Medical Laboratory Error and Its Impact on Quality of Care


Development in Technology has simplified every aspect of human life and it reflects more in the field of heath care. The improvement seen in the overall performance of medical care including laboratory testing is that much. However, the very development, instead of reducing the errors in the health care has literally increased its occurrence. The studies conducted by different departments of medical care hitherto have established that most of these errors originate in the pre-analytical stage and are extended through analytical and post analytical phases of health care to find its last resort in the structural management.

Lack of improved standardization procedures of specimen acquisition, handling and storage of specimens are added elements to the errors. Hence there is a need to advance the system by imparting quality of service to the patients through adoption of cost effective methods.

It is quite impossible to have a cent percent error proof system in any field we are accustomed to. As such there is no chance for a zero error medical care. But the willfulness and motivation of the care professionals can contribute much to reduce the errors and malpractices. To achieve this, new accreditation standards, procedures, better management tools, appropriate techniques for quality care and error prevention, efficient leadership, management skills and strategies, motivation, harmony, patient-physician cooperation and understanding, and above all, the necessity to have all these elements combined together to form a different, but unique empathetic and sensitive health care culture are required.


The beginning of human civilization was marked by the application of several systems of medical treatment and health care practices. Initially, such applications were characterized by the intellect of physicians and the mercy of nurses. The availability of drugs and patient safety systems were very limited and of poor quality then, and the fate proved the deciding factor in the survival or the well being of the patient. But as time passed on the medicines acquired quality, standard and sophistication. Specialized care providing teams emerged on par with the development of medical treatments and along with this, accidents became very frequent on the administration of medicines.

This status continued unabatedly till the last century when it witnessed the origin of a transparent medical profession that revealed the mishaps in the patients due to human errors. In the early 1990s, the Agency for Health Care Policy & Research, which is now known as Agency for Healthcare Research and Quality (AHRQ), has confirmed that medical errors posed one of the major threats against improving quality health care in America. In its latest report, AHRQ has stated that between 44000 and 98000 Americans die every year in hospitals from preventable medical errors. This statement was based on the current estimate prepared by the United States Institute of Medicine (Lippi et al., 2006).

An average US citizen is literally within the healthcare provider net trying to escape from an agonizing death, tortured by the financial stringency and the error prone health care system. Hence the situation warrants immediate revamping of the entire national health care system. According to the IOM report, if a person is sick and seeks medical care, there should be something soothing so that the individual shall not be harmed by the very health care system. It is worth to mention here that the United States of America provides the highest quality of medical care to the citizens but still it is far from a satisfactory level.

Malpractices and shortcomings are so many and they affect the intended quality of medical care and reflect in the relationship between patients and physicians. The increase in health care expenses poses great threat to the effective delivery of service (Lohr, et al., 1988). Therefore, value oriented performance in health care is a necessity for the safety and welfare of the patients. To attain this objective high transparency and accountability have to be maintained in every department of the health care system, and credibility should become the underlying principle for an effective health care service.

It is true that several random corrective measures have already been adopted by private and public sector organizations to impart quality oriented service to the people but they are not enough to improve the clinical conditions. The main troubling part of these measures is that they lack consensus and collaboration and because of these they create confusion in the system to bring unwanted burden to the patients as well as physicians (Tooker, 2004).

Many people believe that Health care in the USA is not safe even after the innumerable corrective steps and insistence of quality control by the authorities. Reliability and guarantee are not all the guiding factors, as these are totally discarded by the care givers and clinical attendants. The clinical errors used to put alarming spells on the system of health care, and hence, such errors take more lives in its death toll year after year.

Apart from the loss of lives, the cost of expenditure burdened on the patients due to these errors (and the additional care), and the resultant income drain in the household productivity subsequent to the medical mishaps and disabilities, is estimated to be from $ 17 billion to $29 billion every year in the USA hospitals. The cost in terms of losing faith in the overall health care system by the health professionals and the patients as well stands separate.

In addition to all these, who will pay for the physical and mental torture inflicted to the patients and their relatives by the faulty health care system? Frustration and loss of morale among the health care professionals are too much and the society is bound to bear the cost of these errors in terms of reduction in worker productivity, drop in school attendance of the children, and the unpardonable sin in lowering the health condition of the people and leaving them to suffer for the rest of their lives (Kohn et al., 2000).

In this context, it is quite apt to point out the several factors that lead to the medical errors in the field of health care in the country. Many quality appraisers and professionals view that the main problem of medical errors is caused by the decentralized and compartmentalized health care delivery system. Mostly, the performance of the system tends to act like a non-system. The myriads of provisions in different settings that appear before the people make them confused in the matter of selection, and when it is mounted by non access to information, the chances to develop the errors are innumerable. The process of giving license and accreditation to the health professional without taking into consideration the expertise they have acquired in the avoidance of medical errors will only undermine the exercises behind the accreditation and its very purpose.

Moreover, the frequent resistance from health care organizations and health care providers add more problems to the already problematic health care system. Some providers hold the notion that the medical liability system fails to cope with the process of learning from the errors. Another factor is that the third party owners of health care do not provide any financial incentives to health care institutions to enhance the safety and quality of the system (Kohn et al., 2000).

In the report of the US Institute of Medicine (Kohn et al., 1999), clinical error is defined as ‘the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim’. According to Kohn and others (1999), such errors may happen at the initial stage when the mode of action is planned or at the time of its execution. Adverse drug incidents and defective transfusions, injuries due to surgical procedures including wrong site surgeries, burns, mistaken identity of the patient etc., among many other things contribute to the clinical errors.

Of these, most of the errors take place at the Intensive care units and operation theatres, where medication errors like administration of wrong drug or dose which can be avoided by alertness, become the leading cause of injury of a patient inflicted by the wrong route administration of the drug or by giving the drug to a wrong patient. Two types of human errors happen in this case. The first one is the person approach and the second one is system approach.

Person- approach is individual centric on errors and can occur due to forgetfulness or moral failures, whereas the system approach identifies the source or workplace as the error source (Reason, 2000). But, Leape et al. (1995) hold the view that lack of drug knowledge and satisfactory information about the patient in the form of test results etc., are the common causes for clinical errors.

Changing Perspectives

After the declaration made by USA Institute of Medicine the whole medical community has started giving more awareness in this matter. The statutory bodies and medical organizations have already begun the incorporation of the several provisions for maintaining patient safety as the guiding principle for giving accreditation to the health care professionals and health care providers. Nevertheless, even after the insistence of such stringent measures the mortality rate of the patients due to medical errors is in the increase.

Since patient’s safety is harmed by the frequent errors happening in the health care system, the Institute for Quality in Laboratory Medicine was formed in 2003 which was then incorporated with the Centre for Disease Control and Prevention in 2005. This was followed by the initiation of quality measurement tools by the College of American Pathologists to avoid the errors in the labs. Though this helped to reduce the errors to a certain level, many institutions are groping darkness to find out the best approach to overcome the lab related errors (Wagar et al., 2006).

In addition to these, lack of proper training in the health care system does much harm on the quality of services. In a recent study conducted by Flores et al. (2003), it was found that most of the hospital interpreters had no adequate training provision in the hospitals. They were of the opinion that the interpreter errors are the main reason for the cause of many of the medical errors.

As a result, some professional groups in the national health care sector such as Council on Graduate Medical Education (COGME) and the National Advisory Council on Nurse Education and Practice (NACNEP) became very active and they jointly declared that the relationship between the physicians and the nurses have impacts on the patient safety and that training programs will be implemented to enhance interdisciplinary collaboration in the health care system.

Kohn et al. (2009) suggest that though there is no single solution to deal with the medical errors, the joint activities mentioned in ‘To Err is Human’ can contribute much in the matter of creating a safe health system. “With adequate leadership, attention, and resources, improvements can be made. It may be part of human nature to err, but it is also part of human nature to create solutions, find better alternatives, and meet the challenges ahead” (Kohn et al., 2000).

With the enforcement of certain standards and inculcating motivation in the professionals, improved quality in health care can be achieved through new regulations on licensing, accreditation etc., and by providing practice and training to the health care providers. Health care purchasers whether they are private or public shall contract for the schemes only with greater concerns for quality health care service while delivering them.

Organizations working in the health care sector must develop a safety culture to get better safe care for their workers. Automated order entry system must be utilized for buying medication and patients are allowed to take periodic safety check in their hospitals. The patients must know the details of the medications administered to them including the side effects. Though the medical errors cannot be removed completely from the system with a single approach, a major portion of such errors can be avoided by efficient leaderships, effective usage of system tools and observance of vigilance (Kohn, 1999).

Classification, prevention and rectification of clinical errors

The errors that originate during the process of extending health care to patients are too many, and they used to come up at different phases of the health care system. Identifying and rectifying these errors in a timely manner to impart quality in service are considered as a matter of high importance now days, without which the welfare of the patients will be jeopardized. Moreover, if there is no awareness about these errors it would not be possible to learn from them to develop appropriate corrective measures for safeguarding the interests of the patients and general public as well.

The Harvard and Australian in depth studies on medical errors have exposed the amount of injuries inflicted on the patients in hospitals. Their findings revealed y that errors occur furthermore due the lack of experience of the clinicians while introducing new procedures. Old age, need for complex and urgent care coupled with prolonged stay in hospitals mark increase in such errors. Patients when injured due a medical error have to stay in hospitals for a longer period which in turn will burden them with more health care costs. The Harvard study has reported that adverse drug events have forced the patients to stay further in the hospital for 2.2 days which hiked the expenditure to $2595, while preventable adverse drug incidents have put an added cost of $4685 against the increased stay for 4.6 days (Weingart et al., 2000).

The report of the Institute of Medicine on medical errors, 1999, has invoked much interest throughout America. The press welcomed it and the regulatory bodies incorporated the directives for increased patient safety for accreditation. Consumer forums have also become vigil to take the cause of patient’s safety. Subsequently the College of American Pathologists and American Society of Clinical Pathologists have started educational programs focusing the need for patient safety in health care and to bring proper awareness among the medical professionals to reduce medical errors (Sirota, 2005).

Types of Errors

Leape et al. (1993) have identified the errors found in the health care system and categorized them in the following manner:


  1. Error or delay in the diagnosis
  2. Failure to employ indicated tests
  3. Use of outmoded tests or therapy
  4. Failure to act on the results of monitoring or testing


  1. Error in the performance of an operation, procedure, and test
  2. Error in administering the treatment to the patient
  3. Error in administering the dose or method of using a drug
  4. Avoidable delay in the treatment or in responding to abnormal test
  5. Inappropriate/inadequate care


  1. Failure in providing prophylactic treatment
  2. Inadequate monitoring of the treatment


  1. Failure of communication
  2. Failure of Equipment
  3. Failure of other systems [Source: Leape et al. (1993) Preventing Medical Injury. Qual Rev Bull. 19(5):144–149].

Since this classification, there were frequent improvements in the technologies, tools and other procedures in the health care system and also other devices that supplement it. Therefore, a reclassification is still needed to sort out the problematic errors at their sources in order to analyze and rectify them.

Pre –analytical & Post analytical errors in clinical lab & its effect on patient’s care

The challenges facing quality health care have attracted much attention these days. During the passage of time this will only increase as the present scenario of the national health care system is confusing and obscure. If we analyze the issue of errors that creep into the laboratory medicine and blood transfusion the result will be very shocking. There are large amounts of heterogeneity and quality degradation which are more or less blunders.

There exists considerable presence of errors in the entire laboratory procedures. A major portion of these errors are seen in the pre-analytical and post-analytical stages, and out of these a significant portion i.e., 13-32% happens in the analytical phase. This situation suggests that a very effective methodology needs to be conceived and implemented in this field to remove or reduce the errors (Bonini et al., 2002).

Measuring the patient outcomes related to laboratory errors (Table-2) and its enhancement requires certain reliable methods of collecting lab information and also adoption of some patient management techniques. Such techniques include clinical diagnosis of the disease and its treatment, clinical monitoring, and executing preventive measures against the disease. The analytical quality should be improved by means of proficiency testing to know the actual performance of the clinics relating to the patient’s health which is in proportion with the lowering of the turnaround time (TAT). In this connection it must be known that improvement in the matter of performance of laboratory does not mean that there is reduction in the sum of analytical and organizational errors (Bonini et al., 2002).

Effects of laboratory errors on patient outcomes.
Table 1. Effects of laboratory errors on patient outcomes.

Most of the studies conducted on this focused only on the analytical errors including pre, intra and post analytical errors. Some other studies were focused on the methodologies like split-specimen design which is not at all sensitive to problems in the testing process. The pre-analytical tests have unspecific choice in the tests many of the post analytical errors are originated from the inappropriate dependency on the lab results.

A systematic laboratory clinical audit review has revealed that the studies made hitherto were based on the inaccurate laboratory utilization without observing the required methodological standards. It is critical to find that there were only a few studies that touch the inappropriate application of the results of laboratory responses. Lack of proper and timely notification about the clinical utilization relating the critical value can affect the result making it negative. In addition to these problems are the problems of reluctance in reporting the errors happened by own mistakes. This will create confusion in the laboratories in identifying the errors because most of the errors will not bring any abnormal results (Bonini et al., 2002).

The new patho-physiologic knowhow and the precision lab tests have altered the laboratory information procedure, and the existing gold standards insist for measuring cardiac troponins to detect even minute myocardial injuries in the myocardial coronary syndrome. Molecular analysis for evaluating the susceptibility of the disease is done in the same line. When it is not easy to compare the results of laboratory tests according to gold standards, the errors are noted by appraising the value of relationship between medical outcomes and available laboratory information.

The laboratory errors and problems that are faced at the blood banks are the points of attraction to the mass media in spite of the fact that their attention is derived out of other related healthcare departments such as drugs and surgery. Most often, such focusing on the reported errors by them are only superficial and patient outcome and its consequences are truly worse than what is elaborated which the media usually ignore for its own convenience (Bonini et al., 2002).

Taking into consideration the problems that exist in the clinical laboratory errors it is imperative that all of the laboratory errors which were noted till now are classified deftly; relating them in accordance with their potential effects like that in the case of patient outcomes with a definition to each such error (Table-2). A hemolyzed specimen is less problematic against a mismatching sample or with an extended TAT. The patient’s safety will be at stake if a new sample is requested in abnormal hemolysis where a prolonged TAT will be fatal. Further defining the acceptable error rate will give the clinical laboratories a compromising but reasonable goal in respect of quality improvement methods which are to be adopted in health care.

Apart from these, there is also a need for fixing a standard for detection of laboratory errors and strict measures have to taken to analyze the risk inherent in the errors in the clinical laboratories. Nobody can eliminate errors completely in human activities, but they can be reduced if needed. Therefore, adequate techniques should be initiated to prevent errors and its evaluation (Bonini et al., 2002).

Classification of errors in laboratory practice.
Table 2. Classification of errors in laboratory practice.

Aims and Objectives

Development of science and technology has in return facilitated improvements in health care quality monitoring through the implementation of analytical standards. Though the frequency of clinical errors is reduced considerably when compared with that of the past decades, the health care sector is far from satisfactory level. Therefore, to assess the Pre-analytical, Analytical, and Post-analytical errors in the clinical laboratory and how they affect the patient’s quality of care, focusing is to be done on the entire laboratory testing procedures along with the quality improvements that exist in the national health care system.

This is required because the current analytical phases are rampant with errors and this is a great concern for the people. It is estimated that 93% of the errors are originated during diagnosis due to the low quality specimen collection, patient preparation and acquisition. This highlights the necessity to determine appropriate laboratory practices and adoption of stringent measures for their compliance. Since the present laboratory testing methods are not error proof, new accreditation policies have to be designed and suitable strategies have to be planned to improve the safety of the patients. To achieve this research paper focuses on the following aims and objectives (Lippi et al., 2006).


The following are the aims of this research work.

  1. Detection of Pre-Analytical, Analytical and Post-Analytical errors in clinical laboratory,
  2. Utilization of lean principles and six-sigma metrics to analyze and quantify error,
  3. To asses the positive outcomes in terms of quality management


  1. To point out how much safe is it to rely on laboratory tests,
  2. To stress the need to implement a Safety Alert System,
  3. To derive out a Plan for improvement of quality in patient healthcare

In order to find out answers to the research questions and objectives several constituents relating to Health care and the quality control methods which are meant to safeguard the interests of the patients and the general public, are keenly studied and analyzed in this research paper. The effectiveness of such methods is appraised with a critique’s approach by comparing the methods adopted by the different departments under Health care. The study is thus compartmentalized and is given under separate chapters including what is stated in the previous pages. The chapters are:

  1. Introduction: This chapter gives the background of the issue and throws light on the outcome of the research paper.
  2. Literature Review: The entire literature and other data available on the issue are reviewed under this chapter.
  3. Methodology: The application of research methods and the description and reasoning of the research methods applied, including data collection, and the method of its collection etc. are covered under this chapter. A brief analysis of data collection procedure is also given here.
  4. Findings & Discussion: In this chapter discussion is carried out on the findings with regard to the contents of the previous chapters.
  5. Conclusion & Recommendation: This chapter gives an interpretation of the problems and offers solutions to them. Also, it provides a few recommendations to the furtherance of remedial measures to the issues.

Literature Review


The United States of America offers comparatively the best form of quality oriented health care and it is assumed that most of its citizens are satisfied with what they get out of it. But this assumption is far from reality and does not mean that medical care system in the States is error proof. It is because quality of care is now determined in terms of technical perfection and the variations observed in the outcomes is reflecting largely on the performance of the system.

Malpractices or errors in the delivery of care and deteriorating relationship between physician-patient have already tarnished the ‘show’ with the hospital expenses escalating in every phase making the patients weighed down to an alarming length. This situation and its gravity warrant more stringent measures to be adopted in the system in the matters of cost containment and risk management. Times are changing and so are the perceptions, expectations, desires and wants of the people.

A care system that cannot fulfill the requirement of the patients will have to face unending problems and to streamline the process and procedures it needs contributory participation of the constituent elements at every level. That is why the American Association of Retired Persons recommends the inclusion of consumer representatives and patients in the improvement programs for evolving better quality of care in the health sector (Lohr et al., 1988).

Health care is precaution and it reflects in the safety of the patients. When error occurs it denotes the failure of a person or system in executing an action, or committing a wrong action while carrying out the safety task. These failures or errors can occur at any time and in every phase of health care from the stage of diagnosis to that of treatment or during preventive care. Errors that cause injuries to patients are known as preventable adverse events.

They are the outcomes of medical mismanagement, though they are not wholly preventable. To prevent an error, it needs proper designing and adaption of the related health care system in every stage to fulfill the safety. Therefore, developing and executing safety procedures of health care is the best approach to reduce errors. There is no meaning in blaming others when an error occurs for, none can prevent it from happening again. After all, to err is human, as the wise said so, but it is true that such errors can be prevented so that safety can become the first step in providing quality of care (Kohn et al., 2000).

Though much is there to learn about the different kinds of errors that are done in health care, and the patients are more worried than ever about these safety errors. Therefore, it is imperative that a person who wants to remain healthy or a patient who wants to become well is injured by the very care itself. The health care providers must adhere to professional ethics and strive to improve the safety measures with motivation and empathy. The interaction between the constituents of both internal and external environments in the organizations working in the health care sector can invoke many changes to promote patient safety to a great extent.

The external environment elements comprises of access to information, utilization of available tools to enhance safety, leadership qualities inherent in the professionals, governmental regulations and statutory orders regarding the initiatives, and the demand for higher safety measures from the patients and other service purchasers. The in-house or internal factors are efficient leadership for implementing safety, the institutional culture to learn from errors, and a potential and effective safety program for patients. There is the need for a well balanced regulatory that can go on par with the market oriented initiatives. These, however, will not provide an all-problem-answer to the health care issues (Kohn et al., 2000).

Several voluntary organizations like National Patient Safety Foundation, Anesthesia Patient Safety Foundation etc., are now working on to reduce safety errors in the health care sector. A very inquisitive and vigilant analysis of the errors can dig out many things to overcome the errors. To facilitate this, all sorts of adverse events that are causing injuries or deaths must be evaluated in order to assess the feasibility of improvements in delivering an error proof health care. Since health care sector is still behind in ensuring safety and preventable injuries have affected the hospital patients up to 4 percent which calls for immediate tangible steps to improve safety measures. For, unsafe care is the price we give against the unorganized systems of health care that lacks accountability and credibility (Kohn et al., 2000).

Medical errors

The IOM report (Institute of Medicine, November 1999) has defined error as “the failure of a planned action to be completed as intended (an error of execution) or the use of a wrong plan to achieve an aim (an error of planning.)” If the error injures the patient, it is known as an “adverse event.” Here, adverse events are

  1. Overuse,
  2. Underuse, and
  3. Misuse.

When a patient accepts some valueless treatment having potential risks it is called overuse, whereas, underuse occurs when the patient does not accept the required treatment. But misuse is errors that are present in the treatment. It is otherwise called as malpractice by the physicians, in generic (Holder, 2005).

An injury caused by medical management is termed as adverse event, and when the injury is caused by an error in the system it becomes a preventable adverse event. If the care given by the physician is below the specified standard, it comes under legal criteria to be represented as negligent adverse event. There are different kinds of errors. They are:

  • Diagnostic error (inappropriate therapy)
  • Equipment failure
  • Infection (nosocomial and post-operative)
  • Transfusion-related injury
  • Misinterpretation of medical orders
  • System failures that compromise diagnoses (Bertholf, n.d.).

Patient Safety in Clinical Laboratory: An insight into Pre-analytical, Analytical and Post-Analytical errors in clinical laboratory

As per the definition of Institute of Medicine (Kohn et al., 2000), medical error is “a health-care provider chose an inappropriate method of care, or it could also mean the health provider chose the right course of care but carried it out incorrectly. It is the failure to complete a planned action as intended or the use of a wrong plan to achieve an aim’’. Immediately after the declaration, the whole medical community started increasing awareness of the errors in health care sector and has incorporated patient safety as the guiding factor for accreditation.

However, there was no move from them to track and prevent diagnostic errors even though they have paid much attention to medical errors that cause morbidity and mortality of patients. Diagnostic errors are multi-factorial and are classified as system errors, no-fault errors and cognitive errors (Kohn et al., 2000).

Many people hold the view that medical errors are caused by drug misuse and surgery done by inexpert hands. But this is not true. Several other types of medical errors are there like misinterpretation of medical statutory orders and prescriptions, post surgical infections, nosocomial problems, equipment failures and diagnostic errors. Here, diagnostic errors are identified as misinterpretation of the results of the clinical tests, inaction on abnormal results etc. Even though clinicians are interactive with laboratory results often and at a higher level, most of them yield to probabilities of errors in clinical practice (Kohn et al., 2000).

Laboratory errors due to the problems in organizational functions are attributed to other errors in health care and as such, they need corrective steps to improve the management of the ward. Mistakes like misidentification of the patient for blood drawing and wrong drug administration are organizational errors. David Blumenthal, (Blumenthal, 1997) in his report, states: “the quantitatively largest reductions in laboratory error are likely to result from interdepartmental cooperation designed to improve the quality of specimen collection and data dissemination”. The necessity to involve the clinical audit to detect this sort of error for the improvement of clinical error is very important. The laboratories must monitor the adverse incidents also to understand the ways to reduce the risk and to prevent its further occurrences (Bonini et al., 2002).

The laboratory errors have to be reclassified by placing them according to the potential effects on the outcomes of the patients. In critical situations hemolyzed samples may prove less problematic than a prolonged TAT. Baele et al. (1994) have reported that there exists one error in every twenty one blood transfusions. This shows that there is high risk in the blood transfusions that are done at the clinical laboratories. The variation in sensitivity of error exposure method which is purely based on the complaints that are categorized as fortuitous detections and the one related to systematic analysis need to be in conformity with the medical act which has a very high sensitivity (Bonini et al., 2002).

There is also a need to devise the methods to reduce laboratory errors in order to avoid any potential and significant harmful effect on the health of a patient. Though these errors could not be eliminated completely, it could be reduced to a certain level if proper techniques are adopted for preventing errors which hamper the health of the patients. To attain this goal, the safety checks should be extended from the laboratory environment and the activity of the wards should be reorganized (Bonini et al., 2002) & (Preanalytical Cost of Poor Quality Model, n.d.).

Designing training programs with the help of latest technology will reduce errors considerably. The solutions that are placed here can contribute to lightening the problems of laboratory errors and will add quality to the patient care in drug administration and the like (Bonini et al., 2002).

Errors that pertain to patient misidentification are considered as a source of major problems that undermines the principles of healthcare. The European Countries released recently a document issuing specific directions regarding patient identification without considering the limitations of the medical act. Italy also published a document on the same line and it was found very effective in reducing clinical errors.

Therefore, adequate error detection techniques have to be adopted and implemented in the clinical environment with enough provision to quantify and evaluate the effects of such techniques to know whether the remedial measures taken are effective or not. If there is reduction in the number of errors it will indicate that the same is successful only in the case of common errors which will not have any effect on patient’s health. The major errors which are fatal to the patients such as mismatch at the time of blood drawing, blood transfusion or drug administration are rare incidents and as such relying on the statistics of reduction in error numbers alone will bring no satisfying results.

As such the new technique adopted shall be auto controlled for identification of the patients which will facilitate the reduction of errors. Another step to be adopted is the bringing up of a culture that is characterized by risk acknowledgement and injury prevention which are considered as the responsibility of every individual. In this attempt it must be known that generally errors are not at all attributed as personal failures, carelessness or inadequacies. Most of such errors will end up in naming and blaming others in order to fix the responsibilities (Bonini et al., 2002).

Inaccuracies in specimen collection and labeling create grave consequences in patients. To reduce its gravity some health care centers have applied zero tolerance lab specimens labeling. In a clinical laboratory hundreds of specimens are collected and analyzed daily and these need correct patient identification. Lack of proper identification will lead to harming the patients. Many institutions are still not sure about the right method for reducing such errors.

In November 2002, UCLA Clinical Laboratories began a study to find out the frequency of errors that happen in the blood specimens. Using the information gathered from it UCLA lab started collecting information on unlabeled specimens, specimen mismatch and mislabeled specimens for

  1. revamping phlebotomy services,
  2. execution of electronic reporting tool, and
  3. installation of a processing system which is totally automated.

To facilitate this they collected specimen error data from Nov. 2002 to March 2003. This study was then continued from Sept. 1 to Aug. 31, 2005. During the study they found that the ICUs were a major variable as phlebotomy was done by lab personnel as well as nurses. This was followed by a series of other related studies which resulted in the observation of 4.29 million specimens and 2.31 million phlebotomy orders. The 3 main errors they noted were

  1. specimen mismatch
  2. mislabeled specimen
  3. unlabeled specimen.

Their findings are given in Figure-1, Figure-2, and Figure-3 (Wager et al., 2006).


The 3 critical errors namely, mislabeled, requisition or specimen and Mismatch contributed 11.9% of specimen errors of which mislabeled was infrequent. Identification errors are less than 1 in 1000. The delectability of the above errors as mislabeled was low due to the fact that in generic it will not be identified till a clinician questions about it. Thus with the implementation of patient safety interventions the maximum reduction was noticed in this type of error (Wager et al., 2006).

Trend analysis: critical errors by type/month.
Figure-1. “Trend analysis: critical errors by type/month.

Longitudinal data for the 3 critical identification errors by month demonstrates a decrease in errors by trend analysis. The 3 patient safety initiative implementation dates are noted by dotted lines” (Wager et al., 2006).

Total blood draw errors for all error types.
Figure-2 “Total blood draw errors for all error types.

Total blood draw errors are demonstrated by month for the evaluation interval. B, Total blood draw errors for selected error types (September 1, 2003–August 31, 2005). Requisition mismatch errors represent the major identification error in cumulative error data. Mislabeled specimens, the most dangerous identification errors, represent 8.4% of the identification error total” (Wager et al., 2006).

Total blood draw errors by errortype.
Figure-3. “Total blood draw errors by errortype.

Data for all specimen error types that result in unacceptable specimens were tabulated for the entire study period (total errors – 16 632). Critical identification errors are noted by red bars. QNS indicates quantity not sufficient” (Wager et al., 2006).

To assess the pre-analytical errors at laboratories, Bonini et al., (2002) have conducted a series of studies at various laboratories of hospitals. The results of the study carried out at San Raffaele Hospital are enumerated in the Table-3 below.

Types of pre-analytical errors registered during the year 2000 at the Laboratory of San Raffaele Hospital.
Table-3. Types of pre-analytical errors registered during the year 2000 at the Laboratory of San Raffaele Hospital.

The above table shows the number of errors linked with pre-analytical phase, which were detected at the laboratory of during 1 year. This indicates the missing test results which are connected with a particular type of pre-analytical error. It is not the number of samples that are problematic. The variation in the number of in and out patients is noticeable. The total number of errors in 2583850 test results is15503 which is around 0.60% for the inpatients, whereas it is 792 errors in 2032133 results relating to the outpatients which come to 0.039%. The reasons for the deviance are:

  1. There was direct control of clinician in the blood sample drawing in the case of the outpatients against the drawing conducted by the busy hospital ward staff who have less expertise in the job.
  2. The second reason for the variation is the complexity of the examinations and the several blood drawings done on the patients.

The above study revealed that most of the errors have occurred during the pre analytical and post analytical phases, while errors between 13 % and 32% have happened in the analytical stage. A recent systematic clinical laboratory audit disclosed that there is inappropriate use of laboratory tools without meeting the methodological standards. The clinical staff is totally reluctant to admit their errors as such errors will not generate any detectable abnormal results and questions from the users. This is very true in the case of blood transfusion. Baele et al. (1994) have established that there is 1 error in every 21 blood transfusion which amounts to 4.7%.

But other studies have confirmed only 1 error in every 6000 to 12000 transfusions. The reduction in the error number denotes the efficiency of the corrective measures. It is evident that most of the errors happen at the pre-analytical stage and it indicates the necessity for the implementation of a strict error detection methodology for detecting the error and classifying it with the procurement of advanced technologies that reduce the errors (Bonini et al., 2002).

Though there are many heterogeneous elements for laboratory errors, Lippi et al. (2006) have narrowed its definition as, “any defect from ordering tests to reporting results and appropriately interpreting and reacting on these’’, which has already been acknowledged by the International Organization for Standardization. The huge volumes of available at present that deal with the prevalence of laboratory errors carry only unreliable data about the rates of pre-analytical, analytical & post-analytical laboratory errors which actually ranges from 0.1% to 9.3%. The advanced automation and computerization have proved that analytical errors will in no way affect the quality of laboratory testing.

This means the errors are happening in the other phases of the laboratory testing such as pre-analytical or post-analytical stages as the management of laboratory medicines are done at three levels namely, pre-analytical, analytical and post-analytical. The error distributions in the three phases are similar in spite of the fact that there is heterogeneity in the designing, processing and error tracking. Studies done earlier have evidenced that most of the laboratory errors happen in pre-analytical stage due to the lack of non standardization of expertise and protocols. This is because it is not possible to monitor pre-analytical variables like phlebotomy which are not under the control of laboratory.

The percentage of errors that occur in this stage is round 84.5 which are quite alarming. The number and percentage of in and out patients vary each time and it reflects as different rates of 0.60 % against 0.039%, respectively (Lippi et al., 2006).

From the above it can be seen that around 95.2% of the medical errors are accountable to the non-laboratory professionals and that most of this pre-analytical errors are closely connected with sample collection. The pre-analytical errors in this regard consist of hemolyzed specimens (54%), insufficient specimens (21%), and incorrect specimens (13%) and clotted specimens (5%), and in vitro hemolysis the reason for the difference is due to the damage caused to the vascular cells during phlebotomy.

The error in this category ranges from 1:2000 in patients and 1: 33-50 in laboratory results. Apart from these, physical variables of the patients including exercise, positional effects, food and stress, undetectable hemolysis, continued tourniquet stasis while drawing blood etc., which cannot be monitored by the laboratory staff are also sources of pre-analytical errors. The variations in the plasma level during physical exercises will influence the biochemical variables causing fluctuation in the level of the specimen collected for testing at the pre-analytical phase (Table-4), which in turn will contribute additional analytical errors to the system (Lippi et al., 2006).

Synopsis of the interference of some lesser identifiable Pre-analytical variables on laboratory testing.
Table-4. Synopsis of the interference of some lesser identifiable Pre-analytical variables on laboratory testing.

It is now generally accepted that alterations in the laboratory testing based on inaccurate use of pre-analytical protocols will only mislead, bringing in errors to harm quality health care. Since the testing errors happen prior to analytical process there is chance that they may affect the other wings of the system such as clinical biochemistry, coagulation, molecular biology etc. In order to conduct studies on DNA microarray technology and spectrometry large number of specimens are required and in such a situation what would be the outcome if the sample collection itself becomes defective.

The genotypic errors caused at the laboratory level can lead to wrong identification of the parentage of the offspring which will result in grave medical, social and legal consequences. Therefore, prior to the application of molecular biology techniques in laboratories the clinicians must have deep knowledge about these problems. Though these professionals working in the laboratories are accustomed to higher level quality the recipients of the test result will keep some doubts about the accuracy of the result. They may attribute the probability of error in the test result to a Trojan horse (Figure-4), which they do in lieu of their long clinical experience practice (Lippi et al., 2006).

Matlow & Berte (2004), while discussing about clinical laboratory errors in blood drawing, define specimen collection as a process by which a proper specimen is taken from the right person at the exact time fixed for such collection. According to them, prior to the collection of specimens, care must be given to disinfect the skin without which the blood culture may produce false results. A recent survey has proved that even the patient identification tool called wrist bands were missing while drawing the blood for culture. The decentralized specimen collection and delivery of it at various nursing stations influence the specimen’s quality very badly.

The volume of specimen decides the future of many tests as the microbial quantity in the blood cultures is in proportion to the quantity of blood cultured. If enough blood is not cultured the result will be false negative and it will affect the antibiotic management adversely (Matlow & Berte, 2004).

Laboratory Testing-A Trojan Horse.
Figure-4. Laboratory Testing-A Trojan Horse.

Specimen collection errors

In the laboratory tests for monitoring glucose in the blood and cardiac isoenzymes sampling time has prime importance. If a patient is discharged immediately after delivery, her new born will miss the metabolic screening which is due within 24 hours after its birth. Specimen transportation is equally important like specimen collection. Improper storage of specimens after post collection and transporting the specimen before testing can affect the quality of the specimens and the test results. In order to get maximum yield, aspirated content for anaerobic culture must be transported within 3 hours from the moment of collection, in anaerobic environment. Likewise, biopsy materials should be sent to the laboratory within 30 minutes in a sterile container and kept in room temperature till it is processed (Matlow & Berte, 2004).

Sources of Analytical Errors in Test methods

The analytical stage starts from the preparation of the specimen for testing and closes when result is verified to report. In the laboratory handling of pipettes, tubes and utensils containing specimens can create some errors like carry over or interaction sample. Amplification technique can lead to contamination to bring false positive results. Non extraction and chromatography before doing Compound S radioimmunoassay can provide only misdiagnosis in a baby suffering from congenital adrenal hyperplasia and ambiguous genitalia.

Substances which interact with performance of assay can influence the result of the tests as in the cases of Heterophile and fibrin clots. In a clinical laboratory diagnostic tests need performance specifications like test accuracy, precision, sensitivity, linearity and specificity. In a study conducted to find out the comparability elements in allergen-specific, the results obtained from different laboratories were void of precision and accuracy causing wrong diagnosis of allergy in patients.

Cytopathology is prone to interpretative errors because of the diagnostician’s subjectivity. Exfoliative respiratory cytology and aspiration biopsy are the usual procedure to diagnose lung cancer. The CLIA 1988 report revealed that the discrepancy in the results of cytology and histology can affect the patient care. Every failure to see the discrepancies will cover up every significant error (Matlow & Berte, 2004).

Point-of-care testing (POCT) is an important tool in the segment of clinical lab testing scenario. It has high potential and is apt to eliminate problems in specimen testing, transportation and distribution. The speed it has in creating results develops more errors and there are concerns about the quality of the results too (Plebani, 2009). As per the CLSI Draft Document (Bertholf, 2007), the clinical specimens are to be collected as per the instructions of the manufacturer abiding clinical laboratory ethics. The specimens for the method should be tested forthwith to avoid any drop in quality and transported using the specific transport system meant for collection and handling.

For quantitative tests, the procedure for random and systematic errors should be taken into consideration. The precision studies must be supported by imprecision estimate near the cut off at analyte concentrations. For the evaluation of precision, test specimen with analyte concentration should be used. The variables that affect the precision near the cut off must be according to the candidate method. The sources may have different samples or conditions under different temperatures and set up, and the replicates should be designed considering the sources of variables (Bertholf, 2007). Clinical laboratories are attentive to quality control methods and programs associated with analytical testing.

But the recent surveys reveal that errors ranging from 46 to 68.2% happen usually at the pre-analytical level, and 18.5 to 47% in the post-analytical phase. The International Organization for Standardization has suggested that there should be an advanced approach to quality focusing on the welfare and satisfaction of the patients while bringing the errors at the minimum in pre analytical and post analytical stages of laboratory services (Plebani, 2006).

By accelerating the turn around time (TAT) the clinicians could improve much on the laboratory tests. Currently, they consider TATs as the duration between the collection of the specimen and the arrival of the result. Therefore, TAT should be redefined as the time starting from the receipt of order for the test till the result is made available to the care giver. To cope with the improvements, a flow chart of testing process should be displayed to initiate understanding about the work done in the laboratory. By this way the processing can be investigated to find out a better method for improvement by reducing errors (Howanitz, 2005).

The clinicians now days are provided with laboratory information in the form of graphics which contains hidden data about pre-analytical errors reducing the quality of the process of testing. This apparently accelerates the health care costs due to the unwanted and avoidable usage of laboratory environment, and will become harmful for the patients and can go to the extreme of undermining the very concept of laboratory testing. The latest statistics reveals that the lab expenses at a hospital is 4% of the total hospital care to be borne by a patient in UK, while it is 5.2% in Australia and 7 to 10% in Canada. In the United States of America the laboratory expenditure of a patient is 5%.

The situation, therefore, requires that more improvements in the collection of specimens at the laboratories are to be initiated and that there should be result oriented health cost reduction procedures at all stages of health care. It is estimated that the clinicians are responsible for testing errors and that the excess budget burdened due to them is 26.9% considering the common 31 tests done at a laboratory. The total percentage of such biological variation in these 31 tests amounts to 7.9% (Lippi et al., 2006).

Analytical interference

Since most of the testing errors at the laboratory occur for the inpatients without having any monitoring of the laboratory staff can make it possible to reduce the pre-analytical complexities. Technologies improve in the course of time and this is applicable in the case of biochemical testing too. The present diagnostic style in vitro will change and new electro-analytical devices like infrared fluorescence spectroscopy, in situ microscopes, optical biosensors etc., will take form by virtue of the new sensing technologies.

Optical sensors can provide non-invasive and nondestructive multianalyte-monitoring to cope with situations that demands simultaneous diagnostic processes. The development of implantable chemical sensors can do excellent job in real time monitoring of clinical species like PO2, pH, lactate and glucose. Commercially these optical detection devices are not developed fully but the glucose sensors that are viable for transdermal and microdialysis technique are in the making to reduce many of the laboratory errors.

In fact, there is an urgent need to develop a standard technique suitable for the detection, classification, and laboratory error reporting. Along with this strict compliance should be insisted in the accreditation standards and the collection and storage of laboratory samples. The extra analytical indicators used for pre-analytical stage must have a tool to compare the laboratory performance of the individual that improves the quality of the laboratory system. Such a tool can be useful as functional device for the quantitative quality measurement (Lippi et al., 2006).

As stated in the previous paragraphs errors can creep in at any stage of the health care system such as pre-analytical, analytical and post analytical activities. Reviews on laboratory oriented errors have unequivocally established that pre-analytical errors are dominating at the rate of 31.6% -75%, whereas analytical errors contribute at the rate of 13.3% to 31.6% only. Post analytical errors are at minimum level with an approximate percentage of 9 to 30.8. The report stated that the reviews on 8 transfusions of blood error cases have confirmed misidentification of patients during specimen collection where the laboratory staff was not involved.

Therefore, reduction of errors in the pre-analytical stage can occur only if there is harmony in designing the procedures for identification of the patients, collection, labeling and transportation of specimens. Moreover, result oriented training should be imparted to the personnel at all levels of health care to make them competent to do their job without any flaws (Matlow & Berte, 2004).

Sources of post-analytical error

The interpretation part of laboratory results is directly related to the probabilities depending on the gravity of the error present in the concerned analytical method. If a convenient probability is assigned to the result by merging the error distribution having the true value with that of a healthy population being the reference. Bayesian statistics allows the improvement of the available information considering it a single probability (Krause et al., n.d.).

Interpretation and therapeutic conclusion are made when the test results are passed on to the clinicians in the post-analytical phase. The unethical and inappropriate use of the test result can lead to severe consequences. To evidence this Matlow & Berte (2004) elaborates the incident pertaining to three patients who were misdiagnosed for HIV where HIV-1 plasma viral tests have been used for the diagnostic test which yielded wrong positive results. Test results which are reported without showing any reference ranges and advises for extended therapeutic may bring wrong judgments. Manual reporting will have transcription flaws while telephoned results become inaudible with noise impediments. Thus crucial results may get overlooked (Matlow & Berte, 2004).

Reduction of analytical errors in laboratories can occur by virtue of

  1. the training imparted to the laboratory testing staff
  2. the directives regarding allowable errors and quality control procedures
  3. the internal comparison of test results, and
  4. the quality assessment by outside elements.

As in the case of pre-analytical errors, post analytical errors are reduced by using the designs and procedures that notify the results in a timely manner, entry of test results in the records of the intended patient, and the correct diagnosis by the clinician using the appropriate test results. In nutshell, the procedures for reducing laboratory errors during the testing process are achieved by the involvement of stakeholders at all levels of patient care (Matlow & Berte, 2004).

The medical errors can originate either from the physician’s wrong judgment or from system errors at the care delivery end, and sometimes such errors happen due to the presence of both the elements. Reporting of medical error is a sensitive issue among the professionals, health care system and the patients. It is always shrouded in mysteries and because of that actual error rectification becomes remote. Individual errors can happen due to lack of knowledge or skill in a physician, but system errors are directly responsible to the flaws that exist in the medical practice. Reporting of system errors is a matter of importance when compared with the disclosure of errors of an individual.

It is because the root cause analysis will reveal information which in turn creates a fault tolerant system. In many cases the physicians shun reporting of errors as they fear that their reputation may be tarnished in front of peers.

Hence, error reporting to the peers shall be accepted as the basis of an effective error reduction program (Murphy et al., 2007). In the medical care system, event reporting also has an important role in promoting quality to patient care, by disclosing malpractices and other errors in the system. In fact, event reporting is intended to collect information about sensitive health care incidents to give insight into the medical errors to accelerate mistake-proofing. The events will be prioritized then to initiate immediate action considering the consequences. The knowledge about a failure or an error will invoke action for investigation towards a root cause analysis (Grout, 2007).

Legal consequences of Laboratory errors

The non adherence to the acceptable norms and directives by a laboratory professional will cause errors leading to injuries to patients. As such laboratory staff is liable for violation of medical practices. Nevertheless, it is the duty of the patient to prove that there is cognizable act of negligence on the part of the laboratory technician. An act of negligence usually arises when neither the admitting clerk nor the phlebotomist would pay any keen attention to identify the patient at the time of specimen collection, without which the actual laboratory information cannot be recorded (Sazama, 2005).

The errors lie through out the work flow path (Table-5), starting from the pre-analytical phase which includes test order errors, wrong patient identification and sample collection etc. Then comes the analytical part where exist testing of wrong specimens, recording results without actually conducting the testing, recording the test results for the wrong patient, incorrect identifying of tissues, slides etc., and the equipment failures such as QC failures, untrained and insufficient staff etc. In the post-analytic stage, there may be erroneous test result interpretation, improper and wayward reporting, incoherent data etc.

The complete solutions to these errors rest in: immediate shift to automation, simplifying process and procedures, improving communication and information systems, and promoting quality performance. In addition to these, modern laboratory set up should be subjected to auditing of performance at all levels of the work flow and the management system. The difference in the input and output of the performances will provide the resources for improvements without invoking legal complications (Sazama, 2005) & (Hoeltge, n.d.).

Structure for a Quality system.
Table-5. Structure for a Quality system.

To defend a law suit against health care errors or negligence the professionals should be equipped with a fair knowledge about the standards and regulations of the system to which they are part and parcel. They must prove compliance to these standards and regulations scrupulously. It is true that humans will err as much as 1: 350 times while doing a task, same and again. As such: ‘It is not the fact that errors will happen that dictate whether legal action will ensue.

It is, rather, how the laboratory responds to such errors that will predictably influence both whether a suit will be filed and, in many instances, what the outcome will be. When errors occur, having a routine method of documenting the error, prompt follow-up to minimize harm, and appropriate interactions with patients to ensure them of an open disclosure and acceptance of responsibility for any injury sustained, will provide the strongest possible defense’ (Sazama, 2005).

Utilization of Lean principles and six-sigma metrics to analyze and quantify error in clinical laboratory

The Lean Lab

The word ‘Lean’ means ‘to eliminate waste’. Health care adopted this word from the manufacturing sector. The manufacturers and the industrial professionals apply this word to indicate removal of wasted materials, rejection of defective products, over misuse of space, unwanted fruitless activities etc. The word lean can be used to mean process optimization or method of improving the system through workflow analysis. Waste originates due to error and the error causes unintended waste of time and effort. As such the application of lean principles can reduce the possibilities of errors that come up in the health care.

An error in this system implicates wasted money and more than that is the patient’s life left to risk. Hospitals need the best and speedy treatment for the patient at the least cost, where least cost denotes proper utilization of the resources available by reducing the inconvenience to the patients to minimal in the matter of delay in treatment, pain relief, diagnostic testing , and the removal of confinement of the patient from the social environment (Doris, 2007).

The Lean concept is built on quality which uses fewer resources. It looks forward to waste minimization at all stages of the system. It recognizes overproduction like unwanted testing and use of tools in the laboratory, and restricts unwanted transportation of specimens, equipments etc (Stankovi, 2008). Lean identifies and eliminates waste by making continuous improvements through systematic approach. Lean Lab in a clinical laboratory is based on the Lean concepts to know what is required for the patients, physicians and other customers. It aims at:

  • Safety improvement
  • Increasing flexibility to respond to the needs of patient, physician & other customers
  • Eliminating wasted motion, space & supplies, and less used equipments
  • Creating consistent flow of test & specimen preparation
  • Maximizing the responsibilities of the staff
  • Expanding capacity by reducing costs & shortening the cycle time between ascension and analysis
  • Positioning everything in proper order and in its place (Connors et al., n.d.)

The Lean methods can be integrated appropriately into the health care delivery model by addressing the primary areas of the clinical laboratories. The 7S system creates the transformation of a given system to Lean Lab which has structure, safety, cleanliness, orderliness, security, pleasantness and efficiency. These are the 7 pillars of Lean Lab known as 7S Pillars that brings in 7 results for the development of the whole organizational set up of a system. The 7S Pillars are identified as: Sort, Straighten, Shine, Standardize, Sustain, Safety and Security (Connors et al., n.d.)

Sort – It removes every unwanted thing from the lab whether it is specimen or test procedures. This is called Red tag which identifies all items that are not needed or wrongly placed. These tagged objects will be placed in another area for evaluation and immediate disposal.

Straighten – Things are placed on the basis of availability, usage, access and return, proximity of the work that is done. Location indicators like labels, arrows and outlines, signboards are applied to locate the tools.

Shine – Complete cleanliness in the work place is insisted here. The procedure will provide service quality reduced tool break downs.

Standardize – It maintains the first 3S guidelines and applies team responsibilities

Sustain – Everybody is supposed to do housekeeping and is responsible for the execution of the first 4S in their particular lab area.

Safety – The employees have to adhere to safety measures and policies deigned for the system.

Security- Insists on limited access to lab area. This will ensure privacy of the patient and record keeping. It will reduce the risks considerably.

Visual Workplace: It provides timely information by providing visual controls. The displayed signs contain performance measures, aims, location of tools and materials, status of commitments, warnings of safety hazards etc.

Facility Layout and Flow

Lean Lab develops a balanced and consistent flow of efficiency through the organizing processes to achieve the goal of a value stream. It is the value laden and non value laden activities needed within the delivery model which has potential to provide the specific care needed by the patients. Conventional improvement methods call for value oriented work. But in Lean Lab, the value stream focuses on the reduction and elimination of the valueless work in the health care system. Implementation of a Lean Lab will definitely increase the satisfaction of the patients and physicians. It will also enhance the moral and morale of the staff; and improve the costs, speed, safety and quality of the work place (Connors, n.d.).

Lab Simulation: Case study of modeling

The laboratory of Port Huron Hospital (PHH) working along with Akros, Inc., was preparing to adapt itself to the lean environment for increasing test quality and reducing TATs and maintenance costs. The lab also wanted to buy new chemistry analyzers so as to replace the worn out equipments. It was assumed that the complexities linked with lean implementation and investment would be compounded by the more variable laboratory operations. The lab faced problems like specimen arrivals, test mixes, and staff monitored activities. Considering these factors the hospital management decided to combine lean based simulation model to combat the variables, flow changes, and capacity utility constraints.

The simulation model was adaptable to the process of analyzer purchasing by quantifying the benefits relating all options. The aim was to develop a system that improves within the lab on the lean concepts so that testing, analyzing and refining could be managed with the help of simulation model. By using this model, process flows could be analyzed, rejecting the elements that are posing challenges. Moreover, with its help the reporting staff could be managed and utilization of equipments and tools could be monitored quantifying the difference between the options for analyzer purchasing (Connors, n.d.).

Defining the Problem

The first step adopted in the simulation model was defining the objectives to be achieved and metrics needed for materializing them. The Port Huron Hospital wanted a tool to decipher, assess and refine the existing operations and required guidance to modify the system to meet the future needs such as purchase of new analyzers or redesigning the layout. However, they wanted it to be very flexible to accommodate multiple scenarios that demanded no rework to cope with the stringent project timeframe. The model should ultimately track the factors like capacity continual, utilization and monitoring of staff and equipments, fixing and regulating TATs, layout, sorting of bottlenecks etc. Accordingly, based on the definition of the general objectives, the specific lab components, processes and procedures were identified and documented to represent the model.

After gathering the required information from the lab staff, the specimen processing and the related core areas were focused for initiating the model. The specimen dealing area was marked to receive specimens, registering, and ordering tests and labeling. The major tasks involved in this area were registering the specimen, ordering tests, centrifuging and labeling the specimens while serving as the gateway to the lab. The main parts of the core lab were hematology, chemistry, coagulation, immune-chemistry, and urinary (Connors, n.d.).

After defining and confirming the scope and relevance of the new model, the details of the way by which each part of the project area and specimen types interacted with each other during the processing of testing the specimens were gathered. These details were collected by charting and tracking the path of the specimen types variedly along the lab. The resultant flow charts were meant for communication and verification of the lab processes throughout and across the new lean team as it would further serve as a guide in data collection and new model building activities (Connors, n.d.).

Six Sigma Metrics

The Six Sigma was introduced by the Motorola Corporation in the beginning of the 1980s to enhance the reliability of their products (Kraemer, 2003). It is a quality management tool used in all areas of business and industry at present. The Six Sigma strategy has the potential to measure deviation of an organization from its goal and objectives. The sigma value points out how many times an error has the tendency to occur.

If the value is higher it means the errors are in the increase. It is an acceptable measurement of quality and performance of all kinds of processes which is attributed on the Sigma scale. The sigma level can be achieved by dividing the permissible tolerance towards the process by doubling the process of SD, i.e., Sigma=Total process tolerance or 2xprocess SD, where SD stands for standard deviation (See Figure-5). In clinical labs the calculation will be Sigma= Tea-bias/CV, where CV is the coefficient value of the variation and Tea is total number of permissible errors.

The best result will be when the Six Sigma fits in the process. The higher level of Six Sigma in the process will not allow more than 3.4 errors per million tests or products, and that too with 1.5 SD. The clinical laboratories use this tool in the analytical phase of the process of testing. In this particular case, the medical loop of the process is consisted of five phases. They are

  1. pre-pre-analytical
  2. pre-analytical
  3. analytical
  4. post- analytical, and
  5. post-post-post-analytical (Coskun, n.d.).

In certain institutions like clinical laboratories where reporting of the patient’s result is required within the prescribed time after interacting with the physician, quality is not the only criteria to decide upon the quality in performance. Therefore, in clinical laboratories Lean concept is combined with Six Sigma to derive the best out of them. Generally, Sigma is quality oriented, whereas, Lean is known as the synonym of speed. The four keys related to the Lean Six Sigma are:

  1. make the patients happy with quality and speed,
  2. enhance the methods and the processes,
  3. be in harmony while doing a job to gain more from it, and
  4. be equipped with facts and figures.

It has been found that clinical laboratories that used Lean Six Sigma in quality management have achieved reduction in errors and contributed very much to patients’ safety than others in the health care sector (Coskun, n.d.).

Concept of six sigma process capability

The quality indicator related to a laboratory is presented in the form of percentage of variance which can go wrong and misleading. Quality assurance programs are not improving the testing standard and processes, as envisaged. The manufacturers of various products that are needed in our daily life use the systems of quality and standard such as ISO 9000 to improve production in cost effective ways. In order to understand the in-house information almost all organizations use the Standard Six Sigma Benchmarking Chart. It gives the number of flaws or defects or adverse events after normalizing it to ppm against sigma. The sigma counts the degree of deviation from its goal.

Irrespective of complexities, every product gets quality 4Sigma, whereas the best product will have only 6 Sigma. If the value indicates the frequency of defects which can happen, then the higher sigma value will show a system-process to have only fewer defects. The Six Sigma reveals the bond between the numbers that relate to the defects of the products developed by the organization, the operation cost drain with respect to the products, and the level of satisfaction achieved by the customers. Thus, if sigma goes up, reliability of the process will also go up, while the maintenance costs or operation costs will come down, whereby, the satisfaction of the customer will reach the maximum level (Nevalainen et al., 2000).

Quality Management System and its implementation in reducing clinical errors

The development of technologies has created unprecedented rise in health care costs which compels the institutions to restructure the organizational set up to maximize quality and efficiency. The increasing number of medical errors and quality erosion in giving service has put the entire system in a dilemma stressing the need to find out a feasible potential solution to the problems. The importance of POCT as a quality management system tool is something distinguishable as it delivers real time answers to the physicians to take decisions on preliminary assessment, diagnosis, and effective treatment to the patients.

Since quality and efficiency are the two elements required to decrease injuries and deaths caused by negligence in the form of failure to use rescue provisions, failure to diagnose and treat in time etc. In addition to making the improvements in the efficiency profile of the institutions the POCT offers social benefits too by invoking the system tools and initiating the professionals to support timely interventions and consultations like HIV screening and if used appropriately it will reduce the chances of litigations and its ensuing liabilities. The rise in testing frequencies at care points, is somewhat affecting the quality of bedside assessment of the health condition of the patient. This sort of challenges facing POCT programs are within the concept of its methodologies ranging from small precision instruments to large table top models which can be placed near the point of care (Wyer et al., 2009).

Patient safety is totally above risk-management and PR problems. It is concerned with the finances of 50% of US Hospitals running with 3 per cent profit margin which underlies the necessity of involving care management in the sector. It is quite true even after investing huge amounts of money in the IT sector and system of electronic medical records; quality management is still at large. There exists some kind of ‘analytic gap’ clinical care is unaware of which is the reason of mismanagement and occurrence of medical errors. Care management is a mix of clinical problem discovery, assessment of available data, benchmarking, and troubleshooting tools.

It brings the clinical staff and physicians, nurses and pharmacists, and other related care givers under one roof for a detailed appraisal of processes and procedures, costs and the patient outcomes. The aim of the system is to develop unique models of care to generate top quality clinical outcomes and maximum patient satisfaction by providing quality of life. Recently, CareScience which is located in Philadelphia, in collaboration with the University of Pennsylvania has implemented a model of Care Management stem that produced a higher order automated data analysis cost and time saving system.

It identified all problems relating to the congestive heart failures and considerably reduced the time spent by the doctors in reviewing charts to identify the real causes of the complications present in the patients. Management of care needs correct data on clinical costs and the outcomes. Low investment in IT is a hurdle in calculating cost benefits from the clinical performance (Coile, 2001). Mark Leavitt of Medscape has stated that healthcare institutions spend only 3.9 percent on IT whereas, the banking sector provides above 10 percent of the yearly budget (Tedeschi, 2000).

It is observed that 35 percent of medical errors happen at the time of administration of medicine. To face this challenge the hospitals now use mobile computing on par with radio frequency networks for implementing POC devices and barcodes to identify the right person for the right drug before its administration (Coile, 2001).

In order to promote quality, the Leapfrog Group supported by IBM and General Motors requested the 20 million employees including the retirees to avail only the services of hospitals that have improved patient safety initiatives (Freudenheim, 2000). The Institute for Healthcare Improvement based at Boston has been maintaining quality improvement system for the last 20 years. Their latest report titled “Reducing Medical Errors and Improving Patient Safety: Success Stories from the Front Lines of Medicine” gives an insight about the progress made in this field (Haglund, 2000).

Other Observations on Quality Management

Quality management begins from the moment the test is ordered and ends with the interpretation of results done by the clinical staff to eliminate the errors if any that might have crept in during the processing stages. Therefore, it is essential that improvements on phlebotomy practices along with the transportation of samples are pre-requisite conditions for placing the laboratory within the quality range (Chawla, 2009). The statistical basics explaining the quality of products were designed in clinical chemistry laboratory 50 years ago which heralded the quality management initiatives in health care. The essentials for a quality system identified were:

  1. Organization
  2. Personnel
  3. Equipment
  4. Inventory
  5. Process Control
  6. Documents or Records
  7. Occurrence Management
  8. Internal Assessment
  9. Process Improvement
  10. Service and Satisfaction (Haara, n.d.)

Health care consists of production processes as in the case of industries. Concepts of quality, satisfaction of the customers and staff, safety and cost efficiency etc. are not at all the monopoly of the industrial sector but they are also the governing principles of health care. Since the making of a product means undergoing several processes, a slight flaw will become fatal to its quality. If so, what will be the quality of health care when there are 10,000 medical errors each year at VMH, and what will happen if that quality is dropped by 5%? (Furman, n.d.).

Quality management systemic approach is required for testing in vitro diagnoses as it is suitable for several tools and settings. It will support the device manufacturers, monitoring and accreditation agencies, and laboratory directors to ensure quality in result, and has accountability so that it can suggest partnership between the end users and manufacturers. Moreover, it can provide failure source matrix and propose different methods to identifying problems towards quality monitoring (Krower et al., 2009).


Introduction to Methodology

There are several sources available over the Internet about research methods that are applicable to academic studies of this nature. The Economic and Social Research Council (ESRC) defines research methods as follows:

Research is the application of systematic techniques and methods in pursuit of answers to questions. These questions and answers can be highly specific, or abstract and general, depending on the type of research being undertaken, from basic to applied ones (ESRC-Research Methods, 2007) & (ESRC- Qualitative Methods, 2007)

Therefore, this research project about “Medical Laboratory Error and Its Impact on Quality of Care” is identified as a quantitative research study. But, Davison and Vogel state that research philosophy is a conviction about the manner in which data should be collected, examined and applied. It involves the compilation and examination of information based on its quality and not quantity. They use un-constructed logic to unscramble the significance of research (Davison & Vogel, 2006).

The present research approach is typically designed to improve the health care quality management, and therefore this study is completely statistical. Also, to get the desired results clinical trial study is also adopted on par with the observational study.

Research Methodology

Information for the conduct of this study was retrieved chiefly from books, journals, governmental agencies, Power point presentations of different study groups etc. Health care guidelines and policy documents and recommendations were also collected and reviewed. Internet sites such as National Electronic Library for Health Guideline Finder, Medline, Cochrane Library, Wiley inter-science, Ovid etc., were visited for study materials to address the research questions.

The primary data, collected thus, was put to analysis and an extensive research was undertaken to gain a comprehensive understanding about Medical laboratory errors and their Impact on quality of care in general. It identified the need to improve the quality of health care by adopting new management strategies to evolve patient satisfaction.

Research Design

A comparative and cross-sectional design is used to enable a collection and comparison of data. Quantitative data related to a few variables were used to detect patterns that answered the research questions.


Medical errors in health care cause death to patients and the liabilities to United States government are 17-29 billion dollars each year. If we compare medical error deaths and other deaths such as automobile accidents, breast cancer and AIDS, the result will be alarming. An average number of medical error deaths every year is 43000 (Figure-6) which is high above the other category pre-stated (Doris, 2007).

Deaths due to medical errors in the US.
Figure 6: Deaths due to medical errors in the US. IOM report To Err is Human: Building a Safer Health System, National Academy Press, 2000

Most of the above errors are accountable to process and systemic problems in the health care. To improve the situation, the sector must seek innovations and face its customers with time framed delivery of quality products that can be reliable and cost effective. To support the sector there are several quality management tools like Lean and Six Sigma which have potential to identify the problems thwarting quality environment (Figure-7).

A simple approach to Lean implementation showing how different levels of management are impacted. 
Figure7: A simple approach to Lean implementation showing how different levels of management are impacted. 

Six Sigma: It means 3.4 defects/million chances with a yield of 99.9997%. It is an efficient tool designed for consistent improvements in an organization by eliminating variations in all sections of operational areas.

Lean: It is similar to Six Sigma and aims at improving the process of work flow by eliminating waste so as to deliver quality and value to the customers within a positive time frame. Here value is calculated from perspective of the customer and is considered as an activity that transforms the profile of the entire organization to the needs of the customer. Non-value-added-activities are something to which the customers will not pay. In Lean these non-value-added-activities are simply waste, whereas, for Six Sigma, the waste is the variation in the efficiency level and that is the enemy of the organization which has to be eliminated. These wastes can be identified as:

  1. Over production – producing more than what was requested,
  2. Waiting – time wasted when raw material is sitting, with no value being added,
  3. Transportation – time wasted moving the raw material through the process,
  4. Inventory – wasted direct or indirect costs of excess inventories of supplies, reagents and disposables or of non-productive items,
  5. Processing – cost of unnecessary or wasteful processing,
  6. Motion – cost of unnecessary or inefficient motion during processing,
  7. Defects – cost or rework and actual defects as well as the associated costs of losing customers,
  8. Intellectual capital – cost of wasted talent or unneeded labor” (Doris, 2007).

The hospitals can work again on a customer’s order or replace the defective order with a flawless new one. Adequate fresh inventories can be purchased if the existing ones are outdated, worn out or non-productive. If proper inventory levels are not well maintained it would count to more space. But the misplaced talent or the time lost due to flaws, idling, bad quality etc. cannot be replaced (Doris, 2007).


Developments in science and technology have paved the way to transform every sphere of human activities, and health care had its share of advancements within no time. The innovations became progressive and they started reflecting in the extensive fields of health care. Thus, along with its counterparts, clinical laboratories have also acquired the best of these technologies and put them into use in the testing methods. The transformation from the manual operations to more complex and sophisticated processes and procedures has become the hall mark of the clinical care. And these methods, though they have the merits like speed and convenience, have become synonyms of errors and malpractices. Accuracy is placed in shadow by the mounting misidentification and mislabeling errors.

The results are misinterpreted and reporting lacked correctness. Evidences reveal that accountability and reliability is still at large in clinical laboratories. Errors are abundant in pre-analytical, analytical and post-analytical phases. These errors are at times become fatal to patients and it tarnishes the whole profile of the system. Several studies conducted so far after the much talked about report of Committee on Quality of Health Care in America, in 1999 have proved that the errors are putting big holes in the government exchequer. The liabilities burdened upon the government and care sector are that much (Chawla et al., 2009).

After analyzing this problem deeply and to overcome the situation the IOM, in the year 1988, constituted a committee on Quality of Health Care in America. The main objective of the committee was to prepare a report to facilitate designing a practical, feasible and productive strategy that would improve the quality of the health care by placing the errors at a minimal level within a span of ten years from the date of its constitution.

The report thus prepared addressed many problems of patients’ safety and laid out guidelines to reduce the errors in the heath care. The committee viewed that there is still much to be known about the numerous errors and the reason for their occurrence. The committee further observed that a person weather he is sick or is in need of remaining healthy should not have a chance to be concerned about the injury the health care system will inflict on him or her. This report acted as a stringent guideline for the revamping of the health care to give maximum safety to the patients (Kohn et al., 2000).

The diagnosis in the present times is highly dependent on data provided by laboratories. As such there is a need to have these data more reliable and accurate. There should be credibility and accountability in the testing procedures without which the very purpose will be jeopardized. The progress made in automation of laboratory processes such as sample collection, transportation, reporting etc, have improved the performance of the labs but to achieve hundred percent accuracy the system has to acquire more enhanced techniques and methods at the management and execution levels. The errors that germinate in pre-analytical, analytical and post-analytical phases should be identified and classified to learn to rectify.

It is known that the pre and post analytical stages are responsible for 93% of the total errors. Such errors exist as inappropriate testing, irregular and improper collection of samples, delays in transportation of specimens, faulty requisitions and the like. Though these errors occur outside the scope of clinical labs the credibility of it is at stake. The lab is held responsible against them and is challenged with flawed reporting (Chawla et al., 2009).

To tackle these problems the IOM has recommended the following:

  1. To establish a national forum to establish leadership, research and tools along with necessary protocols to improve the awareness about safety;
  2. To identify the errors and learning from them towards rectification
  3. To raise the standards for the improvements in safety methods
  4. To create safety systems through safe practices at the end level or at the deliver level.

The committee further opined that till date, the preventable injuries caused to patients from care account to 4 percent when compared to the injuries caused to hospital patients (Kohn et al., 2000).

Typical instances of the lab errors originate due to the organizational problems like patient identification before the drawing of blood or administering medicines to them and recording of the data in the patient’s chart. Therefore, maximum quantitative reductions in lab error will originate only from the interactive mode among the different disciplines or departments in the health care institution. Ultimately, this organizational set up is totally responsible for the improvement of quality in collection of the specimens and dissemination of data. In this connection to alleviate errors first of all classification of such errors has to be done to know the potential impacts on the outcomes of the patients.

For example, a hemolyzed specimen may not be a problem creator, but an abnormal hemolysis that rejects analysis can become problematic requiring another new sample. Naturally it will prolong the TAT which would be affordable due to the time constraint making it fatal to critical patients. Therefore, error detection and reporting tool is required for an accurate analysis of the risky errors. Baele et al. (1994)’s report which was discussed earlier in this paper has established that there is a chance of one error in every 21 transactions which amounts to 4.7% (Lippi et al., 2006).

The incorrect tests done on the patient samples, misidentification of patients, mistreatment provided to patients etc., are all malpractices or errors that need alleviation. For, health care is critical about changes and is reluctant to changes. In spite of these it fits in the domain of Lean philosophy to grab the changes consistently to identify Kaizen chances. By stepping into Lean, patient care can be improved, whereby the occurrence of errors will be reduced to a considerably. The principle of elimination of waste itself ensures simplifying every step of its processes and contributes the maximum usage of the resources-the potential of the organization including the working personnel (Lippi et al., 2006).


The analysis of medical errors has generated continuous discussions and studies all over about the necessity to prioritize patient safety while providing health care. Mistakes and errors creep in when a system works more. The present scenario of health care is confronted with more functions and it is natural that errors will accompany each task. The healthcare providers are therefore, inclined to improve the processes and streamline the organizational set up to a speedy but accurate delivery of care to the patients. While leaning to Lean and Six Sigma, maximum effort should be given to

  1. increase safety to the patients as well as the working personnel,
  2. increase the overall quality of the treatment so that the patients will get immediate relief,
  3. To reduce the waiting time for getting the product or result or care, and
  4. to increase productivity observing the good parts of all the three points mentioned above.

Additionally, it is concluded that applying the proven industrial and management techniques in health care sector will in no way transform the working personnel into stereo typed transgenic mutants, nor it will make them wind mills to do the same thing again and again, but it will definitely make them convinced that they are also responsible for the welfare of the society in which they are the part and parcel, and as such in them the strategies will instill a culture of empathy for their fellow beings which will accelerate the error elimination in what they do and give.


Awareness is the primary element needed to monitor the patient safety measures in the care sector. As such, very advanced training should be provided to the clinical professionals in a flexible manner to reduce the errors in the pre-analytical, analytical and post-analytical phases.

Interaction programs must be designed to provide information to the patients and the public in general about how to derive the maximum output from the care system and how to ward off the unexpected care hazards for their own good. In clinical laboratories patient identification can be made error proof by systematic approach and effective supervision. If a clinical institution wants to apply any of the new strategies to improve quality in its realm it is better to go for a data driven longitudinal model which will provide consistency of safety to the patients and also to the clinical laboratory staff.


Baele P. L., Bruyere, M. D., Deneys, V., Dupont, E., Flament, J. & Lambermont, M. (1994). Bedside transfusion errors. A prospective survey by the Belgium Sanguis Group, 66:117–21.

Bertholf, R. L. (2007). Medical Errors: Causes and Prevention University of Florida Health Science. Laboratory Error Sources and CLSI Evaluation Protocols, Draft Document 0EP12-A2.

Blumenthal D. (1997). The errors of our ways. .American Association for Clinical Chemistry, Inc. Clin Chem 1997; 43:1305.

Bonini, P., Plebani, M., Ceriotti, F., & Rubboli, F. (2002). Clinical Chemistry. American Association for Clinical Chemistry, 48:5 691–698.

Buck, C. (n.d.). Application of Six Sigma to reduce medical errors.

Chawla, R., Goswami, B., Tayal, D. & Mallika, V. (2009). Identification of the Types of Preanalytical Errors in the Clinical Chemistry Laboratory: 1-Year Study at G.B. Pant Hospital. Web.

Coile, R. C. (2001). Quality pays: A case for improving clinical care and reducing medical errors. Publication: Journal of Healthcare Management. Web.

Coile, R. C. (2001). Medical Errors and the Science of Care Management. Health Trends 13 (3): 1-12.

Connors, D., Dronzek, R., Herhold, R. & Rogers, A. (n.d.). Leaning the Lab. Improving the Effectiveness of a Clinical Laboratory.

Coskun, A. (n.d.). Six Sigma and Lean concept in laboratory medicine [Power Point slides].

Davison, R.M. & Vogel, D.R., Group Support Systems in Hong Kong: An Action Research Project, Readings and Reflections, Routledge: 33-46. Web.

Doris, A.K. (2007). Lean thinking and medical error: A perspective Analysis, Lean Application report. 

ESRC Research Methods. (2007). Economic and Social Research Council (ESRC). Web.

ESRC Qualitative Methods (2007). Economic and Social Research Council (ESRC). Web.

Flores, G. M., Laws, B., Mayo, S. J., Zuckerman, B., Abreu, M., Medina, L., Eric J. & Hard, E.J. (2003). Source Details Errors in Laboratory Medicine. Pediatrics Vol. 111 , pp. 6-14. ISSN 1098-4275.

Freudenheim, M. (2000). Big Companies Lead Effort to Reduce Medical Errors. New York Times. C19.

Furman, C. (n.d.). Seeking Zero Defects: Applying the Toyota Production System to Health Care. Implementation of a Patient Safety Alert System. [Power Point slides].

Grout J. (2007). Mistake-proofing the design of health care processes. Agency for Healthcare Research and Quality AHRQ Publication No. 07-0020. Rockville, MD.

Haara, A. (n.d.). A Quality Management System for Total Compliance, Loyola University Medical Center.

Haglund, M. (2000). Medical Errors: While the Policy Debate Rages. Physician Performance & Payment Report 2 (7):1.

Hoeltge, G. A. (n.d.). Your Quality Improvement Plan. CAP Laboratory Accreditation Program. [Power Point slides].

Holder, A.R. (2005). Hematology Medical Errors. American Society of Hematology.

Howanitz, P.J. (2005). Errors in Laboratory Medicine. Practical Lessons to Improve Patient Safety, Howanitz 1252 Arch Pathol Lab Med Vol 129.

Institute of Medicine (November 1999). To Err is Human: Building a Safer Health System, National Academy Press; Washington DC. Web.

Kohn, L. T., Corrigan, J. M. & Donaldson, M. S. (1999). To Err is Human: Building a Safer Health System. Washington, DC:National Academic Press.

Kohn, L. T., Janet, M., Corrigan, J. M., & Donaldson, M. S. (2000). To Err Is Human: Building a Safer Health System. Washington, D.C. National Academy Press. Web.

Kohn, L. T., Corrigan, J. M. & Donaldson, M.S. (2009). To err is human: Building a safer System: Shaping the Future for Health. Washington, DC: National Academy Press. Web.

Kraemer, M. L. (2003). Six Sigma7 Management: A Tool for Implementing: ISO 15189.

Krause, R. D., Anand, V. D., Gruemer, H. D. & WIlIke, T. A. (2007). The Impact of Laboratory Error on the Normal Range: A Bayesian Model. Web.

Krower, J. S., Hatjimihail A.T, Jacobs, E., Nicholas, J.H., Halim, A.B., Manasterski, A. & Glavina, P. (2009). Risk Management Techniques to Identify and Control Laboratory Error Sources: Proposed Guideline-Third Edition EP18-P3. Web.

Leape, L. L., Bates, D. W. & Cullen, D. J. (1995). Systems analysis of adverse drug events. JAMA, 274, 35–43.

Leape, L., Lawthers, A. G. & Troyen, A. (1993). Preventing Medical Injury. Qual Rev Bull. 19(5):144–149.

Lippi, G., Guidi, G. G., Mattiuzzi, C. & Plebani, M. (2006). Preanalytical variability: the dark side of the moon in laboratory testing. Clin Chem Lab Med 2006;44(4):358– 365 New York. Web.

Lohr, K. N., Yordy, K. D. & Their, S. O. (1988). Current issues in quality of care. Health Affairs. Vol 7(1):5-18. PMID: 3360394. Web.

Matlow, A. G., & Berte, L. M. (2004). Sources of Error in Laboratory Medicine. Department of Pediatric Laboratory Medicine. Toronto, Canada. Web.

Murphy, G. J., Stee, L., Marian, T., McEvoy, M. T. & Oshiro, J. (n.d.). Journal Reporting of Medical Errors: The Wisdom of Solomon, the Bravery of Achilles, and the Foolishness of Pan. [Power Point slides].

Nevalainen, D., Berte, L., Kraft, C., Leigh, E., Picaso, L. & Morgan, T. (2000). Evaluating Laboratory Performance on Quality Indicators With the Six Sigma Scale. Arch Pathol Lab Med. 2000;124:516–519.

Oyebode, F. (2006). Advances in Psychiatric Treatment. Vol. 12. 221–227. Web.

Plebani, M. (2006). Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med 2006;44(6):750–759 New York. Web.

Plebani, M. (2009). Does POCT reduce the risk of error in laboratory testing? Clin Chim Acta. Web.

Preanalytical Cost of Poor Quality Model (n.d.). BD Laboratory Consulting Services. [Power Point slides].

Raab, S. S. (2007). Implementation of Lean in Laboratory Medicine Services, Reducing Waste and Enhancing Value in Health Care Delivery. [PDF document].

Reason, J. (2000). Human error: models and management. BMJ, 320, 768–770.

Rhoads, D. G. (2005). Approach Establishing Performance Standards. A Practical Approach, David G. Rhoads Associates, Inc.

Sazama, K. (2005). Legal Implications of Laboratory Errors. Labmedicine- Volume 36, 4. Web.

Sirota, R.L. (2005). Error and Error Reduction in Pathology. Arch Pathol Lab Med—Vol 129, 1228.

Stankovi, A.K. (2008). Developing a Lean consciousness for the clinical laboratory, BD Diagnostics , Preanalytical Systems, New Jersey, USA JMB 2008; 27 (3). Web.

Tedeschi, B. (2000). No Fun for Sisyphus: The Woes of WebMD and Medscape. New York Times. October 25: E12.

Tooker, J. (2004). The Importance of Measuring Quality and Performance in Healthcare. The ambulatory care quality alliance: improving clinical quality and consumer decision making-Background statement. Rockville, Md. Web.

Wagar, E. A., Tamashiro, L., Yasin, B., Hilborne, L. & Bruckner, D.A. (2006). Patient Safety in the Clinical Laboratory: A Longitudinal Analysis of Specimen Identification Errors. Arch Pathol Lab Med—Vol 130.

Weingart, S. N., Wilson, R. M., Gibberd, R. W. & Harrison, B. (2000). Epidemiology of medical error. Web.

Wyer, L. A., Burford, D., Elliott, R. D., Hackett, C., Jacobs, E., Sadek, W., Scruggs, K., Skrlin, S. & Thomas, M. (2009). Quality Management: Approaches to reducing errors at the Point of Care. Proposed Guideline, Volume 29. POCT07P. Web.

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