OPEN FORUM
Measuring Performance in Psychiatry: A Call to Action
Sherry A. Glied, Ph.D., Bradley D. Stein, M.D., Ph.D., Thomas G. McGuire, Ph.D., Rhonda Robinson Beale, M.D.,
Farifteh Firoozmand Duffy, Ph.D., Samantha Shugarman, M.S., Howard H. Goldman, M.D., Ph.D.
Many recent public and private strategies aimed at improving the
quality and efﬁciency of the U.S. health care system focus on
measuring, reporting on, and providing incentives for improving
quality. In behavioral health care, despite recent efforts, quality
measurement for even the more common conditions is less well
developed than for comparable general medical conditions. The
absence of a comprehensive set of well-accepted measures
capable of demonstrating the value of behavioral health treatment
Many recent public and private strategies aimed at improving
the quality and efﬁciency of the U.S. health care system focus
on measuring, reporting on, and providing incentives for
improving quality. Beginning in 2014, for example, all clinicians participating in the Medicare meaningful use incentive
program will be required to report on a set of clinical quality
measures drawn from the U.S. National Quality Strategy (1).
Similarly, the Medicare Shared Savings Program rewards
accountable care organizations (ACOs) only if they meet
measured quality standards (2). Although quality measurement is increasingly popular and important, the development,
dissemination, reporting, and use of valid quality measures
are challenging problems across all health care (3). Assessing
quality is particularly difﬁcult in behavioral health care, where
despite recent efforts, quality measurement for even the more
common conditions is less well developed than for comparable
general medical conditions (4,5).
In their quest for quality measurements, the National Quality
Forum (NQF) has identiﬁed more than 700 measures. Many of
these are relevant and important in psychiatric practice (for example, measures of care coordination), but only 30 are directly
linked to behavioral health care. Most of the behavioral health
measures focus on the treatment process, not on outcomes. Given
the increased attention to and importance of measuring the value
of health care, the limited number of well-deﬁned and widely
accepted quality measures of behavioral health treatment puts
the practice of psychiatry at a disadvantage in demonstrating
value and moving forward with the implementation of meaningful provider performance ratings and pay for performance.
The absence of a comprehensive set of well-accepted
measures capable of demonstrating the value of treatment
makes substantiating the value of behavioral health treatment
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makes building a case for devoting resources to treatment more
difﬁcult. This Open Forum reviews the current state of behavioral
health quality measurement, describes the criteria relevant to
assessing measures, and provides a case for encouraging the
development, collection, and routine use of functional outcome
measures in behavioral health care.
Psychiatric Services in Advance (doi: 10.1176/appi.ps.201400393)
and demonstrating its impact on relevant populations it especially challenging and also makes it more difﬁcult to appropriately position and demand greater attention to
behavioral health services in new health care delivery systems,
such as ACOs. The absence of measures makes it more difﬁcult
to assess whether nonquantitative limits on treatment threaten
parity of coverage between mental health and general medical services. In addition, in the absence of a set of measures,
it is more difﬁcult to make a case for extra payment for care
delivered by more effective providers. In sum, funds for
health care will be increasingly directed to areas where value
is being measured and demonstrated. If value in mental
health care is poorly measured compared with other medical
areas and is measured in ways that do not allow the profession of
psychiatry to demonstrate its beneﬁts, ﬁnancial resources will
likely be diverted from psychiatry, despite high rates of behavioral health conditions and unmet needs for treatment. As we
argue below, increased use of a particular type of measure, the
measurement of functional outcomes, may help to address these
problems.
This Open Forum builds a case for greater use of functional outcome measurement in mental health care. We
begin by describing the types of measures that exist and
laying out criteria for evaluating them. We then turn to the
case for functional outcome measures and evaluate their
potential beneﬁts, while noting the risks they pose.
TYPES OF MEASURES
To understand the problem of measurement in psychiatry,
consider a rudimentary logic model of psychiatric practice.
A logic model is an analytic strategy that proceeds from a set
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MEASURING PERFORMANCE IN PSYCHIATRY: A CALL TO ACTION
FIGURE 1. Sample logic models for creating behavioral health quality measures
Actions/Process
Outputs/Clinicala
Medical therapy provided
at appropriate dosage
Anxiety symptoms improve
Case manager available
Contact with teacher
within time frame
Depression symptoms
improve
Supported employment
program exists
Team assesses interest
in work
Program displays ﬁdelity
to supported
employment model
PANSS score improves
MAST score improves
Lives independently
Holds a full-time,
paying job
Access to gun screener
administered
Depression medication
dosage appropriate
PHQ-9 score improves
No suicide
Holds a full-time,
paying job
Inputs/Structure
Child with
ADHD and
anxiety
disorder
Adult with
schizophrenia
and alcohol
use disorder
Psychiatrist consult
available
Behavioral health care
Adult with
integrated with primary care
depression
Staff trained in
and suicidality
evidence-based treatments
a
ADHD symptoms improve
Completes grade
Graduates from high school
Has friends
PANSS, Positive and Negative Syndrome Scale; MAST, Michigan Alcoholism Screening Test; PHQ-9, nine-item Patient Health Questionnaire
of inputs to a set of actions, which in turn lead to outputs,
and these outputs lead to the ultimately desired outcomes
(6). Logic models are built recursively—that is, the ﬁrst step
is to deﬁne the outcomes, the ultimate goal of treatment. For
the purposes of this analysis, assume that the desired outcome of psychiatric treatment is recovery, which we operationalize as the service user engaging in a self-directed and
fulﬁlling daily life (Figure 1). Working backward in the logic
model, we can then deﬁne the set of treatment outputs that
psychiatric care can produce and that contribute to achievement of this outcome. These outputs could be, for example, the
absence of debilitating symptoms from a psychiatric condition.
Outputs, in turn, are produced through actions. Here, the
actions might include the use of appropriate evidence-based
treatments, as well as effective care coordination. Finally, engaging in these actions requires a set of inputs, such as investment in a therapeutic alliance to allow the service user to
trust and engage in the evidence-based treatment.
This logic model leads naturally into a cascade of measures and measurement milestones from inputs to outcomes.
Corresponding to the rightmost column of the model are
functional outcome measures, which assess the ability of
service users to engage in a self-directed and fulﬁlling daily
life, focusing on those behaviors or activities that are potentially impaired by an individual’s behavioral health disorder,
such as quality of life, workplace productivity, and days
at work. Most of these measures are currently patient
reported (7), although research studies have collected a few
measures from employers’ human resource information
systems (8).
At the next level are clinical outcome measures, which
assess the clinical outputs of treatment. Some of these measures use laboratory values, whereas others, including most
2
Outcomes/Functional
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behavioral health clinical outcome measures, are patient
reported and commonly measure symptom reduction (for
example, a change in [or level of ] a score on the nine-item
Patient Health Questionnaire [PHQ-9]) or observational data
on behavior (for example, a lower incidence of disruptive
behaviors). The measures used in conjunction with DSM-5:s
focus on measurement-based care would ﬁt at this level.
Other clinical outcome measures might include the acquisition of new knowledge and use of replacement behaviors or
self-management skills (for example, measurement tools for
social skills training and for recovery and resilience).
Process measures correspond to the action level of the
model. These measure the extent to which a practice, milieu,
or delivery-of-care system treats service users in a manner
consistent with standards of high-quality care. For example,
the rate at which discharged inpatients are seen as outpatients within a deﬁned period after hospitalization is a process measure that focuses on the effectiveness of the delivery
system. Process measures also capture coordination and integration of services across settings.
Finally, structure measures report whether a practice,
milieu, or delivery-of-care system has in place the infrastructure
and other resources that allow it to provide high-quality care and
care with ﬁdelity. For example, the presence of therapists trained
in cognitive-behavioral therapy in a behavioral health clinic
setting is a structure measure.
Measures of each type can be used at various levels within
the health system, such as at the practice or delivery system
level, because measures at different levels vary in their focus
and purpose. Measures also can be used for various purposes.
They can be used for monitoring, either within a practice
(where they may serve as a benchmark for quality improvement within the service user–provider treatment relationship,
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GLIED ET AL.
as suggested by DSM-5) or across practices. They can be used
to ensure that quality exceeds a minimum standard (as is the
case with accreditation standards). Measures can be used as
a source of comparative information for payers and service
users choosing among providers. Finally, measures can be
used as a basis of payment.
The NQF, a nonproﬁt organization created by public- and
private-sector leaders to improve the quality of health care
in the United States, has examined and endorsed a broad
range of behavioral health measures (Table 1). Most of the
endorsed measures rely on assessing, evaluating, and screening service users for mental health issues. Another subset of
measures examines the treatment of people with diagnosed
conditions, assessing whether providers appropriately treat
these service users according to speciﬁed process standards.
The NQF has endorsed three depression measures based on
the standardized PHQ-9 screening tool. Although the NQF has
begun a program of assessing patient-reported outcome measures, these measures have not yet been endorsed and are not
speciﬁc to behavioral health care (9).
Although structure and process measures account for the
majority of measures currently in use, they provide a weak
basis for demonstrating the value of psychiatry. Most of
these structure and process measures focus on primary care
and rarely capture care provided by psychiatrists. Even
those that assess treatment evaluate only the most basic
aspects of care processes, such as whether people are receiving any care and at what frequency, and do not enable
providers to distinguish themselves by how well they improve the health or lives of their patients. Only three of the
endorsed measures address clinical outcomes, and none
address functional outcomes.
CRITERIA FOR ASSESSING MEASURES
The dearth of functional outcome measures in current use
can partly be explained by the concerns and rationales used
for developing measures to date. Choosing what to measure
and at what level is challenging because measurement can
be used for many purposes, some of which conﬂict. Translating a measure concept into a speciﬁc question for which
data can be routinely collected poses an additional set of
difﬁculties.
One goal of measurement ﬂows from the principle of
transparency: consumers (or payers) are entitled to know
what they are receiving (or paying for) so that they can make
better decisions. This line of thinking emphasizes criteria
related to the inherent importance of the concept being
measured. For example, patient satisfaction is obviously
important, and a measure of patient satisfaction will rank
high in terms of inherent importance of the target of measurement. From this perspective, structure and process measures
score poorly because they have little inherent importance;
clinical and functional outcome measures are preferred.
A second perspective on measurement recognizes that
measurement, reporting, and paying providers on the basis
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of their performance on speciﬁed measures affects the behavior
of providers (and their patients). Once this is recognized, the
natural question arises: in light of how measurement affects
behavior, how do we make choices about measurement so as to
induce the behavior we seek? This is the domain of economics
and related ﬁelds. The general approach in economics is to
design the reporting policy in light of how service users and
providers respond to the presence of information, considering
both intended and unintended consequences.
Almost always, measurement is imperfect and partial.
Although some actions or outcomes are measured (and perhaps rewarded), others are not. This introduces several problems. Practice settings cannot improve everything and are
more likely to focus on improving elements for which performance is being measured and rewarded while paying less
attention to other aspects of care. This problem of “teaching
to the test” may result in a disregard of the real goals of
treatment. This is particularly problematic when improving
one aspect of care may diminish (or fail to affect) quality in
another dimension. For example, some research suggests
that practice settings that achieve high patient satisfaction
with care do not necessarily produce high-quality outcomes
along other dimensions (10).
A related problem is that providers may have (or believe
they have) a limited ability to affect the measured outcomes
for which they are held accountable. Changes in functioning,
for example, are likely to be inﬂuenced substantially by other
factors in the individual’s environment, such as the person’s
living situation or work or school environment. Being held
accountable for performance on a measure seen as largely
outside of one’s control may be seen as unfair to the clinician
or facility being measured, and holding providers accountable for these outcomes may be counterproductive. Note,
however, that the inability of providers to greatly affect a
measured outcome should not automatically eliminate a measure from consideration. In some cases, the measure may be
useful to service users as they choose providers. For example,
it may be very difﬁcult for providers to improve their Spanishlanguage proﬁciency, but measures of such proﬁciency could
still be useful to service users selecting among providers.
Even if, as is often the case, service users pay little attention to information about service quality, measuring and
reporting on quality can still be useful as a means of improving quality (11). If providers can observe and compare
their own performance, dissemination of these measures can
have a substantial impact. For example, about 80% of the
relatively large quality improvement effect generated through
dissemination of information about the quality of cardiac surgeons in Pennsylvania occurred when surgeons compared
their own performance to that of their peers (12).
Another unintended consequence of measurement may
be to encourage providers to favor service users who will
make them look good—that is, the choice of measures can
affect which sets of service users may be more desirable for
providers to attract. Measurement may introduce access
problems for more “difﬁcult” service users (for example,
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MEASURING PERFORMANCE IN PSYCHIATRY: A CALL TO ACTION
those less likely to have positive outcomes,
such as individuals less adherent to treatment).
Measures that focus on achieving improvements for a population—rather than on meeting a ﬁxed bar—may be less susceptible to
selection.
Finally, narrowly deﬁned structure and
process (and even clinical outcome) measures can stymie innovation at the provider
level. Providers who might be able to achieve
better outcomes in a new and different way
will have less incentive to do so (13). For example, a process measure that assesses whether
providers follow a speciﬁc treatment protocol
may hamper efforts to introduce an alternative treatment path that may be more effective.
Measures that require providers to follow deﬁned processes can lead to substantial improvements in quality by eliminating the worst
care—bringing up the ﬂoor. At the same time,
however, they can discourage innovations that
might lead to better processes (if these innovations are appropriately studied and evaluated).
Beyond these issues are considerations in
regard to the choice of speciﬁc measures. For
example, a particular measure needs to be
assessed in terms of its psychometric properties, including validity (that is, how well the
measure captures the target of the measurement) and reliability (that is, whether repeated
measurements produce the same ratings), and
its statistical properties (for example, sensitivity and speciﬁcity). A second set of considerations concerns the cost and complexity
of data collection. The cost of collection should
be weighed against the extent to which measures drive better performance or better choices.
Measures should be easy for clinicians to collect
and use (14).
Trade-offs among these considerations
may depend on the use of the measures.
Structure and process measures are often preferred for the purpose of tying payment to
performance, as in the Medicare Shared Savings Program (2). Narrowly deﬁned structure
and process measures can be designed to be
well within provider control and largely free
of selection incentives. Many can be assessed
by using routinely collected administrative
data, which will minimize intrusiveness and
cost. However, narrow structure and process
measures are susceptible to the problem of
“teaching to the test.” There is no particular
reason why strong performance on one of
these narrow measures should be associated
with strong performance in another arena.
4
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TABLE 1. Behavioral health measures endorsed by the National Quality
Forum (NQF)
Measure
Appraise, assess, evaluate
Bipolar disorder and major
depression: appraisal
for alcohol or chemical
substance use
Bipolar disorder: appraisal
for risk of suicide
Bipolar disorder: assessment
for diabetes
Major depressive disorder:
suicide risk assessment
Back pain: mental health
assessment
Depression assessment
conducted
Child and adolescent major
depressive disorder:
suicide risk assessment
Bipolar disorder and major
depression: assessment for
manic or hypomanic
behaviors
Major depressive disorder:
diagnostic evaluation
Bipolar disorder: level-offunction evaluation
Child and adolescent major
depressive disorder:
diagnostic evaluation
Measure, plan, screen
Depression: utilization of the
nine-item Patient Health
Questionnaire
HBIPS-6: postdischarge
continuing care plan
createdb
HBIPS-7: postdischarge
continuing care plan
transmitted to next level
of care provider upon
dischargeb
Screening for clinical
depression
Depression screening by
13 years of age
Maternal depression screening
Developmental screening in
the ﬁrst three years of life
Depression screening by 18
years of age
Cardiovascular health
screening for people with
schizophrenia or bipolar
disorder who are prescribed
antipsychotic medications
Diabetes screening for people
with schizophrenia or bipolar
disorder who are prescribed
antipsychotic medications
NQF
number
Type of
activity
0110
Appraise
0111
Appraise
0003
Assess
0104
Assess
0316
Assess
0518
Assess
1365
Assess
0109
Assess
0103
Evaluate
0112
Evaluate
1364
Evaluate
0712
Measure
0557
Plan
0558
Plan
0418
Screen
1394
Screen
1401
1448
Screen
Screen
1515
Screen
1927
Screen
1932
Screen
Meaningful use
incentive IIa
✓
✓
✓
✓
✓
continued
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GLIED ET AL.
TABLE 1, continued
Measure
Monitor, manage, treat
Antidepressant medication
management
Cardiovascular monitoring
for people with cardiovascular
disease and schizophrenia
Diabetes monitoring for
people with diabetes and
schizophrenia
HBIPS-4: patients discharged
on multiple antipsychotic
medicationsb
HBIPS-5: patients discharged
on multiple antipsychotic
medications with appropriate
justiﬁcationb
Follow-up after hospitalization
for mental illness
Bipolar antimanic agent
HBIPS-2: hours of physical
restraint useb
HBIPS-3: hours of seclusion
useb
Adherence to antipsychotic
medications for individuals
with schizophrenia
Follow-up after hospitalization
for schizophrenia (7- and
30-day)
Antipsychotic use by persons
with dementia
NQF
number
Type of
activity
0105
Manage
1933
Monitor
1934
Monitor
0552
Treat
0560
Treat
Meaningful use
incentive IIa
✓
providers to improve the quality of care. They
should have good psychometric properties
and avoid untoward unintended consequences.
Considerable progress has been made in the
development of behavioral health measures,
but because it has occurred mainly in the
context of payment reforms, the focus has
been on process measures that are unlikely
to lead to unintended consequences—but are
also unlikely to demonstrate the beneﬁts that
psychiatry brings to the treatment process.
The biggest gap in reaching this goal is the
absence of outcome measures.
FUNCTIONAL OUTCOME MEASURES
As the discussion above suggests, most of the
focus of measurement research in behavioral
health care has been on structure and process
0580
Treat
0640
Treat
measurement. Given the multifaceted nature
of behavioral health problems, functional
0641
Treat
outcome measures have tremendous promise
for assessing treatment effect in a way that
1879
Treat
more closely demonstrates the tangible value
of treatment to service users and to the com1937
Treat
munity. Recovery, for example, can be understood as a comprehensive functional outcome.
The development and use of functional out2111
Treat
come measures to assess the value of health
care has been a challenge to the broader health
Outcome
care ﬁeld, yet in the past several decades, such
Percentage of residents who
0690
Outcome
have depressive symptoms
measures have been developed and incorpo(long-stay)
rated in the routine practice of a range of
Depression remission at
0710
Outcome
✓
health care disciplines, such as chronic ob12 months
structive pulmonary disease (15), stroke (16),
Depression remission at
0711
Satisfaction
✓
and knee orthopedics (17). The World Health
6 months
Inpatient Consumer Survey:
0726
Organization has developed a brief set of such
consumer evaluation of
measures, including measures of cognition,
inpatient behavioral health
interaction with others, and life activities, that
care services
can be administered in clinical settings (18).
a
The indicators marked in this column are part of the set from which clinicians participating in
In behavioral health care, studies have meathe Medicare meaningful use incentive program may select to document incentive-eligible use
sured the effect of behavioral interventions in
of their electronic health record (1).
b
Hospital Based Inpatient Psychiatric Services 1–7 (HBIPS) is a set of seven NQF measures.
treating depression by using workplace productivity and absenteeism as measurement
Structure and process measures also are less desirable from
outcomes (19,20). Functional outcomes measures have also
a transparency perspective.
been used for quality improvement in behavioral health care.
Outcome measures, although preferred from a transFor example, through its outcomes measurement system,
parency perspective, raise much more serious problems of
practitioners in Maryland’s public mental health system routinely collect and view information from their patients on living
selection and provider control. By focusing on broad quality
situations, functioning, substance use, legal involvement, emtargets, however, they are less susceptible to the “teaching to
ployment, and general health (21).
the test” problem and can encourage process innovations.
Outcome measures are often preferred in contexts where they
Given the heterogeneity in the nature and severity of the
are used to monitor performance but not as a basis of payment.
populations receiving treatment for behavioral health disIn the case of psychiatry, measures should ideally address
orders, no single functional measure will likely be appropriate
all of these considerations. They should provide information
for all populations, and any measure will need to be adjusted
that is meaningful to service users, and they should encourage
for the severity of illness in the underlying population. For
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0576
Treat
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MEASURING PERFORMANCE IN PSYCHIATRY: A CALL TO ACTION
example, a measure that assesses absenteeism and presenteeism in the workplace may be appropriate for a population of adults with depression or anxiety, most of whom
are likely to be working, but such a measure is likely to be
less useful in assessing the functioning of individuals with
schizophrenia, who are less likely to be employed. For the
latter group, other measures of social role performance,
such as days spent living outside an institution (community
tenure), will be more useful.
Implementing functional outcome measures can be difﬁcult, because they usually require collecting information
directly from the service user, family member, or another
individual (such as a teacher) or tapping into other nontraditional sources of data (for example, human resources
absenteeism reports and long-term and short-term disability
rates obtained from disability insurers). In the best case,
patient self-reported information can be obtained as part
of the routine processes of care and can inform treatment
planning, but the collection of such information does not
always result in its use (22,23). Obtaining information from
individuals and nontraditional sources is more expensive
and burdensome than using claims-based administrative
records, particularly because collection of data from individuals who may have already discontinued treatment may
be necessary to fully document functional outcomes across
a provider’s population. Increasingly, however, efforts are
under way to use technology to simplify the collection and
use of such data (24); these efforts offer the potential of
supporting the more widespread deployment of functional
outcome measures in community settings that treat individuals with behavioral health disorders.
CONCLUSIONS
Expanding the scope of measurement in behavioral health
care to include functional outcome measures is highly desirable but raises implementation challenges. Implementation of existing process and clinical outcome measures has
proved difﬁcult but has progressed over the years. These
slow but steady gains suggest that over time, implementation
challenges can be overcome. Research shows, for example,
that patient-reported outcome measures can be incorporated
into routine psychiatric practice and can contribute to improvement in the quality of practice (25). Psychiatrists can play
an important role in moving this agenda forward, both by advocating for the development and implementation of these
measures and by participating in efforts to collect them directly.
Clinicians may be frustrated at ﬁrst by the lack of an
obvious link between how they currently view the effect
of their treatment approaches (for example, reduction of
symptoms and reductions in hospitalizations) and the ultimate goal of restoring general functionality, which is measured by functional outcomes. Clinicians may need to change
their practices and methods in response to this change in
focus. Yet collection, monitoring, and analysis of functional
outcome data, even from a single provider’s practice, and
6
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comparisons of data from different providers for quality
improvement purposes are likely to improve the ability of
practitioners to meet quality improvement goals. Given the
challenges of implementation and the demands on practice,
collection and analysis of functional data might be best
implemented initially only for monitoring and quality improvement purposes, rather than for payment. Over time, as
methods improve, linkage of these performance measures to
payment, to public reporting of outcomes for service user
choice, and for certiﬁcation purposes will become possible.
Use of functional measures for these more “high-powered”
purposes will require inclusion of extensive case-mix adjustment methodology to prevent giving clinicians incentives to avoid highly difﬁcult patients.
Despite these challenges, the collection and use of functional outcome measures present new opportunities to behavioral health care. Expanding the focus of measurement
from process measures to broad outcome measures broadens
opportunities for practice innovations that lead to quality
improvement, increases incentives for coordination with
other parts of the health and social service system, and complements attention to recovery. These opportunities have led
other medical specialty societies to explore the use of broader
functional outcome measures, and given the multiple ways that
mental health problems affect the lives of service users, it is
time for psychiatry to consider this broader focus as well.
AUTHOR AND ARTICLE INFORMATION
Dr. Glied is with the Wagner School of Public Service, New York University, New York City (e-mail: [email protected]). Dr. Stein is with
the Department of Psychiatry, University of Pittsburgh, Pittsburgh,
Pennsylvania. Dr. McGuire is with the Department of Health Care Policy,
Harvard Medical School, Boston. Dr. Beale is with the Institute of
Medicine, Washington, D.C. Dr. Duffy and Ms. Shugarman are with the
American Psychiatric Institute for Research and Education, Arlington,
Virginia. Dr. Goldman, who is editor of Psychiatric Services, is with the
Department of Psychiatry, University of Maryland School of Medicine,
Baltimore.
The authors thank the Policy Work Group of the American Psychiatric
Association Board of Trustees for support and assistance in the development of this paper.
The authors report no ﬁnancial relationships with commercial interests.
Received September 5, 2014; revision received December 4, 2014;
accepted February 13, 2015; published online April 15, 2015.
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