ensures quality and error prevention. Womack et al. [17] documented the benefits of Lean philosophy compared to the mass production model, arguing that this philosophy would succeed, not only in the automotive industry or aviation, but also in all activities from distribution, retail, and healthcare. Not being the solution to all the problems that health services faces today, the Lean philosophy can bring significant benefits to this sector and in a range of hospital areas [25], contributing to develop the continuous improvement into the organizational culture and improving quality of care, efficiency and effectiveness, while reducing costs, errors, and waste.
\nIn the Portuguese healthcare sector, the implementation of Lean philosophy has been focused on some specific areas such as quality [26, 27] logistics, supply and storage [28–30], agility and continuous process improvement [31–33], workplace reorganization [34], and reducing waiting times [35, 36]. Particularly in services such as community health centers [37], operating room, imaging, ophthalmology, outpatient, ward, pharmacy, and warehouse. Other studies focused on conducting systematic reviews [38, 39]. There is thus a research gap in applying the Lean philosophy to inhospital medical emergency, especially in inpatient critical care services.
\nThe methodology used in this study was an action research, supported by a longitudinal mixed method approach with a one‐group within‐subjects pretest‐posttest experimental type design.
\nLewin [40] suggests the existence of a cycle in action research. It begins with the diagnosis and identification of the problem(s) with all participants in a democratic way and then follows the proposal, planning interventions, and actions of change. Subsequently, the impact of the changes is monitored, the data collected, analyzed, interpreted, and finally results are reported. This is a flexible research methodology that integrates an exploratory action in order to investigate and support the implementation of changes according to the diagnosis raised [41]. Action research claims that the researcher participates in the change process since the changes suggested are implemented by himself, that is, he “take action to improve the practice and study … the effects of the action taken” [42]. Yin [43] considers this methodology as a variant of qualitative research that emphasizes the researcher action role and his active collaboration with the research participants.
\nThe research was performed at a level 2 patient care four‐bedded NHDU. This unit shares human resources, equipment, and materials with the 44‐bedded standard care neurosurgery and neurotraumatology wards. NHDU is a healthcare facility specialized in the care of neuropatients undergoing neurological, hemodynamic, and respiratory instability with the eventual need of non‐invasive or invasive ventilatory support by tracheotomy. These patients require critical care nursing and permanent vigilance that, although not requiring intensive care, may potential and quickly evolve to a severe status and thus the need of an immediate intervention. Nurse:patient ratio is 1:4. Located in one of an 802‐bedded triple hospital centre at the metropolitan area of Lisbon (Portugal), this centre serves about a million people population. Data available from 2013 institutional performance reports show a surgical movement of 1423 neurosurgeries and a bed occupancy rate of 87.7% and 91.4% at the neurotrauma and neurosurgery wards, respectively.
\nThe research was authorized by the NHDU Medical Director, the NHDU Chief Nurse, and the Ethics for Health Committee of the hospital centre. The unit of analysis is the NHDU with the corresponding nurse team. A convenience sampling was used attending to nurses’ availability during the period that took place the visit of the researcher. The two nurses of the management team (chief and coordinator) were excluded from this sample since the purpose was to simulate the performance of the direct care nurses. Thus, from a population of 20 nurses, a sample of 12 nurses (60%) was selected. This is a longitudinal research in which data were collected from two points in time, which allowed studying the changes that have occurred during the period in which it was conducted (November 2014 to January 2015).
\nThe research design follows several phases. The main three phases were (1) pre‐intervention, (2) intervention, and (3) post‐intervention, in which a simultaneous mixed method approach (qualitative and quantitative) was applied. The pre‐intervention phase was further divided into three sub‐phases: (i) diagnostic assessment (qualitative approach), (ii) simulation (quantitative approach), and (iii) proposal of changes (qualitative approach). The intervention phase consisted on the application of 5S and JIT lean methodologies. The post‐intervention phase was divided into two qualitative approaches: (i) simulation and (ii) unstructured interview.
\nThe pre‐intervention diagnostic assessment sub‐phase involved the following activities: (a) direct observation of the physical space performed by the participant researcher (PR) which focused mainly on the layout of the NHDU and the location of existing materials and equipment. To support the gemba walk, pictures and paper record with graphical representation of the service plan were used to complement the visual management and spaghetti diagram. The transition to digital record was made using Microsoft® Office® 2013 software. (b) Personal unstructured interviews performed by the PR to the nurse team, and questionnaires to identify the difficulties and constraints of nurses in their professional daily routines, especially in emergency situations. The questionnaires were anonymous and blind in order to guarantee their confidentiality. The participants returned them in a sealed envelope deposited at a container left in the nursing room. The analysis of questionnaires and interviews was performed using qualitative content analysis, and it was organized according to the research variables, the types of wastes considered by the Lean philosophy and the suggestions of change by the participants.
\nThe pre‐intervention simulation sub‐phase was accomplished by measuring time, distance, and number of steps (dependent variables) undertaken by nurses in the access to LSE (RT, ECK, TST, and automated infusion systems (AIS)). The simulation context was used because during the research it was not possible to monitor the tasks developed by nurses in a real context. As measuring instruments, the Nokia® 6230 mobile phone chronometer was used to monitor timing performance in seconds, rounded to the unit. Sixty meters’ tape Stanley PowerWinder® was used to measure the distance travelled by nurses, with data rounded to the first decimal place. The PR counted the number of steps, and the data were triangulated with the participant itself. The monitoring was performed from the point of departure (nurses’ station), arrival to LSE and return to the starting point with the respective LSE.
\nThe third pre‐intervention sub‐phase was completed by the suggestion of changes presented, as a proposal like determined by Lewin [40], to the Medical Director and Chief Nurse of NHDU.
\nThe intervention phase consisted on the application of lean 5S and JIT methodologies for the reorganization of physical space, equipment location, and NHDU inventory. The tasks performed by the researcher in this phase consisted on the organization of the contents in the NHDU large cabinet, relocation, and availability of TST and AIS. The reorganization of RT, ECK, and NHDU small cabinets was performed with the help of the nurses’ management and direct care team. Other human resources such as nurses’ aides and the hospital carpentry services were involved to perform small changes and to construct small furniture. Stock boxes abandoned in the hospital storage were recycled and used for better storage and visual management of cabinet contents.
\nThe post‐intervention phase was divided into two sub‐phases: (i) simulations, using the same methodology and equipments applied in the pre‐intervention. (ii) Unstructured interviews, using the same methodology as in the pre‐intervention to collect the opinion of nurses regarding the interventions made to the unit, and how this influenced their daily routines and professional practice.
\nThe quantitative results are presented comparing the pre‐intervention with the post‐intervention phases, allowing a more direct comparison of the data. The IBM SPSS Statistics version 21 and Microsoft® Office® 2013 Excel version 15 software were used for the statistical analysis of data. For the statistical hypothesis tests, the parametric Student’s t‐test with a significance level of 0.025 (one‐sided) was used, such as the nonparametric Wilcoxon W‐test with the exact significance of 0.025 (one‐sided) for the poorly distributed data situations [44]. Standardized response mean, calculated through MedCalc Statistical Software version 15.2.2, was used to analyze the effect size (Cohen’s d) of the intervention made by the application of Lean methodologies, representing the independent variable. The qualitative results are summarized in tables with transcription of the nurses opinions collected from the interviews and the summary of the answers given by them in the questionnaires. Spaghetti diagrams and photographs are also used for better contextualization.
\nAttending to the literature review and the pre‐intervention phase the following hypotheses are formulated:\n
H01: The difference of TST time of access between pre‐ and post‐intervention equals zero.
H02: The difference of TST distance of access travelled between pre‐ and post‐intervention equals zero.
H03: The difference of TST number of steps of access between pre‐ and post‐intervention equals zero.
H04: The difference of AIS time of access between pre‐ and post‐intervention equals zero.
H05: The difference of AIS distance of access travelled between pre‐ and post‐intervention equals zero.
H06: The difference of AIS number of steps of access between pre‐ and post‐intervention equals zero.
Throughout Gemba Walk, twelve unstructured interviews were carried out to nurses in order to identify their difficulties in their professional daily routines and what kind of improvements they would like to implement in NHDU (Table 1). The collected data focused mainly on the inadequate layout and location of equipment, poor organization of clinical material in NHDU cabinets and units of patients, obstacles, restricted circulation and workspaces, frequent journeys out of NHDU to supply missing materials and equipment, and difficulty in implementing improvements because of a great resistance to change. According to these interviews only 50% of nurses knew the existence and location of TST, and only 33.3% of nurses knew the ECK existence or location. For AIS and RT, all participants were aware of them. After Lean methodologies’ intervention and education, 100% of the participants were aware of all life support equipment.
\nIn addition to the interviews, questionnaires were delivered to 12 nurses and eight were returned, representing a 67% response rate. The purpose of the questionnaire was to identify the set of difficulties felt by nurses in their daily professional life in NHDU, mainly in emergencies, monitoring and surveillance of the acute neurosurgical patient. The questionnaire made also possible to study the kind of wastes (according to Lean philosophy) the nurses identify. The collected data from questionnaires are summarized in Table 2 that includes suggestions provided by the respondents.
\nA | \n“My greatest difficulty in NHDU is to always have to go out of the unit to look for supplies …either because we do not have a specific location for them either it was not replaced… Medication and serums, forget it…” | \n
B | \n“We should have an adequate level of stocks according to our needs and not have to always go ‘out there’ seek for supplies.” | \n
C | \n“The NHDU should be independent from all resources of Neurosurgery… Nurses and nurses’ aides should be dedicated to NHDU… Stock, equipment and supplies should be replenished regularly and directly by the supply and pharmacy services.” | \n
D | \n“The vital signs monitors should be fixed to the wall for not taking up space in patients’ desk . . . and because sometimes they drop of the desk, usually when pulled by confused patients.” | \n
E | \n“It’s hard to work when there is not enough space to move around the patient bed without going against curtains, literally upon us, against wheelchairs and other patient’s beds.” | \n
F | \n“There is neither space nor conditions to lift patients to an armchair or wheelchair.” | \n
G | \n“Patients from one bed can touch and reach things of next patients because everything is so tight and so close to each other… Patients are potentially contaminating each other … and we ourselves have a hard time for this cross‐contamination doesn’t happen, I am sure it does eventually happen. “ | \n
H | \n“We have no space to put a RT next to the patient’s units … it is impossible to make secure ALS with the available space that we have.” | \n
I | \n“We usually are trained in basic life support every year, but we should also be trained in the use of RT and ALS… I have some difficulties in perceiving the location of clinical materials in the RT because there is a bad visual perception of it.” | \n
J | \n“I have little practice in the use of the RT, mainly the defibrillator… We should have training…” | \n
K | \n“Practices adopted in NHDU goes against scientific evidences … but it is difficult here to make whatever change we need … some people do not understand what good practices are.” | \n
L | \n“The NHDU has a lack of identity and autonomy.” | \n
M | \n“There is a lack of standards for admittance and clearance of patients… Even the doctors and some nurses do not understand that we only have capacity for 4 patients” | \n
N | \n“We cannot take any initiative to improve anything, because they fear us to take their place.” | \n
O | \n“They never listen to us. They do not realize, or understand, the staff who are working with them. We could make a great contribution to the better functioning of the unit.” | \n
P | \n“There is a huge resistance to change… There is a fear of loss or prestige transfer.” | \n
Excerpts from interviews.
Data Collected from Questionnaires.
According to the previous results and analysis of the interviews, questionnaires, spaghetti diagrams, value stream mapping (data not shown), and simulations, a set of suggestions were proposed by the PR to the Medical Director and Chief Nurse of NHDU (third pre‐intervention sub‐phase). This proposal was drawn up from the data collected attending to the Lean philosophy, the recommendations of best practices, and the standards of Portuguese regulatory institutions. The proposal considers several suggestions for amendments procedures, layout updates of the physical space, RT and NHDU cabinets content, and different locations of the clinical material and equipment. Briefly, these suggestions were the following:
\n\nPlace suction probes supports on the wall at each bed side (accepted);
Place water bottles supports to ensure suction tubes washing after manipulation (accepted);
Place mobile IV pole with AIS mounted at each bed side (accepted);
Remove vital signs monitors from patients’ desks and fixate them on the wall (accepted);
ALS and RT handling workshops for nurse training and education (accepted);
RT standardization (accepted);
Place TST at NHDU next to nurse station (accepted);
Reorganization of NHDU cabinets to improve contents access, variety, and identification (accepted);
Place drug vault at NHDU (rejected);
Place double air and oxygen pressure regulators at each patient unit (rejected);
Place manual ventilator at each unit in the presence of tracheotomized patient (rejected);
Organize trolley with clinical material for isolation room (rejected);
Eliminate one of the beds to increase circulation space (rejected).
After approval, or disapproval, of each suggestion, Lean methodologies (5S, JIT) were undertaken to ensure a better and safer work environment for patients and staff. The cabinets were reorganized into categories to cover the various patients’ needs like breathing, elimination, circulation, and administration, dressings and skin integrity, feeding, individual protection equipment. Sliding frosted glasses were removed from the cabinets, and it was possible to reduce and optimize the occupied space without decreasing the amount of material, but rather increasing its variety and availability, as seen in Figure 1 that also illustrates the post‐intervention TST location. The patients’ units were likewise reorganized with the inclusion of supports for suction probes, water bottles, and AIS (in mobile IV poles). Vital signs monitors were placed at a new shelve on each patient’s unit and ALS, and RT workshops has been schedule for nurse training and education.
\nSupplies in NHDU large cabinet before and after Lean intervention.
Spaghetti diagram for TST access before and after Lean intervention.
The presence of tracheotomized patients or at risk of being tracheotomized in NHDU is constant; therefore, the availability and accessibility to LSE, particularly ECK and TST, are of extreme importance. In the pre‐intervention phase, TST was in the treatment room of neurosurgery, about 63 m (round trip) far from NHDU nurse station. Changing its location into the large cabinet inside NHDU the distance decreased to 6 m (round trip) from the nurse station. Figure 2 represents the spaghetti diagram made before and after Lean intervention for the TST.
\nTable 3 shows the quantitative results obtained from the simulations of TST accessibility before and after Lean intervention. Data show the reduction of waste in time (−87.35%), distance (−90.47%), and steps (−87.12%) achieved with the application of Lean methodologies. According to Cohen’s d, the effect size is large. Shapiro‐Wilk normality test (data not shown) rejected the normality of the distance distribution (p < 0.001). So, for a one‐sided significance level of 0.025, were accepted the alternative hypothesis that time (p = 0.0017), number of steps (p = 0.000015) and distance (p = 0.016) were statistical and significantly lower after the application of Lean methodologies.
\n\n | \n | Time | \nDistance | \nSteps | \n|||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | \n | A | \nB | \n∆ | \n∆% | \nA | \nB | \n∆ | \n∆% | \nA | \nB | \n∆ | \n∆% | \n
\n | \n | Collective | \n\n | Paired | \n\n | Collective | \n\n | Paired | \n\n | Collective | \n\n | Paired | \n\n |
Collective and paired data | \nM | \n45.5 | \n4.58 | \n−40.5 | \n−87.35 | \n64.03 | \n6 | \n−58.03 | \n−90.62 | \n60.17 | \n7.5 | \n−52.5 | \n−87.12 | \n
\n | Mdn | \n39.5 | \n5 | \n−34 | \n−86.1 | \n63 | \n6 | \n−57 | \n−90.47 | \n60.05 | \n8 | \n−52.5 | \n−87.32 | \n
\n | SD | \n18.87 | \n0.79 | \n19.07 | \n5.08 | \n2.43 | \n0 | \n2.43 | \n0.34 | \n9.75 | \n0.91 | \n9.05 | \n1.71 | \n
\n | Max | \n76 | \n6 | \n−71 | \n−93.42 | \n69 | \n6 | \n−63 | \n−91.3 | \n70 | \n9 | \n−62 | \n−89.09 | \n
\n | Min | \n26 | \n3 | \n−21 | \n−80.77 | \n63 | \n6 | \n−57 | \n−90.48 | \n45 | \n6 | \n−38 | \n−84.44 | \n
\n | Range | \n50 | \n3 | \n−50 | \n−12.65 | \n3 | \n0 | \n6 | \n−0.82 | \n25 | \n3 | \n−24 | \n−4.65 | \n
t-test | \n\n | 95% CI | \n\n | \n | [−60.52; −20.48] | \n\n | \n | \n | \n | \n | \n | \n | [−61.99; −43] | \n
\n | \n | \n | t (df) | \n\n | −5.2 (5) | \n\n | \n | \n | \n | \n | \n | \n | −14.21 (5) | \n
\n | \n | \n | pa | \n\n | 0.0017 | \n\n | \n | \n | \n | \n | \n | \n | 0.000015 | \n
Wb‐test | \nZ | \n\n | \n | \n | \n | \n | \n | −2.264 | \n\n | \n | \n | \n | \n |
\n | pa | \n\n | \n | \n | \n | \n | \n | 0.016 | \n\n | \n | \n | \n | \n |
Effect size | \nCohen’s d | \n\n | \n | \n | −2.12 | \n\n | \n | −23.84 | \n\n | \n | \n | \n | −5.8 | \n
Results from TST accessibility.
A: Pre‐intervention (n = 6). B: Post‐intervention (n = 12).
aOne‐sided 0.025 significance.
bW‐test with exact significance.
Although the ECK is correctly located in the RT, 66.7% (n = 8) of nurses were unaware of its existence or location. For ethical reasons, there was an imperative and urgent need to educate them, which was done by the PR to all nurses’ team. In order to identify the difficulties of nurses in using the RT, simulations were performed. These simulations consisted in locating and accessing all RT contents, especially ECK. Through direct observation, it was found that all 12 nurses had some difficulties such as follows: safety seal breakage; retraction of safety latch; removal of back board; opening drawers by poor perception of the handle; finding and identifying critical medications and supplies; swing arm handling; and use of equipment including heart defibrillator. After the simulations, nurses justified their difficulties as a result of little practice and/or experience. An ALS and RT handling workshop intervention were scheduled to nurse’s continuous education plan.
\nIn the pre‐intervention phase, the AIS were in a storeroom forcing nurses to a constant movement and transportation of about 84 m (round trip). Lean 5S and JIT methodologies determined changing AIS location into a mobile IV pole next to the patients’ unit, permanently connected to electricity in order to ensure its permanent availability (Figures 3 and 4).
\nAIS location before and after Lean intervention.
Spaghetti diagram for AIS access before and after Lean intervention.
\n | Time | \nDistance | \nSteps | \n||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | A | \nB | \nA | \nB | \nA | \nB | \n|||||||
\n | Collective | \nPaired | \nCollective | \nPaired | \nCollective | \nPaired | \n|||||||
Collective and paired data | \nM | \n79.5 | \n3 | \n−76.5 | \n−96.27 | \n83.6 | \n3 | \n−80.6 | \n−96.41 | \n107 | \n4.5 | \n−102.5 | \n−95.83 | \n
Mdn | \n78.5 | \n3 | \n−76 | \n−96.29 | \n83.6 | \n3 | \n−80.6 | \n−96.41 | \n104 | \n4.5 | \n−99 | \n−95.84 | \n|
SD | \n8.13 | \n0.95 | \n7.44 | \n0.91 | \n0 | \n0 | \n0 | \n0 | \n9.72 | \n1.17 | \n8.85 | \n0.85 | \n|
Max | \n92 | \n5 | \n−87 | \n−97.40 | \n83.6 | \n3 | \n−80.6 | \n−96.41 | \n130 | \n6 | \n−124 | \n−97.00 | \n|
Min | \n65 | \n2 | \n−63 | \n−94.57 | \n83.6 | \n3 | \n−80.6 | \n−96.41 | \n97 | \n3 | \n−94 | \n−94.55 | \n|
Range | \n27 | \n3 | \n−24 | \n−2.83 | \n0 | \n0 | \n0 | \n−0 | \n33 | \n3 | \n−30 | \n−2.45 | \n|
95% CI | \n\n | \n | [−81.23, −71.77] | \n\n | \n | \n | \n | \n | \n | \n | \n | \n | |
\n | t (df) | \n\n | \n | −35.62 (11) | \n\n | \n | \n | \n | \n | \n | \n | \n | \n |
\n | pa | \n\n | \n | 5.64×10−13 | \n\n | \n | \n | \n | \n | \n | \n | \n | \n |
W b‐test | \nZ | \n\n | \n | \n | \n | \n | \n | −3.46 | \n\n | \n | \n | −3.06 | \n\n |
\n | pa | \n\n | \n | \n | \n | \n | \n | 0.00024 | \n\n | \n | \n | 0.00024 | \n\n |
Effect size | \nCohen’s d | \n\n | \n | −10.28 | \n\n | \n | \n | −5×1015 | \n\n | \n | \n | −11.58 | \n\n |
Results from AIS accessibility.
A: Pre‐intervention (
aOne‐sided 0.025 significance.
b
After the intervention and application of Lean methodologies, the AIS mean access was 96.27% in time, 95.83% in steps, and 96.41% in distance lower than in the pre‐intervention. The effect size is large (or very large) with d = −10.28 for time, d = −11.58 to number of steps, and d = −5×1015 to distance. For the hypothesis test, the Shapiro‐Wilk normality test rejected the normality of steps (p = 0.039) and distance (this one constant) distribution. So, for a one‐sided significance level of 0.025, were accepted the alternative hypothesis that time (p = 5.64×10−13), number of steps (p = 0.00024) and distance (p = 0.00024) were statistical and significantly lower after Lean methodologies application, as shown in Table 4.
\n\nThe results of quantitative data associated to the hypothesis test, the size effect, and the improvements in accessibility to TST and AIS are summarized in Table 5.
\n\nHypotheses | \nStatistical test | \nSize effect | \nPercentage variation (decrease) | \nPercentage variation (improvement) | \n|
---|---|---|---|---|---|
H01: The difference of TST time of access between pre and post‐ intervention equals zero. | \nPaired samples | \n0.0017 | \n−2.12 | \n−87.35% | \n837.22% | \n
H02: The difference of TST distance of access travelled between pre and post‐intervention equals zero. | \nPaired samples | \n0.016 | \n−23.84 | \n−90.47% | \n950% | \n
H03: The difference of TST number of steps of access between pre and post‐intervention equals zero. | \nPaired samples | \n0.0000151 | \n−5.8 | \n−87.12% | \n687.46% | \n
H04: The difference of AIS time of access between pre and post‐ intervention equals zero. | \nPaired samples | \n5.64×10−13 | \n−10.28 | \n−96.27% | \n2733.8% | \n
H05: The difference of AIS distance of access travelled between pre and post‐intervention equals zero. | \nPaired samples | \n0.00024 | \n−5×1015 | \n−96.41% | \n2686.7% | \n
H06: The difference of AIS number of steps of access between pre and post‐intervention equals zero. | \nPaired samples | \n0.00024 | \n−11.58 | \n−95.84% | \n2310% | \n
Summary results from quantitative data.
aα = 0.025 one‐sided.
After all the action research phases performed, it was demonstrated that the application of Lean methodologies contributes for improving the accessibility to equipment and material that are essential to nurses’ safe practice. With the application of the Lean methodologies, it is possible to provide optimized care to acute neurosurgical patients, in emergency and life support situations. Lean methodologies such as Gemba walk and spaghetti diagram made possible to identify wastes and difficulties in LSE accessibility, organization, and provision of other clinical equipment and supplies, and security issues such as potential cross‐contamination provoked by exiguous work areas and architectural barriers. 5S and JIT philosophies together with interviews and questionnaires led to the development of a grounded interventional proposal for a functional and organizational harmonization of NHDU. Each suggestion on the proposal was then analyzed by medical and nurse unit managers giving deferral or refusal to certain interventions. The implementation of 5S and JIT methodologies led to the reorganization of NHDU and the allocation of the equipment closer to patients and nurses as well as to the decrease of waste, non‐value‐added activities and to significant improvements. These same results are argued in Carvalho et al. [45] since they defend that the layout must “reflect the need to reduce the time spent traveling” (p. 291) since “time ‘lost’ in travel between the various services… represents a cost to the organization in question, and that, in most cases, is not noticed or accounted for” (p. 291). For example, a nurse who searches for drugs, supplies, and equipment are doing it to serve the needs of patients, but may not notice that it can result in a waste of time, transport, handling, and human potential. But according to the Institute for Healthcare Improvement [46], if these materials were readily available when, how, and where they are needed (JIT), the time that nurses wasted looking for them would be instantly devoted to other more appropriate and critical tasks.
\nThrough action research and the application of Lean methodologies, nurses of NHDU actually take only 10% of time, 9.37% of the distance travelled and 12.46% of the steps spent accessing TST compared to pre‐intervention. The results of the intervention in AIS showed an improvement even more significant since the post‐intervention access time is just 3.77% of pre‐intervention time, the distance just 3.59%, and the number of steps only 4.21% compared to pre‐intervention. To achieve this, nurses were educated about the location of LSE, and the need for training these nurses in ALS and RT handling was identified. Wastes and barriers that conditioned rapid access and action to acute patients were identified, reduced, or removed. Time, steps, and distance travelled accessing LSE were shortened and reduced more than half (−87.12 to −96.41%).
\nThe same results were reached in other researches. Virginia Mason Medical Center (VMMC), in Seattle (USA), is credited to be one of the pioneers in healthcare industry to implement Lean by applying their own Virginia Mason Production System (based on TPS) [47]. Since 2001 VMMC makes efforts with the reorganization of spaces and workflows, minimizing transportation, and handling wastes, where all clinical equipment and supplies essential to care are placed in the point‐of‐use in UK Hereford Hospital, Lean methodologies led also to reductions of delay in nurses’ response time between 40 and 93% [48]. In Scotland, from a sample of 19 critical care units, nurses available time increased from 35 to 64%, in which 32% of these units reached changes greater than 100%, supported by the program Releasing Time to Care: The Productive Ward, based on Lean and six sigma methodology [49].
\nIn this study, there is a significant and serious lack of nurses’ knowledge on the existence and location of LSE. Intervention trough education, awareness, and change of its location resulted in an improvement of 100% to TST and 200% to ECK leading to health benefits for patient’s safety and quality of care. Still on the ECK and the RT, the simulation demonstrated the difficulties experienced by nurses in the use of the RT, particularly in opening it, use of drawers, location, and rapid visualization of contents. It was retrieved from this analysis that the imperative and urgent need for nurse’s professional training and the need for a clearly defined intervention criteria in emergency situations. This is in line with Silich et al. [50] that also highlights that informed and trained professionals provide better care with potential reduction of adverse events, bad practices, and less waste of resources.
\nCatchpole [51] argues that the undesirable effects of an inadequate working environment can result in fatigue, frustration, reduced performance, and human capacity, increased risk, and adverse events. Hence, the importance that health facility managers have and the impact of their decisions on patients and staff, and “usually, it is the intermediate and elementary level manager, involved in everyday decisions, that affect the care that is actually provided to patients” [52].
\nThis research was intended to interfere in the reality studied by solving identified problems in an effective and participatory manner (through action), not only explain it or proposing a problem solution. The impact for practice and health services (quality indicators, safety, and satisfaction) of the Lean interventions carried out by the PR is well grounded by the results. In this research, it was verified that 66.7% of nurses were unaware of the existence or location of ECK and 50% of the TST. The education intervention resulted in an improvement of knowledge of 100% in the TST and 200% in the ECK, leading to potentially high health gains for the patient, because trained professionals provide better care with fewer mistakes. Furthermore, this research identified needs for periodic training and education on ALS and RT practice. Through Lean methodologies such as 5S, JIT, and spaghetti diagrams, it was possible to decrease time, steps, and distance travelled by nurses accessing TST and AIS between 87.12% and 96.41% and to improve this accessibility between 687.46% and 2733.8%.
\nThese results confirm the contribution of this research to address the need of this healthcare unit to improve the care of neurosurgical acute/critically ill patients. The implementation of Lean 5S and just‐in‐time methodologies led to the reorganization of NHDU environment by allocating LSE closer to patients and nurses station, contributing by this way for improving the security and responsiveness of nurses’ team for having more knowledge and quick access to LSE. In addition, it contributes to overcoming emergency, life support situations, and day‐to‐day professional life action to the needs of patients, freeing up time and availability of nurses for direct care by a work environment with less waste of time, distance, steps, handling, and setup procedures.
\nAlthough not focused in this research, for the unit and hospital management, there are potential economic and financial benefits attained from the application of Lean methodologies through the following factors: hand labor and human capital gains by reducing the time required to perform certain tasks (setup time); reduction of the “snowball” effect that leads to the accumulation of everyday work; reprocessing gains from potential reduction of costs in time of hospital internment and patient morbidity.
\nBesides the advantages reached with the application of the lean methodologies the research findings, however, are tempered by several shortcomings such as the unavailability of participants to collaborate with the research and resistance to change. Financial impact of the intervention was not recorded. Moreover, the results cannot be generalized; other realities can compare them and encounter similar situations that may benefit with the application of Lean methodologies in an attempt to overcome their problems.
\nIt is expected that health professionals, especially their leaders and managers, can take some lessons from the different approaches adopted in this research and may act as a catalyst for future positive changes in all health services.
\nAs a suggestion for future research it would be interesting to study the financial impact (time saved vs. value/hour) of the application of these lean methodologies, the impact on the quality of nurses daily professional life (satisfaction, fatigue, stress, burnout) and on emergency scenarios (LSE accessibility/availability vs. morbidity and mortality).
\nColloidal magnetic fluids are made up of nanometer and micron-size ferromagnetic particles dispersed either in electrolytes or in organic solvents [1]. Due to their easy manipulation with magnetic or electric fields, they are having a significant impact on diverse technological applications ranging from biomedicine [2] and photonic devices [3, 4] up to fundamental studies that motivate the development of modern theories of nonequilibrium condensed matter [5, 6, 7, 8, 9, 10]. In this chapter, we review the studies of static structural and dynamical properties in colloidal magnetic fluids, which provide a comprehensive description of their bulk phase behavior at thermal equilibrium. Presently, model magnetic colloidal systems can be prepared with tunable interaction among particles of the hard sphere and long-range dipolar types [11, 12, 13, 14], especially the colloidal system constituted of micron-size polystyrene spheres that are electrically charged and dispersed in organic solvents [11]. In such a system, particles acquire an induced electric dipole moment under the external static electric field. Confocal microscopy has allowed the determination of its three-dimensional bulk phase diagram as a function of applied electric field and by taking into account the presence of a 1:1 salt. The electric and magnetic dipole pair interaction potential is symmetric. Consequently, a corresponding change of physical units leads to an equivalent description of the magnetic fluid phase diagrams. Novel Monte Carlo simulation methods have confirmed the different experimental phases [15, 16]. Integral equations and density functional theories have assisted in the understanding of the phases formed by molecular liquids [17], and they have been used to gain qualitative insight into the expected phases as a function of volume fraction and dipolar strength of colloidal magnetic fluids [18, 19, 20, 21, 22, 23]. Likewise, the structure factor and diffusion coefficient of magnetic suspensions made of maghemite nanoparticles dispersed in water and equilibrium with electrolyte solutions have also been reported [24, 25, 26, 27, 28, 29, 30, 31]. The measured structure factor provides the microscopic arrangements of particles accurately. Here, we provide a Langevin stochastic approach that allows the determination of the translational and rotational diffusion of the particles in ferrofluids [32, 33]. These dynamic properties, in turn, allow quantifying the viscoelastic and dielectric moduli of the structural evolution of the fluid toward their equilibrium states [34]. This approach may help to interpret recent experiments of passive microrheology [35, 36] and Altern Current spectroscopic techniques that measure the viscoelastic dynamics and dielectric relaxation of colloidal magnetic fluids. It is expected these theoretical methods be extended to help to understand the corresponding experimental observations of similar dynamics in two-dimensional paramagnetic colloids [37] and under external fields.
The importance of knowing the phase diagram of a ferrofluid resides on the information it provides about the undetermined underlying effective interaction of the ferromagnetic particles [13]. For maghemite nanoparticles in aqueous solutions, there have been attempts to determine such electrostatic potentials by using the measured parameters such as dipole strength and fluid density as inputs in Brownian dynamics simulations to reproduce the observed bulk structure factor [30, 31].
There is a set of experiments in a well-characterized system of electrically stabilized maghemite nanometer-size particles, which are dispersed in water [24, 25, 26, 27, 28, 29]. Its stabilization is reached with the citrate electrolyte. By fine-tuning the salt concentration, the particle’s interaction was shifted from repulsive, where they form a solid glass phase, into long-range attractive interactions that yield a fluid or gas state behavior. These experiments have prompted the determination of the corresponding pairwise interaction among particles [13]. The proposed interaction consists of a Yukawa repulsive part, a Van der Waals short-range attraction and includes an angular averaged attractive long-range pair dipole potential. There have not been attempts to predict the phase diagram with these potentials. However, the modeled interactions were used to determine with Brownian dynamics the observed structure factor [30, 31]. By using a generic model of pair dipole interactions together with an effective attraction associated with density gradients, Lacoste, et al. [38] considered a quasi-two-dimensional layer of a dilute ferrofluid subjected to a perpendicular magnetic field, and with the help of a mean field energy approach, they found modulated phases given by stripes and hexagonal formations. The Gibbs free energy they considered for inhomogeneous systems has the general shape
It has been recognized that ferromagnetic particles of 10 -nm size remain dispersed [39]; however, when particles have larger sizes up to the micron scale, experiments find they do assemble into chains, rings, and nets were several chains bound together into an amorphous structure [40]. A mean field theory that takes into account such topological structures was developed to explain the liquid-gas phase transition by the formation of Y-like bounds of chains in the network [41]. There remains a quantitative verification of this theory with its experimental counterpart and with computer simulations. Another method to validate the proposed model of particle’s interaction is based on the parameters that appear in the Lennard-Jones potential that represents the Van der Waals attractions together with the pair dipole-dipole potential, and by fitting the predicted magnetization curve as a function of the applied magnetic field to the experimental one [42]. Even though there is not yet a realistic model interaction potential that represents the interaction of ferromagnetic particles, the use of fitting parameters as mentioned above has led to the prediction of the structure factor and the birefringence as a function of the applied field, which shows qualitative agreement with the experimental values [22, 29, 30, 31].
Yethiraj et al. [11] made a colloidal system of charged and sterically stabilized polymethyl methacrylate spheres of micron size in an organic solvent to have dipole moments on particles induced by an electric field. This monodisperse suspension shows both long-range repulsion, and attractive anisotropic interaction potential that is fixed with the addition of salt, whereas the dipolar interaction is controlled by the external electric field. For low Reynolds numbers and in an infinite fluid, a solid spherical particle that sinks in the fluid reaches a terminal velocity due to a balance of the friction force exerted by the fluid that opposes the gravitational force on the particle. If the fluid has a dynamic viscosity
Finite-temperature calculations of ground state free energies with Yukawa repulsion and dipolar-dipolar interactions of varying strength were performed by Hynninen and Dijkstra [15]. In their calculations, they used canonical Monte Carlos simulations to obtain the free energy minimum as a function of volume fraction and dipolar strength in three-dimensional model systems. They found a phase diagram that contains the same phases as was observed by Yethiraj et al. [11]. However, additionally, they predicted a new hexagonal close-packed phase at the hard sphere repulsion limit and body-centered orthorhombic when the repulsion becomes long range by lowering the content of electrolyte in solution. Their method allows quicker and reliable determinations of the three-dimensional phase diagram than the evolutionary algorithm method that searches for the ground state at zero temperature for two-dimensional systems [45]. The bulk phase diagram has not been searched yet with genetic algorithm (GA) at finite temperature. A particular detail of GA is that to look for the minimum of the free energy, the derivative of the energy function at each evolution step is required for finding the best-adapted crystal structures (individuals) in the population, which is made up of several crystal structures produced by the algorithm. The search of the best-adapted individuals (crystal phase) is done in the energy landscape. For fixed pressure and finite temperature, the Gibbs free energy as a function of pairwise interaction strength and particles concentration in the fluid yields a three-dimensional plot of the free energy known as energy landscape, which has local minima and maxima. The global minimum of an equilibrium crystal structure is reached with the assistance of a local gradient algorithm that requires the derivative of the energy. Such a procedure makes an indirect search of the crystal structure by sampling the energy landscape. Thus, it becomes technically more involved to implement than the Hynninen et al. method of MC ground state energy searches. In Figure 1, we provide two nonequilibrium states of local minima that result from the application of a genetic algorithm approach at zero temperature and fixed pressure.
Genetic algorithm prediction of minimum local structures at two densities of equally sized ferroparticles in the aqueous colloidal magnetic fluid at
Recently, Spiteri and Messina [16] have proposed an efficient nonlinear optimization technique that allows predicting the crystal phases of dipolar colloids at zero temperature without the need to use derivatives of the free energies. It was found that for a monodisperse repulsive hard sphere plus dipole-dipole interaction, the predicted phase diagram has the same phases as was previously found by Hynninen et al. [15] and that a knew so-called clinohexagonal prism span all known ground state structures at any density. There remains to be verified if this prediction fulfills at a finite temperature also.
The microstructural order inside of the ferrofluid is determined by the potential interaction among particles. The measured structure factor yields the details of the particles’ spatial geometric arrangement. The water-based maghemite ferrofluid is electrostatically stabilized. The interparticle interaction was modeled in Ref. [13] with a Yukawa repulsion part together with the anisotropic dipolar potential. The highest peak of the structure factor regarding wave number
Simulation results of structure factor versus wave number. The contact values at k=0 yield the compressibility modulus. The material parameters of maghemite colloid were used [
The contact values at k = 0 yield the compressibility modulus. The material parameters of maghemite colloid were used [40]. At low densities and magnetic moment, there is liquid order. For higher dipole moments, formation of chain appears.
Figure 3 is a plot of the collective diffusion coefficient
Calculated collective diffusion coefficient
The researchers in Ref. [46] also measured the wave vector-dependent collective translational diffusion coefficient in the absence of an external field using X-ray correlation spectroscopy. Such a dynamical property has a known linear dependence on the particles’ hydrodynamic interactions (HIs). The proposed theoretical hydrodynamic function that captures the HI among particles overestimates the experimental data. On the other hand, Meriguet et al. [29] used small-angle neutron scattering to measure the incoherent scattering function at the fixed magnetic field. The incoherent part gives in the long-time overdamped regime, the single translational diffusion coefficient for long wave vectors k, and the coherent part provides the collective diffusion as a function of k. Using liquid theory definitions of these two dynamical functions, their comparison with the experimental values yields good agreement at all wave scattering vectors k. The same collective diffusion coefficient can be measured by forced Rayleigh scattering also [26]. In this technique, the fluctuations in concentrations of the particles are considered a dynamic variable. We note that similar studies have been undertaken in the case of rodlike macromolecules in suspension such as Tobacco mosaic virus [48]. Explicit statistical mechanics derivations for the dynamical collective correlation functions (intermediate scattering function) have been given that fit well Brownian dynamics simulations just at long wave numbers but fail at intermediate and short k values. In Refs. [32, 33, 34], we proposed a Langevin equation theory for a tracer ferroparticle whose motion is coupled to the cloud of the other colloidal magnetic particles with which it interacts.
with
Here,
where the Onsager coefficient
The propagator
These correlation function components are obtained from the Fourier transform of their definitions
In Figure 4, Ref. [34] is provided a plot of the translational and rotational self-diffusion coefficients of such a theory. In this picture, we compare the diffusion coefficients with Langevin dynamics simulation results for the same diffusion coefficients by using typical parameters of
Translational (rotational) self-diffusion coefficients
Ferrofluids are complex fluids whose viscoelastic response to weekly applied strain rates
where
Logarithmic plot of elastic
We notice that the effective viscosity at the overdamped regime
The time-dependent magnetic susceptibility
where
This equation is valid for colloidal suspensions of particles with axially symmetric potentials, where the memory function
Real
Alternative kinetics methods for low-density ferrofluids are given in [40].
This review highlights several active research lines on the structure and dynamics in ferrofluids. These investigations are motivated by many experimental observations that colloidal ferromagnetic particles both in bulk or in thin film aggregate, building several macroscopic structures of practical and scientific interest. As for all applications where colloidal materials are being processed, it is necessary to understand the interparticle interactions to have better control of the resulting structures and their properties. The interactions are known experimentally under specific conditions through the measured phase diagrams [11]; it has been found [29] that a useful potential that represents well the structure factor of ferrofluids is a Lennard-Jones plus dipolar interaction between pairs of particles. Therefore, our use of this potential in an evolutionary genetic algorithm leads to Figure 1, which shows transient metastable crystalline structures of a monodisperse ferrofluid at
The authors acknowledge the General Coordination of Information and Communications Technologies (CGSTIC) at CINVESTAV for providing HPC resources on the Hybrid Supercomputer ″Xiuhcoatl″ that has contributed to the research results reported within this chapter.
There are no conflicts to declare.
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\\n\\nAll translated Chapters have to be properly attributed in accordance with the requirements included in IntechOpen's Attribution Policy. Besides proper attribution translated sections of Works must include the following sentence: "This is an unofficial translation of a work published by IntechOpen. The publisher has not endorsed this translation".
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\n\nAll translated Chapters have to be properly attributed in accordance with the requirements included in IntechOpen's Attribution Policy. Besides proper attribution translated sections of Works must include the following sentence: "This is an unofficial translation of a work published by IntechOpen. The publisher has not endorsed this translation".
\n\nAll rights to Books and other compilations are reserved by IntechOpen. The copyright to Books and other compilations is subject to a Copyright separate from any that exists in the included Works.
\n\nA Book in its entirety, or a significant part of a Book, cannot be translated freely without specific written consent by the publisher. Requests for permission can be made at permissions@intechopen.com.
\n\nPolicy last updated: 2016-06-09
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Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. 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Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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