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ABDULLAAH 520
The term “medical error” incorporates a variety of events with varying severity and potential
for patient damage. According to the 2019 World Health Organization (WHO) Factsheet on
Patient Safety, adverse events resulting from hazardous patient care are among the top ten
causes of mortality and disability worldwide.(Singh et al., 2023)
An error is a behavior that can result in a negative consequence. Everyone makes errors;
it is a part of being human. Cognitive psychologists believe that lapses, slip-ups, and errors
are inevitable, as they are the price, we pay for advanced higher brain function. Specifically,
a medical error is a preventable adverse effect of treatment, regardless of whether it is
obvious to the patient or detrimental. This may involve a misdiagnosis or inadequate
treatment of a disease, injury, behavior, infection, or other ailment.(Jhugursing et al., 2017)
Root cause analysis (RCA) is a technique for identifying the factors responsible for
performance variations. This variation in efficacy may result in a sentinel event in cases of
medical error. The Joint Commission mandates a standardized RCA procedure to identify the
cause of medical errors and thus enable healthcare institutions to develop strategies to prevent
future errors.(Singh et al., 2023)
Errors are inevitable in all health care systems. To enhance patient safety, it is vital that
these errors are identified, and lessons are drawn from these cases. Error data are collected by
incident reporting systems (IRS) to facilitate learning and improve patient safety. The
fundamental premise of the system-based approach is that humans are fallible and that even
in the finest organizations, errors are inevitable. The systems-based approach is significantly
more applicable to the NHS because it considers the organizational processes and sequence
of events that led to the error. Errors are seen as consequences rather than causes, having their
origins not so much in the perversity of human nature as in the ‘upstream’ systemic
factors.(Jhugursing et al., 2017)
RCA is a structured, exhaustive investigation of a patient safety incident to identify the
underlying causes and contributing factors, which are then analyzed to identify any learning
opportunities. The learning points can be implemented to reduce the likelihood of a similar or
identical incident occurring again.
The RC investigation technique.(Jhugursing et al., 2017)
1. starting, and to perform an RCA. The incident must be classified according to its severity,
and an appropriate team must be convened.
2.Collecting and organizing the data. This phase involves gathering all pertinent information
regarding the incident.
Identifying issues with care and service delivery.
Care delivery issues and service delivery issues encompass all acts of commission and
omission.
4. analyzing the data by identifying contributing factors and underlying causes.To determine
the fundamental cause of a CDP or SDP, it is necessary to identify the contributing factor to
each problem. Contributing factors include any action, omission, or deficiency that paves the
way for an error to occur.
5. Developing suggestions and solutions. The solutions provide the impression that patient
safety incidents can be prevented permanently and readily.
6. putting solutions into effect. Communication, dissemination, diffusion, adoption, spread,
and sustainability are ongoing, dynamic processes involved in the implementation of a
solution.
7. Create the report. Each trust has its own customized template. When analyzing
investigation results, it is crucial to be aware of and avoid hindsight bias and outcome bias.
Reference:
Jhugursing, M., Dimmock, V., & Mulchandani, H. (2017). Error and Root Cause
Analysis. BJA Education, 17(10), 323–333. https://doi.org/10.1093/bjaed/mkx019
Singh, G., Patel, R. H., & Boster, J. (2023). Root Cause Analysis and Medical Error
Prevention. In StatPearls. StatPearls Publishing.
http://www.ncbi.nlm.nih.gov/books/NBK570638/
ABDULLLAH 525
The use of health technology in various areas of health care is growing. It offers numerous
options to satisfy societal requirements for enhancing quality, maximizing resource
utilization, and coproducing care within the health care system. As health technology has
progressed beyond supporting the treatment of life-threatening or congenital diseases and into
genomics, diagnosis, surveillance, and big data, as well as artificial intelligence, the central
ethical questions have shifted to concerns regarding individual and system-level integrity and
equity. Such concerns relate to the possibility that technology is biased, contributes to or even
exacerbates inequalities, and overturns the principles for how care has been traditionally
practiced and the logical framework for structuring the care system.(Steerling et al., 2022)
Professionals in health informatics are governed by federal, state, and local regulations, as
well as an American Health Information Management Association (AHIMA) code of ethics.
Keeping up with legal and ethical issues can be difficult due to the relative youth of the
profession and its rapid evolution as a result of rapid technological development. Healthcare
workers and consultants, health policymakers, and medical researchers are just some of the
professional communities affected by altering regulations, laws, and ethical standards.
American Medical Informatics Association (AMIA) members have access to a working
group dedicated to continuing education regarding ethical, legal, and social issues associated
with health informatics.(“Legal and Ethical Issues in Healthcare Informatics,” 2020)
Ethical and legal considerations influence every aspect of the health informatics
profession. The issue essentially boils down to finding a method to strike a balance between
the need to safeguard the security of patient information and the potential for enhanced care
and outcomes resulting from increased interoperability and the ability to share records among
healthcare entities.(“Legal and Ethical Issues in Healthcare Informatics,” 2020) Here are a
few of the ethical, legal, and social issues that are currently influencing the profession of
health informatics:
•
The protection of patient confidentiality
•
Patient security
•
Risk analysis
•
Design and presentation of data for reporting System implementation
•
Curriculum planning
•
Research morality
•
Legal duty
•
Participation of users and accessibility
•
There are ethical dilemmas deriving from the availability and sharing of data.
The rapid development and implementation of multiple health information technologies
enabled medical organizations to store, communicate, and analyze a vast quantity of personal
medical/health and biomedical data, the majority of which are electronic health records
(EHR) and genomic data. Emerging technologies, such as smart phones and wearable
devices, have also enabled third-party companies to offer a variety of complementary
mHealth services and collect vast quantities of consumer health data.(Xiang & Cai, 2021)
Reusing health data under the premise of preserving privacy is the direct and crucial
strategy for balancing the two issues. The most fundamental concept is to share de-identified
health data by protected health information (PHI), while eliminating 18 specified PHI. On the
basis of deidentified health data, machine learning and data mining can be used for
knowledge extraction or learning health system building for the purpose of analyzing and
enhancing care by tailoring treatment to the patient’s clinical or genetic characteristics.(Xiang
& Cai, 2021)
Confidentiality protects confidential information by restricting unauthorized access to
specific information and ensuring the safety and security of personal data. Unauthorized
access may result in data loss and, in certain cases, pose personal hazards to the individual
patient at multiple levels (e.g., data breaches/leaks concerning HIV and other sexually
transmitted disease cases). The accumulation of health information must comply with legal
and ethical privacy regulations, such as the General Data Protection Regulation (GDPR) in
Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United
States. The primary purpose of these regulations is to ensure that confidential patient
information is kept private and not disclosed, as well as to secure the hospital and its
numerous service informatics.(Almaghrabi & Bugis, 2022)
Reference:
Almaghrabi, N. S., & Bugis, B. A. (2022). Patient Confidentiality of Electronic Health
Records: A Recent Review of the Saudi Literature. Dr. Sulaiman Al Habib Medical
Journal, 4(3), 126–135. https://doi.org/10.1007/s44229-022-00016-9
Legal and Ethical Issues in Healthcare Informatics. (2020, April 10). USF Health Online.
https://www.usfhealthonline.com/resources/health-informatics/legal-and-ethical-issues-inhealth-informatics/
Steerling, E., Houston, R., Gietzen, L. J., Ogilvie, S. J., de Ruiter, H.-P., & Nygren, J. M.
(2022). Examining how Ethics in Relation to Health Technology is Described in the Research
Literature: Scoping Review. Interactive Journal of Medical Research, 11(2), e38745.
https://doi.org/10.2196/38745
Xiang, D., & Cai, W. (2021). Privacy Protection and Secondary Use of Health Data:
Strategies and Methods. BioMed Research International, 2021, 6967166.
https://doi.org/10.1155/2021/6967166
ABDULLAH 530
The field of Human Factors (HF) has emerged as a multidisciplinary discipline after the
conclusion of World War II (WW-II). The subject of Human Factors (HF) has three primary
areas of expertise, namely organizational ergonomics, cognitive ergonomics, and physical
ergonomics, each focusing on distinct domains. Organizational ergonomics encompasses
several aspects pertaining to job duties, work processes, operational philosophies, and nontechnical abilities. Cognitive ergonomics encompasses several aspects pertaining to task
analysis, the human-machine interface (HMI), workload management, and alarm concepts.
Physical ergonomics encompasses concerns pertaining to the arrangement of the workplace
and the conditions under which labor is conducted, often referred to as the working
environment (WE).(Johnsen et al., 2017)
The importance of HF engineering in the design and use of safety-critical systems, the
necessity of focusing on non-technical skills (such as communication, teamwork, and
decision-making between different actors), as well as the assessment of safety-critical tasks
and identification of controls that could maximize the likelihood of successful human
performance, were a few of the specific areas mentioned.(Johnsen et al., 2017)
Ergonomics, as defined by the International Ergonomics Association (IEA), is the scientific
field that investigates the interactions between humans and other system components.
Workplace ergonomics refers to interactions between employees and other elements of the
work environment. It is fundamentally about matching the laborer to the task. The IEA
divided ergonomics into three distinct categories: physical, organizational, and
cognitive.(Hoe et al., 2018)
Physical domain is concerned with human anatomy, anthropometry, physiology, and
biomechanics as they pertain to physical activity. This domain includes the employees’ work
environment and apparatus, such as the keyboard, mouse, hand tools, workstations, visual
display units (VDUs), and illumination.(Hoe et al., 2018)
Human Factors and Ergonomics complement each other in healthcare.
The field of health care encompasses individuals fulfilling different roles, such as
patients, caregivers, and clinicians, who engage in interconnected care procedures including
diagnosis, treatment, monitoring, and management. The global problem lies in the endeavor
to guarantee favorable results for both patients, encompassing quality of treatment, patient
safety, and positive patient experience, and physicians participating in their care, including
the quality of their working life.
Human factors (or ergonomics) (HFE) provide systems concepts and methodologies to
enhance care processes and outcomes for patients, caregivers, and clinicians. International
Ergonomics Association defines HFE as “the scientific discipline concerned with the
understanding of interactions among humans and other elements of a system, and the
profession that applies theory, principles, data, and methods to design in order to optimize
human well-being and overall system performance” According to the IEA’s definition of
HFE, people are at the center of (work) systems; systems, their components, and their
interactions should be designed to support performance and improve the well-being of
people. HFE places an emphasis on the physical, cognitive, and organizational aspects of
labor systems.
healthcare example
Existing HFE principles and instruments for single-site or small-scale quality
improvement initiatives may not be applicable to large-scale dissemination programs. In
single-site or small-scale quality development initiatives, direct observations and interviews,
for instance, are comprehensive and manageable assessment instruments. Observations and
interviews at each site participating in a large-scale dissemination program will likely be
impractical and possibly unnecessary. One alternative is to develop a survey-based work
system evaluation tool and remotely administer it at each location.(Xie et al., 2019)
Human Factors and Ergonomics (HFE) is essential to enhancing the healthcare system.
There is no organizational system that supports the deliverance of high-quality, secure care
alongside the general advancement of medicine’s technology. The potential for care delivery
enhancement is immense. System viewpoint: The healthcare system is composed of
interdependent and interrelated social and technical components, forming a highly variable
socio-technical system. User-friendly design: User-centricity entails incorporating human
characteristics and abilities into system design. Work completed: Human and organizational
performance is inherently variable, and few systems could function without regular patterns
of approximate performance adjustments.(Xie et al., 2019)
Reference:
Hoe, V. C., Urquhart, D. M., Kelsall, H. L., Zamri, E. N., & Sim, M. R. (2018). Ergonomic
interventions for preventing work‐related musculoskeletal disorders of the upper limb and
neck among office workers. The Cochrane Database of Systematic Reviews, 2018(10),
CD008570. https://doi.org/10.1002/14651858.CD008570.pub3
Johnsen, S. O., Kilskar, S. S., & Fossum, K. R. (2017). Missing focus on Human
Factors – organizational and cognitive ergonomics – in the safety management for the
petroleum industry. Proceedings of the Institution of Mechanical Engineers. Part O,
Journal of Risk and Reliability, 231(4), 400–410.
https://doi.org/10.1177/1748006X17698066
Xie, A., Woods-Hill, C. Z., Berenholtz, S. M., & Milstone, A. M. (2019). Use of Human
Factors and Ergonomics to Disseminate Health Care Quality Improvement Programs. Quality
Management in Health Care, 28(2), 117–118.
https://doi.org/10.1097/QMH.0000000000000211
HQS-525: Technology and Health Informat 10845-Riyadh-Males
MEZNA
Ethics In Health Informatics
Ethical guidelines in the context of health informatics play a crucial role in ensuring the
responsible and ethical use of technology and data in healthcare. The healthcare providers
have access to a critical and sensitive patient information. These information should be
secured to prevent any misuse by unauthorized personal. The ethical guidelines provide a
framework for healthcare professionals, researchers, and organizations to navigate the
complex landscape of health information technology while safeguarding patient rights,
privacy, and confidentiality. The ethics in informatics is similar to the principle of ethics
in medicine (Masters, 2012). Theses ethics as following:
Privacy and Confidentiality: Health informatics should adhere to strict privacy and
confidentiality standards to protect patients’ sensitive information. Personal health data
should be collected, stored, and transmitted securely, with limited access except to
authorized individuals. Encryption, access controls, and data anonymization techniques
are employed to minimize the risk of unauthorized disclosure.
Informed Consent: Informed consent is a fundamental principle in health informatics.
Individuals should be fully informed about the purpose, potential risks, and benefits of
health information collection and use. They have the right to give or withhold consent,
and their choices should be respected.
Data Governance: Health informatics should establish robust data governance
frameworks to ensure the responsible management of health data. This includes defining
clear policies and procedures for data collection, storage, access, sharing, and disposal.
Data quality, integrity, and security should be maintained throughout the data lifecycle.
Continuous Improvement and Adaptation: Ethical guidelines need to evolve and adapt
with the changing landscape of health informatics. Regular review and updates are
necessary to address emerging ethical challenges, technological advancements, and legal
requirements.
The American Medical Informatics Association (AMIA) has ethical code called
“Professional Code of Ethics for Health Information Professionals” (Masters, 2012). The
IMIA code consists of fundamental ethical principles such as principle of principle of
Autonomy, principle of Equality and Justice, principle of Beneficence, principle of NonMalfeasance, principle of Impossibility, and principle of Integrity. In addition, it consist
of general principles of informatics Ethics such as principle of Information-Privacy and
Disposition, principle of Openness, principle of Security, principle of Access, principle of
Legitimate Infringement, principle of the Least Intrusive Alternative, principle of
Accountability (Moghaddasi & Ebrahimpour Sadagheyani, 2016). These ethical
principles were established to protect patient information and regulate access to patient
date.
Sharing medical information, particularly patient date does take place in medical practice
for the purpose of education, research and establishment of medical guidelines. However,
the healthcare provider should obtain patient consent to share medical information and
explain how these information will be protected from misuse and inappropriate utilization
of information (Goodman, 2020).
To conclude, patient information are private and critical date, if it was accessed by
unauthorized person it could lead to fraud and other inappropriate date usage. Informatics
ethical principle are similar to the international ethical principles, in addition the AMIA
established code of ethics for health information professionals as they deal with a
sensitive information which ensure the patient date are been secure and utilized in right
way with patient approval.
References
Goodman, K. W. (2020). Ethics in health informatics. Yearbook of medical informatics,
29(1), 026-031.
Masters, K. (2012). Health informatics ethics. Health Informatics: Practical Guide for
Healthcare and Information Technology, 195-215.
Moghaddasi, H., & Ebrahimpour Sadagheyani, H. 2016( .). Code of Ethics of medical
informatics in Asia and America. Journal of Research and Health, 6(5), 463-464.
Fahad Alsatami
Health informatics, which merges healthcare, information technology, and data
management, has significantly transformed healthcare provision. However, it is crucial to
adhere to ethical guidelines during its implementation to ensure patient privacy and data
security (Goodman, 1998).
Ethical Principles in Health Informatics
Key ethical principles in health informatics include:
1. Confidentiality: Patient information should be secure and confidential, with
access limited to authorized personnel (Goodman, 1998).
2. Integrity: Data should be accurate, reliable, and updated. All changes should be
traceable (Goodman, 1998).
3. Consent and Autonomy: Patients should have the right to control and give
informed consent about their health data’s use.
4. Justice: There should be equitable access to, benefits from, and control over one’s
data (Mittelstadt & Floridi, 2016).
Balancing Public Health Protection and Individual Rights
Healthcare providers balance public health protection with respect for individual rights
primarily through data minimization and purpose limitation, collecting only necessary
data and using it for its intended purpose (Kluge, 2004).
In situations like an epidemic, it’s vital to collect and share data to track disease spread
and plan interventions, but the data should be anonymized to protect individual identities.
Additionally, robust security measures should be in place to prevent unauthorized data
access.
Transparency is also essential. Providers must inform patients about the necessity of their
data, how it will be employed, and the protective measures in place (Mittelstadt &
Floridi, 2016). This enhances transparency and cultivates patient trust.
References
Goodman, K. W. (1998). Ethics, Information Technology, and Public Health: New
Challenges for the Clinician-Patient Relationship. Journal of the American Medical
Informatics Association, 6(1), 50–59.
Kluge, E. H. W. (2004). Informed consent and the security of the electronic health record
(EHR): some policy considerations. International Journal of Medical Informatics, 73(3),
229–234.
Mittelstadt, B., & Floridi, L. (2016). The ethics of big data: Current and foreseeable
issues in biomedical contexts. Science and Engineering Ethics, 22(2), 303–341.
Faten
Ethical Guidelines and Principles in Health Informatics
The ethical principles and guidelines can be used to help healthcare professionals make
ethical decisions in all areas of practice. Health informatics professionals can help ensure
the responsible and ethical use of health information technology to improve patient care,
protect patient privacy, and advance healthcare research and innovation. Here are the key
principles that underpin ethical guidelines in health informatics:
•
•
•
•
“Respect for autonomy” means supporting autonomous decisions but also in the
choice of whether or not to use health technology innovations and share personal
information (Maeckelberghe et al., 2023).
“Beneficence” The moral obligation to act in a way that benefits others, promoting
their well-being and legitimate interests. In the context of health informatics, the
principle of beneficence guides health informatics professionals in using
technology and data to improve patient care and outcomes.
“Non-maleficence” An example that relates to this principle is once a system is
tested against any residual risk of harm to the patient and also in terms of
cybersecurity and data protection, then it might be assumed that the system
ensures the “non-maleficence” principle (Maeckelberghe et al., 2023).
“Justice” Health informatics plays a role in promoting justice by improving
healthcare access and reducing healthcare disparities. Telehealth and
telemedicine, for example, enable patients to receive care from a distance.
Healthcare providers need access to medical information in order to provide appropriate
care and make informed decisions. They must balance the need for information with the
ethical obligation to respect patient autonomy and privacy. To achieve this balance,
healthcare professionals must obtain informed consent from patients. For consent to be
meaningful, individuals need to have a sense of control over their data. They need to be
able to request the correction or removal of inaccurate or inappropriately held data.
Reference:
Heslop, P. A., Davies, K., Sayer, A., et al. (2020). Making consent for electronic health
and social care data research fit for purpose in the 21st century. BMJ Health & Care
Informatics, 27, e100128. doi: 10.1136/bmjhci-2020-100128
Maeckelberghe, E., Zdunek, K., Marceglia, S., Farsides, B., & Rigby, M. (2023). The
ethical challenges of personalized digital health. Frontiers in medicine, 10, 1123863.
https://doi.org/10.3389/fmed.2023.1123863
Abdul,majed
Ethical Principles
Health informatics professionals are guided by a code of ethics and federal,
state, and local regulations
The principles of ethical guidelines in health informatics are essential for
balancing the needs to protect population health while showing respect for
individuals and their medical information
Healthcare providers must navigate the ethical challenges presented by the
development and appropriate use of technology, individual privacy, and the
influence of technologies on healthcare policy
Some of the key principles and considerations in this context include:
•
Respect for autonomy: Healthcare professionals should respect individuals’ right
to make decisions about their own health information and ensure that they
have the necessary information and understanding to make informed choices
•
Nonmaleficence: Healthcare providers should strive to do no harm and ensure
that the use of health informatics technologies does not result in adverse effects
on individuals or populations
•
Beneficence: Healthcare professionals should use health informatics
technologies to promote the well-being of individuals and populations, ensuring
that the benefits outweigh any potential risks or harms
•
Justice: The use of health informatics should be fair and equitable, ensuring that
all individuals have equal access to the benefits of technology and that the
distribution of resources and services is just
•
Privacy and confidentiality: Health informatics professionals must adhere to
strict ethical codes to protect patient privacy and confidentiality, ensuring that
sensitive information is only accessed by authorized individuals and used for
appropriate purposes
•
Transparency and accountability: Healthcare providers should be transparent in
their use of healthcare data, ensuring that individuals understand how their
information is being used and that they are held accountable for the responsible
and ethical use of technology
•
Preventing bias in data collection and use: Health informatics professionals
should be aware of and actively work to prevent bias in the collection and use of
healthcare data, ensuring that technology does not perpetuate or exacerbate
existing inequalities or disparities
•
Balancing access and privacy: Health informatics must strike a balance between
necessary access to information for providing quality care and protecting
patient privacy, ensuring that individuals’ rights are respected while still
enabling effective healthcare delivery
•
Compliance with regulations and codes of ethics: Healthcare providers should
adhere to federal, state, and local regulations, as well as codes of ethics
published by professional associations, to ensure that their use of health
informatics is legal, ethical, and responsible
References:
Ethical Controversies About Proper Health Informatics Practices – PMC – NCBI
THE ROLE OF INFORMATICS IN PROMOTING PATIENT-CENTERED CARE – PMC NCBI
Legal and Ethical Issues in Healthcare Informatics | USF Health Online
Identifying and Addressing Ethical Issues with Use of Electronic Health Records
| OJIN
AHIMA Code of Ethics
What are the principles of ethical guidelines and the use of health… |
CliffsNotes
HQS-520: Risk Management and Patient Sa 10838-Riyadh-Males
Nourah Alhodaithy
There are two main types of error that are classified in Root Cause Analysis:
1. Action-based error, or execution failure, which is associated with familiar tasks
that require little conscious attention. These ‘skill-based’ errors occur if attention
is diverted, even momentarily. Resulting action is not intended: ‘not doing what
you meant to do’. Common during maintenance and repair activities. Actionbased errors can be further categorized into slip and lapse. Slip is a simple,
frequently-performed physical action goes wrong, for example, move a switch up
rather than down (wrong action on right object). While lapse is a short-term
memory lapse; omit to perform a required action, for example, medical implement
left in patient after surgery.
2. Thinking-based error, or planning failure, which is decision-making failures;
errors of judgement (involve mental processes linked to planning; info. Gathering;
communication etc.). Action is carried out, as planned, using conscious thought
processes, but wrong course of action is taken: ‘do the wrong thing believing it to
be right’.Thinking- based errors can be further categorized into rule-based
mistake and knowledge-based mistake. Rule-based mistake occurs if behaviour is
based on remembered rules and procedures, mistake occurs due to mis-application
of a good rule or application of a bad rule, for example, ignoring alarm in real
emergency, following history of spurious alarms. Knowledge-based mistake
occurs if an individual has no rules or routines available to handle an unusual
situation: resorts to first principles and experience to solve problem, for
example, misdiagnose process upset and take inappropriate corrective action (due
to lack of experience or insufficient / incorrect information etc.) (Lyon & Popov,
2023).
Accident models are used to understand cause and
effect of relationships. Examples for accident models include:
a. Domino theory:where risk is represented as a weak link in a linear
chain of events.
b. Fault tree: where risk is represented as combinations of conditions
and causes following multiple linear paths and considers barriers to prevent
event.
c. Event tree: where there are multiple outcomes represented as
consequences of a risky event with consideration of barriers to contain risk.
d. Bow tie model: which is used when combines fault tree and event
tree to consider both prevention of the event and containment of hazards for
events that are not completely prevented.
e. Swiss cheese model: where risk is represented as aligment of latent
and active failures that permeate weak layers of defense.
f. Sharp end-blunt end: The point where events occur is the sharp end
while the blunt end (system, policies, culture) is where the causes are typically
rooted. (Shah & Godambe, 2021).
References
Lyon, B. K., & Popov, G. (2023). PREVENTION THROUGH
ERGONOMICS: Integrating Human Factors Into a Prevention Through
Design Approach. Professional Safety, 68(6), 24–33.
Shah, R., & Godambe, S. (2021). Chapter 6, Patient safety and quality
improvement in healthcare: a case-based approach. Springer
Dunya
Root Cause Analysis
Root cause analysis (RCA) is a systematic process for identifying the underlying causes
of a problem or event. It is used in a variety of industries to improve safety, quality, and
reliability.
There are two main types of errors that are classified in RCA:
Active errors: These are errors that are made by people at the time of an event. They can
be caused by a variety of factors, such as fatigue, distraction, lack of training, or human
error.
Latent errors: These are errors that are embedded in the system or processes that lead to
an event. They can be caused by factors such as inadequate design, poor communication,
lack of resources, or organizational culture.
How to Use to Analyze Errors
Accident models can be used to analyze errors in RCA by identifying the factors that
contributed to the error and the ways in which the system could have been designed to
prevent the error from occurring.
For example, if a nurse accidentally administers the wrong medication to a patient, the
following accident models could be used to analyze the error:
Domino theory: The domino theory could be used to identify the chain of events that led
to the error, such as the nurse being fatigued, the medication labels being similar in
appearance, and the lack of a double-checking procedure.
Fault tree analysis: FTA could be used to identify the different ways that the error could
have occurred, such as the nurse selecting the wrong medication, the nurse administering
the medication to the wrong patient, or the nurse failing to double-check the medication
before administering it.
Event tree analysis: ETA could be used to identify the different consequences of the
error, such as the patient suffering a mild adverse reaction, the patient suffering a serious
adverse reaction, or the patient dying.
Bow tie model: The bow tie model could be used to combine the FTA and ETA analyses
to provide a more comprehensive view of the risks associated with the error.
Swiss cheese model: The Swiss cheese model could be used to identify the holes in the
system that allowed the error to occur, such as the similar appearance of the medication
label
