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Live Session
Module #1
Patient Safety at a Glance: Ch. 1
Basics of Patient Safety

HCM520

Quality and Performance Improvement

Introduction


Patient demographics shifting




Errors result due to demographics




Treating older and sicker patients

And decreased financial resources

Two reports called start of global patient safety
movement in late 1990s


To Err Is Human (1999)



An Organisation with a Memory (2000)



Recognized errors are common



Reports drew attention to poor healthcare performance



Reports called for focus on reducing risks

Introduction: WHO Programs




In 2004, WHO launched patient safety program


Worldwide patient safety still source of deep concern



Unsafe actions occur in almost every part of healthcare

Countries set up groups to deal with patient safety


National Patient Safety Agency (NPSA)


Now part of NHS England



Agency for Healthcare Research and Quality (AHRQ) in the US



Canadian Patient Safety Institute (CPSI)



Australian Commission on Safety and Quality in Health



Worldwide patient safety still source of deep concern



Unsafe actions occur in almost every part of healthcare



Many events recur with efforts to prevent them ineffective


Possibly due to punitive culture of blame and system failures

Definitions


Patient safety




Reducing risk of unnecessary harm associated with healthcare to
an acceptable minimum

Acceptable minimum


Refers to current knowledge, resources available and context in
which care is delivered, weighed against risk of non-treatment or
other treatment



Simply put – prevention of errors and adverse effects to patients
associated with healthcare

Visual of Key Definitions

Concepts


Systems thinking approach used in other industries
applies to healthcare as well



Rare that doctor or nurse to blame for error




Environment and systems play strong part

Swiss cheese model developed by James Reason to
visually explain steps and factors of adverse events

Key Points of Swiss Cheese Model


Defenses, barriers, safeguards


Protect patients from hazards



Alarms to ensure adequate pre-operative work-up of patients, for
example.



Defenses can be breached, like holes in swiss cheese



Unlike in the cheese, these hole continually open, shut, and shift
location



Presence of holes does not mean bad outcome



Holes occur due to combination of active failures and latent conditions

Active Failures




Unsafe acts by people in direct patient contact

Latent conditions


Arise from decisions made by various levels of employees/management



Translate into error-provoking conditions




Understaffing as an example

Can create long-lasting holes or weaknesses


ICU being in a different building than operating room, for example

Conclusion
 Jens Rasmussen
 Suggested errors occur for different reasons
 Skills deficiency
 Asking medical student to perform certain tasks

 Observation of rules
 Not washing hands appropriately

 Knowledge
 Unaware that certain lab values need to be

checked before procedures or medication
ordering

Global Frequency of Errors

Questions?

Health Administration Press

Chapter 1: Overview of Healthcare Quality

Chapter Outline
• History of the Quality Movement
• Frameworks and Stakeholders
• Quality Improvement Models
• Quality Improvement Tools
• Study Questions

Health Administration Press

History of the Quality Movement:
Five Important Reports
• Quality in the healthcare system is not what it should be.
• Five major reports identify gaps and call for action:
–
–
–
–

–

The National Roundtable on Health Care Quality’s “The
Urgent Need to Improve Health Care Quality” (1998)
The Institute of Medicine’s (IOM) To Err Is Human (2000)
IOM’s Crossing the Quality Chasm (2001)
The Agency for Healthcare Research and Quality’s (AHRQ)
National Healthcare Quality Report (2003–2011)
National Academies of Sciences, Engineering, and
Medicine’s report on Improving Diagnosis in Health Care

(2016)
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

IOM’s “The Urgent Need to Improve Health
Care Quality”
• “Serious and widespread quality problems exist
throughout American medicine.”
• Establishes the classification scheme of “overuse,
underuse, and misuse” to categorize quality defects

Health Administration Press

IOM’s To Err Is Human
• Captured the attention of key
stakeholders for the first time
• Framed the problem in a way
everyone could understand
• Led to the identification of
patient safety as a solidifying
force for policymakers,
regulators, providers, and
consumers

Health Administration Press

IOM’s Crossing the Quality Chasm
• Offers a new framework for a
redesigned US healthcare system
• Identifies six aims for improvement:
• Safe
• Effective
• Efficient
• Equitable
• Timely
• Patient centered

Health Administration Press

The Four Levels of the Healthcare System

The underlying
framework for
achieving the
IOM’s six aims for
improvement
depicts the
healthcare system
in four levels, all of
which require
changes.

Health Administration Press

AHRQ’s National Healthcare Quality Report
• Identifies areas and opportunities for improvement and
highlights progress that has been made
• Developed in combination with the National Healthcare

Disparities Report
• Aims to answer three questions:
• What is the status of healthcare quality and disparities in the
United States?
• How have healthcare quality and disparities changed over
time?
• Where is the need to improve health care quality and reduce
disparities greatest?
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

National Academies of Sciences, Engineering, and
Medicine’s Improving Diagnosis in Health Care
• Claims most people will experience at least one diagnostic error in
their lifetime.
• Defined as either a missed or delayed diagnosis, diagnostic errors
are thought to account for up to 17% of hospital-related adverse
events.
• Up to 5% of patients in the outpatient setting may experience a
diagnostic error.
• Recommends healthcare organizations involve patients and families
in the diagnosis process, develop health information technologies
to support the diagnostic process, establish a culture that embraces
change.
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

Frameworks and Stakeholders
• The STEEP Framework
• Stakeholders
• Measurement

Health Administration Press

IOM’s STEEEP Framework
Aim

Definition

Safe

Care should be as safe for patients in healthcare facilities as
in their homes.

Effective

The science and evidence behind healthcare should be
applied and serve as standards in the delivery of care.

Efficient

Care and service should be cost-effective, and waste should
be removed from the system.

Equitable

Unequal treatment should be a fact of the past; disparities in
care should be eradicated.

Timely

Patients should experience no waits or delays when receiving
care and service.

Patient centered

The system of care should revolve around the patient,
respect patient preferences, and put the patient in control.

Health Administration Press

Stakeholders
• Different stakeholders tend to attach different levels of
importance to the elements of the STEEEP framework.
• Clinicians
• Patients
• Payers
• Administrators
• Society/public/consumers

Health Administration Press

Measurement
• Evaluations of care quality can be classified in terms of
one of three measures:
• Structure
• Process
• Outcome

Health Administration Press

Measurement:
Structure
• Structure measures focus on the relatively static
characteristics of the individuals who provide care and the
settings in which the care is delivered.
• E.g., education, training, certification
• Structure-focused assessments are most revealing when
deficiencies are found.
• Good quality is unlikely if those who provide care are
unqualified or if necessary equipment is missing or in
disrepair.

Health Administration Press

Measurement:
Process
• Process measures focus on what takes place during the
delivery of care.
• Two aspects:
• Appropriateness: whether the right actions were taken
•

E.g., whether the correct test was ordered

• Skill: how well the actions were carried out
•

E.g., how well a surgeon completed a procedure

• The use of process measures to assess quality assumes
that if the right things are done and are done well, good
outcomes of care for the patient will result.
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

Measurement:
Outcome
• Outcome measures focus on whether the goals of care
were achieved.
•

E.g., whether a patient’s pain subsided, the condition
cleared up, or the patient regained full function

• Many factors that determine clinical outcomes (e.g.,
genetics, environmental factors) are not under the
clinician’s control.

Health Administration Press

Measurement:
Metrics and Benchmarks
• Metrics refer to specific variables that form the
basis for assessing quality.
• Benchmarks quantitatively express the level the
variable must reach.

Health Administration Press

Measurement
Type of
Measure

Focus of
Assessment

Metric

Structure

Nurse staffing in
nursing homes

Hours of nursing
At least four hours of
care per resident day nursing care per
resident day

Process

Patients undergoing Percentage of
100% receive
surgical repair of hip patients who
antibiotic on day of
fracture
received prophylactic surgery
antibiotics on day of
surgery

Outcome

Hospitalized patients Rate of falls per
1,000 patient days

Benchmark

Fewer than five falls
per 1,000 patient
days
17

Health Administration Press

Quality Improvement Models
• PDSA Cycle
• Model for improvement
• Lean/Toyota Production System
• Six Sigma
• Human-centered design

Health Administration Press

Quality Improvement Models:
PDSA

• Plan. What are you trying to accomplish? What do you think will happen?
What will you measure? Who will do what, where, and when?

• Do. Educate and train staff, carry out the plan, document problems and
unexpected observations, begin analysis of the data.

• Study. Assess the effect of the change and determine the level of success
as compared to the goal/objective, compare results to predictions,
summarize lessons learned, determine what changes need to be made.

• Act. Act on what you have learned, perform necessary changes, identify
remaining gaps in process or performance, carry out additional cycles.
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

Quality Improvement Models:
Model for Improvement

Health Administration Press

Quality Improvement Models:
Lean/Toyota Production System
• Lean manufacturing, or Toyota Production System (TPS),
focuses on the removal of waste (muda) and improving flow.
• Seven forms of waste:
•
•
•
•
•
•
•

Overproduction
Waiting
Unnecessary transport
Overprocessing
Excess inventory
Unnecessary movement
Defects

• Place the needs of the customer first.
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

Quality Improvement Models:
Six Sigma
• The aim of Six Sigma is to reduce variation in key business
processes.
• Five steps (DMAIC):
• Define
• Measure
• Analyze
• Improve
• Control

Health Administration Press

Quality Improvement Models:
Human-Centered Design
• Empathize. Thoroughly understand the motivations, needs, and concerns of
the client or user.
• Define. Translate the perspectives gained from interviewing and observing
the end user into clear design challenges and goals
• Ideate. Generate a broad array of potential solutions with minimal selfediting or concern for real or imagined limitations.
• Narrow. Identify the most promising solutions usually through the
application of specific criteria.
• Prototype. Create tangible products representing the potential future
solutions, with the goal of communicating back to the end user and further
exploring/refining ideas.
• Test. Share prototypes and gather feedback, working toward a final solution.

Health Administration Press

Quality Improvement Tools
• 7 categories of tools
• Cause analysis
• Evaluation and decision making
• Process analysis
• Data collection and analysis
• Idea creation
• Project planning and implementation
• Knowledge transfer and spread techniques

Health Administration Press

Quality Tools:
Cause Analysis
• Why is actual performance lagging behind optimal
performance or benchmarks?
• Examples of cause analysis tools:
• 5 whys
• Cause-and-effect / fishbone diagram

Health Administration Press

Quality Tools:
Evaluation and Decision Making
• Collecting, reviewing, and visualizing data can help to
identify correlations and patterns to help guide decisions.
• Examples of tools:
• Scatter diagram
• Pareto chart

Health Administration Press

Quality Tools:
Process Analysis
• Fully understanding an existing or proposed process is
a vital step in improvement.
• Examples of tools:
• Flowchart
• Failure mode and effects analysis / mistake proofing

Health Administration Press

Quality Tools:
Data Collection and Analysis
• Identifying measures, setting benchmarks, and trending
performance data is at the heart of quality improvement.
• Examples of tools:
• SMART aims
• Run charts and control charts

Health Administration Press

Quality Tools:
Idea Creation
• There is a hierarchy to improvement, with strategies like
exhortation and education at the bottom, and systems-based
interventions like checklists, automation, and forcing functions at
the top.

Health Administration Press

Quality Tools:
Project Planning and Implementation
• Tools that help to organize, prioritize, and communicate
are vital to keeping a team on track.
• Examples of tools:
• Stakeholder analysis
• Checklists
• 2×2 matrix
• 5S

Health Administration Press

Quality Tools:
Knowledge Transfer and Spread Techniques
• A key aspect of any quality improvement effort is the
ability to replicate successes in other areas of the
organization.
• Examples of tools:
• Kaizen blitz/event
• Rapid-cycle testing and pilots

Health Administration Press

Conclusion
• Healthcare quality is not what it should be.
• The patient is paramount in quality improvement
efforts.
• There is promising evidence of the capacity for
significant improvement.
• Many examples of breakthrough improvements are
happening today.
• Call to action for all healthcare stakeholders to
continue to rethink and redesign systems.

Health Administration Press

Conclusion (cont.)
• The strength of an organization depends on the
foundation on which it was built and the strength of the
systems, processes, tools, and methods used to sustain
benchmark levels of performance and to identify and
improve performance when expectations are not being
met.

Live Session
Module #13
Patient Safety at a Glance: Ch. 3
Quality and Safety

HCM520
Quality and Performance Improvement

Overview

• What is quality healthcare?
• What is safety?

• Similarities and differences between quality
and safety
• The Donabedian framework
• Approaches to improvement

Course Code and Title

Introduction to Quality and
Safety
• Started with ‘first do no harm’
• Call from Hippocrates

• Continued with call for hygiene
• Florence Nightengale

• Progress has been unsatisfactory
• Needs systems thinking

What is Quality Healthcare?
• Quality is total system characteristic

• About doing the right thing
• For the right patient
• At the right time
• With the best results
• At affordable costs
• Eight dimensions

• Timeliness, effectiveness,
safety, equity, efficiency,
caring, continuity of care,
and patient centerdness
• Quality, cost effective organization comes from
safety
• Overuse, underuse, misuse, and fraud are
common quality challenges

What is Safety?
• Fundamental system property
• Without safety, quality does
not exist
• One of most pressing
healthcare challenges
• Definition: freedom from
avoidable injuries
• James Reason’s trajectory of
errors
• Situational errors
• Unusual workload
• Power outage
• Latent errors
• Design deficiency, operation,
maintenance
• Management issues
• Active failures
• Human fallibility

Similarities/Differences of
Quality/Safety
• Eight dimensions of quality housed in protective
Donabedian encompassing ‘structure, process, outcome’
• Safe setting – vital dimension of quality, deals with
•
•
•
•
•
•
•
•

Systemic threats
Variability from patient to patient
Inconsistencies in standards
Poor interfacing
Lack of error-preventing barriers
Lack of initiative
Inappropriate time constraints
Human fallability

• Awareness allows ability to design and manage systems
with barriers to prevent errors

The Donabedian Framework

• Triad of structure ↔ process ↔ outcome helps quality evaluation
• Structural Quality
• Evaluates healthcare system capacities
• How the system is configured
• Components and inter-relationships

• Process Quality

• Assess interactions between patients/clinicians
• How care is delivered

• Outcomes Quality

• Assesses changes in health status of patients and satisfaction
• Best outcomes measured are tied to processes healthcare influences

• Donabedian offered 11 principles to support design, operation,
effectiveness of quality dome
• Supported by seven pillars of quality

• Institute for Healthcare Improvement (IHI) uses triple aim for
systems improvement in three areas
• Improving individual care experience
• Improving health of populations
• Reducing per capita costs of care

Donabedian Framework
Visual

Approaches to Improvement
• Healthcare face challenges, must be adaptive
• Quality improvement is systematic, data-driven
• Improvement approaches should meet three needs
• Creation of culture of safety/high-reliability
• Acknowledgement/treatment of setting as unique
• Facilitation of workflow, processes, task assessment and
improvement

Retrospective Quality Approach
• Retrospective methods
• Error reports (root cause), internal/external audits, trigger
tools, quality/safety indicators
• Reveals tip of quality gap iceberg
• Generalizations of results can lead to stakeholder
dissatisfaction
• Top-down, not fully meet needs

Course Code and Title

Prospective Quality Approach
• Prospective Approach based on failure
modes and effective analysis (FMEA)
• FMEA widely used in other high-risk
industries
• Advocated by Institute of Medicine to
analyze system to identify failure modes
• Identify possible consequences of failures
• Prioritize areas for improvement

Course Code and Title

Questions?

Chapter 2: History and the Quality Landscape

Chapter Outline
• Quality Measurement and Management Prior to
1965
• Medicare and Medicaid passage
• Case Mix and Risk Adjustment
• The Role of the Consumer
• Political Polarization Impact on Quality Mgmt
• Future Trends

The Three-Legged Stool of Quality Management
• Consumer empowerment
• Regular release by payers of transparent outcomes comparative
data, thereby fostering collaboration with payers
• Financial incentives

Universal Health Insurance Coverage
• A critical quality outcome measure
• The United States is the only industrialized country
without universal coverage for its citizens.

Deming, Juran, Shewhart
• The historical/nonhealthcare “giants” of quality
measurement and management
• Deming said:
– “Uncontrolled variation is the enemy of quality.”
– “Defects are not free. Somebody makes them, and
gets paid for making them.”
– A complete shift of financial risk from a payer to a
provider means that the payer has abdicated any
interest in quality.

Quality Measurement and Management before 1965
• Florence Nightingale – the first to look at outcomes –
mortality
• Codman – the first to look systematically at surgical
outcomes
• IS Falk and the Committee on the Costs of Medical Care –
group practice is the quality management way to go
• Many other researchers begin to explore new techniques,
such as Lembcke and the medical audit.

Medicare and Medicaid –
The Immediate Research Aftermath
• Avedis Donabedian – systematization of definitions of
quality – structure, process and outcomes
• Sidney Katz – development of functional status measures
• Jack Wennberg – significant variation in practice down to
a metropolitan area

Medicaid and Medicare –
The Immediate Management/ Policy Aftermath
• Regulatory apparatus put into place – Professional
Standard Review Organizations or PSROs – in an attempt
to measure quality and encourage quality improvement.
• Government expenditures for these two programs skyrocket.
• In the early 70s, the federal government began to explore
ways of controlling health care costs.

Diagnosis-Related Groups
• The three key ingredients to their development:
– Organizational management
– Public health
– Analytic infrastructure
• DRGs were first implemented in New Jersey in the 1970s.
• DRGs were focused on cost control and initially were not
linked to quality measurement and management.
• DRG implementation immediately led to a large focus
refinement for severity and new measures of quality.

• For most quality measures that consumers and payers
are interested in, risk adjustment is necessary.
Severity
and
• Need to
be Risk
sure Adjustment
that one is comparing “apples with
apples.”
• The historical debate on risk adjustment revolves
around whether or not to use claims-based data and
the proper role of information abstracted from the
clinical record.
• The field has evolved, and there is a proper role for
both.
• CMS has largely opted for claims based data—which
has continuously improved.

Medical Malpractice
• The Harvard Medical Malpractice Study: Adverse events
occurred in 3.7 percent of hospitalizations, and 27.6 percent
of adverse events were caused by negligence. Although 70.5
percent of the adverse events gave rise to disabilities lasting
less than six months, 2.6 percent caused permanently
disabling injuries and 13.6 percent led to death.
• New trends: incident reports, disclose medical errors to the
affected parties, and provide up-front payment for the cost
of the medical error
• Financial/legal limitations on malpractice suits

The Role of the Consumer Has Almost Arrived
• John Ware specified the types of information we can obtain
from consumers: patient reports (e.g., am I able to climb a
flight of stairs) and ratings (satisfaction with service provided
in a hospital) on patient health and healthcare.
• Paul Cleary and others in the 1980s and 1990s established the
science of consumer ratings of healthcare, particularly patient
satisfaction with hospital services.
• Judith Hibbard and John Wasson have contributed significantly
to the new science of “consumer activation or
empowerment.”

Politics and Quality Measurement/Management
• There is no point in having quality measures and an
outstanding, Deming-inspired quality management
system if the evidence supporting the medical
intervention is not robust.
• Unlike other industries, medical societies, device
manufacturers, and hospital associations regularly
lobby against evidence-based methods and in favor
or ineffective procedures.

Politics and Quality Measurement/Management
• As a consequence of these lobbying efforts, federal agencies
critical to the development of valid quality measures and the
best methods of quality management have lost significant
funding; some have been completely defunded.

Politics and Quality Measurement/Management–
John Kerry and Newt Gingrich wrote the following in NYT
• “Remarkably, a doctor today can get more data on
the starting third baseman on his fantasy baseball
team than on the effectiveness of life-and-death
medical procedures… Nearly 100,000 Americans are
killed every year by preventable medical errors. We
can do better if doctors have better access to concise,
evidence-based medical information… To deliver
better health care, we should learn from the
successful teams that have adopted baseball’s new
evidence-based methods.”

Future Trends in Quality Measurement/Management
• Insulin and antibiotics did not exist 100 years ago.
Dialysis and coronary artery bypass grafts were just
beginning fifty years ago. Similarly, the SF-36
measure of patient-derived rating of health,
measures of consumer empowerment, were not in
existence 50 years ago.
• Today’s quality outcomes measures are increasingly
scientifically valid. Along with case mix and risk
adjustment, they will get even better.

Three Types of Improvement in Quality Measurement
• Information abstracted from claims data will be linked easily to
information from the electronic medical record across the entire
continuum of healthcare.
• Medical (including electronic) technology will provide us with
additional information not only on individual consumers (taking
into account their genetic predisposition to certain diseases) and
their families but also the communities in which these individuals
live—much if not all of this information will be available to
consumers on a real-time basis.
• This information will be available to predict with increased
reliability the potential occurrence of adverse events and/or risks
that can be mitigated with action.

Future Trends in Quality Management
• Increased organizational consolidation of providers,
together with greater assumption of financial risk, will
heighten a focus on population health.
• The degree of politicization of quality measurement will
determine the impact that increasingly precise measures
can have.
• The number of Americans without health insurance
coverage will influence the degree to which quality
management or measurement has any overall relevance to
society.

Quality Measurement and Management in the
Future Are Dependent on Empowered Consumers
• Newly empowered consumers, along with groups of
healthcare professionals and possibly a few health
systems truly committed to population health, hold
the key to a reformed healthcare system that is truly
based on relentless quality improvement
management utilizing the measures described in this
chapter.

Study Questions
1. What is the difference between patient reports and ratings of health
and healthcare?
2. What tools and techniques have been implemented since the
Harvard Malpractice Study (choose one or more). Which do you
agree with? What more needs to be done?

3. What do you see as the future in quality measurement? What is the
role of technology? What other factors will be important?
4. What are the roles of competition and antitrust laws in the future of
quality measurement?
5. How does the consumer fit in with the manifold changes taking place
in our healthcare system?
6. In what ways should healthcare professionals become involved in
today’s polarized political environment?

Live Session
Module #2
Patient Safety at a Glance: Ch. 4
Human Factors

HCM520
Quality and Performance Improvement

Introduction


Study of clinical human factors…


Enhancing clinical performance through an understanding
of the effects of teamwork, tasks, equipment, workspace,
culture, organization on human behavior and abilities, and
application of that knowledge in clinical settings



Examines relationship between people and systems



Place humans at center of system of work, sets
precedence to provide the best environment



Allows clinicians to perform at the highest level



Provide care effectively

Originated in 1940s-1950s


Applied to most high-risk industries and consumer
products

Swiss Cheese Model
 Best known theory (introduced in Ch 1)

 Predisposed latent factors pile up in

unique situations to cause accidents,
injuries, deaths
 Cannot only blame individuals
 Need to understand the predisposed

factors always there
 Only become critical when the holes line up

Swiss Cheese Model continued




View helps the following understanding:


Humans are not the cause of accidents



Humans hold complex and deficient systems together



Humans create safety in complex systems



Accidents have their roots in organizations, not individuals



Complex, high-risk systems are inherently unsafe



Accidents signify problems deep in system



Problems can be visible but may seem innocuous



Accidents happen when problems combine

Put people at the center of the system


Provides new thinking about future healthcare and how it can be
configured and delivered

SEIPS Model


Involves people, tasks, technology, environment, and
organization



People


Center of any system, must exist in system to…


Design, operation, maintain technology or process



Perform key decision-making tasks



Work to support each other



Circumvent poor processes



Avoid errors



Trap errors as they happen



Mitigate effects of errors

Non-technical Skills and
Situational Awareness


Grouped into




Social skills


Leadership and management



Teamwork and cooperation

Cognitive skills


Problem solving and decision making



Situational awareness



Situational awareness describes how we notice
information in our environment, understand it, project
into the future



Emphasizes ability of experts to predict what may
happen to patients



Allows timely and appropriate response

Tasks


What we need to achieve a goal



Changing order of tasks can make a difference



To understand tasks, we can…



Use hierarchical task analysis to describe tasks



Use human reliability analysis techniques and failure modes
and effect analysis (FMEA) to predict likelihood and
consequences of errors



Perform direct observation



Examine different between what should happen, what people
say happens, and what actually happens

Possible to provide methods to assist with tasks such as…


Sign-posting key processes



Ensure errors are captured



Use standard methods



Use checklists



Holding briefings and debriefings

Technology and Tools


Tools can be pen and paper, checklist, could be
imaging system or device



Technology can assist people



Technology not designed with end users in mind might
not reduce errors



Technology surprises include:


Doesn’t replace need for humans



Requires them to work in different ways



Requires them to work harder, longer, faster



New skills required



Different errors possible



Different people may be better at technology



De-skill people in old tasks



Over-reliance to technology



Human interaction with technology impacts likelihood of errors



Challenge includes integrating technology with current systems

Environment



Effect of environment on human performance included
in study of human factors




Noise and lighting


Noise can be disruptive



Lighting is important for clinical work and optimal lighting
should be identified

Temperature and ventilation




Impact human performance and infection rates

Workspace and physical location


Items too high/low, without a place to be stored or off site in
storage, mislabeled reduce ability



Rooms too small increase risk and frustration, reduce
performance

Organization


Final component of SEIPS model



Considerations include…


Safety culture



Balance between throughput, cost and equality



Organizational leadership and management structure



Preventing organizational drift



Learning from safety incidents and achieving fair culture



Culture often described as ‘how we do it around here’



Variety of tools for assessing staff perception of levels
of risk and safety

SEIPS Visual

Cost and Quality Management


Care staff required to decide on trade-offs to make



Leadership sets priorities



Example:


Key performance targets and measures for finances and
throughputs with unclear quality or safety goals will lead
to increased throughput and reduced cost at the potential
expense of quality and safety



Throughput, cost and quality must have clear
expectations



Fail to recognize when safety is being traded can drift
until a tragedy occurs

Learning from Incidents


Response to incident essential to organizational ability
to learn, improve, avoid safety failures, future adverse
events



Response includes…


Debriefing of minor events



Analysis of incident reports



Root cause analysis



Look deep in the system can be difficult



Don’t blame, instead encourage fair and open culture

Summary


Performance and safety influenced by:


People at center of system



Tasks required to perform



Technology and tools



Environment



Organization



These interact with each other



Provides excellent opportunity to understand and
enhance clinical care



This application is ‘human factors’

Questions?

Live Session
Module #4
Patient Safety at a Glance: Ch. 5
Teamwork and Communication

HCM520
Quality and Performance Improvement

Introduction


Leading, recognized cause of medical failure


Breakdown in teamwork and communication



70% of events from ‘95-’03 caused by this breakdown



Training lacking for leadership



Variation in quality of non-technical skills



Communication



Situational awareness



Decision making



Teamwork

Effective communication, teamwork essential


Promotes culture of openness and safe care

Course Code and Title

Case Study



Three lapses in human factors were noted in this case
study, can you identify them? Let’s discuss

Communication


Two approaches define communication
 Information Engineering


Defines communication as ‘linear transmission of messages
through a conduit’



Accurate transmission of information



Results in the receiver understanding message



Noise is main barrier

 Social construction


Examines how people work



Inter-relationships



Behaviors in team context


how this impacts quality of team communication



Implies communication is social practice



Efforts to improve only if team improvement is parallel



Not just transmitting information, but social process of receiving
information

Teamwork
 Key features of a team…
 Consists of 2 or more individuals
 Each individual has specific role or task
 Interacts/coordinates with other members
 Team makes decisions
 Functions with high workload
 Interdependencies of workflow, collective action, goals

 Part of larger organizational system

 Priority is for teams to be coordinated and cooperative
 Members must engage in tasks and team process
 Interdependent component of performance among

multiple members

 Multilevel process develops as members engage

Characteristics of Effective Teams
 Organizational

structure
 Clear purpose
 Appropriate culture
 Specified task
 Distinct roles
 Suitable leadership
 Relevant members
 Adequate resources
 Individual contribution
 Self-knowledge
 Trust
 Commitment
 Flexibility

 Team processes
 Coordination
 Communication
 Cohesion
 Decision making

 Conflict

management
 Social relationships
 Performance
feedback

Tools to Improve




Briefings


Crucial to determine how cohesive team is



Initiated at start of task



Set tone for team interaction



Ensures care providers have shared mental model



Can establish predictability, reduce interruptions, prevent
delays, build better working relationships

Debriefings


Short exchanges at end of task



Identifies what happened, what was learned, possible
improvements

SBAR


Situation, Background, Assessment, Recommendation



Structured approach to convey information to colleague



Regular use reduces number of incidents

Conclusion


Quality of clinical skills or discrete clinical
interventions not root cause



Evidence suggests major cause of avoidable harm…


Cumulative impacts of poor communication



Sub-optimal teamwork

Health Administration Press

Chapter 5:
Statistical Tools for Quality Improvement
Chapter Outline
• Intro: Framing “Improvement”
• Process-Oriented Thinking and Statistics
• Variation: Common vs. Special Causes
• Analyzing Data over Time:
• Run Chart
• Quantifying a Process’s Inherent Variation: Control Chart
• IChart: “Swiss Army Knife” for Data over Time

• Common Cause Strategies: Stratification
• “Are We ‘Perfectly Designed’ for ‘Never Events’?”

• “Did We Make a Difference?”

Health Administration Press

Different Mindset from “Basic”
Statistics Courses
• No mention of normal distribution (assumption not
needed)… or any distribution
• Power of plotting data over time (context of “process”)
• Whether or not you understand statistics, you are
already using statistics.
• You are surrounded with daily opportunities.
• Key: understanding common vs. special causes of variation

• People tend to treat all variation as special.
• Tampering: treating common cause as special

Health Administration Press

“Safety” Concerns
Year
11
Year
Year
Year
22

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

130

122

Total

↓ 6.2 %

Want “tough” 25% reduction: What’s next?
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Everything is a process
Improving quality = Improving processes
Inputs

Conversion
action

Outputs

D
a
t
a

• GAP (VARIATION): How it currently works vs. how it should work
o Reduce inappropriate, unintended variation (more predictable)
• Inputs: people, methods, machines, materials, measurements
(data), environment
o Each input is a source of variation, reflected in output.
• Two types of variation: special (unique) and common (systemic)
ALL variation
as special
o People
Treatingtend
one to
astreat
the other
makes things
worsecause.
• The use of data is a process (4 processes):
definition, collection, analysis, interpretation (each has variation)

Health Administration Press

Reduce Variation in Analysis/Interpretation
Run chart: time-ordered plot with median as a reference line

24 months
safety concern
datacause
No change
in of
2 years:
common

Trend: Six successive increases or decreases (RARE)
Shift: Eight-in-a-row all above or all below median
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press

Point to point variation:
Does it look like this…?

Common cause
context of variation



Used as “yardstick” to
determine special cause

…or this?

Timeordered
Data

Moving Range:
ABSO(xi-x(i-1))

Moving
Range (MR)

Sorted
MR

10
14

ABSO(14-10)

ABSO(9-14)

ABSO(12-9)

ABSO(8-12)

ABSO(11-8)

ABSO(14-11)

ABSO(11-14)

ABSO(9-11)

ABSO(8-9)

ABSO(9-8)

ABSO(15-9)

ABSO(11-15)

3 Median

ABSO(10-11)

ABSO(16-10)

ABSO(6-16)

ABSO(7-6)

ABSO(8-7)

ABSO(8-8)

ABSO(12-8)

ABSO(7-12)

ABSO(14-7)

ABSO(15-14)

ABSO(8-15)

Common cause limits:
(Process average) + (3.14* x MRmed )
10.5 + (3.14 x 3) = [1 to 20]
MRmax = (3.865*x MRmed )

MRmax = (3.865 x 3) ~ 12
* From statistical theory
o Used only with MR med

7
Copyright 2019 Foundation of the American College of
10
Healthcare Executives. Not for sale.

Health Administration Press

Data points between red lines are indistinguishable:

(1) from each other
(2) from process average
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Health Administration Press
Transition: “perfectly designed”
for 50% to “perfectly designed” for ~68%

Intervention worked: need another intervention to get to 75%

What part of
“No more trend lines ever!”
don’t you understand?
1

Same data
Only 3 increases



Intervention

Health Administration Press

Two Invalid ICharts

Using overall average
and overall standard
deviation

Default of most software
(uses MRavg)
Note reduced width of limits

Health Administration Press

Correct Assessment of Guideline
Compliance Current “Process”
New process

Intervention worked
Significant performance drop

2 special cause moving ranges > 11
Copyright 2019 Foundation of the American College of
Healthcare Executives. Not for sale.

Suppose GOAL =
75?
Green: >= 75
Yellow: 70 to 74
Red:
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