If you think quality and safety are the same...think again - PowerPoint PPT Presentation


PPT – If you think quality and safety are the same...think again PowerPoint presentation | free to download - id: 3c1c1c-NDlhN


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation

If you think quality and safety are the same...think again


Karen Cardiff, School of Population and Public Health, University of BC Samuel B Sheps, School of Population and Public Health, University of BC – PowerPoint PPT presentation

Number of Views:71
Avg rating:3.0/5.0
Slides: 35
Provided by: canadaSys
Tags: again | quality | safety | same | think


Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: If you think quality and safety are the same...think again

If you think quality and safety are the
same...think again
  • Karen Cardiff, School of Population and Public
    Health, University of BC
  • Samuel B Sheps, School of Population and Public
    Health, University of BC
  • Jim Nyce, Department of Anthropology, College of
    Sciences and Humanities, Ball State University,
    Muncie Indiana
  • Sidney Dekker, Lund School of Aviation, Lund
    University, Lund, Sweden
  • June 10, 2010
  • System Safety Society Canada ChapterSpring
  • Ottawa, Ontario

  • The findings presented today are based on the
    thesis work for completion of an MSc in Human
    Factors and System Safety with the Department of
    Aviation, Lund University

  • Also informed by work that began a decade ago
  • Canadian Adverse Events Project (Canadian
    Institutes of Health Research, 2000-2003)
  • Management and Regulation of Safety in Risk
    Critical Sectors (Health Canada, 2004-2007)
  • Creating High Reliability Organizations in the
    Canadian Health Care System (Canadian Patient
    Safety Institute, 2007-2008)
  • Current work co-funded by the Canadian Health
    Services Research Foundation
  • and the Canadian Patient Safety Institutea four
    year multi-partner capacity building project that
    is focused on building capacity within acute care
    hospitals to do critical incident investigation
    (Sheps and Cardiff, 2009-2013)
  • Interaction with international opinion leaders
    and experts in system safety on the
  • emerging ideas of resilience and safety (Sidney
    Dekker, Eric
  • Hollnagel, René Amalberti, Richard Cook, etc)

Outline of presentation
  • Background
  • Why is the topic important
  • Theories and models of why things go wrong
  • Findings from the thesis work

  • When patients entrust themselves to our care, we
    make two implicit, but key professional and
    organizational promises
  • we promise to do everything possible to help
    patientsto provide good (possibly excellent)
    care and, we promise not to hurt them
    (Reinertsen Clancy, 2006)
  • However, there are many instances where people do
    not get the care that they need (McGlynn et al
    2003) or are inadvertently harmed through the
    process of care (Kohn et al, 1999 Vincent et al,
    2001 David et al 2002 Norton et al, 2004 Leape
    et al, 2005).

  • While being concerned with quality for many
    years, healthcare did not, in general, think
    systematically about patient safety until the
    magnitude of the problem became very clear and
    could no longer be ignored.
  • Now, after more than a decade of activity that
    has measured, tracked, and in many instances
    investigated adverse events in acute care, no one
    doubts that enhancing patient safety (i.e.
    reducing harm) is an important and necessary goal
  • Although there continues to be widespread buy-in
    that the healthcare system must take steps to
    reduce patient harm, the struggle in how to
    achieve this, and make it sustainable, remains.
  • Even as the number of activities to improve
    patient safety and quality increases, along with
    a the range of tools available to assist with the
    process the healthcare system has not yet
    achieved the status of being a high reliability
    or resilient industry.

  • While emerging theoretical and applied work
    acknowledge that quality and safety are distinct
    concepts, in healthcare the majority of
    activities, to date, have focused on activities
    designed to improve adherence to accepted
    standards of care, such as hand-washing,
    appropriate use of antibiotics (i.e. telling
    people what they already know they should be
    doing), and are more aligned with the classic
    quality model than safety safety by constraint
    marked by barriers, regulations, procedures,
    training and standardization.
  • The current efforts are largely based on
    reductionistic thinking that attempts to
    trouble shoot and fix things.
  • Even though many of these efforts have been met
    with success, they have largely ignored issues
    related to what it means to create safety in
    complex, dynamic settings, such as preparing
    frontline staff to cope with the complexity that
    they face on a daily basis and supporting them to
    become more experienced with anticipating what
    might go wrong (requisite imagination) and
    knowing when and how to adapt their performance
    under conditions of uncertainty.

Understanding adverse events in healthcare
  • A model often used in health care is that
    accidents are thought to occur when individual
    components or processes fail to meet
    criteria.this model of risk and safety builds on
    the assumption that safety, once established, can
    be maintained by keeping the performance of a
    systems parts (human and technical) within
    certain bounds (e.g. people should not violate
    rules and procedures)
  • Sidney Dekker, Past the edge of chaos. 2006

Why does the classic quality model distort
efforts to achieve safety?
  • The classic quality model was developed to ensure
    that the system meets pre-specified criteria.
  • Quality is viewed as the characteristics of a
    service or product that must be present to meet
    needs or expectations such as high professional
    standards, effective use of resources and high
    patient satisfaction
  • The goal of quality assurance activity is to keep
    performance variability under control
    organizations develop policies, rules and
    protocols to keep performance within a particular

  • In linear production systems (e.g. Toyota,
    McDonalds) quality may have safety as an additive
    result this is because
  • the systems can be decomposed into meaningful
  • the failure-probability of individual components
    can be described and analyzed individually
  • the order or sequence of events is predetermined
    and fixed
  • when combinations of events occur they can be
    described as non interacting
  • the influence of context is limited or
  • (Dekker, 2007)
  • However, since the process of producing
    healthcare is neither linear nor fixed, the
    classic quality model is not adequate.

Complex systems
  • in complex systems (such as healthcare),
    unpredictability and paradox are ever present,
    and some things will remain unknowable.new
    conceptual frameworks that incorporate a dynamic,
    emergent, creative and intuitive view of the
    world must replace traditional reduce and
    resolve approaches to clinical care and service
    organization (Plsek, 2001)

Examples of complexity in healthcare
  • Demand frequently pushes performance goals
  • Rapid introduction of new, complex technology
  • Many discontinuities and transitions in care
    (e.g. multiple care providers caring for the same
    patient and often in multiple settings
    emergency department to operating room to
    surgical wardeach unit managed independently)
  • Strong autonomous and semi-autonomous
    professional cultures with concomitant power
  • Often rapid turnover in staff
  • Continual influx of new patients, each with their
    own inherent biological variability and in many
    instances language and cultural differences.

  • The key challenge of creating safety in complex
    non linear systems is that the knowledge base is
    inherently and permanently incomplete.
  • In healthcare work situations are always
    underspecified (i.e. the conditions of work
    rarely match what has been specified or
    prescribed), and with this comes an unpredictable
    component, and thus adaptation is often necessary
    (Hollnagel et al, 2006 Grote, 2006)
  • Performance variability is both normal and
    necessary in complex non linear systems (Dekker,
    2007 Hollnagel, 2008)

Performance variability, adaptation safety
  • IF keeping things safe equals keeping performance
    within a particular bandwidth, why do complex,
    dynamic organizations value experience or
  • It is because experience brings a broader
    bandwidth people at the sharp end of care can
    judge whether that which they used before will
    work in the current situation.
  • There is always a tension around when and how to
    adapt rules and protocols to the set of
    circumstances one finds themselves in, but the
    experienced person is more likely to know when
    and how to do this.
  • Complex systems are generally well protected from
    vulnerabilities with barriers, but safety is
    created through practice, i.e. practitioners
    recognize local pitfalls and forestall them, and
    this often involves adaptation.

Theories and models of why things go wrong
Linear views (Dekker, 2007 Hollnagel, 2008)
  • Assumption and consequence
  • Accidents are the natural outcome of a series of
    events or circumstances which occur in a specific
    and recognizable manner (e.g. Domino Model,
    Heinrich, 1930) ? accidents are prevented by
    finding and eliminating possible causes
    component failures, such as human technical and
  • Assumption and consequence
  • More recently, accidents have been seen to result
    from a combination of active failures (unsafe
    acts) and latent conditions (hazards) ? accidents
    are prevented by strengthening barriers and
    defenses (e.g. Swiss Cheese Model, Reason, 1990)
    and safety is ensured by measuring performance
    indicatorsin particular people rely on
    understanding past events (e.g. Root Cause
    Analysis) to develop solutions for the future.

Reasons Swiss Cheese Model Layers of defense
(J. Reason, Managing the Risks of Organizational
Accidents, 2002)
  • Linear models provide the basis for investigators
    to easily take the position of retrospective
    outsider, looking back on a sequence of events
    that seems to lead to an inevitable outcome, and
    pointing out where people went wrong, or where
    individual components of the system failed.
  • Although this perspective is often adequate in
    linear systems, the approach seriously limits
    what the investigator can learn about failure in
    non linear systems ( i.e. the complex and
    unexpected combination of system interactions)
    and may not help prevent recurrence.

Understanding safety in non linear systems
(Dekker, 2007 Hollnagel, 2008)
  • Assumption and consequence
  • Accidents result from unexpected combination
    (resonance) of normal performance variability
    hazards emerge from expected (and necessary)
    variability within the system and accidents are
    prevented by monitoring and damping the
  • The variability of normal performance is rarely
    sufficient to result in an accident, but the
    variability from multiple functions may combine
    in unexpected ways to produce a non linear
    effect, thus safety is an emergent property of
    the system and cannot be explained by simply
    examining individual components of the system
    and/or trying to identify a root cause.
  • Complex socio-technical systems (such as
    healthcare) are dynamicthe systems change and
    develop in response to competing demands,
    production pressures and changes in technology
    and knowledge. Resilience exists when operators
    in the system are able to recognize, absorb and
    adapt to disruptions/changes that fall outside of
    their design base.

Functional Resonance Accident Model (Hollnagel,
An emerging model that attempts to understand the
dynamics of normal organizational activity
  • Non linear accident models provide investigators
    with the basis to find out why peoples actions
    and assessments made sense to them at the time
    rather than identifying what rule, protocol or
    process the person violated (people often adapt
    their actions given the context at hand and this
    is part of the normal performance variability
    that takes place as part of normal work in
    dynamic, complex systems).
  • Human error is not an explanation, but demands
    an explanation
  • Sidney Dekker, 2006

  • In contrast to this, linear models provide the
    basis for investigators to easily take the
    position of retrospective outsider, looking back
    on a sequence of events that seems to lead to an
    inevitable outcome, and pointing out where people
    went wrong, or where individual components of the
    system failed.
  • Although this perspective is often adequate in
    linear systems, the approach seriously limits
    what the investigator can learn about failure in
    non linear systems (i.e. the complex and
    unexpected combination of system interactions)
    and may not help prevent recurrence.
  • Hindsight Bias!

Accident models The challenge of hindsight bias
  • Hindsight bias is always present when the
    outcome is known a retrospective outsider can
    easily confuse post hoc reality with the actual
    reality surrounding people during the event.
  • Hindsight bias is a powerful reason for old
    view explanations for human error and accidents
    tending to look for individual components of
    the system that need fixing people deficient in
    skills or egregious mistakes.
  • Hindsight bias makes it difficult to objectively
    judge behavior leading up to the outcome. In
    particular, past complexity is transformed into a
    linear string of bad decisions, missed
    opportunities, flawed assessments, and faulty
  • Thus, recommendations too often focus on
    protecting the system from unreliable humans
    through procedures, automation, training and

Thesis work
  • The aim of the thesis work was to begin to
    explore the extent, and in what ways, safety and
    quality are conflated in healthcare, at both the
    sharp and blunt ends of care in an acute care
    institutional setting within a large health
    authority in Canada.
  • The key questions this research sought to answer
  • How are the notions of patient safety
    operationalized through local context?
  • How is safety thought about and constructed?
  • How is it discussed?
  • Is it neglected?

  • Survey work interviewed key informants
    (registered nurses working in acute care nurse
    managers responsible for acute care units and
    senior decision makers).
  • Semi-structured face-to-face interviews were
    conducted (interview guide was developed to
    support the discussion and contained a series of
    open ended questions) to find out how the key
    informants thought about safety and how they feel
    they contribute to safety on a day-to-day basis.

Interview guide (registered nurses)
  • How long have you worked as a registered nurse?
  • How do you define the term safety?
  • What factors and activities help contribute to
    patient safety at your institution, in general,
    and in particular, on your unit?
  • What do you think would improve patient safety in
    acute care hospitals, in general, and in
    particular, on your unit?

Interview guide (nurse managers and senior
decision makers)
  • What is your role in the organization?
  • How long have you worked in healthcare?
  • How do you define the term safety?
  • What factors and activities help contribute to
    patient safety at your institution?
  • What do you think would improve patient safety in
    acute care hospitals?
  • Does the work you do contribute to safety? If
    yes, in what ways?

Survey results Major themes
  • Designing robust organizations (prescriptive
  • Designing robust organizations (compliance)
  • Designing robust organizations (rules and
    procedures are important but insufficient to
    create safety)
  • Expertise and experience
  • Adaptation of work, depending on the context and
    competing priorities
  • Efficiency-thoroughness-tradeoff
  • Unpredictable notion of safety
  • Learning from near misses and critical incidents
  • Storytelling as a form of learning
  • Communication and teamwork
  • Leadership
  • Competing system challenges
  • Vigilance and troubleshooting

  • There were notable differences regarding the
    emphasis that each group placed on the respective

Thesis findings cont
  • Safety is important, but people are still looking
    for standard fixes and are influenced by
    conventional opinion leaders (e.g. Safer Health
    Care Now campaign, and Saving 100,000 Lives
  • Confusion regarding the difference between safety
    and quality exists and the confusion is greater
    at more senior levels in the organization (i.e.
    people continue to think that if you improve
    quality through standardization, guidelines,
    procedures, etc that safety will automatically
  • People at senior levels focus on the need to
    develop robust systems that are marked by
    guidelines, protocols, rules and also focus on
    training, technology, rules and enforcing
    compliance as solutions.
  • People at the front lines (the practitioners)
    understand the need to adapt their behaviour and
    practice in unusual situations, but are tentative
    in how they discuss this with both their peers
    and managers, aware of potential negative
    consequences or sanctions, if things dont work
    out well.

Thesis findings cont
  • Set of ingrained attitudes about how work is
    performed, i.e. there is no gap between work as
    imagined and work as done, i.e. work can be
    performed in a high quality manner, despite the
    context this is an easy perspective for senior
    management to adopt since it feeds off the sense,
    amongst most professional groups in healthcare,
    that they are, or should be, perfect and can
    provide high quality care under a range of
  • Lack of deep understanding of the source of
    failure in complex organizations.
  • Superficial understanding of hindsight bias and
    its impact on what you look for when you are
    doing critical incident investigations.
  • Accountability remains a thorny issue,
    particularly at the senior management and
    governance level, with little consideration of
    the accountability/authority dynamic.

  • In practical terms conflating the concepts of
    quality and safety in a complex, dynamic setting
    such as healthcare can result in investing
    efforts to solve the wrong problem and thus
    potentially misappropriates limited human and
    financial resources.
  • Besides the potential misappropriation of
    resources, if quality and safety are conflated,
    it is far too easy to assume that if one improves
    quality that safety will automatically follow,
    and thus the system, unfortunately, continues
    doing more of the same neither fully
    understanding or adequately tackling the problem.

  • Safety and quality are often conflated in health
    care and this may limit progress on both creating
    safety AND enhancing quality.
  • Safety is the attribute of being able to respond
    to surprise or instability of the
    system--creating safety involves anticipating
    what could go wrong.
  • Non linear accident models, based on an
    understanding of both high reliability and
    resilience theories, and empirical evidence from
    high risk, dynamic settings, can help us
    appreciate why safety and quality need separate
  • There were noticeable differences in how the key
    informants (from the thesis work) talked about
    safety and the perspectives of the people at the
    sharp end of the system (point of care) are
    fairly consistent with what the thought leaders
    in system safety are telling us about creating
    safety in complex dynamic environments.

  • Making progress in safety may be supported by a
    better understanding by system leaders about how
    work at the frontline actually gets done (normal
    work) as well as a better understanding about the
    necessity and value of performance variation in
    complex, dynamic systems. There needs to be
    discussion around the tension between developing
    robust systems (marked by rules, procedures etc),
    while at the same time, supporting performance
  • A dedicated interdisciplinary Safety Management
    System, with a broad mandate, is one structural
    tool that may help healthcare organizations make
    progress on safety
  • Develops an analytical framework for critically
    monitoring safety using a non linear perspective
  • Keeps the discussion of risk alive within the
  • Enables people at the sharp end to actively look
    for the things that could go wrong and understand
    how to keep these at bay
  • Surveillance activity

  • Bagian, James, Director, VA National Centre for
    Patient Safety. Personal communication, July
  • Cook, R. I., Woods, D. D., Miller, C. (1998). A
    tale of two stories Contrasting views of patient
    safety. Report from a Workshop on Assembling the
    Scientific Basis for Progress on Patient Safety
    National Patient Safety Foundation.
  • Dekker, S. W. A. (2001). Reconstructing human
    contributions to accidents The new view on error
    and performance (Rep. No. Technical Report
    2001-01). Ljungbyhed, Sweden Lund University
    School of Aviation.
  • Dekker, SWA (2002). The field guide to human
    error investigations. Bedford, UK Cranfield
    University Press/Aldershot UK Ashgate Publishing
  • Dekker, S. W. A. (2003). Errors in understanding
    of human error the real lessons from aviation
    for healthcare (Rep. No. Technical Report
    2003-01). Ljungbyhed, Sweden Lund University
    School of Aviation.
  • Dekker, SWA (2005). Ten questions about human
    error A new view of human factors and system
    safety. Mahwah, NJ Lawrence Erlbaum Associates.
  • Dekker, S. W. A. (2005). Why we need new accident
    models (Rep. No. 2005-02). Ljungbyhed, Sweden
    Lund University School of Aviation.
  • Dekker, S.W.A. Past the edge of chaos. Technical
    Report 2006-03. Lund University School of
    Aviation. Ljungbyhed, Sweden.
  • Dekker, S.W.A. Professor, Lund University School
    of Aviation. Personal communication, October
    2007, Winnipeg, Manitoba.
  • Hollnagel, E. (2004). Barriers and accident
    prevention. Aldershot, UK Ashgate Publishing Co.
  • Hollnagel, E. Woods, DD. And Leveson, N. (2006).
    Resilience engineering. Concepts and precepts.
    Aldershot, UK Ashgate Publishing Co.
  • Hollnagel, E. Theory W and theory Z Contrasting
    views on safety. Presentation. LEcole de Mines,
  • Leveson, N. (2004). A new approach to systems
    safety engineering. MIT.
  • Perrow, C. (1999). Normal accidents Living with
    high-risk technologies. Princeton, NJ Princeton
  • Reason JT. (1997) Managing the risks of
    organizational accidents. Aldershot, UK Ashgate
    Publishing Co.
  • Reinertsen, James L. and Clancy, Carolyn Foreword
    to Keeping our Promises Research Practice, and
    Policy Issues in Health Care Reliability. A
    Special Issue of Health Services Research, Vol
    41, No. 4, Part II, August 2006
  • Resar, R. Consultant, Institute for Health
    Improvement. Personal communication, July 2007.
  • Roberts, K. H. Bea, R. G. (2001). When systems
    fail. Organizational Dynamics, 29, 179-191
  • Sagan, SD (1993). The limits of safety
    Organizations, accidents and nuclear weapons.
    Princeton, NJ Princeton Paperbacks.
About PowerShow.com