1_4 Quality of Care

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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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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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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


Evidence from singlerandomized trial ornonrandomized studies


Some conictingevidence from singlerandomized trial or non-randomized studies


Greater conictingevidence from singlerandomized trial ornonrandomized studies


Evidence from singlerandomized trial ornonrandomized studies

Level CVery limited populationsevaluated*

Only consensus opinionof experts, case studies,or standard of care


Only expert opinion,case studies, orstandard of care


Only diverging expertopinion, case studies,or standard of care


Only diverging expertopinion, case studies,or standard of care


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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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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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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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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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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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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Documents

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