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1.4: Quality o Care: Measurement and Improvement 1.4.1
inorm changes to the health care system at the practice,
hospital, and national levels. This serves to optimize health
care delivery and thus the best care possible or patients.
Why Are There Concerns About Quality?
The rapid growth o health care spending in the United States
has ocused increased attention on the quality o care that results
rom this large commitment o resources. Unortunately, when the
quality o health care in the United States is measured, signicant
deciencies are ound. Moreover, there is a lack o correlation
between higher expenditures and higher quality o care.1
Poor quality results rom a variety o deciencies in any one o the
properties o high-quality health care, including: unsae practices,
use o ineective therapies, application o the wrong therapy to the
wrong patient, delayed delivery o care, use o resource intensive
care or marginal benet, and dierential health care delivery strictly
based on age, gender, race, or ethnicity. Decits in the quality o
health care are also ramed as deriving rom three types o short-
comings, each o which may constitute a orm o ineciency.2
Overuse occurs when a service is provided that may not
be necessary or may expose the patient to greater potential
harm than benet (i.e., when it is not warranted on medical
grounds).
Underuse occurs when a service with a avorable benet-
risk ratio is not provided.
Misuse includes incorrect diagnoses as well as medical er-
rors and other sources o avoidable complications.
One o the most compelling arguments implicating the eciency
o health care in the United States derives rom the marked
geographic variation in per capita health care spending, without
Introduction
Clinicians may perceive the topic o measuring and improv-
ing quality o care as one that is largely under the purview
o administrators and health policy makers. Instead, clinicians
should be highly motivated to understand how to measure and
improve quality o care or a variety o reasons, including:
Quality o care is evidence-based medicine.Quality
measurement and improvement initiatives help clinicians to
stay current with the best available evidence or therapeu-
tics and care delivery, thereby supporting the practice oevidence-based medicine.
Quality o care is central to lielong learning, certifca-
tion, and licensure. The maintenance o certications, as
well as state licensure activities, is increasingly centered on
quality measurement and improvement. This may include
the demonstration o practice improvement.
Quality o care is at the center o health care reorm.
Consumer groups, hospitals, health care systems, payers,
states, the ederal government, and other stakeholders
are heavily ocused on quality o care. There is a particular
ocus on unexplained variation in care delivery. This varia-tion is viewed as a marker o variation in quality, as a major
contributor to health care expenditures, and as a target or
health care reorm.
Quality o care is increasingly about accountability.
Public reporting and perormance-based reimbursement are
increasingly based on quality measures or both processes
o care and outcomes o care.
Quality o care drives health care system improve-
ment. Quality measurement and improvement initiatives
Chapter 1: General Principles
1.4: Quality of Care: Measurement and ImprovementLarry Allen, MD, FACC
Consulting Fees/Honoraria: Ortho-McNeil Janssen Scientifc Aairs, Robert Wood Johnson Foundation, Amgen;
Research Grants: American Heart Association
John S. Rumsfeld, MD, PhD, FACC
Consulting Fees/Honoraria: United Healthcare
Learner Objectives
Upon completion o this module, the reader will be able to:
1. Dene quality o care and describe the major domains o high quality health care.
2. Explain the eatures o quality initiatives that are relevant to practicing clinicians, including delivery o evidence-based medicine,
public reporting and reimbursement based on quality metrics, and maintenance o certication and licensure.
3. Compare and contrast the tools o quality, including clinical data standards, clinical practice guidelines, quality metrics, peror-
mance measures, and appropriate use criteria (AUC).
4. Describe the health care system eatures that are necessary to achieve high quality care, including measurement, eedback,
system changes, engaged clinicians, and administrative support.
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1.4.2 Chapter 1: General Principles
Process reers to the way in which care is delivered. The ideal
process is to do the right thing or the right patient at the right
time. Processes reer to the actions perormed in the delivery
o patient care, including the timing and technical competency
o their delivery. Process o care measures oten ocus on patient
selection and administration o therapies (e.g., prescription o
aspirin or patients with acute myocardial inarction).
Outcomes reer to the results o care. These are measures o
the end-results o health care delivery. From the patient,clinician, and societal perspectives, primary outcomes concepts
are refected in just two questions. The rst question is related
to mortality versus survival: Did the care/therapy delivered help
patients live longer? The second question is related to morbid-
ity versus quality o lie: Did the care/therapy improve patient
health status and/or make patients eel better? For a variety o
reasons, outcomes measures have ocused largely on survival,
which is objective and easy to obtain, or on surrogate measures
(e.g., blood pressure). However, there is a growing recognition
o the importance o patient-centered outcomes, including
patient health status or quality-o-lie measurements such as
angina burden (e.g., Seattle Angina Questionnaire).
The Donabedian model proposes that each component has a
direct infuence on the next. In other words, the structural at-
tributes o the system in which care occurs (i.e., resources and
administration) dictate processes o care (i.e., delivery o thera-
peutics) which in turn aect the outcomes (i.e., goal achieve-
ment). Importantly, the patient is at the center, with the ultimate
goal o improving outcomes that are important to patients and
their amilies.
It is also important to note that patients have dierent demo-
graphic and clinical proles (e.g., comorbidities, disease sever-
ity). Thus, clinicians and hospitals care or dierent case-mixes
o patients. As such, it is generally true that valid measures o
patient outcomes, especially or comparison among hospitals or
other groups, must be risk-adjusted (i.e., case-mix adjusted).
What About Cost?There is an increasing interest in assessing quality in relation-
ship to resource use. Multiple studies have shown that higher
costs o care and higher resource utilization do not translate
into higher quality o care.2 Thereore, many current quality as-
sessment and improvement eorts are ocused on eciency o
care (i.e., cost per outcomes). A similar concept is that o value,
which is the measurement o patient health outcomes, including
the patient experience with care, achieved per dollar spent.
9
It isthe ratio that is critical. Costly interventions are not necessarily
o low value, i they have signicant benet. Conversely, cheap
interventions are not necessarily o high value, i they have
minimal or no benet.
A Systems Problem, A Systems SolutionFor most clinicians, day-to-day interest in quality would seem
to ocus on individual decisions as they relate to the delivery o
cardiovascular care to individual patients. However, quality im-
provement cannot rest upon individual clinicians being asked to
do more or do better.10 Instead, quality should be consid-
obvious correlation to measures o health care quality or patient
outcomes. The current substantial growth in the perormance
o cardiovascular testing and procedures has been character-
ized by increasing regional dierences, as documented among
Medicare beneciaries in the Dartmouth Atlas o Cardiovascular
Health Care.3 Yet, those regional dierences in use do not ap-
pear to translate to signicant dierences in the perormance o
well-accepted standards o care or the health o those commu-
nities.4 Furthermore, the Institute o Medicine (IOM) and others
have issued several reports documenting the extent o medical
errors and their consequences.5,6 Clinicians must recognize that
their actions, both in terms o errors o omission (i.e., not doing
things they should) and errors o commission (i.e., doing things
they should not), are under increasing scrutiny.
What Is High Quality Health Care?
The goal o health care is to help people live longer and better
lives. Thereore, the extent to which health care delivery accom-
plishes this overall goal represents the quality o that care. The
IOM report, Crossing the Quality Chasm: A New Health System
or the 21st Century, denes quality as: the degree to which
health care systems, services, and supplies or individuals and
populations increase the likelihood or desired health outcomes
in a manner consistent with current proessional knowledge.7
The IOM urther dened six domains o the highest quality
health care, health care should be:7
Sae: Avoiding harm to patients rom the care that is
intended to help them
Eective: Providing services based on scientic knowledge
to all who could benet and reraining rom providing ser-
vices to those not likely to benet (avoiding underuse and
misuse, respectively)
Patient-Centered: Providing care that is respectul o and re-
sponsive to individual patient preerences, needs, and values,
and ensuring that patient values guide all clinical decisions
Timely: Reducing waits and sometimes harmul delays or
both those who receive care and those who give care
Efcient: Avoiding waste, including the waste o equip-
ment, supplies, ideas, and energy
Equitable: Providing care that does not vary in quality be-
cause o personal characteristics such as gender, ethnicity,
geographic location, and socioeconomic status
How Should We Assess Quality?
The Donabedian model is requently used to conceptualize
quality assessment. It ocuses on three domains: structure,
process, and outcomes.8
Structure reers to the resources available to provide care. This
typically includes such domains as personnel, equipment, acili-
ties, laboratory systems, training, certication and protocols.
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1.4: Quality o Care: Measurement and Improvement 1.4.3
Evidence-based medicine involves two undamental principles.11
First, a hierarchy o evidence exists rom which to guide clinical
decision making. While individual clinical observations can generate
important hypotheses, unsystematic clinical observations are limited
by sample size and deciencies in the ability to make accurate
causal inerences. Thus, only systematic approaches to data col-
lection and analysis are generally considered as evidence to guide
clinical decisions. These systematic approaches, listed in increasing
order o strength o evidence or inorming clinical decision mak-
ing, include: physiological experiments, case series, cross-sectional
studies, case-control studies, retrospective observational cohorts,prospective observational cohorts, and randomized clinical trials.
Stronger study designs minimize bias and improve power, leading
to improved evidence to support clinical decision making.
It is important to note that this evidence hierarchy is not
absolute. For example, randomized clinical trials can suer rom
studying only highly selected patients, and thus may have
limited generalizability. Similarly, observational studies must be
cautious o unmeasured actors that can conound the interpre-
tation o attribution, yet may give a broader assessment o care
and outcomes in routine clinical practice. Thus, a synthesis o all
ered largely on a system level. As such, quality improvement is
achieved through a systems approach that provides a supportive
environment or the delivery o health care. Continuous quality
improvement is an organized, scientic process or evaluating,
planning, improving, and controlling quality. The ollowing sec-
tions describe the pieces o continuous quality improvement and
how they t together to promote optimal care delivery both at
the national and local levels.
The Tools of Quality Assessment
The success o achieving ideal quality in health care delivery
requires that a quality inrastructure be in place. This quality
inrastructure consists o clinical evidence, standardized deni-
tions, clinical guidelines, perormance measures and other
quality metrics, and AUC (Table 1). The goal o these tools is to
promote the optimal use o evidence-based medicine in care
delivery, thereby maximizing eciency by promoting diagnostic
and therapeutic strategies with the highest value to patients.
The EvidenceThe determination o care quality is grounded in clinical evidence.
Table 1The Toolkit of Quality Improvement
The Toolkit of Quality Improvement
Tool Definition / Purpose
Evidence
Data
Standards
Clinical
Practice
Guidelines
Process
Performance
Measures
Appropriate
Use Criteria
Outcomes
Measures
Data on associations between actions and outcomes; derived from a hierarchy of
scientic research:
Unsystematic clinical observation
Physiological experiments
Expert opinion
Case series
Cross-sectional studies
Case-control studies
Retrospective observational cohorts
Prospective observational cohorts
Randomized controlled trials
Agreed upon denitions, nomenclature, and data elements; facilitate accurate
communication and fair comparison
Detailed summary of the body of evidence-based medicine for a given disease process
or clinical content area; includes specic recommendations for standards of care,
graded on level (I, IIa, IIb, III) and type of evidence (A, B, C)
Discrete processes of care that imply that clinicians are in error if they do not care for
patients according to these clinical standards; must also allow for practical identication
of those patients for whom a specic action should be taken (a clear denominator), easy
determination of whether or not the measure has been performed (a clear numerator),
and opportunities for timely feedback
Identify common, prototypical patient subgroups for which expert clinicians assess the
benets and risks of a test or procedure on patient outcomes (score 1-9); primary goal
is to reduce overuse, thereby improving safety and efciency
Measures of health that are important to patients and are through to be affected by
processes of care; generally require risk-standardization to account for case mix
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1.4.4 Chapter 1: General Principles
available evidence, such as in a systematic review and/or
evidence-based clinical practice guideline, may enhance the
assessment o benets and risks o a given therapy. A systematic
review will provide guidance or care decisions above and
beyond any single study.
The second undamental principle is that evidence alone will
never be sucient to make a clinical decision. Decision mak-
ers must always integrate and trade the benets, risks, incon-
veniences, and costs associated with alternate management
strategies. This should be done within the context o patients
goals, values, and preerences.
Data StandardsStandardized sets o denitions, nomenclature, and data ele-
ments acilitate accurate communication and air comparison.
They help avoid the Tower o Babel syndrome with the in-
ability to accurately compare clinical trials and other outcomes
assessments due to diering denitions o clinical status and
adverse outcomes. The American College o Cardiology (ACC),
in association with the American Heart Association (AHA), has
implemented Clinical Data Standards, the lexicon needed to
achieve commonality and consistency in denitions in many
areas o cardiovascular disease.12 Standardized denitions allow
accurate comparisons between multiple relevant clinical trials
as well as clinical outcomes collected through clinical registry
programs.13
Clinical Practice Guidelines
The creation o clinical guidelines is intended to summarize thebody o evidence-based medicine or a given disease process or
clinical content area. Preerably these guidelines are based upon
multiple large, randomized controlled trials. When substantial
randomized clinical trial data are lacking, smaller clinical trials,
careully perormed observational analyses, or even expert
consensus opinion is utilized as the weight o evidence or a
particular clinical guideline. Over the past 25 years, the ACC
and the AHA have published multiple cardiovascular clinical
guidelines covering many relevant areas o cardiology, with
continued updating as clinical advances dictate. These include
Figure 1Levels of Evidence for Clinical Practice Guidelines
Reproduced with permission rom The Evidence-Based Medicine Working Group. Users Guide to the Medical Literature: A Manual or Evidence-Based
Clinical Practice. 2nd ed. Chicago: American Medical Association Press.
Class IBenefit >>> RiskProcedure/Treatment
Should beperformed/administered
Class IIaBenefit >> Risk
Additional studieswith focusedobjectives needed
It is reasonable to
perform procedure/administer treatment
Class IIbBenefit Risk
Additional studies withbroad objectives needed;additional registry datawould be helpful
Procedure/Treatmentmay be considered
COR III:No Benefit
NotHelpful
No ProvenBenet
COR III:Harm
Excess Cost w/oBenet or Harmful
Harmful toPatients
tClass III No Benefi
or Class III Harm
Level AMultiple populationsevaluated*
Data derived frommultiple randomizedclinical trials ormeta-analyses
Recommendation thatprocedure or treatmentis useful/effective
Sufcient evidence frommultiple randomizedtrials or meta-analyses
Recommendation infavor of treatment orprocedure being useful/effective
Some conictingevidence from multiplerandomized trials ormeta-analyses
Recommendationsusefulness/efcacyless well established
Greater conictingevidence from multiplerandomized trials ormeta-analyses
Recommendation thatprocedure or treatmentis not useful/effectiveand may be harmful
Sufcient evidence frommultiple randomizedtrials or meta-analyses
Level BLimited populationsevaluated*
Data derived from asingle randomized trialor nonrandomized
studies
Recommendation thatprocedure or treatmentis useful/effective
Evidence from singlerandomized trial ornonrandomized studies
Recommendation infavor of treatment orprocedure being useful/effective
Some conictingevidence from singlerandomized trial or non-randomized studies
Recommendationsusefulness/efcacyless well established
Greater conictingevidence from singlerandomized trial ornonrandomized studies
Recommendation thatprocedure or treatmentis not useful/effectiveand may be harmful
Evidence from singlerandomized trial ornonrandomized studies
Level CVery limited populationsevaluated*
Only consensus opinionof experts, case studies,or standard of care
Recommendation thatprocedure or treatmentis useful/effective
Only expert opinion,case studies, orstandard of care
Recommendation infavor of treatment orprocedure being useful/effective
Only diverging expertopinion, case studies,or standard of care
Recommendationsusefulness/efcacyless well established
Only diverging expertopinion, case studies,or standard of care
Recommendation thatprocedure or treatmentis not useful/effectiveand may be harmful
Only expert opinion,case studies, orstandard of care
Levels of Evidence for Clinical Practice Guidelines
Size of Treatment Effect
EstimateofCert
ainty(Precision)ofTreatmentEffect
Procedure/test
Treatment
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1.4: Quality o Care: Measurement and Improvement 1.4.5
ity in routine practice; 2) practical identication o those patients
or whom a specic action should be taken (a clear denominator);
3) easy determination o whether or not the measure has been
perormed (a clear numerator); 4) adherence to the measure
results in meaningul improvements in clinically meaningul out-
comes; and 5) opportunities or timely eedback to clinicians and
institutions to promote continuous quality improvement.19
Process Performance Measures
Process perormance measures are distilled rom clinical guide-line therapeutic recommendations, generally capturing those
Class I or Class III, Level o Evidence A recommendations or
which the evidence is particularly strong. Process perormance
measures describe discrete processes o care that are explicit
diagnostic or therapeutic actions to be perormed or not per-
ormed (e.g., the provision o aspirin or acute myocardial inarc-
tion). The implication is that clinicians are in error i they do not
ollow these care processes or do not document specic reasons
or disregarding these recommendations.
Outcome Performance Measures
Outcome perormance measures are being increasingly used as
perormance measures. Adding outcomes measures to process
measures has important benets. For example, process mea-
sures, even when reported together, capture a small raction
o the care delivered; in contrast, outcomes measures, such
as mortality or health-related quality o lie, should integrate
the totality o care that a patient receives.20 The government
website, Hospital Compare, reports 30-day r isk-standardized
mortality and rehospitalization rates or ee-or-service Medicare
beneciaries ater hospitalization or heart ailure, acute myo-
cardial inarction, or pneumonia.21 These statistics are used or
reimbursement purposes.
Critiques o outcomes measures include, or example, that
the methods or risk-standardization are not suciently air to
account or important dierences in case mix. Also, outcomes
measures do not tell clinicians and institutions specically what
they are doing correctly or incorrectly. Thereore, risk-standard-
ized outcomes measures should be combined with detailed
measures o structure and process perormance, thereby provid-
ing clinicians and institutions with audit and eedback on their
overall perormance alongside data highlighting those areas in
particular need o quality improvement activities.
Composite Measures
Composite measures have been constructed and deployed to
address the prolieration o perormance measures and the need
to ensure that these measures comprehensively represent health
care quality.22 Composite measures utilize data reduction in
order to simpliy presentation and interpretation. They also pro-
mote scope expansion to better integrate multiple metrics into a
more comprehensive assessment o provider perormance. How-
ever, these advantages come at a cost. Standard psychometric
properties o composites can be more complex to determine,
methods or scoring (e.g., all-or-none vs. any vs. weighting) can
lead to dierent conclusions, and problems with missing data
acute myocardial inarction, unstable angina, chronic stable
angina, coronary revascularization, heart ailure, supraventricu-
lar arrhythmias, atrial brillation, implantation o pacemakers,
and antiarrhythmia devices.14 These practice guidelines are
intended to assist health care providers in clinical decision mak-
ing through describing generally acceptable approaches or the
diagnosis, management, or prevention o disease states.15-17
Figure 1 provides a ramework or evaluating various procedures
and treatments. The ramework includes both levels o evidenceand types o evidence.16
Levels o Evidence: Recommendations are given one o the
ollowing indication classications based on the evaluation o
evidence by a panel o guidelines experts.
Class I: procedure or treatment should be perormed or
administered; the benet to risk ratio is avorable.
Class IIa: it is reasonable to perorm the procedure or treat-
ment; benet to risk ratio is probably avorable.
Class IIb: procedure o treatment may be considered; ben-et to risk ratio is unknown.
Class III: the procedure or treatment should not be per-
ormed; no benet or risk outweighs benet.
Types o Evidence: The weight o evidence to support a given
recommendation is listed as A, B, or C. The highest level o
evidence, A, implies data derived rom multiple randomized tri-
als, while the lowest level o evidence, C, refects the consensus
opinion o experts, case studies, or standard o care.
Although we would like guidelines to be based on the high-
est level o evidence in the hierarchy, multiple actors (e.g., the
diculty o conducting large randomized trials) limit the extent
to which the wide array o clinical decisions can be strongly
recommended. O the 16 ACC/AHA clinical practice guidelines
that report levels o evidence in September 2008, only 11% o
2,711 recommendations were classied as Level o Evidence A,
whereas 46% were level C.17
Performance MeasuresPerormance, or care accountability, measures are those process,
structure, eciency, and outcome measures that have been de-
veloped using ACC/AHA methodology. This includes the process
o public comment and peer review and the specic designa-
tion as a perormance measure by the ACC/AHA Task Force onPerormance Measures.18,19 This may occur in collaboration with
other national practice organizations and ederal agencies, such
as the National Quality Forum (NQF), Centers or Medicare and
Medicaid Services (CMS), or the Joint Commission on Accredita-
tion o Health Care Organizations.
Perormance measures must have a number o qualities that al-
low them to be used or both continuous quality improvement as
well as accountability and reimbursement, including: 1) ace valid-
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1.4.6 Chapter 1: General Principles
or various common clinical scenarios. Additionally, a complete
evaluation o appropriateness might also include a compari-
son o the relative marginal cost and benets o each imaging
modality. Regrettably, there is currently insucient evidence to
make such evaluations across a broad spectrum o potential
clinical indications or diagnostic and procedural decisions.
Quality Improvement
The tools o quality assessment t into a comprehensive cycle o
activities that work to dene, measure, and ultimately promote
quality health care (Figure 2).24 Discoveries rom basic science
are translated into clinical diagnostics and therapies. These are
then tested in clinical trials to determine ecacy and saety. This
evidence is then synthesized into clinical practice guidelines,
which are made available or consumption. A select group o
can be amplied.
Quality MetricsQuality metrics are those measures that have
been developed to support sel-assessment
and quality improvement at the provider, hos-
pital, and/or health care system level.18 These
metrics are oten a major ocus o clinical
registry and quality improvement programs.13
These metrics may not have been ormally
developed using the ACC/AHA perormance
measure methodology. However, they may
be identied as preliminary, candidate,
test, evolving, or quality measures,
which indicates that they may be worthy o
consideration or urther development into
perormance measures. Quality metrics may
not meet all specications o ormal peror-
mance measures used in public reporting and
accountability, but can still represent valuable
tools to aid clinicians and hospitals in improv-
ing quality o care and enhancing patient
outcomes.
Appropriate Use CriteriaAUC are intended to be a supplement to
clinical practice guidelines and perormance
measures, and dier rom them in important
ways. AUC identiy common, prototypical
patient subgroups or which expert clinicians,
using available evidence rom the medical
literature and clinical practice, assess the
benets and risks o a test or procedure on
patient outcomes. AUC are scored as ollows:
a score o 7-9 means appropriate, 4-6 meansuncertain, and 1-3 means inappropriate.23 Ide-
ally, AUC dene what to do, when to do,
and how oten to do a certain modality or
procedure, with consideration or local care
environments and patient goals, preerences,
and value. AUC should ideally be simple,
reliable, valid, and transparent. AUC oer a
ramework rom which to examine the ratio-
nale o diagnostic and therapeutic actions to support a more
ecient use o medical resources. The primary goals o AUC
are to identiy overuse and in so doing, improve the saety and
cost-eectiveness o care.
The ACC, in partnership with relevant specialty and subspecialty
societies, has been developing an increasing portolio o AUC
in a variety o diagnostic modalities (e.g., cardiac computed
tomography, cardiac magnetic resonance imaging, cardiac
radionuclide imaging, transthoracic and transesophageal echo-
cardiography, stress echocardiography) as well as procedural
modalities (e.g., coronary revascularization).
Ideally, such AUC would arise rom high-quality research
evaluating the benets and risks o perorming imaging studies
Figure 2The Cycle of Quality
A cycle o specic eorts is needed to create systematic approaches to translating knowledge
across the continuum rom discovery science to public health intervention. The cycle begins
with the discovery o undamental biological, physical, and social constructs. Once a discovery is
made, it undergoes a development cycle including extensive preclinical applied research beore
it can be developed as a treatment with plausible human benet. Evidence is then gathered
in human experiments, and assessments are made about the interventions value; these
evaluations continue ater the treatment is clinically available. What is learned through the cycle
is oten ed back to rene the science o discovery. At the clinicians level, measurement and
education are central to completing the cycle.
Reproduced with permission rom Cali RM, Harrington RA, Madre LK, Peterson ED, Roth D,
Schulman KA. Curbing the cardiovascular disease epidemic: aligning industry, government,
payers, and academics. Health A (Millwood) 2007;26:62-74.
The Cycle of Quality
Measurement
and
Education
Discoveryscience
Outcomes
Performancemeasures
Earlytranslational
steps
Clinicaltrials
Clinicalpractice
guidelines
DataStandards
3
Networkinformation
4
Empirical
ethics
5
Priorities andprocesses
6
Inclusiveness
7
Use forfeedback
on priorities
8
Conict-of-interestmanagement
9
Evaluation ofspeed and uency
10
Pay-for-performance
11
Transparencyto consumers
12
FDACritical Path
1
NIHRoadmap
2
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1.4: Quality o Care: Measurement and Improvement 1.4.7
these guidelines are condensed into perormance measures,
which are used or benchmarking, public reporting, and pay
or perormance. Outcomes measures provide assessment o
how well this process is achieving its ultimate goals. Any o this
inormation can be ed back into the cycle to guide and reocus
quality eorts at all steps.
National Quality Improvement Registry ProgramsThe oundation o any quality improvement eort is measure-
ment. Without systematic assessment and evaluation, it is dicult
to know the quality o various care decisions. Participation in na-
tional clinical registries and quality improvement programs, such
as the National Cardiovascular Data Registry (NCDR), oers
a method or accurately assessing clinical outcomes and oers
eedback on how individual hospital and clinician practices com-
pare with their peers. This is done through benchmarking peror-
mance against aggregate national or similar hospital outcomes
ollowing adjustment or case mix (Figure 3).13,25 Participation in
these eedback systems is known to be a critical element in qual-
ity improvement. The eedback o process and outcomes data to
clinicians pinpoints opportunities to improve clinical perormance
and quality. For example, they can also be used to help state
regulatory agencies oversee the quality o demonstration projects,
such as percutaneous coronary intervention (PCI) without onsite
surgical backup. They also oer opportunities or post-market
device surveillance, particularly or low requency adverse events.
National Quality InitiativesNational quality initiatives can also be eective. One illustrative
example is the Door-to-Balloon Alliance. It is known that PCIs
or acute myocardial inarction are grounded in the principle o
rapid reperusion. There is strong evidence that a shorter time
rom patient presentation (i.e., emergency room door) to
coronary artery opening via angioplasty (i.e., balloon infa-
tion in the catheterization laboratory) is associated with better
patient outcomes, particularly when these door-to-balloon (D2B)
times are less than 90 minutes.
However, despite D2B recommended quality measures being
in place or years, as o 2006 only 40% o hospitals were able
to consistently perorm primary PCI in less than 90 minutes. A
team o cardiovascular outcomes researchers evaluated hospitals
with best practices and identied the key processes o care that
were associated with shorter D2B times. Six o these strategies
became the core strategies o the D2B Alliance. These are: hav-
ing emergency medicine physicians activate the catheterization
Figure 3Example of a Quality Metrics Report From the NCDR CathPCI Executive Summary
Reproduced with permission rom Rumseld JS, Dehmer GJ, Brindis RG. The National Cardiovascular Data Registry Its Role in Benchmarking and
Improving Quality. US Cardiology 2009;Touch Briefngs:11-15.
Example of a Quality Metrics Report
from the NCDR CathPCI Executive Summary
Percutaneous Coronary Intervention Quality Measures
My hospital: 1.02% (rank: 118 of 366; rank percentile: 68)
Your hospitals PCI morality rate adjusted using the ACC-NCDR
risk adjusted model (detail line: 1,732)
Risk-adjusted Mortality
1.251.7124.4 0.94 0.73
Lagging Leading
Proportion of STEMI Patients with DBT 90 Minutes
My hospital: 65% (rank: 87 of 389; rank percentile: 78)
The proportion of primary PCI patients with DBT 90 minutes.
The goal is to have a DBT of 90 minutes for all non-transferred
patients having STEMI and having primary PCI (detail line: 1,767)
50.036.423.9 63.0 76.9
Lagging Leading
BetterWorse
My hospital: 2.7% (rank: 286 of 401; rank percentile: 68)Includes procedures with at least one vascular complication
(detail line: 2,029)
Incidence of Vascular Complications
1.93.04.3 1.1 0.5
LeadingLagging
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1.4.8 Chapter 1: General Principles
Figure 4The Central Role of Data and Benchmarking in Quality Improvement
EMR = electronic medical record.
Adapted with permission rom Rumseld JS, Dehmer GJ, Brindis RG. The National
Cardiovascular Data Registry Its role in Benchmarking and Improving Quality. US
Cardiology 2009;6:11-5.
The Central Role of Data and Benchmarking
in Qualty Improvement
System ChangesEMR
Standing orders
Critical pathways
Integrated care
BenchmarkingData
Clinical Leaders
Administrative Support
laboratory, having a single call to a central page
operator activate the catheterization laboratory,
having the emergency department activate the
catheterization laboratory while the patient is en
route to the hospital, expecting sta to arrive in
the catheterization laboratory within 20 minutes
ater being paged, having an attending cardi-
ologist always on site, and having sta in the
emergency department and the catheterization
laboratory use real-time data eedback.26
The ACC thereby supported the national D2B
Alliance to promote participation by hospitals,
physician champions, and strategic partners com-
mitted to addressing the D2B challenge. Partici-
pating hospitals committed to implementing as
many o the six strategies as possible. The goal o
the D2B Alliance was to achieve D2B times o
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1.4: Quality o Care: Measurement and Improvement 1.4.9
programs (such as national clinical registry programs) is also
important, oten providing a solid inrastructure or quality mea-
surement and improvement.
Local activities or quality improvement should be iterative and
involve breaking down quality eorts into small pieces. Multiple
small quality cycles should be occurring in various domains o
local health care delivery, involving multidisciplinary members o
the team. The quality initiatives should be supported by adminis-
tration and aligned with external entities (i.e., regulatory agenciesand national quality improvement initiatives). For example, a hos-
pital with a high risk-adjusted mortality rate among its patients
with acute myocardial inarction cannot set on a single course
o action to x this problem. Instead, it is necessary to have an
integrated approach involving multiple smaller initiatives within
the continuum o care. This could include community education,
emergency medical services, the emergency department, the
interventional catheterization laboratory, in-hospital care, transi-
tional services, and ambulatory ollow up. Measurement within
each level should target areas or improvement.
At the individual and local level, the Institute or Health Care Im-
provement (IHI) promotes the Model or Improvement, developed
by Associates in Process Improvement.28 The model organizes qual-
ity improvement into actionable parts.
1. Set Aims: These should be small goals that are targeted to
a defned group o patients. They should be time-specifc
and measureable.
2. Establish Measures: Pick a quantitative measure that can
determine i a specifc change leads to an improvement in
quality.
3. Select Changes: All improvement requires making
changes but not all changes result in improvement.
Clinicians and organizations must identiy the changes that
they believe are most likely to result in improvement.
4. Test Changes: Once the frst three undamental questions
have been answered, the Plan-Do-Study-Act (PDSA) cycle
should be used to test and implement changes in real work
settings. The PDSA cycle uses action-oriented learning to
determine i the change is an improvement. This is done by
planning it, trying it, observing the results, and acting on
what is learned (Figure 5).
Including the right people on a process improvement team iscritical to a successul improvement eort. Teams vary in size
and composition, but typically involve multidisciplinary represen-
tation.
Conclusion
For clinicians who want to deliver the best possible care, be
graded and reimbursed appropriately, and maintain certica-
tion and licensure, understanding quality and being engaged in
quality measurement and improvement must become central to
clinical practice. Feedback o process and outcomes are critical
elements leading to quality improvement. I you do not measure
it, you will not improve it.
Key Points
Health care quality is highly relevant to patients, clinicians,
and society.
The highest quality health care is that which is eective,
sae, timely, ecient, equitable and patient centered.
The major domains o quality assessment are structure,
process, and outcomes (Donabedians triad).
Key tools or dening and measuring quality o care
include: evidence, data standards, clinical practice
guidelines, quality metrics, perormance measures, and
appropriateness criteria.
Quality improvement requires accurate data collection,
risk-adjustment and benchmarking to make perormance
measurement meaningul, persistent and iterative cycles o
quality improvement, clinician champions, and a supportive
organizational context.
National clinical registry programs such as the NCDR utilize
data standards, standardized tools or data collection, risk-
adjustment, and benchmarking.
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